Combining data from different sample areas in the imaging system's field of view

Abstract

The imaging system includes one or more cores, each of which outputs a system output signal that illuminates multiple sample regions in a field of view. The core targets include optical couplings that generate a composite signal that beats at a beat frequency. An electronic circuit uses the beat frequency values ​​to calculate multiple different potential LIDAR data solutions for the target of the sample region illuminated by the system output signal output from the target core. Each potential LIDAR data solution includes a comparison component that indicates a value of the radial velocity between the LIDAR system and an object in the target sample region. The electronic circuit identifies a correct LIDAR data solution 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.

Description

Related Applications

[0001] This application is a continuation of U.S. Patent Application No. 17 / 945,072, filed September 14, 2022, entitled "Combining Data from Different Sample Areas Within the Field of View of an Imaging System," the entire contents of which are incorporated herein by reference. [Technical Field]

[0002] The present invention relates to imaging systems. In particular, the present invention relates to LIDAR systems.

[0003] There is growing commercial demand for economically deployable 3D imaging systems for 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 scene with laser light and measuring the returned signal.

[0004] Many LIDAR approaches transmit a system output signal that is reflected by an object, and a portion of the reflected optical signal returns to the LIDAR chip as the LIDAR input signal. The LIDAR input signal is processed by electronic circuitry so that the distance and line-of-sight velocity between the LIDAR system and the object can be determined. While the LIDAR input signal is typically an analog signal, processing is performed digitally, so LIDAR systems often include one or more analog-to-digital converters (ADCs) to convert the optical signal from the LIDAR input signal to a digital signal. Analog-to-digital converters (ADCs) are a significant cost component in commercial LIDAR systems.

[0005] For the above reasons, there is a need for a LIDAR system with reduced cost and complexity. Summary of the Invention

[0006] The imaging system includes one or more cores, each outputting a system output signal that illuminates multiple sample areas within a field of view. A reference core among the cores includes an optical coupling configured to generate a composite signal that beats at a beat frequency. The system also includes electronic circuitry configured to use the beat frequency value of the composite signal to calculate a magnitude of a radial velocity indicator for the reference core in the sample area illuminated by the system output signal output from the reference core. The radial velocity indicator indicates a radial velocity between the LIDAR system and an object in the reference sample area. The electronic circuitry is configured to identify a direction of the radial velocity indicator by comparing the magnitude of the radial velocity indicator with data calculated for one of the objects in the sample area. The reference sample area is different from the target sample area.

[0007] Another embodiment of the imaging system includes one or more cores, each of which outputs a system output signal that illuminates multiple sample regions in a field of view. A target one of the cores has an optical coupling that generates a composite signal that beats at a beat frequency. An electronic circuit uses the beat frequency value to calculate multiple different potential LIDAR data solutions for one of the targets in the sample region illuminated by the system output signal output from the target core. Each of the potential LIDAR data solutions has a comparison component that indicates a value of the radial velocity between the LIDAR system and an object in the target sample region. The electronic circuit identifies a correct LIDAR data solution by comparing the LIDAR data solution to data calculated for one or more reference sample regions selected from among the sample regions. The one or more reference sample regions are different from the target sample region.

[0008] A method for operating an imaging system includes illuminating multiple sample areas of 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, using a value of the beat frequency of the composite signal, a magnitude of a radial velocity indicator for one of the objects in the sample area illuminated by the system output signal output from the reference core. The radial velocity indicator indicates a radial velocity between the LIDAR system and an object in the reference sample area. 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 one of the objects in the sample area. The reference sample area is different from the sample area of ​​interest.

[0009] Another method of operating an imaging system includes illuminating multiple sample areas of a field of view with system output signals 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 uses the value of the beat frequency to calculate different potential LIDAR data solutions for objects in one of the multiple sample areas. Each of the potential LIDAR data solutions has a comparison component indicative of a value of the radial velocity between the LIDAR system and an object in the target sample area. The method further includes identifying a correct LIDAR data solution by comparing the LIDAR data solution to data calculated for one or more reference sample areas selected from among the sample areas. The one or more reference sample areas are different from the target sample area. [Brief explanation of the drawings]

[0010] FIG. 1A is a schematic plan view of a LIDAR system having or consisting of a LIDAR chip that outputs a LIDAR output signal and receives a LIDAR input signal in a common waveguide.

