Combining data from different sample regions in imaging system field of view

Abstract

The imaging system includes one or more cores. Each core outputs a system output signal that illuminates a plurality of sample regions in a field of view. A target core of the cores includes an optical combiner that generates a composite signal that is beat-oscillated at a beat frequency. The electronics calculate a plurality of different possible LIDAR data solutions for a target sample region of the sample regions illuminated by the system output signal output from the target core using the values of the beat frequencies. Each possible LIDAR data solution includes a comparison component indicative of a value of a radial velocity between the LIDAR system and an object in the target sample region. The electronic device identifies a correct one of the LIDAR data solutions by comparing the LIDAR data solutions to data calculated for one or more reference sample regions selected from the sample regions. The one or more reference sample regions are different from the target sample region.

Description

[0001] Related Applications

[0002] This application is a continuation of U.S. patent application serial number 17 / 945,072, filed on September 14, 2022, entitled “Combining Data from Different Sample Regions in an Imaging System Field of View,” and the entire text of that U.S. patent application is incorporated herein. Technical Field

[0003] The present invention relates to imaging systems. In particular, the present invention relates to LIDAR systems. Background Art

[0004] There is an increasing commercial demand for 3D imaging systems that can be economically deployed in applications such as ADAS (Advanced Driver Assistance Systems) and AR (Augmented Reality). Imaging systems such as LIDAR (Light Detection and Ranging) are used to construct a 3D image of a target scene by illuminating the target scene with lasers and measuring the return signal.

[0005] Many LIDAR methods transmit a system output signal. The system output signal is reflected by the object, and a portion of the reflected light signal is returned to the LIDAR chip as a LIDAR input signal. The LIDAR input signal is processed by an electronic device to determine the distance and radial velocity between the LIDAR system and the object. Since the LIDAR input signal is typically an analog signal, but the processing is performed on the digital signal, the LIDAR system typically includes one or more analog-to-digital converters (ADCs) for converting the optical signal including the light from the LIDAR input signal into a digital signal. The analog-to-digital converter (ADC) becomes a large cost in the commercialization of the LIDAR system.

[0006] For the above reasons, there is a need for LIDAR systems with reduced cost and complexity. Summary of the invention

[0007] An imaging system includes one or more cores, each core outputting a system output signal, the system output signal illuminating a plurality of sample regions in a field of view. A reference core among the cores includes a light combiner configured to generate a composite signal that beats at a beat frequency. The system also includes an electronic device configured to calculate the size of a radial velocity indicator of a reference sample region among the sample regions illuminated by the system output signal output from the reference core using the value of the beat frequency of the composite signal. The radial velocity indicator indicates a radial velocity between a LIDAR system and an object in the reference sample region. The electronic device is configured to identify a direction of the radial velocity indicator by comparing the size of the radial velocity indicator with data calculated for a subject sample region in the sample region. The reference sample region is different from the subject sample region.

[0008] Another embodiment of the imaging system includes one or more cores. Each core outputs a system output signal that illuminates multiple sample areas in a field of view. A subject core in the core includes a light combiner that generates a composite signal that beats at a beat frequency. The electronic device uses the value of the beat frequency to calculate multiple different possible LIDAR data solutions for a target sample area in the sample area illuminated by the system output signal output from the subject core. Each possible LIDAR data solution includes a comparative component that indicates a value of a radial velocity between the LIDAR system and an object in the target sample area. The electronic device identifies a correct LIDAR data solution in the LIDAR data solution by comparing the LIDAR data solution with data calculated for one or more reference sample areas selected from the sample area. The one or more reference sample areas are different from the target sample area.

[0009] A method of operating an imaging system includes illuminating a plurality of sample regions in a field of view with system output signals output from different cores. The method also includes combining the optical signals to generate a composite signal that beats at a beat frequency. The method also includes calculating a magnitude of a radial velocity indicator for a reference sample region in the sample regions illuminated by the system output signal output from a reference core using a value of the beat frequency of the composite signal. The radial velocity indicator indicates a radial velocity between the LIDAR system and an object in the reference sample region. The method also includes identifying a direction of the radial velocity indicator by comparing the magnitude of the radial velocity indicator with data calculated for a target sample region in the sample region. The reference sample region is different from the target sample region.

[0010] Another method of operating an imaging system includes illuminating a plurality of sample areas in a field of view with system output signals output from different cores. The method also includes combining the light signals to generate a composite signal that beats at a beat frequency. The method also includes calculating a plurality of different possible LIDAR data solutions for a target sample area in the sample area using the value of the beat frequency. Each possible LIDAR data solution includes a comparison component that indicates a value of a radial velocity between the LIDAR system and an object in the target sample area. The method also includes identifying a correct LIDAR data solution in the LIDAR data solution by comparing the LIDAR data solution with data calculated for one or more reference sample areas selected from the sample area. The one or more reference sample areas are different from the target sample area. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1A is a top view of a schematic diagram of a LIDAR system including or consisting of a LIDAR chip that outputs a LIDAR output signal and receives a LIDAR input signal on a common waveguide.

[0012] Figure 1B is a top view of a schematic diagram of a LIDAR system that includes or consists of a LIDAR chip that outputs LIDAR output signals on different waveguides and receives LIDAR input signals.

[0013] Figure 1C is a top view of a schematic diagram of another embodiment of a LIDAR system that includes or consists of a LIDAR chip that outputs LIDAR output signals on different waveguides and receives multiple LIDAR input signals.

[0014] Figure 2 is suitable for Figure 1B A top view of an example of a LIDAR chip used together with a LIDAR adapter.

[0015] Figure 3 is suitable for Figure 1C A top view of an example of a LIDAR chip used together with a LIDAR adapter.

[0016] Figure 4 Included on the common support Figure 1A LIDAR chips and Figure 2 A top view of an example of a LIDAR system with a LIDAR adapter.

[0017] Figure 5A An example of a signal processor suitable for use with a LIDAR system is shown.

[0018] Figure 5B Provides suitable for Figure 5A Construct a schematic diagram of the electronics used in conjunction with the signal processor.

[0019] Figure 5C is a graph of the frequency of the system output signal versus time.

[0020] Fig. 6A A LIDAR system comprising a plurality of different cores on a common support is shown.

[0021] Figure 6B Shows Figure 5C The relationship between the data period (date period) and the field of view of the LIDAR system disclosed in.

[0022] Figure 6C Shows Figure 6B Objects in the field of view that are exposed in the scene.

[0023] Fig.6D A number of different field positions in the sample region illuminated by the range and velocity kernels are shown.

[0024] Figure 7 is a two-dimensional schematic diagram of the field of view of the LIDAR system.

[0025] Figure 8 Common electronics configured to receive preliminary LIDAR data generated by different cores are shown.

[0026] Fig. 9 Shows Figure 7 Target sample area and potential sample area in the middle field of view.

[0027] Fig.10 is a flow chart for generating range data for a sample area illuminated by a velocity kernel in a LIDAR system including range and velocity kernels.

[0028] Fig.11A is a top view of a schematic diagram of a LIDAR core suitable for use as a velocity core.

[0029] Fig. 11B is suitable for Fig.11A An example of a signal processor used with the LIDAR core.

[0030] Fig. 11C Provides suitable for Fig. 11B Construct a schematic diagram of the electronics used in conjunction with the signal processor.

[0031] Fig. 12Ais an example of a flow chart that an electronic device may use to identify a correct LIDAR data solution from a plurality of possible LIDAR data solutions.

[0032] Fig. 12B A LIDAR system comprising a plurality of different real data signal cores on a common support is shown.

[0033] Fig. 12C yes Fig. 12B Two-dimensional schematic diagram of the field of view of the LIDAR system.

[0034] Fig.12D Shows Fig. 12C The target RV sample area and the reference V sample area on the middle field of view.

[0035] Fig.12E A flow chart for generating LIDAR data of a sample area illuminated by a LIDAR system having a real data signal kernel is shown.

[0036] Fig.13A The electronic device can be used to identify the sample region SR k An example of a flow chart of radial velocity of ...

[0037] Fig. 13B A LIDAR system comprising a plurality of different real data signal cores on a common support is shown.

[0038] Fig. 13C yes Fig. 13B Two-dimensional schematic diagram of the field of view of the LIDAR system.

[0039] Fig.13D Shows Fig. 13C The target RV sample area and the reference V sample area on the field of view.

[0040] Fig.13E An example of a flow chart that electronics may use to identify the correct LIDAR data solution for the target RV sample region and determine the correct radial velocity for the reference V sample region is shown.

[0041] Fig.13F A flow chart for generating LIDAR data of a sample area illuminated by a LIDAR system having a real data signal kernel is shown.

[0042] Figure 13G Shows Fig. 12C or Fig. 13C A portion of the field of view in which the sample areas illuminated by different nuclei partially overlap.

[0043] Fig.14 is a cross section of a portion of a silicon-on-insulator wafer including a waveguide. DETAILED DESCRIPTION

[0044] The LIDAR system typically illuminates multiple different sample areas in the field of view. The system generates LIDAR data for each sample area. The LIDAR data may indicate the radial velocity and / or distance between the LIDAR system and any (one or more) objects located in each field of view. These systems typically apply a mathematical transform (e.g., a Fourier transform) to the beat signal to identify the beat frequency of the beat signal. When a real transform is used, the transform may output multiple different frequencies. In many cases, it is unclear which of these frequencies is the correct frequency. Therefore, the LIDAR data of the sample area may typically have multiple solutions. In order to identify which solution is the correct solution for the sample area, the LIDAR system compares the possible LIDAR data solutions of the sample area with data from other sample areas. Therefore, the LIDAR system can use a real Fourier transform instead of a complex Fourier transform. A real Fourier transform typically requires fewer analog-to-digital converters (ADCs) than a complex Fourier transform. Therefore, the ability to use a real Fourier transform reduces the cost and complexity of the LIDAR system.

[0045] Figure 1A is a top view of a schematic diagram of a LIDAR chip, which chip LIDAR can act as a LIDAR core, or can be included in an imaging system including components other than the LIDAR chip. The LIDAR chip can include a photonic integrated circuit (PIC), and can be a photonic integrated circuit chip. The LIDAR chip includes a light source 4, which outputs a preliminary outgoing LIDAR signal. Suitable light sources 4 include, but are not limited to, semiconductor lasers, such as external cavity lasers (ECL), distributed feedback lasers (DFB), discrete mode (DM) lasers, and distributed Bragg reflector lasers (DBR).

[0046] The LIDAR chip includes a utility waveguide 12 that receives an outgoing LIDAR signal from a light source 4. The utility waveguide 12 terminates at a facet 14 and carries the outgoing LIDAR signal to the facet 14. The facet 14 can be positioned so that the outgoing LIDAR signal traveling through the facet 14 leaves the LIDAR chip and serves as a LIDAR output signal. For example, the facet 14 can be positioned at an edge of the chip so that the outgoing LIDAR signal traveling through the facet 14 leaves the chip and serves as a LIDAR output signal. In some cases, a portion of the LIDAR output signal that leaves the LIDAR chip can also be considered a system output signal. As an example, when the departure of the LIDAR output signal from the LIDAR chip is also the departure of the LIDAR output signal from the LIDAR system, the LIDAR output signal can also be considered a system output signal.

[0047] The LIDAR output signal travels away from the LIDAR system through free space in the environment and / or atmosphere in which the LIDAR system is located. The LIDAR output signal may be reflected by one or more objects in the path of the LIDAR output signal. When the LIDAR output signal is reflected, at least a portion of the reflected light is transmitted back toward the LIDAR chip as the LIDAR input signal. In some cases, the LIDAR input signal can also be considered a system return signal. As an example, when the departure of the LIDAR output signal from the LIDAR chip is also the departure of the LIDAR output signal from the LIDAR core, the LIDAR input signal can also be considered a system return signal.

[0048] The LIDAR input signal may enter the utility waveguide 12 through the end face 14. The portion of the LIDAR input signal that enters the utility waveguide 12 serves as the incoming LIDAR signal. The utility waveguide 12 carries the incoming LIDAR signal to a splitter 16, which moves a portion of the outgoing LIDAR signal from the utility waveguide 12 to a comparison waveguide 18 as a comparison signal. The comparison waveguide 18 carries the comparison signal to a signal processor 22 for further processing. Figure 1A A directional coupler is shown operating as the splitter 16, but other signal tapping components may also be used as the splitter 16. Suitable splitters 16 include, but are not limited to, directional couplers, optical couplers, Y-junctions, tapered couplers, and multi-mode interference (MMI) devices.

[0049] The utility waveguide 12 also carries the outgoing LIDAR signal to a splitter 16. The splitter 16 moves a portion of the outgoing LIDAR signal from the utility waveguide 12 to a reference waveguide 20 as a reference signal. The reference waveguide 20 carries the reference signal to a signal processor 22 for further processing.

[0050] The percentage of light diverted from the utility waveguide 12 by the splitter 16 can be fixed or substantially fixed. For example, the splitter 16 can be configured so that the power of the reference signal diverted to the reference waveguide 20 is an outgoing percentage of the power of the outgoing LIDAR signal, or so that the power of the comparison signal diverted to the comparison waveguide 18 is an incoming percentage of the power of the incoming LIDAR signal. In many splitters 16, such as directional couplers and multimode interferometers (MMIs), the outgoing percentage is equal to or substantially equal to the incoming percentage. In some cases, the outgoing percentage is greater than 30%, 40% or 49% and / or less than 51%, 60% or 70%, and / or the incoming percentage is greater than 30%, 40% or 49% and / or less than 51%, 60% or 70%. Splitters 16 such as multimode interferometers (MMIs) typically provide an outgoing percentage and an incoming percentage of 50% or about 50%. However, multimode interferometers (MMIs) are easier to manufacture in platforms such as silicon on insulators than some alternatives. In one example, the separator 16 is a multi-mode interferometer (MMI), and the outgoing percentage and the incoming percentage are 50% or substantially 50%. As will be described in more detail below, the signal processor 22 combines the comparison signal with the reference signal to form a composite signal that carries the LIDAR data for the sample area on the field of view. Thus, the composite signal can be processed to extract the LIDAR data for the sample area (radial velocity and / or distance between the LIDAR core and objects outside the LIDAR core).

[0051] The LIDAR chip may include a control branch for controlling the operation of the light source 4. The control branch includes a splitter 26 that moves a portion of the outgoing LIDAR signal from the utility waveguide 12 to the control waveguide 28. The coupled portion of the outgoing LIDAR signal acts as a tapped signal. Figure 1A A directional coupler is shown operating as the splitter 26, but other signal tapping components may also be used as the splitter 26. Suitable splitters 26 include, but are not limited to, directional couplers, optical couplers, Y-junctions, tapered couplers, and multi-mode interference (MMI) devices.

[0052] The control waveguide 28 carries the tap signal to a control component 30. The control component may be in electrical communication with local electronics 32. All or a portion of the control component may be included in the local electronics 32. During operation, the electronics may utilize the output of the control component 30 in a control loop configured to control one, two, or three process variables of the loop control optical signal selected from the group consisting of the tap signal, the system output signal, and the outgoing LIDAR signal. Examples of suitable process variables include the frequency of the loop control optical signal and / or the phase of the loop control optical signal.

[0053] The LIDAR core can be modified so that the incoming LIDAR signal and the outgoing LIDAR signal can be carried on different waveguides. For example, Figure 1B It is modified so that the incoming LIDAR signal and the outgoing LIDAR signal are carried on different waveguides. Figure 1A 1. A top view of a LIDAR chip of FIG. 1. The outgoing LIDAR signal leaves the LIDAR chip through end face 14 and serves as a LIDAR output signal. When light from the LIDAR output signal is reflected by an object outside the LIDAR core, at least a portion of the reflected light returns to the LIDAR chip as a first LIDAR input signal. The first LIDAR input signal enters the comparison waveguide 18 through end face 35 and serves as a comparison signal. The comparison waveguide 18 carries the comparison signal to the signal processor 22 for further processing. Figure 1A As described in the context of FIG. 1 , the reference waveguide 20 carries the reference signal to a signal processor 22 for further processing. As will be described in more detail below, the signal processor 22 combines the comparison signal with the reference signal to form a composite signal that carries LIDAR data for a sample area on the field of view.

[0054] The LIDAR chip can be modified to receive multiple LIDAR input signals. For example, Figure 1C is shown modified to receive two LIDAR input signals Figure 1B The LIDAR chip of the present invention. The separator 40 is configured to place a portion of the reference signal carried on the reference waveguide 20 on the first reference waveguide 42 and place another portion of the reference signal on the second reference waveguide 44. Therefore, the first reference waveguide 42 carries the first reference signal and the second reference waveguide 44 carries the second reference signal. The first reference waveguide 42 carries the first reference signal to the first signal processor 46, and the second reference waveguide 44 carries the second reference signal to the second signal processor 48. Examples of suitable separators 40 include, but are not limited to, a Y-junction, an optical coupler, and a multimode interference coupler (MMI).