[0011] FIG. 1B is a schematic plan view of a LIDAR system having or consisting of a LIDAR chip that outputs a LIDAR output signal and receives a LIDAR input signal on a different waveguide.

[0012] FIG. 1C is a schematic plan view of another embodiment of a LIDAR system having or consisting of a LIDAR chip that outputs a LIDAR output signal and receives multiple LIDAR input signals in different waveguides.

[0013] FIG. 2 is a plan view of an example LIDAR adapter suitable for use with the LIDAR chip of FIG. 1B.

[0014] FIG. 3 is a plan view of an example LIDAR adapter suitable for use with the LIDAR chip of FIG. 1C.

[0015] FIG. 4 is a plan view of an example LIDAR system having the LIDAR chip of FIG. 1A and the LIDAR adapter of FIG. 2 on a common support.

[0016] FIG. 5A shows an example of a signal processor suitable for use with a LIDAR system.

[0017] FIG. 5B is a schematic diagram of electronic circuitry suitable for use with a signal processor constructed in accordance with FIG. 5A.

[0018] FIG. 5C is a frequency versus time graph of the system output signal.

[0019] FIG. 6A shows a LIDAR system with multiple different cores on a common support.

[0020] FIG. 6B illustrates the relationship between the data period and the field of view of the LIDAR system disclosed in FIG. 5C.

[0021] FIG. 6C shows an object in the field of view disclosed in the context of FIG. 6B.

[0022] FIG. 6D shows several different field positions relative to the range and sample area illuminated by the velocity core.

[0023] FIG. 7 is a two-dimensional view of the field of view of a LIDAR system.

[0024] FIG. 8 shows a general electronic circuitry configured to receive auxiliary LIDAR data generated by different cores.

[0025] FIG. 9 shows the target sample area and potential sample area for the field of view of FIG.

[0026] FIG. 10 is a process flow for generating throw distance data for a sample area illuminated by a velocity core of a LIDAR system having throw distance and velocity cores.

[0027] FIG. 11A is a schematic plan view of a LIDAR core suitable for use as a velocity core.

[0028] FIG. 11B is an example of a signal processing section suitable for use with the LIDAR core of FIG. 11A.

[0029] FIG. 11C provides a schematic of electronic circuitry suitable for use with a signal processing section constructed according to FIG. 11B.

[0030] FIG. 12A shows an example of a process flow that the electronic circuitry can use to identify the correct LIDAR data solution from among multiple possibilities.

[0031] FIG. 12B shows a LIDAR system with multiple different real data signal cores on a common support.

[0032] FIG. 12C is a two-dimensional view of the field of view of the LIDAR system of FIG. 12B.

[0033] FIG. 12D shows the target RV sample area and the reference V sample area for the field of view of FIG. 12C.

[0034] FIG. 12E shows a process flow for generating LIDAR data for a sample area illuminated by a LIDAR system having a real data signal core.

[0035] FIG. 13A shows an example of a process flow that the electronic circuitry can use to identify the radial velocity of the sample region SRk.

[0036] FIG. 13B shows a LIDAR system with multiple different real data signal cores on a common support.

[0037] FIG. 13C is a two-dimensional view of the field of view of the LIDAR system of FIG. 13B.

[0038] FIG. 13D shows the target RV sample area and the reference V sample area for the field of view of FIG. 13C.

[0039] FIG. 13E shows an example of a process flow that the electronic circuitry 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.

[0040] FIG. 13F shows a process flow for generating LIDAR data for a sample area illuminated by a LIDAR system having a real data signal core.

[0041] FIG. 13G shows a portion of the field of view of FIG. 12C or FIG. 13C, where the sample areas illuminated by different cores partially overlap.

[0042] Figure 14 is a cross-sectional view of a portion of a silicon-on-insulator wafer with a waveguide. DETAILED DESCRIPTION OF THE INVENTION [Example]

[0043] LIDAR systems typically illuminate multiple different regions of a field of view. The system generates LIDAR data for each sample region. The LIDAR data can indicate the line-of-sight velocity and / or distance between the LIDAR system and objects located in each field of view. These systems often apply a mathematical transform, such as a Fourier transform, to the beat signal to identify the beat signal's beat frequency. With a real transform, the transform can output multiple different frequencies. In many environments, it is unclear which of these frequencies is the correct frequency. As a result, multiple solutions for the LIDAR data for a sample region are often possible. To identify which solution is correct for a sample region, the LIDAR system compares the possible LIDAR data solutions for the sample region with data from other sample regions. As a result, LIDAR systems can use a real Fourier transform rather than a complex Fourier transform. A real Fourier transform typically requires fewer analog-to-digital converters (ADCs) than a complex Fourier transform. As a result, the cost and complexity of LIDAR systems is reduced by being able to use real Fourier transforms.