[0055] The outgoing LIDAR signal leaves the LIDAR chip through the end face 14 and serves as the LIDAR output signal. When light from the LIDAR output signal is reflected by one or more objects outside the LIDAR core, at least a portion of the reflected light returns to the LIDAR chip as a first LIDAR input signal. The first LIDAR input signal enters the comparison waveguide 18 through the end face 35 and serves as a first comparison signal. The comparison waveguide 18 carries the first comparison signal to the first signal processor 46 for further processing.

[0056] In addition, when light from the LIDAR output signal is reflected by one or more objects outside the LIDAR core, at least a portion of the reflected signal returns to the LIDAR chip as a second LIDAR input signal. The second LIDAR input signal enters the second comparison waveguide 50 through the end face 52 and serves as a second comparison signal carried by the second comparison waveguide 50. The second comparison waveguide 50 carries the second comparison signal to the second signal processor 48 for further processing.

[0057] Although the light source 4 is shown as being located on the LIDAR chip, the light source 4 may be located outside the LIDAR chip. For example, the utility waveguide 12 may terminate at a second end face through which an outgoing LIDAR signal may enter the utility waveguide 12 from the light source 4 outside the LIDAR chip.

[0058] In some cases, according to Figure 1B or Figure 1C The constructed LIDAR chip is used in combination with a LIDAR adapter. In some cases, the LIDAR adapter can be physically and optically positioned between the LIDAR chip and one or more reflective objects and / or the field of view, such that the optical path of the (one or more) first LIDAR input signal and / or the LIDAR output signal traveling from the LIDAR chip to the field of view passes through the LIDAR adapter. In addition, the LIDAR adapter can be configured to operate on the first LIDAR input signal and the LIDAR output signal such that the first LIDAR input signal and the LIDAR output signal travel on different optical paths between the LIDAR adapter and the LIDAR chip, but travel on the same optical path between the LIDAR adapter and the reflective objects in the field of view.

[0059] Figure 2 The figure shows a suitable Figure 1B 102. An example of a LIDAR adapter for use with a LIDAR chip of the present invention. The LIDAR adapter includes a plurality of components positioned on a base. For example, the LIDAR adapter includes a circulator 100 positioned on a base 102. The optical circulator 100 shown includes three ports and is configured such that light entering one port exits from the next port. For example, the optical circulator shown includes a first port 104, a second port 106, and a third port 108. The LIDAR output signal enters the first port 104 from the utility waveguide 12 of the LIDAR chip and exits from the second port 106.

[0060] The LIDAR adapter can be configured such that the output of the LIDAR output signal from the second port 106 can also serve as the output of the LIDAR output signal from the LIDAR adapter and, therefore, from the LIDAR core. Thus, the LIDAR output signal can be output from the LIDAR adapter such that the LIDAR output signal travels toward the sample area in the field of view. Thus, in some cases, the portion of the LIDAR output signal that exits the LIDAR adapter can also be considered a system output signal. For example, when the exit of the LIDAR output signal from the LIDAR adapter is also the exit of the LIDAR output signal from the LIDAR core, the LIDAR output signal can also be considered a system output signal.

[0061] The LIDAR output signal output from the LIDAR adapter includes, consists of, or consists essentially of light from the LIDAR output signal received from the LIDAR chip. Thus, the LIDAR output signal output from the LIDAR adapter may be the same or essentially the same as the LIDAR output signal received from the LIDAR chip. However, there may be differences between the LIDAR output signal output from the LIDAR adapter and the LIDAR output signal received from the LIDAR chip. For example, the LIDAR output signal may experience light loss as it travels through the LIDAR adapter, and / or the LIDAR adapter may optionally include an amplifier configured to amplify the LIDAR output signal as it travels through the LIDAR adapter.

[0062] When one or more objects in the sample area reflect the LIDAR output signal, at least a portion of the reflected light is transmitted back to the circulator 100 as a system return signal. The system return signal enters the circulator 100 through the second port 106. Figure 2 It is shown that the LIDAR output signal and the system return signal travel along the same optical path between the LIDAR adapter and the sample area.

[0063] The system return signal exits the circulator 100 through the third port 108 and is directed to the comparison waveguide 18 on the LIDAR chip. Thus, all or a portion of the system return signal can serve as the first LIDAR input signal, and the first LIDAR input signal includes or consists of light from the system return signal. Thus, the LIDAR output signal and the first LIDAR input signal travel along different optical paths between the LIDAR adapter and the LIDAR chip.

[0064] like Figure 2It is clear that the LIDAR adapter may include optical components in addition to the circulator 100. For example, the LIDAR adapter may include components for directing and controlling the optical paths of the LIDAR output signal and the system return signal. As an example, Figure 2 The adapter includes an optional amplifier 110 positioned to receive and amplify the LIDAR output signal before it enters the circulator 100. The amplifier 110 may be operated by the local electronics 32, allowing the local electronics 32 to control the power of the LIDAR output signal.

[0065] Figure 2 Also shown is a LIDAR adapter including an optional first lens 112 and an optional second lens 114. The first lens 112 can be configured to couple the LIDAR output signal to a desired location. In some cases, the first lens 112 is configured to focus or collimate the LIDAR output signal at the desired location. In one example, when the LIDAR adapter does not include the amplifier 110, the first lens 112 is configured to couple the LIDAR output signal to the first port 104. As another example, when the LIDAR adapter includes the amplifier 110, the first lens 112 can be configured to couple the LIDAR output signal to the entrance port of the amplifier 110. The second lens 114 can be configured to couple the LIDAR output signal to a desired location. In some cases, the second lens 114 is configured to focus or collimate the LIDAR output signal at a desired location. For example, the second lens 114 can be configured to couple the LIDAR output signal to the end face 35 of the comparison waveguide 18.

[0066] The LIDAR adapter may also include one or more direction changing components, such as mirrors. Figure 2 The LIDAR adapter is shown to include a mirror as a direction changing component 116 that redirects the system return signal from the circulator 100 to the end face 20 of the comparison waveguide 18 .

[0067] The LIDAR chip includes one or more waveguides that constrain the optical path of one or more optical signals. Although the LIDAR adapter may include waveguides, the optical path that the system return signal and the LIDAR output signal travel between components on the LIDAR adapter and / or between components on the LIDAR chip and the LIDAR adapter may be free space. For example, when traveling between different components on the LIDAR adapter and / or between components on the LIDAR adapter and the LIDAR chip, the system return signal and / or the LIDAR output signal may travel through the environment and / or atmosphere in which the LIDAR chip, the LIDAR adapter, and / or the base 102 are located. Thus, optical components such as lenses and direction-changing components may be utilized to control the characteristics of the optical path that the system return signal and the LIDAR output signal travel on, to, and from the LIDAR adapter.

[0068] Suitable bases 102 for the LIDAR adapter include, but are not limited to, substrates, platforms, and plates. Suitable substrates include, but are not limited to, glass, silicon, and ceramics. The components may be discrete components attached to the substrate. Suitable techniques for attaching discrete components to the base 102 include, but are not limited to, epoxy, solder, and mechanical clamping. In one example, one or more of the components are integrated components and the remaining components are discrete components. In another example, the LIDAR adapter includes one or more integrated amplifiers and the remaining components are discrete components.

[0069] The LIDAR core can be configured to compensate for polarization. The light from the laser source is typically linearly polarized, so the LIDAR output signal is typically also linearly polarized. Reflection from an object may change the polarization angle of the returned light. Therefore, the system return signal may include light of different linear polarization states. For example, the first part of the system return signal may include light of a first linear polarization state, and the second part of the system return signal may include light of a second linear polarization state. The intensity of the resulting composite signal is proportional to the cosine square of the angle between the comparison signal and the reference signal polarization field. If the angle is 90°, LIDAR data may be lost in the resulting composite signal. However, the LIDAR core can be modified to compensate for changes in the polarization state of the LIDAR output signal.

[0070] Figure 3 The LIDAR adapter is shown modified to make it suitable for use with Figure 1C Used with LIDAR chips Figure 3The LIDAR adapter includes a beam splitter 120 that receives the system return signal from the circulator 100. The beam splitter 120 splits the system return signal into a first portion of the system return signal and a second portion of the system return signal. Suitable beam splitters include, but are not limited to, Wollaston prisms and MEMS-based beam splitters.

[0071] The first part of the system return signal is guided to the comparison waveguide 18 on the LIDAR chip and acts as Figure 1C The second portion of the system return signal is directed to the polarization rotator 122. The polarization rotator 122 outputs the second LIDAR input signal, which is directed to the second input waveguide 76 on the LIDAR chip and serves as the second LIDAR input signal.

[0072] The beam splitter 120 may be a polarization beam splitter. An example of a polarization beam splitter is constructed so that a first portion of the system return signal has a first polarization state, but no or substantially no second polarization state, and a second portion of the system return signal has a second polarization state, but no or substantially no first polarization state. The first polarization state and the second polarization state may be linear polarization states, and the second polarization state is different from the first polarization state. For example, the first polarization state may be TE and the second polarization state may be TM, or the first polarization state may be TM and the second polarization state may be TE. In some cases, the laser source may be linearly polarized so that the LIDAR output signal has a first polarization state. Suitable beam splitters include, but are not limited to, Wollaston prisms and MEMS-based polarization beam splitters.

[0073] The polarization rotator may be configured to change the polarization state of the first portion of the system return signal and / or the second portion of the system return signal. Figure 3 The polarization rotator 122 shown can be configured to change the polarization state of the second portion of the system return signal from the second polarization state to the first polarization state. Therefore, the second LIDAR input signal has the first polarization state, but has no or substantially no second polarization state. Therefore, the first LIDAR input signal and the second LIDAR input signal both have the same polarization state (the first polarization state in this example). Although carrying light of the same polarization state, the first LIDAR input signal and the second LIDAR input signal are associated with different polarization states due to the use of a polarization beam splitter. For example, the first LIDAR input signal carries light reflected in the first polarization state, while the second LIDAR input signal carries light reflected in the second polarization state. Therefore, the first LIDAR input signal is associated with the first polarization state, while the second LIDAR input signal is associated with the second polarization state.

[0074] Since the first LIDAR input signal and the second LIDAR input signal carry light of the same polarization state, the comparison signal generated from the first LIDAR input signal has the same polarization angle as the comparison signal generated from the second LIDAR input signal.

[0075] Suitable polarization rotators include, but are not limited to, rotation of polarization maintaining fibers, Faraday rotators, half-wave plates, MEMS-based polarization rotators, and integrated optical polarization rotators using asymmetric Y-branches, Mach-Zehnder interferometers, and multimode interference couplers.

[0076] Since the outgoing LIDAR signal is linearly polarized, the first reference signal can have the same linear polarization state as the second reference signal. In addition, the components on the LIDAR adapter can be selected so that the first reference signal, the second reference signal, the comparison signal, and the second comparison signal all have the same polarization state. Figure 3 In the example disclosed in the scenario of , the first comparison signal, the second comparison signal, the first reference signal, and the second reference signal may all have light in a first polarization state.

[0077] Due to the above configuration, the first composite signal generated by the first signal processor 46 and the second composite signal generated by the second signal processor 48 are each generated by combining the reference signal and the comparison signal of the same polarization state, and thus will provide the desired beat between the reference signal and the comparison signal. For example, the composite signal is generated by combining the first reference signal and the first comparison signal of the first polarization state, and does not include or substantially does not include light of the second polarization state, or the composite signal is generated by combining the first reference signal and the first comparison signal of the second polarization state, and does not include or substantially does not include light of the first polarization state. Similarly, the second composite signal includes the second reference signal and the second comparison signal of the same polarization state, and thus will provide the desired beat between the reference signal and the comparison signal. For example, the second composite signal is generated by combining the second reference signal and the second comparison signal of the first polarization state, and does not include or substantially does not include light of the second polarization state, or the second composite signal is generated by combining the second reference signal and the second comparison signal of the second polarization state, and does not include or substantially does not include light of the first polarization state.

[0078] The above configuration results in LIDAR data for a single sample area in the field of view being generated by a plurality of different composite signals (i.e., a first composite signal and a second composite signal) from the sample area. In some cases, determining the LIDAR data for the sample area includes the electronics combining the LIDAR data from the different composite signals (i.e., the composite signal and the second composite signal). Combining the LIDAR data may include taking the average, median, or mode of the LIDAR data generated by the different composite signals. For example, the electronics may average the distance between the LIDAR nucleus and the reflecting object determined from the composite signal with the distance determined from the second composite signal, and / or the electronics may average the radial velocity between the LIDAR nucleus and the reflecting object determined from the composite signal with the radial velocity determined from the second composite signal.

[0079] In some cases, determining the LIDAR data for the sample area includes the electronic device identifying one or more composite signals (i.e., the composite signal and / or the second composite signal) as the source of LIDAR data that best represents reality (representative LIDAR data). The electronic device can then use the LIDAR data from the identified composite signal as representative LIDAR data for additional processing. For example, the electronic device can identify a signal (composite signal or second composite signal) with a larger amplitude as representative LIDAR data, and can use the LIDAR data from the identified signal for further processing by the LIDAR core. In some cases, the electronic device combines the identification of the composite signal with representative LIDAR data with the LIDAR data from different LIDAR signals. For example, the electronic device can identify each of the composite signals with an amplitude above an amplitude threshold as having representative LIDAR data, and when more than two composite signals are identified as having representative LIDAR data, the electronic device can combine the LIDAR data from each of the identified composite signals. When a composite signal is identified as having representative LIDAR data, the electronics may use the LIDAR data from the composite signal as the representative LIDAR data. When any composite signal is not identified as having representative LIDAR data, the electronics may discard the LIDAR data for the sample areas associated with the composite signals.

[0080] although Figure 3 is described in the context of components being arranged so that the first comparison signal, the second comparison signal, the first reference signal, and the second reference signal all have a first polarization state, but Figure 3Other configurations of the components in can be arranged such that a composite signal is generated by combining the reference signal and the comparison signal of the same linear polarization state, and a second composite signal is generated by combining the reference signal and the comparison signal of the same linear polarization state. For example, the beam splitter 120 can be configured such that the second portion of the system return signal has a first polarization state and the first portion of the system return signal has a second polarization state, the polarization rotator receives the first portion of the system return signal, and the outgoing LIDAR signal can have the second polarization state. In this example, both the first LIDAR input signal and the second LIDAR input signal have the second polarization state.

[0081] The above system configuration results in the first portion of the system return signal and the second portion of the system return signal being directed into different composite signals. Thus, because the first portion of the system return signal and the second portion of the system return signal are each associated with a different polarization state, but the electronics can process each composite signal, the LIDAR core compensates for a change in the polarization state of the LIDAR output signal reflected in response to the LIDAR output signal.

[0082] Figure 3 The LIDAR adapter can include additional optical components, including passive optical components. For example, the LIDAR adapter can include an optional third lens 126. The third lens 126 can be configured to couple the second LIDAR output signal at a desired location. In some cases, the third lens 126 focuses or collimates the second LIDAR output signal at a desired location. For example, the third lens 126 can be configured to focus or collimate the second LIDAR output signal on the end face 52 of the second comparison waveguide 50. The LIDAR adapter also includes one or more direction changing components 124, such as mirrors and prisms. Figure 3 The LIDAR adapter is shown to include a mirror 124 as a direction changing component that redirects a second portion of the system return signal from the circulator 100 to the end face 52 of the second comparison waveguide 50 and / or the third lens 126 .

[0083] When the LIDAR core includes a LIDAR chip and a LIDAR adapter, the LIDAR chip, the electronic device and the LIDAR adapter can be positioned on a common mounting member. Suitable common mounting members include, but are not limited to, glass plates, metal plates, silicon plates and ceramic plates. As an example, Figure 4 is a top view of a LIDAR core comprising a plurality of LIDAR cores on a common support 140. Figure 1A The LIDAR chip and local electronics 32 and Figure 2Although the local electronics 32 are shown as being located on the common support, all or a portion of the electronics may be located outside the common support. When the light source 4 is located outside the LIDAR chip, the light source may be located on or outside the common support 140. Suitable methods for mounting the LIDAR chip, electronics, and / or LIDAR adapter on the common support include, but are not limited to, epoxy, solder, and mechanical clamping.

[0084] FIG. 5A to FIG. 5C An example of a signal processor suitable for use as all or part of a signal processor selected from the group consisting of signal processor 22, first signal processor 46, and second signal processor 48 is shown. The signal processor receives a comparison signal from comparison waveguide 196 and a reference signal from reference waveguide 198. Figure 1A and Figure 1B The comparison waveguide 18 and the reference waveguide 20 shown in FIG. 1 can serve as the comparison waveguide 196 and the reference waveguide 198, Figure 1C The comparison waveguide 18 and the first reference waveguide 42 shown in FIG. 4 can serve as the comparison waveguide 196 and the reference waveguide 198, or Figure 1C The second comparison waveguide 50 and the second reference waveguide 44 shown in FIG. 4 can serve as the comparison waveguide 196 and the reference waveguide 198 .

[0085] The signal processor includes a second splitter 200 that distributes the comparison signal carried on the comparison waveguide 196 to a first comparison waveguide 204 and a second comparison waveguide 206. The first comparison waveguide 204 carries a first portion of the comparison signal to a signal combiner 211. The second comparison waveguide 208 carries a second portion of the comparison signal to a second signal combiner 212.

[0086] The signal processor includes a first splitter 202 that distributes the reference signal carried on the reference waveguide 198 to a first reference waveguide 204 and a second reference waveguide 206. The first reference waveguide 204 carries a first portion of the reference signal to a signal combiner 211. The second reference waveguide 208 carries a second portion of the reference signal to a second signal combiner 212.

[0087] The second signal combiner 212 combines the second part of the comparison signal and the second part of the reference signal into a second composite signal. Due to the frequency difference between the second part of the comparison signal and the second part of the reference signal, the second composite signal oscillates between the second part of the comparison signal and the second part of the reference signal.

[0088] The second signal combiner 212 also splits the resulting second composite signal onto a first auxiliary detector waveguide 214 and a second auxiliary detector waveguide 216. The first auxiliary detector waveguide 214 carries a first portion of the second composite signal to a first auxiliary optical sensor 218, which converts the first portion of the second composite signal into a first auxiliary electrical signal. The second auxiliary detector waveguide 216 carries a second portion of the second composite signal to a second auxiliary optical sensor 220, which converts the second portion of the second composite signal into a second auxiliary electrical signal. Examples of suitable optical sensors include germanium photodiodes (PDs) and avalanche photodiodes (APDs).

[0089] In some cases, the second signal combiner 212 divides the second composite signal so that the portion of the comparison signal included in the first portion of the second composite signal (i.e., the portion of the second portion of the comparison signal) is phase-shifted by 180° relative to the portion of the comparison signal in the second portion of the second composite signal (i.e., the portion of the second portion of the comparison signal), but the portion of the reference signal in the second portion of the second composite signal (i.e., the portion of the second portion of the reference signal) is not phase-shifted relative to the portion of the reference signal in the first portion of the second composite signal (i.e., the portion of the second portion of the reference signal). Alternatively, the second signal combiner 212 divides the second composite signal so that the portion of the reference signal in the first portion of the second composite signal (i.e., the portion of the second portion of the reference signal) is phase-shifted by 180° relative to the portion of the reference signal in the second portion of the second composite signal (i.e., the portion of the second portion of the reference signal), but the portion of the comparison signal in the first portion of the second composite signal (i.e., the portion of the second portion of the comparison signal) is not phase-shifted relative to the portion of the comparison signal in the second portion of the second composite signal (i.e., the portion of the second portion of the comparison signal). Examples of suitable light sensors include germanium photodiodes (PDs) and avalanche photodiodes (APDs).

[0090] The first signal combiner 211 combines the first part of the comparison signal and the first part of the reference signal into a first composite signal. Due to the frequency difference between the first part of the comparison signal and the first part of the reference signal, the first composite signal oscillates between the first part of the comparison signal and the first part of the reference signal.

[0091] The first signal combiner 211 also separates the first composite signal onto a first detector waveguide 221 and a second detector waveguide 222. The first detector waveguide 221 carries a first portion of the first composite signal to a first photosensor 223, which converts the first portion of the second composite signal into a first electrical signal. The second detector waveguide 222 carries a second portion of the second composite signal to a second photosensor 224, which converts the second portion of the second composite signal into a second electrical signal. Examples of suitable photosensors include germanium photodiodes (PDs) and avalanche photodiodes (APDs).

[0092] In some cases, the signal combiner 211 splits the first composite signal so that a portion of the comparison signal included in the first portion of the composite signal (i.e., a portion of the first portion of the comparison signal) is phase-shifted by 180° relative to a portion of the comparison signal in the second portion of the composite signal (i.e., a portion of the first portion of the comparison signal), but a portion of the reference signal in the first portion of the composite signal (i.e., a portion of the first portion of the reference signal) is not phase-shifted relative to a portion of the reference signal in the second portion of the composite signal (i.e., a portion of the first portion of the reference signal). Alternatively, the signal combiner 211 splits the composite signal so that a portion of the reference signal in the first portion of the composite signal (i.e., a portion of the first portion of the reference signal) is phase-shifted by 180° relative to a portion of the reference signal in the second portion of the composite signal (i.e., a portion of the first portion of the reference signal), but a portion of the comparison signal in the first portion of the composite signal (i.e., a portion of the first portion of the comparison signal) is not phase-shifted relative to a portion of the comparison signal in the second portion of the composite signal (i.e., a portion of the first portion of the comparison signal).

[0093] When the second signal combiner 212 splits the second composite signal so that the portion of the comparison signal in the first portion of the second composite signal is phase-shifted by 180° relative to the portion of the comparison signal in the second portion of the second composite signal, the signal combiner 211 also splits the composite signal so that the portion of the comparison signal in the first portion of the composite signal is phase-shifted by 180° relative to the portion of the comparison signal in the second portion of the composite signal. When the second signal combiner 212 splits the second composite signal so that the portion of the reference signal in the first portion of the second composite signal is phase-shifted by 180° relative to the portion of the reference signal in the second portion of the second composite signal, the signal combiner 211 also splits the composite signal so that the portion of the reference signal in the first portion of the composite signal is phase-shifted by 180° relative to the portion of the reference signal in the second portion of the composite signal.

[0094] The first reference waveguide 210 and the second reference waveguide 208 are configured to provide a phase shift between a first portion of the reference signal and a second portion of the reference signal. For example, the first reference waveguide 210 and the second reference waveguide 208 can be configured to provide a 90 degree phase shift between the first portion of the reference signal and the second portion of the reference signal. For example, one reference signal portion can be an in-phase component and the other reference signal portion can be an orthogonal component. Therefore, one of the reference signal portions can be a sine function and the other reference signal portion can be a cosine function. In one example, the first reference waveguide 210 and the second reference waveguide 208 are configured so that the first reference signal portion is a cosine function and the second reference signal portion is a sine function. Therefore, a portion of the reference signal in the second composite signal is phase shifted relative to a portion of the reference signal in the first composite signal, however, a portion of the comparison signal in the first composite signal is not phase shifted relative to a portion of the comparison signal in the second composite signal.

[0095] The first light sensor 223 and the second light sensor 224 may be connected as a balanced detector, and the first auxiliary light sensor 218 and the second auxiliary light sensor 220 may also be connected as a balanced detector. Figure 5B A schematic diagram of the relationship between the electronics, first light sensor 223, second light sensor 224, first auxiliary light sensor 218, and second auxiliary light sensor 220 is provided. The symbol of a photodiode is used to represent the first light sensor 223, second light sensor 224, first auxiliary light sensor 218, and second auxiliary light sensor 220, but one or more of these sensors may have other configurations. In some cases, Figure 5B All components shown in the schematic are included on the LIDAR chip. In some cases, Figure 5B The components shown in the schematic diagram are distributed between the LIDAR chip and the electronic devices located outside the LIDAR chip.

[0096] The electronics connect the first light sensor 223 and the second light sensor 224 as a first balanced detector 225, and connect the first auxiliary light sensor 218 and the second auxiliary light sensor 220 as a second balanced detector 226. In particular, the first light sensor 223 and the second light sensor 224 are connected in series. In addition, the first auxiliary light sensor 218 and the second auxiliary light sensor 220 are connected in series. The series connection in the first balanced detector communicates with the first data line 228, which carries the output from the first balanced detector as a first data signal. The series connection in the second balanced detector communicates with the second data line 232, which carries the output from the second balanced detector as a second data signal. The first data signal is an electrical representation of the first composite signal, and the second data signal is an electrical representation of the second composite signal. Therefore, the first data signal includes contributions from the first waveform and the second waveform, and the second data signal is a composite of the first waveform and the second waveform. The portion of the first waveform in the first data signal is phase-shifted relative to the portion of the first waveform in the first data signal, but the portion of the second waveform in the first data signal is in phase relative to the portion of the second waveform in the first data signal. For example, the second data signal includes a portion of the reference signal that is phase-shifted relative to a different portion of the reference signal included in the first data signal. In addition, the second data signal includes a portion of the comparison signal that is in phase with a different portion of the comparison signal included in the first data signal. The first data signal and the second data signal beat due to the beat between the comparison signal and the reference signal, i.e., the beat in the first composite signal and the second composite signal.

[0097] The local electronic device 32 includes a beat frequency finder 238 configured to find the beat frequency of the composite signal. The beat frequency finder 238 can perform a mathematical transformation on the first data signal and the second data signal. For example, the mathematical transformation can be a complex Fourier transform with the first data signal and the second data signal as input. Since the first data signal is an in-phase component and the second data signal is its orthogonal component, the first data signal and the second data signal together act as a complex data signal, wherein the first data signal is the real part of the input and the second data signal is the imaginary part of the input.

[0098] The beat frequency finder 238 includes a first analog-to-digital converter (ADC) 264 that receives a first data signal from the first data line 228. The first analog-to-digital converter (ADC) 264 converts the first data signal from an analog form to a digital form and outputs a first digital data signal. The beat frequency finder 238 includes a second analog-to-digital converter (ADC) 266 that receives a second data signal from the second data line 232. The second analog-to-digital converter (ADC) 266 converts the second data signal from an analog form to a digital form and outputs a second digital data signal. The first digital data signal is a digital representation of the first data signal, and the second digital data signal is a digital representation of the second data signal. Therefore, the first digital data signal and the second digital data signal together act as a complex signal, wherein the first digital data signal acts as a real part of the complex signal, and the second digital data signal acts as an imaginary part of the complex data signal.

[0099] The beat frequency finder 238 includes a transformer 268 that receives a complex data signal. For example, the transformer 268 receives as input a first digital data signal from a first analog-to-digital converter (ADC) 264 and also receives as input a second digital data signal from a second analog-to-digital converter (ADC) 266. The transformer 268 can be configured to perform a mathematical transformation on the complex signal to convert from the time domain to the frequency domain. The mathematical transformation can be a complex transformation, such as a complex fast Fourier transform (FFT). The complex transformation (e.g., a complex fast Fourier transform (FFT)) provides a clear solution for the frequency offset of the LIDAR input signal relative to the LIDAR output signal caused by the radial velocity between the reflecting object and the LIDAR chip. The electronic device uses the one or more frequency peaks output from the transformer 268 for further processing to generate LIDAR data (the distance and / or radial velocity between the reflecting object and the LIDAR chip or LIDAR core). The local electronic device 32 may include a peak finder (not shown) to identify the beat frequency of the one or more frequency peaks.

[0100] The local electronics 32 may include a preliminary LIDAR data generator 269 configured to receive the beat frequency from the transducer 268. The preliminary LIDAR data generator 269 is configured to generate preliminary LIDAR data for the sample area. The LIDAR data for the sample area includes values ​​of radial velocity and / or separation distance between the LIDAR system and the object in the sample area. In some cases, the LIDAR data includes an indicator that the LIDAR data for the sample area is "unavailable". In some cases, the preliminary LIDAR data generator 269 calculates LIDAR data that serves as preliminary LIDAR data. For example, in some cases, the preliminary LIDAR data generator 269 calculates the radial velocity and / or separation distance between the LIDAR system and the object in the sample area as preliminary LIDAR data. As will be discussed below, other examples of preliminary LIDAR data that can be calculated by the preliminary data generator include, but are not limited to, possible solutions for the LIDAR data for the sample area and potential radial velocity magnitude indicators and / or velocity magnitude indicators for the sample area. The transformer 268 and / or the preliminary LIDAR data generator 269 may perform attributed functions using firmware, hardware, or software, or a combination thereof.

[0101] although Figure 5A A signal combiner is shown that combines a portion of the reference signal with a portion of the comparison signal, but the signal processor may include a single signal combiner that combines the reference signal with the comparison signal to form a composite signal. Thus, at least a portion of the reference signal and at least a portion of the comparison signal may be combined to form a composite signal. The combined reference signal portion may be the entire reference signal or a portion of the reference signal, and the combined comparison signal portion may be the entire comparison signal or a portion of the comparison signal.

[0102] The electronics adjust the frequency of the system output signal over time. The system output signal has a frequency versus time pattern with a repeating cycle. Figure 5C An example of a suitable frequency versus time pattern of the system output signal is shown. The fundamental frequency (f o ) can be the frequency of the system output signal at the beginning of the cycle.

[0103] Figure 5C Shown is the cycle j and cycle j+1 The frequency-versus-time relationship of two cyclic sequences of . In some cases, the frequency-versus-time pattern repeats in each cycle, such as Figure 5C The cycles shown do not include a repositioning period and / or the repositioning period is not located between cycles. Therefore, Figure 5C Results of consecutive scans are shown.

[0104] Each cycle includes M data cycles, each of which is associated with a cycle index m and is labeled DP m .exist Figure 5C In the example shown in Figure 1, each cycle consists of three data cycles, labeled DP m , where m = 1 and 2. In some cases, such as Figure 5C As shown in FIG. 1 , the frequency-to-time pattern is the same for data periods corresponding to each other in different cycles. Corresponding data periods are data periods with the same cycle index. Therefore, each data period DP1 can be regarded as a corresponding data period, and the related frequency-to-time pattern is Figure 5C At the end of the cycle, the electronics restores the frequency to the same frequency level it had at the beginning of the previous cycle.

[0105] In the data period DP m During this time, the electronics operates the light source so that the frequency of the system output signal changes at a linear rate α. m (chirp rate) changes. Figure 5C , α2=-α1.

[0106] Figure 5C The sample regions are labeled, each of which is associated with a sample region index k and is labeled SR k . Figure 5C The sample area SR is marked k-1 To SR k+1 Each sample area is Figure 5C The sample region SR is illuminated by the system output signal during the data period associated with the sample region shown. k+1 The system output signal is illuminated during the data period marked as DP2 in cycle j+1 and the data period marked as DP1 in cycle j+1. k+1 The sample regions SR are associated with the data periods labeled DP1 and DP2 in cycle j+1. The sample region index k can be assigned relative to time. For example, the sample regions can be illuminated by the system output signal in the order indicated by the index k. Therefore, the sample region SR 10 It can be after sample region SR9 and before SR 11 Previously irradiated.

[0107] The frequencies output from the complex Fourier transform represent the beat frequencies of composite signals, each of which includes a comparison signal for a reference signal beat frame. The beat frequencies from two or more different data periods associated with the same sample area can be combined to generate LIDAR data. For example, the beat frequencies in the sample area SR k The beat frequency determined from DP1 during the irradiation period is related to the kThe beat frequency combination determined from DP2 during the illumination period is used to determine the sample region SR k As an example, the following equation applies during a data period in which the electronics increases the frequency of the outgoing LIDAR signal, e.g. Figure 5C What happens in data cycle DP1: ub =-f d +α u τ, where f ub is the frequency provided by converter 268, f d represents the Doppler frequency shift (f d =2V k f c / c), where f c represents the optical frequency (f o ), c represents the speed of light, V k is the radial velocity between the reflecting object and the LIDAR core, where the direction from the reflecting object toward the chip is assumed to be the positive direction, c is the speed of light, and α u The chirp rate (α) of the data period that represents the frequency increase of the system output signal over time m )(in this case α1). The radial velocity may be a relative radial velocity, since both the LIDAR core and the object may be in motion or the LIDAR core and / or the object may be stationary.

[0108] The following equation applies during such data periods where the frequency of the outgoing LIDAR signal decreases, e.g. Figure 5C What happens in data cycle DP2: db =-f d -α d τ, where f db is the frequency provided by converter 268, and α d The chirp rate (α) of the data period that represents the frequency increase of the system output signal over time m )(in this case, α2). In both equations, f d and τ are unknowns. These equations can be solved for these two unknowns. The electronics (e.g., preliminary LIDAR data generator 269) can calculate the Doppler frequency shift (V k =c*f d / (2f c )) Calculate the radial velocity (V) of sample area k k ) and / or the separation distance (R k ).

[0109] When the LIDAR kernel includes FIG. 5A to FIG. 5CWhen the signal processor is constructed in the disclosed manner in the context of the present invention, and the electronic device is configured to calculate the radial velocity and distance between the LIDAR core and the object for each sample area, the LIDAR core is suitable for use as a distance and velocity core. However, the LIDAR core may include FIG. 5A to FIG. 5B In the case of the disclosed signal processor, the electronic device can be configured to calculate radial velocity instead of distance. In these cases, the LIDAR core is suitable for use as a velocity core.