[0044] 1A is a schematic plan view of a LIDAR chip that can function as a LIDAR system or be included in a LIDAR system with additional components in addition to the LIDAR chip. The LIDAR chip can include a photonic integrated circuit (PIC) or can be a photonic integrated circuit chip. The LIDAR chip has a light source 4 that outputs a preliminary emitted LIDAR signal. Suitable light sources 4 include, but are not limited to, semiconductor lasers such as external cavity lasers (ECLs), distributed feedback lasers (DFBs), discrete mode (DM) lasers, and distributed Bragg reflector lasers (DBRs).

[0045] The LIDAR chip has a utility waveguide 12 that receives the outgoing LIDAR signal from the light source 4. The utility waveguide 12 terminates at a facet 14 and conveys the outgoing LIDAR signal to the facet 14. The facet 14 can be positioned such that the outgoing LIDAR signal traveling through the facet 14 exits the LIDAR chip and functions as the LIDAR output signal. For example, the facet 14 can be positioned at the edge of the chip such that the outgoing LIDAR signal traveling through the facet 14 exits the chip and functions as the LIDAR output signal. In some cases, a portion of the LIDAR output signal exiting the LIDAR chip can also be considered a system output signal. As an example, if the exit for the LIDAR output signal from the LIDAR chip is also the exit for the LIDAR output signal from the LIDAR system, the LIDAR output signal can also be considered a system output signal.

[0046] The LIDAR output signal travels away from the LIDAR system through the environment in which the LIDAR system is located and free space in the atmosphere. 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 travels back toward the LIDAR chip as the LIDAR input signal. In some examples, the LIDAR input signal may also be considered a system return signal. As an example, if the exit of the LIDAR output signal from the LIDAR chip is also the exit of the LIDAR output signal from the LIDAR core, the LIDAR input signal may also be considered a system return signal.

[0047] A LIDAR input signal can enter utility waveguide 12 through facet 14. A portion of the LIDAR input signal entering utility waveguide 12 serves as the incident LIDAR signal. Utility waveguide 12 carries the incident LIDAR signal to splitter 16, which moves a portion of the outgoing LIDAR signal from utility waveguide 12 to comparison waveguide 18 as a comparison signal. Comparison waveguide 18 carries the comparison signal to processing component 22 for further processing. While FIG. 1A shows a directional coupler operating as splitter 16, other signal tap components can be used as splitter 16. Suitable splitters 16 include, but are not limited to, directional couplers, optical couplers, y-couplers, tapered couplers, and multi-mode interference (MMI) devices.

[0048] 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 processing component 22 for further processing.

[0049] The fraction of light redirected by splitter 16 from utility waveguide 12 can be fixed or substantially fixed. For example, splitter 16 can be configured so that the power of the reference signal redirected to reference waveguide 20 is the ratio of the power of the outgoing LIDAR signal, or so that the power of the comparison signal redirected to comparison waveguide 18 is the ratio of the power of the incoming LIDAR signal. In many splitters 16, such as directional couplers and multimode interferometers (MMIs), the ratio of the outgoing light is equal to or substantially equal to the ratio of the incoming light. In some examples, the ratio of the outgoing light is greater than 30%, 40%, or 49% and / or less than 51%, 60%, or 70% and / or the ratio of the incoming light is greater than 30%, 40%, or 49% and / or less than 51%, 60%, or 70%. Splitter 16, such as a multimode interferometer (MMI), typically provides a 50% or approximately 50% exit and entrance ratio. However, multimode interferometers (MMIs) are easier to fabricate on platforms such as silicon-on-insulator platforms than some alternatives. In one example, splitter 16 is a multimode interferometer (MMI) and the exit and entrance ratios are 50% or substantially 50%. As described in more detail below, processing component 22 combines the comparison signal with the reference signal to form a composite signal that carries LIDAR data about a sample area on the field of view. Thus, the composite signal can be processed to extract LIDAR data about the sample area (e.g., radial velocity and / or distance between the LIDAR core and objects external to the LIDAR system).