[0110] In the example of the velocity kernel, the electronics may operate the light source 4 such that Figure 5C The system output signal disclosed in the context of having a frequency as a function of time is replaced by a system output signal whose frequency is not a function of time. For example, the frequency of the system output signal is Figure 5C As shown, it may be constant during each data period. As an example, the system output signal may be a continuous wave (CW). For example, the outgoing LIDAR signal and therefore the system output signal may be a non-chirped continuous wave (CW). As an example, the outgoing LIDAR signal and therefore the LIDAR output signal may be expressed as Equation 2: G*cos(H*t), where G and H are constants and t represents time. In some cases, G represents the square root of the power of the outgoing LIDAR signal.

[0111] Since the frequency of the system output signal is constant, changing the distance between the reflecting object and the LIDAR chip does not result in a change in the frequency of the LIDAR input signal. Therefore, the separation distance has no effect on the frequency offset of the LIDAR input signal relative to the LIDAR output signal. Therefore, the effect of the separation distance is eliminated or substantially eliminated from the frequency offset of the LIDAR input signal relative to the system output signal.

[0112] The velocity core can have Figure 5A and Figure 5B The signal processor is constructed in the manner disclosed in the context of Figure 5B As discussed in the context of FIG. 2 , a first analog-to-digital converter (ADC) 264 receives a first data signal 228 and outputs a first digital data signal. A second analog-to-digital converter (ADC) 266 receives a second data signal and outputs a second digital data signal. The first digital data signal is a digital representation of the first data signal, and the second digital data signal is a digital representation of the second data signal. Therefore, the first digital data signal and the second digital data signal together act as a complex signal, wherein the first digital data signal acts as the real part of the complex signal, and the second digital data signal acts as the imaginary part of the complex data signal.

[0113] The transformer 268 receives a complex data signal. The transformer 268 can be configured to perform a mathematical transform on the complex signal to convert from the time domain to the frequency domain. The mathematical transform can be a complex transform, such as a complex fast Fourier transform (FFT). The complex transform (e.g., a complex fast Fourier transform (FFT)) provides a clear solution for the frequency offset of the LIDAR input signal relative to the LIDAR output signal caused by the radial velocity between the reflecting object and the LIDAR chip. Since the frequency offset provided by the transformer 268 has no input from the frequency offset caused by the separation distance between the reflecting object and the LIDAR chip, and due to the complex nature of the velocity data signal, the output of the transformer 268 can be used to calculate the radial velocity between the reflecting object and the LIDAR chip. For example, the electronic device (e.g., a preliminary LIDAR data generator) can use the following equation 4 to approximate the radial velocity (v) between the reflecting object and the LIDAR chip: v=c*f d / (2*f c ), where f d is approximately the peak frequency output from converter 268, c is the speed of light, and f c Represents the frequency of the LIDAR output signal. Therefore, the velocity kernel does not require multiple data periods and / or chirps to calculate the radial velocity.

[0114] The first analog-to-digital converter (ADC) 264 converts the first data signal into a first digital data signal by sampling the first data signal at a sampling rate. Similarly, the second analog-to-digital converter (ADC) 266 converts the second data signal into a second digital data signal by sampling the second data signal at a sampling rate. When the velocity core uses a continuous wave as the first data signal and the second data signal, the influence of the distance between the reflecting object and the LIDAR chip is effectively eliminated from the beat of the composite signal and the resulting electrical signal. Therefore, the beat frequency of the composite signal is reduced and the required sampling rate is reduced. For example, the sampling rate of the analog-to-digital converter in the distance and velocity core can be on the order of 4GSPS. In contrast, the sampling rate of the analog-to-digital converter in the velocity core can be on the order of 400MSPS.

[0115] although Figure 5A and Figure 5B The signal processor is disclosed in the context of complex data signals, but real data signals can also be used. Figure 5A and Figure 5B The signal processor may be modified to not include components associated with the second data signal together, and the transformer 268 may be configured as a real Fourier transform (FFT). Thus, the signal processor may include a single signal combiner 211 and a single analog-to-digital converter (ADC).

[0116] A LIDAR system may include one or more range and velocity cores and one or more velocity cores. As an example, Fig. 6A A LIDAR system is shown comprising a plurality of different cores on a common support 140. Each LIDAR core may be as shown in FIG. Figure 1A 5, or have an alternative configuration. One or more of the LIDAR cores may be a velocity core, and one or more of the LIDAR cores may be a range and velocity core. For illustration purposes, Fig. 6A The LIDAR core in the LIDAR system includes a range and velocity core 270 and three velocity cores 272 .

[0117] Each LIDAR core outputs a different system output signal. The system output signals are received by a redirecting component 274 that redirects the system output signal. Suitable redirecting components 274 include, but are not limited to, convex lenses and concave mirrors. The system output signal output from the collimator 274 is received by one or more beam steering components 276 that output the system output signal. The direction in which the system output signal travels away from the LIDAR system is Fig. 6A The electronics may operate one or more beam steering components 276 to steer each system output signal to a different sample region in the field of view. Fig. 6A As shown by the arrows marked A and B in FIG, one or more beam steering components 276 can be configured to enable the electronic device to steer the system output signal in two or three dimensions. Thus, one or more beam steering components 276 can be used as a beam steering mechanism, which is operated by the electronic device to steer the system output signal within the field of view of the LIDAR system. Suitable beam steering components 276 include, but are not limited to, movable mirrors, MEMS mirrors, optical phased arrays (OPA), optical gratings, and actuated optical gratings. In some cases, the redirecting component 274 and / or one or more beam steering components 276 are configured to operate on the system output signal so that the system output signal is collimated or substantially collimated when traveling away from the LIDAR system. Additionally or alternatively, the LIDAR system may include one or more collimating optical components (not shown) that operate on the system output signal so that the system output signal is collimated or substantially collimated when traveling away from the LIDAR system.

[0118] As described above, the sampling rate of the ADC on the velocity core can be lower than the sampling rate of the ADC on the range and velocity core. In some cases, the LIDAR component includes a velocity core having an ADC with a sampling rate greater than 100, 200, or 300 and less than 500, 800, or 1000MSPS (million samples per second) and / or a range and velocity core having an ADC with a sampling rate greater than 1, 2, or 3 and less than 5, 8, or 10GSPS (billion samples per second). In some cases, the ratio of the sampling rate of the ADC on one or more velocity cores to the sampling rate of the ADC on one or more range and velocity cores is greater than 2:1, 5:1, or 10:1 and less than 15:1, 50:1, or 100:1. Additionally or alternatively, the velocity core can be a lower bandwidth core compared to the range and velocity core. As an example, the photodetector in the velocity core can be used with a transimpedance amplifier (TIA) that converts the current of the resulting data signal output from the photodetector into a voltage. For example, Figure 5B A transimpedance amplifier 282 is shown, which is optionally positioned along the first data line 228 and the second data line 232 to convert the current of the first data signal to a voltage and convert the current of the second data signal to a voltage. The transimpedance amplifier (TIA) and associated circuits in one or more speed cores can be configured to operate at a lower bandwidth than the transimpedance amplifier (TIA) and associated circuits in one or more distance and speed cores. In some cases, the LIDAR component includes one or more speed cores that operate at a bandwidth range greater than 0.1Gz, 0.2Gz or 0.3Gz and less than 0.5Gz, 1Gz or 2Gz; and one or more distance and speed cores that operate at a bandwidth range greater than 0.5Gz, 1Gz or 1.5Gz and less than 2Gz, 3Gz or 5Gz. In some cases, the ratio of the bandwidth of one or more distance and speed cores to the bandwidth of one or more speed cores is greater than 2:1, 4:1 or 8:1 and less than 10:1, 15:1 or 20:1. The bandwidth requirements of the speed core relative to the range and speed core are reduced, so that the speed core can operate at a lower frequency, thereby reducing the cost associated with the components on the speed core. In some cases, the LIDAR assembly includes one or more speed cores whose TIAs operate at a bandwidth range greater than 0.1Gz, 0.2Gz or 0.3Gz and less than 0.5Gz, 1Gz or 2Gz; and one or more range and speed cores whose TIAs operate at a bandwidth range greater than 0.5Gz, 1Gz or 1.5Gz and less than 2Gz, 3Gz or 5Gz. In some cases, the ratio of the bandwidth of the TIA of one or more range and speed cores to the bandwidth of the TIA of one or more speed cores is greater than 2:1, 4:1 or 8:1 and less than 10:1, 15:1 or 20:1.

[0119] Figure 6B Shows Figure 5CThe relationship between the data period and the field of view of the LIDAR system is disclosed in . For illustration, only the system output signals of the range and velocity kernel C1 are shown. The field of view is represented by the SR k-1 To SR k+1 The system output signal is scanned along the solid line direction marked as "scan". The system output signal passes through a series of sample regions (SR k-1 To SR k+1 ) scan. The set of sample areas scanned by the system output signal constitutes the field of view of the LIDAR system. The (one or more) objects in the field of view may change over time. Therefore, the position of the sample area is determined relative to the LIDAR system, rather than relative to the environment in which the LIDAR system is located. For example, the sample area can be defined as being within an angular range relative to the LIDAR system. Figure 6B The dashed lines labeled as scans in FIG. 1 show that the scanning of the sample area can be repeated in multiple scanning cycles. Thus, each scanning cycle can cause the system output signal to scan through the same sample area as the object in the field of view moves and / or changes. The sample areas in the field of view can be scanned in the same order in different scanning cycles, or can be scanned in different orders in different scanning cycles.

[0120] Each sample region corresponds to a portion of one of the data periods in Figure 6B In the figure, they are marked as DP1 or DP2 respectively. Figure 5C As shown, the chirp rate from core C1 during data period DP1 is α1, and the modulation rate during data period DP2 is α2. As described above, the system output signals from speed cores C2-C4 may not have frequency chirp, but may have a constant frequency.

[0121] Each sample area includes a k The dotted line is marked as L k The dotted line can serve as a position reference line for the sample area k. Figure 6B Including marked L k-1 To L k+1 The position reference line. Figure 6B In the example, each position reference line (L k ) is plotted along the vertical axis of the sample region with sample region index k.

[0122] Figure 6B The figure is marked as θ k where k represents the sample region index k. Orientation angle θ k The sample area SR can be measured k Angular orientation relative to the LIDAR system. In some cases, the orientation angle θ k Relative to the position reference line Lk Take measurements such as Figure 6B Therefore, the orientation angle θ k Can measure the position reference line L k angular orientation. Figure 6B shows that the LIDAR system has a two-dimensional field of view, so a single angle (θ k ) can limit the sample area SR k Angular orientation relative to the LIDAR system; however, the field of view is typically three-dimensional. Therefore, the LIDAR system may use two or more angles and / or other variables to define the orientation of the sample area relative to the LIDAR system.

[0123] Figure 6C Shows Figure 6B For example, two different objects are located in the field of view of the LIDAR system. Each position reference line (L k ) from the LIDAR system to the marker fl k The field of view extends to a distance R k . Distance R k Indicates that due to the sample area SR k During the illumination period, the system output signals transmitted, the distance and velocity kernel electronics determine the values ​​of the distance between the LIDAR system and the object. Therefore, the values ​​marked as fl k The field of view position can be expressed along the position reference line (L k ) electronic device determines the location of the object surface at which the output signal of the reflection system is located. The set of view positions in the field of view can serve as a point cloud.

[0124] With distance R k The associated field of view position (fl k ) can also be related to the radial velocity V k where k represents the sample region index. The radial velocity V k It can be the radial velocity generated by the electronics for the sample region with sample region index k.

[0125] With each field position (fl k ) is associated with one or more orientation angles (θ k ) and distance R k can effectively act as polar or spherical coordinates. Thus, the electronics can optionally convert the field of view position fl k The coordinates of are converted to other coordinate systems, including but not limited to Cartesian coordinates. As an example, Fig.6D An example of a number of different field of view positions in a sample area of ​​the distance and velocity kernel C1 is shown. In addition, the axes of the Cartesian coordinate system are shifted over the field of view. Thus, the field of view position fl kThe position of is also shown relative to a Cartesian coordinate system. The electronics may optionally use a coordinate system corresponding to each field of view position (fl k ) is associated with an orientation angle (θ k ) and distance R k Set the field of view position (fl k ) to other coordinate systems.

[0126] In some cases, the field of view position (fl k ) does not exist in all or part of the sample area. For example, when the sample area (SR k ), a beat signal is generally not generated and LIDAR data is not generated for the sample area. Therefore, some sample area indices may not correspond to the field of view position (fl k ) association.

[0127] When the kernel is a range and velocity kernel, all or part of the sample area (range and velocity sample area, RV sample area) illuminated by the kernel can be respectively associated with the field of view position, coordinates, distance R k and radial velocity V k In contrast, when the kernel is a velocity kernel, all or part of the sample area illuminated by the kernel (velocity sample area, Vsample area) can be individually associated with the field of view position, coordinates and radial velocity V k association. Figure 6B The coordinates are shown as two-dimensional Cartesian coordinates (x, y), but three-dimensional coordinates and / or other coordinate systems are possible. In some cases, the coordinates are the field of view position (fl k ) in polar or spherical coordinates.

[0128] Figure 7 is a two-dimensional diagram of the LIDAR system's field of view. For example, Figure 7 The 3D field of view may be represented by a projection of the 3D field of view onto a 2D plane. The field of view includes a plurality of rectangles, each of which may represent a projection of a sample region in the field of view onto a plane. For illustration, the sample regions are shown as rectangles, and the sample regions may have other geometric shapes. The sample regions are each labeled SR k , where k ranges from 1 to 30.

[0129] The sample areas are each marked as C i , where i is the core index identifying the core that illuminates the sample area. The core index is an integer that can be extended from i=1 to i=M, where M is the number of system output signals output by the LIDAR system. Label C i Indicates which of the system output signals illuminates the sample area. For example, the sample area marked as C1 is illuminated by Fig. 6Airradiated by the distance and velocity nuclei labeled C1 in . Thus, the sample region labeled C1 is an RV sample region. In contrast, the sample region labeled C2 is irradiated by the velocity nuclei labeled C2; the sample region labeled C3 is irradiated by the velocity nuclei labeled C3; and the sample region labeled C4 is irradiated by the velocity nuclei labeled C4. Thus, the sample regions labeled C2-C4 are V sample regions.

[0130] Figure 7 The arrows are labeled A. The arrows indicate the order in which the system output signal scans through the field of view. In addition, the sample region index (k) is assigned to the sample regions in chronological order. Therefore, the samples labeled C2 and SR 11 The sample area is marked as C2 and SR 12 The sample area is scanned by velocity kernel C1 before being scanned by velocity kernel C2.

[0131] The LIDAR system includes electronics configured to operate the LIDAR system. The electronics may include local electronics 32 and common electronics 280 from one or more cores. Common electronics 280 may be located at Fig. 6A The common electronics 280 may be located on the common support 140 as shown, or may be located outside the common support 140. The common electronics 280 may be located in the same physical location and / or housing as the local electronics associated with the different cores, or may be located in a different physical location and / or housing than the local electronics 32 associated with the different cores.

[0132] The common electronics 280 may be in electrical communication with the local electronics 32 associated with the different cores. For example, the common electronics 280 may include a LIDAR data generator 291 that is in electrical communication with the local electronics 32 from the different cores. Figure 8 Common electronics 280 is shown having a LIDAR data generator 291 configured to receive preliminary LIDAR data generated by preliminary LIDAR data generator 269 in a different core.

[0133] The electrical communication between the common electronic device 280 and the local electronic devices 32 associated with different cores allows the common electronic device 280 to access preliminary LIDAR data generated by the different cores. For example, the common electronic device 280 can access the distance and / or speed calculated by the local electronic device 32 associated with the distance and speed core for the sample area, and / or can access the speed calculated by the local electronic device 32 associated with the speed core for the sample area. The LIDAR data generator 291 can combine the preliminary LIDAR data generated by the different cores to calculate the LIDAR data for one of the sample areas. Additionally or alternatively, the LIDAR data generator 291 can combine the preliminary LIDAR data generated by the same core for different sample areas to calculate the LIDAR data for one of the sample areas.

[0134] The preliminary LIDAR data generated by the electronic device for the sample area may include isolated LIDAR data and shared LIDAR data. The isolated LIDAR data may be LIDAR data calculated by the local electronic device for the sample area, wherein one or more beat frequencies used to calculate the isolated LIDAR data are generated by the system output signal illuminating the sample area. Therefore, the system output signal is not required to illuminate another sample area to calculate the isolated LIDAR data of the sample area. Therefore, the radial velocity (V) of the V sample area with sample area index k can be calculated without illuminating another one of the sample areas with the system output signal. k ). However, the LIDAR data generator 291 may combine isolated LIDAR data and / or shared LIDAR data from different cores and / or generated by illuminating different sample regions to approximate shared LIDAR data. Thus, shared LIDAR data for a sample region may be calculated by combining beat frequencies generated by illuminating different sample regions. As an example, the distance (R) of a V sample region may be calculated by combining beat frequencies from a plurality of different sample regions. k ). Therefore, the distance (R k ) can be shared LIDAR data, and for the radial velocity (V k ) can be isolated LIDAR data. In contrast, for the same V sample area, the distance (R k ) and radial velocity (V k ) can all be isolated LIDAR data.

[0135] An example of computing shared LIDAR data is to calculate the distance (R) of the target V sample area from the coordinates of the field of view position associated with the RV sample area by interpolating or extrapolating the coordinates of the field of view position of the V sample area. k). When the coordinates are polar coordinates or spherical coordinates, the range (distance) (R) of the target V sample area k can be directly extracted from the coordinates. k ). Alternatively, the range (distance) (Rk) of the V sample area k can be calculated based on the coordinates. For example, when the coordinates are Cartesian coordinates, the coordinates can be converted into polar coordinates or spherical coordinates, and the expected distance can be extracted. In some applications of the LIDAR system, the expected data of the V sample area is the coordinates of the field of view position of the sample area, rather than the distance. Therefore, in some applications, the distance is not calculated for all or part of the V sample area for which the coordinates are calculated. The distance and / or coordinates estimated for the V sample area can serve as the position data of the V sample area. Therefore, interpolation and extrapolation provide an estimate of the position data of the object in the target sample area. The interpolation or extrapolation is performed relative to the coordinates and / or distances from multiple RV sample areas. The field of view position in the RV sample area based on which the position data of the V area is calculated serves as a known point in the interpolation or extrapolation algorithm.

[0136] The LIDAR data generator 291 may identify target sample areas for which coordinates and / or distances are to be interpolated or extrapolated, and may identify potential sample areas including potential data points from which coordinates and / or distances are to be interpolated or extrapolated. As an example, Fig. 9 Shown from Figure 7 The field of view of FIG. 1 is a field of view of FIG. 1 , wherein the sample region labeled SR6 for core C4 is identified as the target sample region. Potential data points include field of view locations in the RV sample region that are physically located near the target sample region. Fig. 6A The kernel labeled C1 in the LIDAR system in is the only range and velocity kernel, so every potential data point is labeled C1.

[0137] The LIDAR data generator 291 may apply a recognition algorithm to identify potential data points. The recognition algorithm may associate a particular set of RV sample regions with each different possible target sample region. The association may be specific to each possible target sample region, or may be general to multiple different possible target sample regions. As an example of a specific association, the recognition algorithm may Fig. 9 The potential set of data points shown in Fig. 9 As an example of a general association, the recognition algorithm can Fig. 9 The potential data point pattern shown in is associated with a plurality of different target sample regions, each of which is located at Fig. 9 The target sample area is in the same sample area row.

[0138] In another example of a suitable recognition algorithm, potential data points may be identified by applying recognition criteria to the target sample region and the adjacent RV sample region. fl Each of the view positions can be identified as a potential data point, where R fl is a constant.

[0139] The LIDAR data generator 291 may compare the LIDAR data at the potential data point to one or more criteria to determine which potential data point is suitable for use as a known data point. In some cases, the one or more criteria include or consist of a velocity criterion that is a function of the radial velocity associated with the potential data point. For example, the LIDAR data generator 291 may compare the LIDAR data associated with the target sample area and the data associated with each potential data point to one or more velocity criteria to determine whether the potential data point is suitable for use as a known data point.

[0140] The speed criterion may be selected so that the criterion is satisfied when the same object may be located in the target sample area and the sample area associated with the potential data point. When the object is located in the target sample area and the sample area associated with the potential data point, the radial velocities calculated for these sample areas may be the same or similar. For example, an example of applying the speed criterion may include comparing a variable with a threshold value, which is a function of the radial velocity calculated for the target sample area and the velocity associated with the potential data point. The threshold value may be a constant, or may be a function of the radial velocity calculated for the target sample area and / or the radial velocity calculated for the potential data point. As an example, the difference between the radial velocity associated with the target sample area and the radial velocity associated with the potential data point may be compared with a speed threshold value. When the difference is less than the speed threshold value, the speed criterion is satisfied, but when the difference is greater than or equal to the speed threshold value, the speed criterion is not satisfied. Another example of applying the speed criterion compares the percentage change from the radial velocity associated with the target sample area to the radial velocity associated with the potential data point with the speed threshold value. When the difference is less than the speed threshold value, the speed criterion is satisfied, but when the difference is greater than or equal to the speed threshold value, the speed criterion is not satisfied.

[0141] Potential data points that meet one or more criteria are marked as known data points, while potential data points that do not meet one or more criteria are not marked as known data points. As an example, Fig. 9The field of view positions in the RV sample areas marked as F in the figure can be marked as known data points, while the field of view positions in the RV sample areas not marked as F are not marked as known data points. The LIDAR data generator 291 uses the coordinates associated with the known data points in an interpolation algorithm or an extrapolation algorithm to estimate the coordinates of the field of view positions in the target sample area. In contrast, potential data points that are not marked as known data points are not used in the interpolation algorithm or the extrapolation algorithm. Therefore, in some cases, the number of known data points used in the interpolation algorithm or the extrapolation algorithm varies depending on the radial velocity calculated for the potential data points.

[0142] Suitable interpolation algorithms include, but are not limited to, piecewise constant interpolation, linear interpolation, polynomial interpolation, spline interpolation, function approximation interpolation, and Gaussian interpolation. Suitable extrapolation algorithms include, but are not limited to, linear extrapolation, polynomial extrapolation, conic extrapolation, and French curve extrapolation.

[0143] Fig.10 is a flow chart for generating range data for a sample area illuminated by a velocity kernel in a LIDAR system that includes range and velocity kernels.

[0144] At block 300, the local electronics of each core generate isolated LIDAR data for the sample area scanned by the core. For example, the preliminary LIDAR data generator 269 in the velocity core calculates radial velocity for each V sample area scanned by the core. In addition, the preliminary LIDAR data generator 269 in the range and velocity core calculates the range and radial velocity for each RV sample area scanned by the RV core. As described above, one or more orientation angles (θ) associated with the sample area are k ) and the range or distance R calculated for the sample area k may effectively serve as polar or spherical coordinates of the field of view position in that sample region. Alternatively, the local electronics may optionally convert the polar or spherical coordinates to other coordinate systems. Thus, the preliminary LIDAR data generator 269 associated with each range and velocity kernel may calculate coordinates of radial velocity and field of view position associated with the RV sample region scanned by those kernels.

[0145] At block 302, the LIDAR data generator 281 may identify one of the V sample regions to serve as a target sample region for which coordinates and / or distances are to be estimated. A field of view position in the target sample region may serve as a target field of view position.

[0146] From block 302, the LIDAR data generator 281 may proceed to block 304. At block 304, the LIDAR data generator 281 may execute an identification algorithm to identify RV sample regions containing field of view locations that may be suitable for serving as known data points. The identified RV sample regions and / or field of view locations may serve as potential data points.

[0147] The LIDAR data generator 281 may proceed from block 304 to block 306. At block 306, the LIDAR data generator 281 may initialize the RV sample regions of the identified potential data points and / or the identified potential data points. For example, the LIDAR data generator 281 may mark each identified potential data point and / or the sample region containing the identified potential data point as not being a known data point.

[0148] From process block 306, the LIDAR data generator 281 may proceed to process block 308. At process block 308, the LIDAR data generator 281 may compare the radial velocity associated with the target field of view position (or target V sample area) and the radial velocity associated with the target potential data point (or potential RV sample area) in the potential data points (or potential RV sample area) to one or more velocity thresholds to determine whether it is possible that the same object is located in the sample area associated with the target field of view position and is also located in the sample area associated with the potential field of view position. This comparison may be repeated until each potential data point has served as a target potential data point, until a predetermined number of potential data points have served as a target potential data point, or until a predetermined number of potential data points have met one or more velocity criteria. The LIDAR data generator 281 may mark each potential data point that meets one or more velocity criteria as a known data point.

[0149] From block 308, the LIDAR data generator 281 may proceed to block 310. At block 310, the LIDAR data generator 281 may interpolate or extrapolate the coordinates of the target field of view position from the coordinates of the known data points. Potential data points that are not marked as known data points are not used for interpolation or extrapolation.

[0150] In some cases, the target interpolation or extrapolation includes the interpolation or extrapolation of the distance associated with the target field of view position. For example, when the target interpolation or extrapolation is performed in polar coordinates or spherical coordinates, the distance is one of the coordinate variables. Alternatively, the distance can be calculated from the coordinates of the target field of view position. When the target field of view position fl k When determining the distance, this distance can serve as the V sample area SR k The distance R k Therefore, V sample area SR k can be related to the radial velocity V kTherefore, the V sample area that has served as the target sample area can be associated with the field of view position, the estimated distance R k and radial velocity V k association.

[0151] The LIDAR data generator 281 may proceed from process block 310 to determination block 312, where it is determined whether a desired number of V sample areas have served as target sample areas. It may be desirable to have all or a portion of the sample areas in the field of view of the LIDAR system serve as target sample areas. In some cases, each V sample area in the field of view of the LIDAR system is to serve as a target sample area. Therefore, in some cases, the common electronic device may determine whether each V sample area in the field of view of the LIDAR system has served as a target sample area. When the determination is negative, the common electronic device may return to process block 302.

[0152] When the determination at decision block 310 is positive, the LIDAR data generator 281 has estimated the distance (R k ) value. The estimated distance (R k ) value is estimated from the beat frequency of the composite signal generated by illuminating multiple different sample areas with the system output signal. Therefore, the estimated distance (R k ) values ​​can be considered as shared LIDAR data. The estimated distance (R k ) values ​​can be added to the isolated LIDAR data of the RV region and the isolated LIDAR data of the V region to provide LIDAR data of the LIDAR system field of view. Therefore, all or part of the V sample area in the LIDAR system field of view is consistent with the field of view position, estimated distance R k and radial velocity V k Similarly, all or part of the RV sample area in the field of view of the LIDAR system is associated with the field of view position and the estimated distance R k and radial velocity V k association.

[0153] When the determination at determination block 310 is positive, the common electronics 280 proceeds from determination block 312 to process block 314. At process block 314, the common electronics may further process the LIDAR data of the LIDAR system field of view. The further processing varies with the application of the LIDAR system. Examples of further processing applications include, but are not limited to, image generation, self-driving vehicle control, point cloud generation, object recognition, and statistical analysis. The further processing may utilize all or part of the distance, radial velocity, and field of view position associated with the V sample area and associated with the RV sample area in the LIDAR system field of view.

[0154] The above LIDAR core configurations are examples, and other LIDAR core configurations may be used. As an example, FIG. 11A to FIG. 11C An example of a LIDAR kernel suitable as a velocity kernel is shown. Fig.11A is modified to include a frequency shifter 298 positioned along the utility waveguide 12 Figure 1A 298 to create a frequency deviation between the LIDAR output signal and the reference signal. Since the system output signal includes or consists of light from the LIDAR output signal, there is also a frequency deviation between the system output signal and the reference signal. Suitable frequency shifters include, but are not limited to, acousto-optic frequency shifters. The frequency shifter may be integrated into the LIDAR chip or LIDAR core, or may be a separate electro-optical component mounted on the LIDAR chip or LIDAR core using techniques such as flip chip mounting techniques.

[0155] Fig.11A The LIDAR core can provide an explicit solution for the beat frequency without the second data signal and therefore without the imaginary part of the complex signal. Fig.11A The signal processor used in conjunction with the LIDAR core does not need to generate a second composite signal. Fig.11A The LIDAR core can be used in conjunction with a signal processor such as Fig. 11B The illustrated embodiment is modified to not include the components required to generate and process the second composite signal. Figure 5A Similarly, the relationship between the electronic device, the first light sensor 223 and the second light sensor 224 can be as shown in Figure 5B The configuration disclosed in the scenario is as follows, but does not include the first auxiliary light sensor 218 and the second auxiliary light sensor 220, such as Fig. 11C As shown. Figure 1C As shown, the transformer 268 receives the first data signal but does not receive the second data signal. Therefore, the first data signal acts as a real data signal received by the transformer 268. A LIDAR core having a transformer 268 receiving a real data signal can be considered a real data signal LIDAR core.

[0156] The beat frequency finder 238 includes a transformer 268 that receives as input a first digital data signal from a first analog-to-digital converter (ADC) 264. The transformer 268 can be configured to perform a mathematical transformation on the first digital data signal to convert from the time domain to the frequency domain. The mathematical transformation can be a real transformation, such as a Fourier transform. The local electronics use the one or more frequency peaks output from the transformer 268 for further processing to generate LIDAR data (the distance and / or radial velocity between the reflecting object and the LIDAR chip or LIDAR core). The local electronics 32 may include a peak finder (not shown) to identify the beat frequency of the one or more frequency peaks. The transformer 268 and / or the preliminary LIDAR data generator 269 can perform the attribute function using firmware, hardware, or software, or a combination thereof.

[0157] The local electronics 32 may include a preliminary LIDAR data generator 269 configured to receive the beat frequency from the transducer 268. The preliminary LIDAR data generator 269 is configured to generate preliminary LIDAR data for the sample area. The LIDAR data for the sample area includes values ​​of radial velocity and / or separation distance between the LIDAR system and the object in the sample area. In some cases, the LIDAR data includes an indicator that the LIDAR data for the sample area is "unavailable". In some cases, the preliminary LIDAR data generator 269 calculates LIDAR data that serves as preliminary LIDAR data. For example, in some cases, the preliminary LIDAR data generator 269 calculates the radial velocity and / or separation distance between the LIDAR system and the object in the sample area as preliminary LIDAR data. As will be discussed below, other examples of preliminary LIDAR data that the preliminary data generator may calculate include, but are not limited to, possible solutions for the LIDAR data for the sample area and potential radial velocity magnitude indicators for the sample area.

[0158] With Fig. 11C The different cores of the local electronic device 32 configured in the disclosed manner in the scenario can be used as Figure 8 Alternatively, the common electronic device 280 disclosed in the context of Fig. 11C The disclosed scenario is configured in a manner such that one or more cores of the local electronic device 32 and having Figure 5B In the scenario disclosed herein, one or more cores of a local electronic device configured in a manner as disclosed herein may be used with Figure 8 The common electronic device 280 disclosed in the scenario is in electrical communication.

[0159] From Fig.11AThe system output signal of the LIDAR core can be a continuous wave (CW). For example, the outgoing LIDAR signal and therefore the system output signal can be a non-chirped continuous wave (CW). As an example, the outgoing LIDAR signal and therefore the LIDAR output signal can be expressed as Equation 2: G*cos(H*t), where G and H are constants and t represents time. In some cases, G represents the square root of the power of the outgoing LIDAR signal. Local electronic devices, such as the preliminary LIDAR data generator 269, can approximate the radial velocity (v) between the reflecting object and the LIDAR chip using the following Equation 5: v=c*f ft / (2*(f c +f os )), where f ft represents the peak frequency output from the converter 268, c is the speed of light, and f c represents the frequency of the LIDAR output signal, and therefore also the frequency of the system output signal, and f os Indicates the frequency deviation between the system output signal and the reference signal. In many cases, f c >>f os , and the equation for radial velocity can be approximated as v = c*f ft / (2*f c ). Therefore, multiple data periods and / or chirps are not required to generate radial velocity.

[0160] Figures 1A to 1C Any of the LIDAR cores shown can also be used with Fig. 11B The signal processor operates as a distance and velocity kernel when used in conjunction with Fig. 11C local electronics to provide a real data signal core. For example, Figure 5C The frequency-versus-time pattern can be represented as a function of the distance and velocity kernels. Figure 1A The frequency-versus-time pattern is constructed using a real data signal kernel. In this case, the frequency peaks output from the Fourier transform represent the beat frequencies of the composite signals, each of which includes a comparison signal beating relative to a reference signal. However, the real Fourier transform output has positive and negative beat frequencies of equal magnitude. It may not be clear which beat frequency represents the correct value of the beat frequency of the composite signal. Therefore, for the real Fourier transform output from the reference signal, the frequency peaks output from the Fourier transform represent the beat frequencies of the composite signals. Figures 1A to 11C There are multiple possible solutions for the LIDAR data of the RV sample area illuminated by the system output signal of the LIDAR kernel constructed and operated as a range and velocity kernel.