[0050] The LIDAR chip can include a control branch for controlling the operation of the light source 4. The control branch has a splitter 26 that moves a portion of the outgoing LIDAR signal from the utility waveguide 12 to a control waveguide 28. The combined portion of the outgoing LIDAR signal serves as a tap signal. While FIG. 1A shows a directional coupler acting as the splitter 26, other signal tap components can be used as the splitter 26. Suitable splitters 26 include, but are not limited to, directional couplers, optical couplers, y-couplers, tapered couplers, and multi-mode interference (MMI) devices.

[0051] The control waveguide 28 carries the tap signal to a control component 30, which can be in electrical communication with electronic circuitry 32. In operation, the electronic circuitry can use the output from the control component 30 in a control loop configured to control one, two, or three process variables of the loop-controlled 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-controlled optical signal and / or the phase of the loop-controlled optical signal.

[0052] LIDAR systems can be modified so that the incoming and outgoing LIDAR signals are carried in different waveguides. For example, FIG. 1B is a plan view of the LIDAR chip of FIG. 1A modified to carry the incoming and outgoing LIDAR signals in different waveguides. The outgoing LIDAR signal exits the LIDAR chip through facet 14 and serves as the LIDAR output signal. When light from the LIDAR output signal is reflected by an object external to the LIDAR system, at least a portion of the reflected light returns to the LIDAR chip as the first LIDAR input signal. The first LIDAR input signal enters comparison waveguide 18 through facet 35 and serves as the comparison signal. Comparison waveguide 18 carries the comparison signal to signal processor 22 for further processing. As described in connection with FIG. 1A, reference waveguide 20 carries the reference signal to signal processor 22 for further processing. As will be explained 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 about the sample area on the field of view.

[0053] The LIDAR chip can be modified to receive multiple LIDAR input signals. For example, FIG. 1C shows the LIDAR chip of FIG. 1B modified to receive two LIDAR input signals. The splitter 40 is configured to direct a portion of the reference signal carried in the reference waveguide 20 to a first reference waveguide 42 and another portion of the reference signal to a second reference waveguide 44. Thus, 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 a first signal processor 46, and the second reference waveguide 44 carries the second reference signal to a second signal processor 48. Examples of suitable splitters 40 include, but are not limited to, y-couplers, optical couplers, and multimode interference couplers (MMIs).

[0054] The outgoing LIDAR signal exits the LIDAR chip through facet 14 and serves as the LIDAR output signal. When light from the LIDAR output signal is reflected by one or more objects located 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 comparison waveguide 18 through facet 35 and serves as a first comparison signal. Comparison waveguide 18 conveys the first comparison signal to first signal processor 46 for further processing.

[0055] Additionally, when light from the LIDAR output signal is reflected by one or more objects located external to the LIDAR system, 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 facet 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.

[0056] Although the light source 4 is shown as being located on the LIDAR chip, the light source 4 can be located off the LIDAR chip. For example, the utility waveguide 12 can terminate at a second facet where the outgoing LIDAR signal can enter the utility waveguide 12 from the light source 4 located off the LIDAR chip.

[0057] 1B or 1C is used with a LIDAR adapter. In some examples, 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 along which the first LIDAR input signal and / or the LIDAR output signal travel from the LIDAR chip to the field of view passes through the LIDAR adapter. Furthermore, the LIDAR adapter can be configured to manipulate the first LIDAR input signal and the LIDAR output signal so that the first LIDAR input signal and the LIDAR output signal travel different optical paths between the LIDAR adapter and the LIDAR chip, but travel the same optical path between the LIDAR adapter and reflective objects in the field of view.

[0058] An example of a LIDAR adapter suitable for use with the LIDAR chip of FIG. 1B is shown in FIG. 2. The LIDAR adapter includes multiple components located on a base. For example, the LIDAR adapter includes a circulator 100 disposed on a base 102. The illustrated optical circulator 100 has three ports and is configured so that light entering one port exits the next port. For example, the illustrated optical circulator 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 the second port 106.

[0059] The LIDAR adapter can be configured such that the output of the LIDAR output signal from the second port 106 can also function as an output of the LIDAR output signal from the LIDAR adapter, and therefore the LIDAR system. As a result, the LIDAR output signal can be output from the LIDAR adapter such that the LIDAR output signal travels toward a sample area within the field of view. Thus, in some examples, a portion of the LIDAR output signal that exits the LIDAR adapter can also be considered a system output signal. As an example, if the exit of the LIDAR output signal from the LIDAR adapter is also an exit of the LIDAR output signal from the LIDAR core, the LIDAR output signal can also be considered a system output signal.