[0161] The beat frequencies from two or more different data periods associated with the same sample region may be combined to generate a signal consisting of a Figures 1A to 1CAny of the possible LIDAR data solutions constructed and operated as range and velocity kernels for the RV sample area illuminated by the system output signal of the LIDAR kernel. For example, in the sample area SR k The beat frequency determined from DP1 during the illumination period can be compared with the sample area SR k The beat frequency combination determined from DP2 during the irradiation period is used to determine the RV sample region SR k Possible LIDAR data solutions.

[0162] As mentioned above, during the data period when the frequency of the outgoing LIDAR signal increases, the beat frequency of the composite signal can be expressed as f ub , and during the data period when the frequency of the outgoing LIDAR signal decreases, the beat frequency of the composite signal can be expressed as f db The contribution of the distance between the LIDAR system and the object to these beat frequencies can be expressed as f r , where f r =2*α u *R k / c, where α u The chirp rate (α) of the data period that represents the frequency increase of the system output signal over time m )(in this case α1), R k Represents the LIDAR system and the sample area SR k is the distance between the objects in , and c is the speed of light. The contribution of the Doppler effect to these beat frequencies can be expressed as f d =2V k f c / c, where f c Indicates the fundamental frequency (f o ), V k is the radial velocity between the reflecting object in sample region k and the LIDAR system, assuming that the radial velocity is positive when the object moves towards the LIDAR system.

[0163] For the RV sample area, f r and f d There are three possible solutions for LIDAR data. r =(f ub +f db ) / 2 and f d =(f db -f ub ) / 2 can serve as the first solution. The second solution can be f r =(f db -f ub ) / 2 and f d =(f db +f ub ) / 2. The third solution can be fr =(f ub -f db ) / 2 and f d =-(f db +f ub ) / 2. As mentioned above, the real Fourier transform output has positive and negative beat frequencies of equal magnitude. Therefore, in these LIDAR data solutions, f ub represents the magnitude of the peak frequency output from the converter 268, f db represents the magnitude of the peak frequency output from the converter 268. As described above, f d and f r The values ​​of are respectively related to the radial velocity (V K ) and distance (R k ) is directly related to: f d =2V k f c / c and f r =2*α u *R k / c. Therefore, the RV sample area SR k Each possible LIDAR data solution can have a r Value, f d Value, radial velocity (V K ) value and distance (R k ) values. In some cases, each possible LIDAR data solution includes at least possible f r Value, possible f d In some cases, each possible LIDAR data solution includes at least the RV sample region SR k Possible radial velocity (V K ) value and possible distance (R k )value.

[0164] Fig. 12A An example of a flow chart of a common electronic device that can be used to identify a correct LIDAR data solution for a target RV sample area is shown. At process block 320, a plurality of possible LIDAR data solutions are calculated. For example, the preliminary LIDAR data generator 269 may calculate possible solutions for a first solution, a second solution, and a third solution. r value and / or possible distance (R k ) value. At process block 321, the preliminary LIDAR data generator 269 may identify a candidate LIDAR data solution from possible LIDAR data solutions. For example, the electronic device may select from possible f r Identify candidate f in the value r values, and / or from possible R k Identify candidate R valuesk Value. k The value of is positive by definition. Therefore, f r The value of is also positive. However, f from the second solution r The value is f from the third solution r Therefore, the possible f r and / or R k The value will include one or more negative values. Possible f with negative values r Value and / or R k The value can be removed from the candidate pool. Therefore, every possible f with a positive value r The value can serve as a candidate f r Additionally or alternatively, each possible R with a positive value k The value can serve as a candidate R k value.

[0165] At block 322, the LIDAR data generator 281 identifies the correct solution. For example, when each possible LIDAR data solution does not yet include the radial velocity (V k ), we can use the f associated with the solution d For each solution, calculate the radial velocity (V k ), and f d =2V k f c / c. V from different solutions k The results can be compared with radial velocity results from one or more V sample regions to identify the correct V k Results. Includes identified V k The resulting LIDAR data solution can be selected as the correct LIDAR data solution. Therefore, the V of the selected LIDAR data solution is k value can be chosen to be the correct V k Value and R k value.

[0166] At block 323, the LIDAR data generator 281 may determine the LIDAR data for the RV sample region associated with the sample region index k. For example, when the selected possible LIDAR data solution does not yet include the distance (R K ), the f associated with the selected LIDAR data can be used r The value for the selected LIDAR data solution to calculate the distance (R K ), and f r =2*α u *R k / c. V de-correlated with the selected LIDAR data k and R k Value can serve as RV sample region SRk Thus, the LIDAR data for the RV sample region associated with the sample region index k may include the V selected in process block 322. k and R k value or the V selected in process block 322 k and R k Value composition.

[0167] A LIDAR system may include one or more range and velocity cores, which are real data signal cores, and one or more velocity cores, which are real data signal cores. As an example, Fig. 12B A LIDAR system is shown including a plurality of different real data signal cores on a common support 140. One or more of the LIDAR cores may be as shown in FIG. FIG. 11A to FIG. 11C The velocity kernel is constructed in the manner disclosed in the context of FIG. 1 , and one or more of the LIDAR kernels may be as follows: Figures 1A to 1C The distance and velocity kernels constructed in the open manner in the scenario of Fig. 11C Electronic devices Fig. 11B To illustrate, Fig. 12B The LIDAR core in the LIDAR system consists of two FIG. 11A to FIG. 11C The velocity core 325 is constructed in the manner disclosed in the scenario of FIG. 1 and further includes two Figures 1A to 1C The distance and velocity kernel 324 constructed in the disclosed manner in any of the scenarios has the combination Fig. 11C Electronic devices Fig. 11B The distance and speed core 324 alternates with the speed core 325 .

[0168] Fig. 12C yes Fig. 12B A two-dimensional diagram of the field of view of a LIDAR system. For example, Fig. 12C The 3D field of view may be represented by a projection of the 3D field of view onto a 2D plane. The field of view includes a plurality of rectangles, each of which may represent a projection of a sample region in the field of view onto a plane. For illustration, the sample regions are shown as rectangles, and the sample regions may have other geometric shapes. The sample regions are each labeled SR k , where k ranges from 1 to 30.

[0169] The sample areas are each marked as C i , where i is the core index identifying the core that illuminates the sample area. The core index is an integer that can be extended from i=1 to i=M, where M is the number of system output signals output by the LIDAR system. Label C i Indicates which of the system output signals illuminates the sample area. For example, the sample area marked as C1 is illuminated by Fig. 12BThe distance and velocity of the nuclear irradiation marked as C1, and the sample area marked as C3 is determined by Fig. 12B . Thus, the sample regions labeled C1 and C3 are RV sample regions. In contrast, the sample region labeled C2 is irradiated by the velocity nucleus labeled C2 and the sample region labeled C4 is irradiated by the velocity nucleus labeled C4. Thus, the sample regions labeled C2 and C4 are V sample regions.

[0170] Fig. 12C The arrows are labeled A. The arrows indicate the order in which the system output signal scans through the field of view. In addition, the sample region index (k) is assigned to the sample regions in chronological order. Therefore, the samples labeled C2 and SR 11 The sample area is marked as C2 and SR 12 The sample area is scanned by velocity kernel C1 before being scanned by velocity kernel C2.

[0171] The local electronics 32 may be local electronics because they are specific to each core on the LIDAR system. In addition to the local electronics 32, the LIDAR system may also include public electronics 280. The public electronics 280 may be located at Fig. 12C The common electronics 280 may be located on the common support 140 as shown, or may be located outside the common support 140. The common electronics 280 may be located in the same physical location and / or housing as the local electronics associated with the different cores, or may be located in a different physical location and / or housing than the local electronics associated with the different cores.

[0172] The LIDAR data generator 281 may combine possible LIDAR data solutions with isolated LIDAR data from one or more V sample regions to select the correct LIDAR data solution, such as Fig. 12A In some cases, the RV sample region and one or more V sample regions that are de-associated with possible LIDAR data may be illuminated by a system output signal that includes light from the same core or different cores.

[0173] To identify the correct possible LIDAR data solution, the possible LIDAR data solution for the target RV sample area can be compared with the radial velocities calculated for one or more V sample areas, each serving as a reference V sample area. All or part of the reference V sample area and the target sample area can be illuminated by the same core or different cores. For example, the electronic device can identify the target RV sample area for which the correct LIDAR data solution is to be identified. Fig.12D Shown from Fig. 12C The field of view, where the area illuminated by the system output signal including the light from the velocity core C4 is marked as SR 15The RV sample area is identified as the target RV sample area.

[0174] One or more V sample regions may each be identified as a reference V sample region. A possible LIDAR data solution for the target RV sample region may be compared to the radial velocity (V k ) to identify the correct LIDAR data solution for the target RV sample area from the possible LIDAR data solutions for the target RV sample area. In some cases, the V sample area that is physically closest to the target RV sample area is identified as the only reference V sample area. As an example, in Fig.12D , the V sample region labeled SR5 illuminated by the system output signal including light from velocity core C1 is identified as the only reference V sample region.

[0175] The LIDAR data generator 281 may employ one or more solution identification criteria to identify the correct LIDAR data solution from the possible LIDAR data solutions for the target RV sample region. An example of a solution identification criterion includes an approximate velocity criterion, wherein a possible LIDAR data solution having a radial velocity closest to the radial velocity of one or more reference V sample regions is identified as the correct LIDAR data solution. For example, the V sample region that is physically closest to the target RV sample region may be identified as the only reference V sample region and having a radial velocity V closest to the radial velocity of the one or more reference V sample regions. k The possible LIDAR data solution of can be selected as the correct LIDAR data solution for the target RV sample area. Therefore, the radial velocity V associated with the LIDAR data solution is k and distance R k LIDAR data that can serve as a target RV sample area.

[0176] The LIDAR data generator 281 may apply other identification criteria in addition to or in lieu of the approximate velocity criterion. Another example of an identification criterion may be a range criterion, where the radial velocity V of each identified reference V sample region is k Within a range of radial velocity values. Examples of suitable radial velocity value ranges include, but are not limited to, the radial velocity of the target RV sample region + / - 10%, 20%, or 30% of the radial velocity of the target RV sample region. If the radial velocity of an identified reference V sample region (V k) is outside the range of radial velocity values, the reference V sample region may be removed from the identified reference V sample regions. If no identified reference V sample region has a radial velocity within the range of radial velocity values, the LIDAR data for the target RV sample region may be classified as unusable. In some cases, the LIDAR data generator 281 applies both the range criteria and the approximate velocity criteria to the target RV sample region.

[0177] Fig.12E A method for generating a LIDAR system (e.g. Fig. 12B Flow chart of an example process for obtaining LIDAR data of a sample area illuminated by a LIDAR system (shown in FIG. 3 ). At process block 326 , the field of view of the LIDAR system is scanned.

[0178] At process block 327, isolated LIDAR data may be calculated for each V sample region. As described above, isolated LIDAR data for a sample region is LIDAR data that may be calculated without using a composite signal generated by illuminating different sample regions with the system output signal. For example, to generate isolated LIDAR data, the preliminary LIDAR data generator for each velocity kernel 269 may calculate radial velocity for each V sample region illuminated by the velocity kernel.

[0179] At block 328, the preliminary LIDAR data generator 269 for each range and velocity kernel may calculate possible LIDAR data for each RV sample region illuminated by one of the range and velocity kernels. For example, the preliminary LIDAR data generator 269 for each range and velocity kernel may calculate the LIDAR data for each RV sample region illuminated by one of the range and velocity kernels. Fig. 12A The possible LIDAR data solutions for each RV sample area illuminated by one of the disclosed range and velocity kernels in the scenario.

[0180] At block 329, the correct LIDAR data solution may be selected for each RV sample region illuminated by each range and velocity kernel. Fig. 12A The correct LIDAR data solution for the RV sample area is selected from the possible LIDAR data solutions disclosed in the scenario. The radial velocity (V k ) and distance (R k ) can be considered as shared LIDAR data, which serves as the target RV sample region SR k All or part of the LIDAR data.

[0181] LIDAR data from the RV sample area can serve as Fig.10The distance and radial velocity of each RV sample area scanned by the RV core in the process block 300 of FIG. 300. Therefore, the preliminary LIDAR data generator 269 or the LIDAR data generator 281 can calculate the radial velocity and coordinates of the field of view position associated with the RV sample areas scanned by these cores disclosed in the context of process block 300. In addition, the isolated LIDAR data of the V sample area can serve as the radial velocity of each V sample area scanned by the V core in process block 300. Therefore, in some cases, performing Fig.10 The rest of the process shown in is to interpolate and / or extrapolate the distance (R) of each V sample area illuminated by the velocity kernel k As an example, at process block 310, the LIDAR data generator 281 may combine the distance data (R k ) to approximate the distance data (R) for each V sample area illuminated by one of the velocity kernels k ). For example, as described above, the LIDAR data generator 281 may generate coordinate and / or distance data (R ) from different RV sample regions. k ) interpolates and / or extrapolates the distance data (R) for each V sample area k The LIDAR data of the sample area of ​​the field of view may include the LIDAR data of the RV sample area, the isolated LIDAR data of each V sample area (V k ) and approximate distance data (R) for each V sample area k ) or the LIDAR data of the RV sample area, the isolated LIDAR data of each V sample area (V k ) and approximate distance data (R) for each V sample area k )composition.

[0182] Figure 7 and Fig. 12B The fields of view shown in show sample areas that are spaced apart from one another, however, the sample areas may partially or completely overlap. For example, all or part of the V sample area may partially or completely overlap the RV sample area, or be partially or completely overlapped by the RV sample area. Thus, all or part of the sample area may be simultaneously illuminated by a system output signal that includes light from the RV core and by a system output signal that includes light from the V core.

[0183] although Fig. 12B The LIDAR system is disclosed as having a real data signal kernel, where the velocity kernel is as FIG. 11A to FIG. 11C The speed kernel can be constructed in the manner disclosed in the context of FIG. 1 , but some of the kernels can be complex data signal kernels. For example, the speed kernel can be as follows Figures 1A to 5C The distance and speed kernel 324 is alternated with the speed kernel 325.

[0184] exist FIG. 11A to FIG. 11C The real data signal core disclosed in the scenario of and acting as the V core includes a frequency shifter. However, the frequency shifter can be removed. For example, Fig. 12B The velocity kernel in can be Figures 1A to 1C Any one of the disclosed methods is constructed with a combination Fig. 11C Electronic devices Fig. 11B signal processor to provide a real data signal core that can operate as a V core. For example, the system output signal can be a continuous wave (CW). As an example, the outgoing LIDAR signal and therefore the system output signal can be a non-chirped continuous wave (CW). In some cases, the outgoing LIDAR signal and therefore the system output signal can be expressed as Equation 2: G*cos(H*t), where G and H are constants and t represents time. In some cases, G represents the square root of the power of the outgoing LIDAR signal. In these cases, the real Fourier transform outputs frequency peaks at positive and negative beat frequencies with the same magnitude. For example, the real Fourier transform can be at f d and -f d The output frequency peak value under the beat frequency value, where f d represents the Doppler shift and can be expressed as f d =2V k f c / c, where f c represents the frequency of the continuous wave, c represents the speed of light, V k The LIDAR system and the sample area SR k The radial velocity between the reflecting objects in V is assumed to be the positive direction from the reflecting object toward the LIDAR system. Since it may not be clear which beat frequency represents the correct value of the beat frequency of the composite signal, there are two possible radial velocity solutions, one in V k , one in -V k Therefore, for Figures 1A to 1C For any one of the systems of real data signal kernels constructed in the disclosed manner, the output signal is the radial velocity of the illuminated sample region V, for which there are multiple potential solutions.

[0185] Fig.13A It is shown that when a LIDAR data solution is available from the RV sample region, the electronics can be used to identify the V sample region SR k At block 340, the preliminary LIDAR data generator 269 generates a sample region SR k The radial velocity index is used to calculate the velocity magnitude index. The magnitude of the potential radial velocity index indicates the LIDAR system and the V sample area SR kThe magnitude of the radial velocity between objects in the image. For example, the magnitude of the potential radial velocity indicator sets the magnitude of the radial velocity. Thus, the radial velocity indicator can be determined by f d =2V k f c / c provides radial velocity (V k ) value, where f d It can represent any peak frequency output from the Fourier transform. d The magnitude of the radial velocity is directly related to that of the radial velocity by the following equation: |f d |=|2V k f c / c|, so any beat frequency (f d ) or Doppler frequency shift (f d ) may also serve as a radial velocity indicator. The preliminary LIDAR data generator 269 may identify the magnitude of the radial velocity indicator as a velocity magnitude indicator.

[0186] At block 342, the LIDAR data generator 281 may identify a sample region SR k The radial velocity indicator direction. For example, the V sample area SR k The velocity magnitude indicator is compared with a comparison component of the LIDAR data solution from one or more RV sample regions to identify the direction of the radial velocity indicator. As an example, when the V sample region SR k When the velocity magnitude indicator of the sample region SR matches the magnitude of a possible radial velocity solution from an adjacent RV sample region, the system output signals illuminating different sample regions are likely incident on the same object. Therefore, the direction of the possible radial velocity solution that matches the velocity magnitude indicator is assigned to the velocity magnitude indicator to provide a directional radial velocity indicator. Thus, the directional radial velocity indicator has the magnitude of the velocity magnitude indicator and the direction of the comparison component from the matching LIDAR data solution. As an example, when the V sample region SR k The radial velocity index is a radial velocity index that provides a speed magnitude index of 20 mph (V k ) is calculated and matched with a possible radial velocity solution of -20 mph, the negative value of the possible radial velocity solution is assigned to the velocity magnitude index to provide a directional radial velocity index value of -20 mph.

[0187] At block 344, the LIDAR data generator 281 may determine a V sample region SR k When the velocity magnitude indicator is the magnitude of the radial velocity calculation, the directional radial velocity indicator can serve as the sample area SR kWhen the velocity magnitude index is a magnitude other than the radial velocity calculation, the radial velocity can be calculated from the directional radial velocity index. For example, when the velocity magnitude index is the magnitude of any beat frequency (fd), it can be calculated based on Cf d =2V k f c / c Calculate radial velocity (V k ), where Cf d Represents the directional radial velocity index.

[0188] Fig. 12B One or more LIDAR cores in a LIDAR system can be as follows Figures 1A to 1C The scenario is constructed in an open way, with Fig. 11C Electronic devices combined with Fig. 11B signal processor and operates as a range and velocity core, while one or more LIDAR cores in a LIDAR system can be as Figures 1A to 1C constructed in any one of the disclosed manners, having Fig. 11C Electronic devices combined with Fig. 11B signal processor and operates as a V core. As an example, Fig. 13B A LIDAR system is shown that includes a plurality of different real data signal cores on a common support 140. One or more of the LIDAR cores may be velocity cores, such as Figures 1A to 1C constructed in any one of the disclosed manners, having Fig. 11C Electronic devices combined with Fig. 11B signal processor, and one or more of the LIDAR cores may be range and velocity cores, such as Figures 1A to 1C The scenario is constructed in an open way, with Fig. 11C Electronic devices combined with Fig. 11B To illustrate, Fig. 13B The LIDAR core in the LIDAR system of FIG. 1 includes two velocity cores 325 and two range and velocity cores 324 . The range and velocity cores 324 alternate with the velocity cores 325 .

[0189] Fig. 13C yes Fig. 13B A two-dimensional diagram of the field of view of a LIDAR system. For example, Fig. 13C The 3D field of view may be represented by a projection of the 3D field of view onto a 2D plane. The field of view includes a plurality of rectangles, each of which may represent a projection of a sample region in the field of view onto a plane. For illustration, the sample regions are shown as rectangles, and the sample regions may have other geometric shapes. The sample regions are each labeled SR k , where k ranges from 1 to 30.

[0190] The sample areas are each marked as C i, where i is the core index identifying the core that illuminates the sample area. The core index is an integer that can be extended from i=1 to i=M, where M is the number of system output signals output by the LIDAR system. Label C i Indicates which of the system output signals illuminates the sample area. For example, the sample area marked as C1 is illuminated by Fig. 13B The distance and velocity of the nuclear irradiation marked as C1, and the sample area marked as C3 is determined by Fig. 13B . Thus, the sample regions labeled C1 and C3 are RV sample regions. In contrast, the sample region labeled C2 is irradiated by the velocity nucleus labeled C2 and the sample region labeled C4 is irradiated by the velocity nucleus labeled C4. Thus, the sample regions labeled C2 and C4 are V sample regions.

[0191] Fig. 13C The arrows are labeled A. The arrows indicate the order in which the system output signal scans through the field of view. In addition, the sample region index (k) is assigned to the sample regions in chronological order. Therefore, the samples labeled C2 and SR 11 The sample area is marked as C2 and SR 12 The sample area is scanned by velocity kernel C1 before being scanned by velocity kernel C2.

[0192] The local electronics 32 may be local electronics because they are specific to each core on the LIDAR system. In addition to the local electronics 32, the LIDAR system may also include public electronics 280. The public electronics 280 may be located at Fig. 13C The common electronics 280 may be located on the common support 140 as shown, or may be located outside the common support 140. The common electronics 280 may be located in the same physical location and / or housing as the local electronics associated with the different cores, or may be located in a different physical location and / or housing than the local electronics associated with the different cores.

[0193] Public electronic devices can be used with Figure 8 The local electronic devices 32 associated with different cores disclosed in the scenario of FIG. 280 are in electrical communication. Therefore, the public electronic device 280 can access the LIDAR data generated by the different cores. For example, the public electronic device 280 can access the preliminary LIDAR data calculated by the local electronic device 32 for the sample area.

[0194] The electronics may combine possible LIDAR data solutions with radial velocity indicators and / or velocity magnitude indicators from one or more V sample regions to identify correct LIDAR data for the RV sample regions and V sample regions in the field of view.

[0195] To identify the correct possible LIDAR data solution for the RV sample region and the correct direction of the radial velocity indicator, the electronics may compare the possible LIDAR data solution for the target RV sample region with the radial velocity magnitude indicators for one or more V sample regions, each V sample region acting as a reference V sample region.

[0196] All or part of the reference V sample region and the target RV sample region may be illuminated by the same core or different cores.For example, the electronics (eg, LIDAR data generator 281) may identify a target RV sample region for which a correct LIDAR data solution is to be identified. Fig.13D Shown from Fig. 13C The field of view, where the area illuminated by the system output signal including the light from the velocity core C4 is marked as SR 15 The RV sample area is identified as the target RV sample area.

[0197] The LIDAR data generator 281 may identify one or more V sample regions as reference V sample regions. The LIDAR data generator 281 may compare possible LIDAR data solutions for the target RV sample region with velocity magnitude indicators calculated for each of the one or more reference V sample regions to identify a correct LIDAR data solution for the target RV sample region from among possible LIDAR data solutions for the target RV sample region. In some cases, the V sample region that is physically closest to the target RV sample region is identified as the only reference V sample region. As an example, in Fig.13D , the V sample region labeled SR5 illuminated by the system output signal including light from velocity core C1 is identified as the only reference V sample region.

[0198] The LIDAR data generator 281 may employ one or more solution identification criteria to identify the correct LIDAR data solution for the target RV sample region from the possible LIDAR data solutions for the target RV sample region and / or to identify the correct direction of the radial velocity indicator for the reference V sample region. Example identification criteria include an approximate magnitude velocity criterion that provides a reference V sample region SR k The velocity magnitude indicator of the reference V sample area is matched with the comparison component of the LIDAR data solution of the target RV sample area. For example, the possible LIDAR data solutions of the reference V sample area have a component that serves as the comparison component as the equivalent of the radial velocity indicator and can be compared with the velocity magnitude indicator. For example, when the velocity magnitude indicator is the magnitude of the radial velocity calculation, each possible LIDAR data solution of the reference V sample area includes a radial velocity (V) that can serve as the comparison component. KAs another example, when the velocity magnitude indicator is the magnitude of the Doppler frequency shift, each possible LIDAR data solution of the reference V sample area includes f that can serve as a comparison component. d The LIDAR data solution for the target RV sample area and having a comparison component whose magnitude is closest to the velocity magnitude indicator of the reference V sample area can be selected as the correct LIDAR data solution for the target RV sample area. Therefore, the radial velocity V associated with the selected LIDAR data solution is k and distance R k The LIDAR data of the target RV sample area can serve as the LIDAR data. In addition, the direction of the comparison component in the selected LIDAR data solution can serve as the direction of the radial velocity indicator for the reference V sample area associated with the radial velocity indicator. Therefore, the direction of the comparison component in the selected LIDAR data solution is assigned to the radial velocity indicator to provide a directional radial velocity indicator. Therefore, the directional radial velocity indicator has the magnitude of the velocity magnitude indicator and the direction (positive or negative) of the comparison component in the selected LIDAR data solution. As an example, when the radial velocity indicator is a radial velocity (V) that provides a velocity magnitude indicator of 20 mph k ) calculation, and when the comparison component in the selected LIDAR data solution has a value of -20 mph, the negative value of the comparison component is assigned to the velocity magnitude index to provide a directional radial velocity index value of -20 mph.

[0199] The LIDAR data generator 281 may apply other solution identification criteria as a supplement or alternative to the approximate velocity magnitude criteria. Another example of an identification criterion may be a range criterion, in which the comparison component in each LIDAR data solution of the target sample area has a value within a range of comparison component values. In some cases, the size range of the comparison component value includes, but is not limited to, the value of the velocity magnitude index of the reference V sample area + / - 10%, 20%, or 30% of the velocity magnitude index of the reference V sample area. In some cases, the size range of the comparison component value includes, but is not limited to, the value of the velocity magnitude index of the reference V sample area + / - a constant value. If the size of the comparison component value of the target RV sample area is out of range, the LIDAR data solution including the comparison component value can be removed from the list of possible LIDAR data solutions. If none of the possible LIDAR data solutions of the target RV sample is within the range, the LIDAR data of the target RV sample area can be classified as unavailable. In some cases, the LIDAR data generator 281 applies the range criterion and the approximate velocity magnitude criterion to the target RV sample area.

[0200] Fig.13EAn example of a flow chart that the LIDAR data generator 281 can use to identify the correct LIDAR data solution for the target RV sample region and determine the correct radial velocity for the reference V sample region is shown. At process block 346, the LIDAR data generator 281 identifies the target RV sample region. The LIDAR data generator 281 also identifies one or more reference V sample regions. In some cases, the V sample region that is physically closest to the target RV sample region is identified as the only reference V sample region.

[0201] At block 347, the LIDAR data generator 281 may access Fig. 12A The possible LIDAR data solutions calculated by the preliminary LIDAR data generator for the target RV sample area in the scenario disclosed in FIG. 281. For example, the LIDAR data generator 281 electronics may access the possible f of the first solution, the second solution, and the third solution. r value and / or possible distance (R k ) value. At process block 348, the LIDAR data generator 281 may identify a candidate LIDAR data solution from the possible LIDAR data solutions. For example, the LIDAR data generator 281 may identify a candidate LIDAR data solution from the possible f r Identify candidate f in the value r values, and / or from possible R k Identify candidate R values k Value. k The value of is positive by definition. Therefore, f r The value of is also positive. However, f from the second solution r The value is f from the third solution r Therefore, the possible f r and / or R k The value will include one or more negative values. Possible f with negative values r Value and / or R k The value can be removed from the candidate pool. Therefore, every possible f with a positive value r The value can serve as a candidate f r Additionally or alternatively, each possible R with a positive value k The value can serve as a candidate R k value.

[0202] At block 349, the LIDAR data generator 281 may identify the correct solution. The radial velocity (V k ) components and / or f dThe component may serve as a comparison component of the LIDAR data solution. The component serving as the comparison component may be determined by a velocity magnitude indicator. For example, as described above, when the velocity magnitude indicator is the magnitude of the radial velocity calculation, each possible LIDAR data solution of the reference V sample area includes a radial velocity (V) that may serve as a comparison component. K ) value, but when the velocity magnitude indicator is the magnitude of the Doppler shift, each possible LIDAR data solution of the reference V sample area includes f that can serve as a comparison component d When the radial velocity (V K ) value serves as a comparison component, and the possible LIDAR data solution does not yet have a radial velocity (V K ) component, the f d For each possible LIDAR data solution, calculate the radial velocity (V k ), and f d =2V k f c / c.

[0203] The LIDAR data generator 281 may use one or more solution identification criteria to compare the comparison components from different LIDAR data solutions with the velocity magnitude indicators from one or more V sample regions to identify the correct LIDAR data solution. The LIDAR data generator 281 may select the LIDAR data solution that includes the identified comparison components as the correct LIDAR data solution.

[0204] At block 350, the LIDAR data generator 281 identifies LIDAR data for the target RV sample region associated with the sample region index k. For example, when the components of the selected possible LIDAR data solution do not yet include the distance (R K ), the f associated with the selected LIDAR data can be used r The value of calculating the distance (R K ), and f r =2*α u *R k / c. In addition, when the components of the possible LIDAR data solution are selected, the radial velocity (V K ), the f associated with the selected LIDAR data can be used d The radial velocity (V K ), and f d =2V k f c / c. V de-correlated with the selected LIDAR data k and R k The value can serve as the target RV sample region SR kThus, the LIDAR data for the RV sample region associated with the sample region index k may include the V selected in process block 322. k and R k value or the V selected in process block 322 k and R k Value composition.

[0205] At process block 351, the LIDAR data generator 281 can determine a radial velocity for the reference V sample area. A direction of the radial velocity indicator can be identified. For example, the direction of the comparison component in the selected LIDAR data solution can serve as the direction of the radial velocity indicator for the reference V sample area associated with the radial velocity indicator. Therefore, the direction of the comparison component in the selected LIDAR data solution is assigned to the radial velocity indicator to provide a directional radial velocity indicator. Therefore, the directional radial velocity indicator has the magnitude of the velocity magnitude indicator and the direction (positive or negative) of the comparison component in the selected LIDAR data solution. When the velocity magnitude indicator is the magnitude of the radial velocity calculation, the directional radial velocity indicator can serve as the sample area SR k Radial velocity (V k ). When the velocity magnitude index is other than the radial velocity calculation, the radial velocity can be calculated based on the directional radial velocity index. For example, when the velocity magnitude index is any beat frequency (f d ) can be calculated based on Cf d =2V k f c / c Calculate radial velocity (V k ), where Cf d Represents the directional radial velocity index.

[0206] Fig.13F shows a method for generating a Fig. 13B A flow chart of constructing LIDAR data of a sample area illuminated by a LIDAR system of a real data signal kernel in the scenario disclosed. At block 352, the electronic device causes the field of view to be scanned by the system output signals of different kernels.

[0207] At block 353, the preliminary LIDAR data generator in one or more velocity kernels calculates a velocity magnitude indicator for each V sample region. At block 354, the preliminary LIDAR data generator in one or more range and velocity kernels calculates a possible LIDAR data solution for each RV sample region illuminated by one of the range and velocity kernels. For example, the preliminary LIDAR data generator 269 may calculate a possible LIDAR data solution for each RV sample region illuminated by one of the range and velocity kernels.

[0208] At block 355, the LIDAR data generator 281 identifies a target RV sample region. The LIDAR data generator 281 also identifies one or more reference V sample regions. In some cases, the V sample region that is physically closest to the target RV sample region is identified as the only reference V sample region.

[0209] At block 356, the LIDAR data generator 281 identifies the correct LIDAR data solution for the target RV sample area. For example, the LIDAR data generator 281 may select a LIDAR data solution from the following examples: Fig.13E The correct LIDAR data solution for the RV sample area is selected from the possible LIDAR data solutions disclosed in the scenario. The radial velocity (V k ) and distance (R k ) can be considered as sharing LIDAR data, which serves as the target RV sample region SR k All or part of the LIDAR data.

[0210] At block 358, the LIDAR data generator 281 may determine the radial velocity (V k ). For example, the common electronic device 280 may determine Fig.13E The radial velocity (V) of each V reference sample area disclosed in the scenario k ).

[0211] Process blocks 355 through 358 may be repeated until each RV sample region has served as a target RV sample region, or until a desired portion of the RV sample region has served as a target RV sample region, and until each V sample region has served as a reference V sample region, or until a desired portion of the V sample region has served as a reference V sample region. Fig. 13C shows a 1:1 ratio of V sample areas to RV sample areas. In this case, each target RV sample area can be associated with a different V sample area that serves as a reference V sample area for the target RV sample area. Thus, a 1:1 ratio of V sample areas to RV sample areas can be performed for the field of view. Fig.13D , wherein each RV sample region serves as a target sample region, and each V sample region serves as a reference sample region for an associated RV sample region in the RV sample regions. In some cases, multiple V sample regions may serve as reference sample regions for an associated RV sample region in the RV sample regions. In these cases, the V sample regions serving as reference sample regions for an associated RV sample region in the RV sample regions may include the V sample regions that are closest to or have the shortest distance to the associated target RV sample region.

[0212] Fig. 12C and Fig. 13CThe sample areas irradiated by different nuclei are shown to be spatially separated, however, adjacent sample areas may fully or partially overlap. As an example, Figure 13G Shown from Fig. 12C or Fig. 13C A portion of a field of view, wherein the sample areas irradiated by different nuclei partially overlap, so that each V sample area is overlapped by a different RV sample area in one RV sample area. In some cases, the V sample area closest to the target RV sample area is the V sample area that overlaps the most with the target RV sample area. Therefore, the V sample area that serves as a reference sample area for the associated target RV sample area may include the V sample area that overlaps the most with the associated target RV sample area.

[0213] LIDAR data from the RV sample area can serve as Fig.10 The distance and radial velocity of each RV sample area scanned by the RV core in process block 300 is calculated by the preliminary LIDAR data generator 269 or the LIDAR data generator 281. Therefore, the radial velocity and coordinates of the field of view position associated with the RV sample area scanned by these cores as disclosed in the context of process block 300. In addition, the radial velocity determined for the V sample area can serve as the radial velocity of each V sample area scanned by the V core in process block 300. Therefore, in some cases, performing Fig.10 The rest of the process shown in FIG. 1 is to interpolate and / or extrapolate the distance (R) of each V sample area illuminated by the velocity kernel. k As an example, at process block 330, common electronics 280 may combine distance data (R k ) to approximate the distance data (R) for each V sample area illuminated by one of the velocity kernels k For example, the common electronics 280 may be configured to collect coordinate and / or distance data (R) from different RV sample regions as described above. k ) interpolates and / or extrapolates the distance data (R) for each V sample area k The LIDAR data of the sample area of ​​the field of view may include the LIDAR data of the RV sample area, the isolated LIDAR data of each V sample area (V k ) and approximate distance data (R) for each V sample area k ), or the LIDAR data of the RV sample area, the isolated LIDAR data of each V sample area (V k ) and approximate distance data (R) for each V sample area k )composition.

[0214] Example 1

[0215] The LIDAR system has a two-dimensional field of view. The field of view position fl1 is located in the RV sample region SR1 and is identified as a known data point with coordinates R1 = 10m and angular orientation θ1 = 10°. 10 Located in RV sample area SR 10 and is identified as having coordinates R 10 = 16m and angular orientation θ 10 = 12° known data point. Field of view position fl 15 is selected as the target field position and is located in the V sample area SR 15 The angular orientation is θ 15 =11°. Field of view position fl 15 The distance R 15 Use linear interpolation from the known data points fl1 and fl 10 Interpolate to R 15 =13m, where R 15 =R1+(R 10 -R1)(θ 15 -θ1) / (θ 10 -θ1).

[0216] Suitable platforms for LIDAR chips include, but are not limited to, silicon dioxide, indium phosphide, and silicon-on-insulator wafers. Fig.14 is a cross section of a portion of a chip constructed from a silicon-on-insulator wafer. The silicon-on-insulator (SOI) wafer includes a buried layer 431 between a substrate 432 and an optical transmission medium 434. In a silicon-on-insulator wafer, the buried layer 431 is silicon dioxide, while the substrate 432 and the optical transmission medium 434 are silicon. The substrate 432 of an optical platform such as an SOI wafer can serve as the base of the entire LIDAR chip. For example, Figures 1A to 1C The optical components shown on the LIDAR chip in FIG. 4 can be positioned on top of or above and / or on the sides of substrate 432 .

[0217] The size of the ridge waveguide is Fig.14. For example, the ridge has a width labeled w and a height labeled h. The thickness of the slab region is labeled T. For LIDAR applications, these dimensions may be more important than other dimensions because higher levels of optical power than used in other applications need to be used. The ridge width (labeled w) is greater than 1 μm and less than 4 μm, the ridge height (labeled h) is greater than 1 μm and less than 4 μm, and the slab region thickness is greater than 0.5 μm and less than 3 μm. These dimensions may apply to straight or substantially straight portions of the waveguide, curved portions of the waveguide, and tapered portions of (one or more) waveguides. Therefore, these portions of the waveguide will be single-mode. However, in some cases, these dimensions apply to straight or substantially straight portions of the waveguide. Additionally or alternatively, the curved portion of the waveguide may have a reduced plate thickness to reduce optical losses in the curved portion of the waveguide. For example, the curved portion of the waveguide may have a ridge extending away from the slab region having a thickness greater than or equal to 0.0 μm and less than 0.5 μm. While the above dimensions will typically provide a straight or substantially straight portion of the waveguide having a single-mode structure, they may result in tapered portion(s) and / or curved portion(s) that are multi-mode. Coupling between a multi-mode geometry and a single-mode geometry may be achieved using a taper that does not substantially excite higher-order modes. Thus, a waveguide may be constructed such that a signal carried in the waveguide is carried in a single mode even when the signal is carried in a portion of the waveguide having multi-mode dimensions. Fig.14 The waveguide structure disclosed in the context of Figures 1A to 1C Construct all or part of the waveguide on the LIDAR chip.

[0218] As described above, the electronic devices of the operating system include local electronic devices 32 and public electronic devices 280. The distinction between local electronic devices and public electronic devices is used to illustrate the part of the electronic device associated with one of the cores (local electronic devices) and the part of the electronic device associated with multiple cores (public electronic devices). Although the local electronic device 32 and the public electronic device 104 are shown as being in different locations, the local electronic device 32 and the public electronic device 104 can be located in a common location and / or in a common package. In addition, the local electronic device 32 and the public electronic device 104 can be integrated and do not necessarily refer to separate or different electronic components. Therefore, the functions described as being performed by the local electronic device can be performed by the public electronic device, and / or the functions described as being performed by the public electronic device can be performed by the local electronic device. Certain components of the electronic device, such as the preliminary LIDAR data generator and the LIDAR data generator, are disclosed above; however, the electronic device also includes other components not shown. For example, a portion of the local electronic device and / or the public electronic device can be configured to control the frequency of the system output signal, the steering of the system output signal, and the operation of the frequency shifter 298.

[0219] Suitable local electronic devices 32 and / or public electronic devices 104 may include, but are not limited to, controllers comprising or consisting of analog circuits, application specific integrated circuits (ASICs), digital circuits, processors, microprocessors, digital signal processors (DSPs), field programmable gate arrays (FPGAs), computers, microcomputers, or combinations thereof suitable for performing the above-described operating, monitoring, and control functions. In some cases, the controller may access a memory comprising instructions to be executed by the controller during the performance of the operating, control, and monitoring functions. Although the electronic device is shown as a single component in a single location, the electronic device may include multiple different components that are independent of each other and / or placed in different locations. In addition, as described above, all or part of the disclosed electronic device may be included on a chip, including an electronic device integrated with a chip.

[0220] The optical sensor connected to the waveguide interface on the LIDAR chip can be a component that is separated from the chip and then attached to the chip. For example, the optical sensor can be a photodiode or an avalanche photodiode. Examples of suitable optical sensor components include, but are not limited to, InGaAs PIN photodiodes manufactured by Hamamatsu located in Hamamatsu City, Japan or InGaAs APDs (avalanche photodiodes) manufactured by Hamamatsu located in Hamamatsu City, Japan. These optical sensors can be located in the center of the LIDAR chip. Alternatively, all or part of the waveguides that terminate at the optical sensor can terminate at a small face located at the edge of the chip, and the optical sensor can be attached to the edge of the chip above the small face so that the optical sensor receives light transmitted through the small face. The use of an optical sensor as a component separated from the chip is suitable for all or part of the optical sensors selected from the group consisting of a first auxiliary optical sensor 218, a second auxiliary optical sensor 220, a first optical sensor 223, and a second optical sensor 224.

[0221] As an alternative to the light sensor being a separate component, all or part of the light sensor may be integrated with the chip. For example, examples of light sensors connected to a ridge waveguide interface on a chip made of a silicon-on-insulator wafer may be found in: Optics Express Vol. 15, No. 21, 13965-13971 (2007); U.S. Patent No. 8,093,080, issued on January 10, 2012; U.S. Patent No. 8,242,432, issued on August 14, 2012; and U.S. Patent No. 6,108,472, issued on August 22, 2000, each of which is incorporated herein in its entirety. The use of a light sensor integrated with the chip is applicable to all or part of the light sensor selected from the group consisting of the first auxiliary light sensor 218, the second auxiliary light sensor 220, the first light sensor 223, and the second light sensor 224.

[0222] The light source 4 interfaced with the practical waveguide 12 may be a laser chip that is separated from the LIDAR chip and then attached to the LIDAR chip. For example, the light source 4 may be a laser chip that is attached to the chip using a flip chip arrangement. When the light source 4 is to be interfaced with a ridge waveguide on a chip constructed from a wafer on insulator, it is appropriate to use a flip chip arrangement. Alternatively, the practical waveguide 12 may include an optical grating (not shown) that acts as a reflector for an external cavity laser. In these cases, the light source 4 may include a gain element that is separated from the LIDAR chip and then attached to the LIDAR chip in a flip chip arrangement. Suitable examples of interfaces between flip chip gain elements and ridge waveguides on chips constructed from wafers on insulators can be found in U.S. Pat. No. 9,705,278, issued on July 11, 2017; and U.S. Pat. No. 5,991,484, issued on November 23, 1999, each of which is cited in its entirety. When the light source 4 includes a gain element or a laser chip, the local electronic device 32 can adjust the frequency of the outgoing LIDAR signal by changing the current level applied to the gain element or the laser cavity.

[0223] The above-mentioned LIDAR system includes a plurality of optical components, such as a LIDAR chip, a LIDAR adapter, a light source, a light sensor, a waveguide, and an amplifier. In some cases, in addition to the optical components shown or as a substitute for the optical components shown, the LIDAR system includes one or more passive optical components. Passive optical components can be solid-state components that do not include moving parts. Applicable passive optical components include, but are not limited to, lenses, reflectors, optical gratings, reflective surfaces, beam splitters, demultiplexers, multiplexers, polarizers, polarization beam splitters, and polarization rotators. In some cases, in addition to the optical components shown or as a substitute for the optical components shown, the LIDAR system includes one or more active optical components. Suitable active optical components include, but are not limited to, optical switches, phase tuners, attenuators, steerable reflectors, steerable lenses, adjustable multiplexers, and adjustable multiplexers.

[0224] In view of these teachings, those skilled in the art will readily recognize other embodiments, combinations and modifications of the present invention. Therefore, the present invention is limited only by the appended claims, which include all such embodiments and modifications when viewed in conjunction with the above description and drawings.

Claims

1. A LIDAR system, comprising: one or more cores, each core outputting a system output signal that illuminates a plurality of sample regions in the field of view, A reference core among the cores includes an optical combiner configured to generate a composite signal that beats at a beat frequency, and an electronic device configured to determine a beat frequency of the composite signal using a real Fourier transform, the electronic device is configured to calculate a magnitude of a radial velocity indicator of a reference sample region among sample regions illuminated by a system output signal output from the reference core using the beat frequency of the composite signal, The radial velocity indicator indicates a radial velocity between the LIDAR system and an object in the reference sample region, The electronics are configured to identify a direction of the radial velocity indicator, the identification of the direction comprising comparing a magnitude of the radial velocity indicator to data calculated for a target sample region selected from the sample regions, the reference sample region being different from the target sample region.

2. The system according to claim 1, wherein: The radial velocity index is a calculation of the radial velocity of the reference sample region.

3. The system according to claim 1, wherein: The radial velocity index is the beat frequency of the composite signal produced by one of the system output signals illuminating the reference sample region.

4. The system according to claim 1, wherein: The data from the target sample area includes a plurality of possible LIDAR data solutions for the target sample area.

5. The system according to claim 4, wherein: Each of the possible LIDAR data solutions for the target sample area includes the following: r Value, f d All or part of the components selected by the group consisting of value, radial velocity value and distance value, The f d The value is the Doppler shift, The f r The value is the frequency shift caused by the distance between the system and the object in the target sample area, The radial velocity value indicates a radial velocity between the system and an object in the target sample region, and The distance value indicates the distance between the system and an object in the target sample area.

6. The system according to claim 4, wherein: Each of the possible LIDAR data solutions includes d The comparison component of the value and radial velocity value selection, The f d The value is a Doppler shift, and the radial velocity value indicates a radial velocity between the system and an object in the target sample region; and Comparing the magnitude of the radial velocity indicator to data calculated for one or more reference sample regions includes comparing the magnitude of the radial velocity indicator to the comparison component.

7. The system according to claim 6, wherein: The electronics identifies a possible LIDAR solution for which the comparison component has a magnitude closest to a magnitude of the radial velocity indicator.

8. The system according to claim 7, wherein: The electronics sets the direction of the radial velocity index to be equal to the direction of the identified comparison component.

9. The system according to claim 1, wherein: The reference sample region and the target sample region at least partially overlap.

10. The system according to claim 1, wherein: The reference sample region is a sample region closest to the target sample region.

11. The system according to claim 10, wherein: The one or more cores are a plurality of cores, and a system output signal illuminating the target sample region is different from a system output signal illuminating a sample region proximal to the target sample region.

12. The system of claim 1, wherein: The electronics estimates the distance of the target sample region by interpolating between distances calculated for a plurality of different sample regions selected from among the sample regions illuminated by the system output signal from the one or more nuclei.

13. The system of claim 1, wherein: The electronics calculates a value for the beat frequency using a real Fourier transform.

14. A LIDAR system comprising: one or more cores, each core outputting a system output signal that illuminates a plurality of sample regions in the field of view, A target core among the cores includes an optical combiner configured to generate a composite signal that beats at a beat frequency, and an electronic device configured to calculate a plurality of possible LIDAR data solutions for a target sample area within a sample area illuminated by the system output signal output from the target core using the value of the beat frequency of the composite signal, Each of the possible LIDAR data solutions includes a comparison component indicating a value of radial velocity between the LIDAR system and an object in the target sample region, The electronics are configured to identify a correct LIDAR data solution among the LIDAR data solutions, the identification of the correct LIDAR data solution comprising comparing the LIDAR data solution with data calculated for one or more reference sample regions selected from the sample regions, the one or more reference sample regions being different from the target sample region.

15. The system of claim 14, wherein: The comparison component is a calculation of the likely radial velocity of the target sample region.

16. The system of claim 14, wherein: The comparison component is the beat frequency of the composite signal produced by one of the system output signals illuminating the reference sample area.

17. The system of claim 14, wherein: The data from each of the one or more reference sample regions includes a radial velocity indicator for the reference sample region, the radial velocity indicator indicating a radial velocity between the LIDAR system and an object in the reference sample region.

18. The system of claim 17, wherein: Each of the possible LIDAR data solutions includes d The comparison component of the value and radial velocity value selection, The f d The value is a Doppler shift, and the radial velocity value indicates a radial velocity between the system and an object in the reference sample region; and Comparing the comparison component to data calculated for one or more reference sample regions includes comparing the magnitude of the radial velocity indicator to the magnitude of the comparison component.

19. The system of claim 18, wherein: The electronics identifies the possible LIDAR solution whose comparison component has a magnitude closest to the magnitude of the radial velocity indicator as the correct LIDAR solution.

20. The system of claim 14, wherein: The one or more reference sample regions are a single sample region.

21. The system of claim 14, wherein: The one or more reference sample regions and the target sample region at least partially overlap.

22. The system of claim 14, wherein: The one or more reference sample regions include a sample region among the sample regions that is closest to the target sample region.

23. The system of claim 22, wherein: The one or more cores are a plurality of cores, and a system output signal illuminating the target sample region is different from a system output signal illuminating a sample region proximal to the target sample region.

24. The system of claim 14, wherein: The electronics estimates a distance of at least one of the one or more reference sample regions by interpolating between distances calculated for a plurality of different sample regions selected from sample regions illuminated by the system output signal from the one or more nuclei.

25. The system of claim 14, wherein: The electronics calculates a value for the beat frequency using a real Fourier transform.

26. A method of operating a LIDAR system, comprising: illuminating a plurality of sample regions in the field of view with system output signals output from different nuclei; combining the optical signals to generate a composite signal that beats at a beat frequency; calculating the magnitude of the radial velocity indicator of the reference sample area in the sample area illuminated by the system output signal output from the reference nucleus using the value of the beat frequency of the composite signal, The radial velocity index indicates a radial velocity between the LIDAR system and an object in the reference sample region; and identifying a direction of the radial velocity indicator by comparing a magnitude of the radial velocity indicator with data calculated for a target sample region in the sample region, The reference sample region is different from the target sample region.

27. A method of operating a LIDAR system, comprising: illuminating a plurality of sample regions in the field of view with system output signals output from different nuclei; combining the optical signals to generate a composite signal that beats at a beat frequency; Calculate a plurality of different possible LIDAR data solutions for a target sample region in the sample region using the beat frequency value, Each of the possible LIDAR data solutions includes a comparison component indicating a value of radial velocity between the LIDAR system and an object in the target sample region; as well as identifying a correct one of the LIDAR data solutions by comparing the LIDAR data solution with data calculated for one or more reference sample regions selected from the sample regions, The one or more reference sample regions are different from the target sample region.

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