[0060] The LIDAR output signal output from the LIDAR adapter comprises, consists of, or essentially consists of light derived from the LIDAR output signal received from the LIDAR chip. Thus, the LIDAR output signal output from the LIDAR adapter will be the same or substantially 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 optical loss as the LIDAR output signal 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.

[0061] When one or more objects in the sample area reflect the LIDAR output signal, at least a portion of the reflected light travels 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 shows the LIDAR output signal and the system return signal traveling along the same optical path between the LIDAR adapter and the sample area.

[0062] 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 function as the first LIDAR input signal, and the first LIDAR input signal comprises or comprises light derived 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.

[0063] As is apparent from Figure 2, the LIDAR adapter can include optical components in addition to the circulator 100. For example, the LIDAR adapter can include components that direct and control the optical paths of the LIDAR output signal and the system return signal. As an example, the adapter of Figure 2 includes an optional amplifier 110 that is positioned to receive and amplify the LIDAR output signal before it enters the circulator 100. The local electronics 32 can operate the amplifier 110 such that the local electronics 32 can control the power of the LIDAR output signal.

[0064] FIG. 2 also illustrates a LIDAR adapter having 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 can be configured to focus or collimate the LIDAR output signal at a desired location. In one example, if the LIDAR adapter does not include an amplifier 110, the first lens 112 can be configured to couple the LIDAR output signal to the first port 104. As another example, if the LIDAR adapter includes an amplifier 110, the first lens 112 can be configured to couple the LIDAR output signal to an entrance port to 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 can be 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 facet 35 of the comparison waveguide 18.

[0065] The LIDAR adapter may also have one or more redirecting components, such as a mirror. Figure 2 shows a LIDAR adapter with a mirror as the redirecting component 116 that redirects the system return signal from the circulator 100 to the facet 20 of the comparison waveguide 18.

[0066] The LIDAR chip includes one or more waveguides that constrain the optical path of one or more optical signals. While the LIDAR adapter includes waveguides, the optical paths along which the system return signal and the LIDAR output signal travel between components of the LIDAR adapter and / or between the LIDAR chip and components of the LIDAR adapter can be free space. For example, the system return signal and / or the LIDAR output signal can travel through the atmosphere and / or the environment in which the LIDAR chip, LIDAR adapter, and / or base 102 are located when traveling between different components of the LIDAR adapter and / or between components of the LIDAR adapter and the LIDAR chip. As a result, optical components such as lenses and redirecting components can be used to control the characteristics of the optical paths along which the system return signal and the LIDAR output signal travel on, toward, and from the LIDAR adapter.

[0067] Suitable bases 102 for LIDAR adapters include, but are not limited to, substrates, platforms, and plates. Suitable substrates include, but are not limited to, glass, silicon, and ceramic. The components can be separate components attached to the substrate. Suitable techniques for attaching separate components to the base 102 include, but are not limited to, epoxy, solder, and mechanical clamps. In one example, one or more components are integrated components and the remaining components are separate components. In another example, the LIDAR adapter has one or more integrated amplifiers and the remaining components are separate components.

[0068] LIDAR systems can be configured to compensate for polarization. Light from a laser light source is typically linearly polarized, and therefore the LIDAR output signal is also typically linearly polarized. Reflection from an object may change the polarization angle of the returning light. Thus, the system return signal may contain light of different linear polarization states. For example, a first portion of the system return signal may have light of a first linear polarization state, and a second portion of the system return signal may have light of a second linear polarization state. The strength of the resulting composite signal is proportional to the cosine squared of the angle between the comparison signal polarization field and the reference signal polarization field. If the angle is 90 degrees, LIDAR data may be lost in the resulting composite signal. However, LIDAR systems can be modified to compensate for changes in the polarization state of the LIDAR output signal.

[0069] FIG. 3 shows the LIDAR system of FIG. 3 modified so that the LIDAR adapter is suitable for use with the LIDAR chip of FIG. 1C. The 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, a Wollaston prism and a MEMS-based beam splitter.

[0070] A first portion of the system return signal is directed to a comparison waveguide 18 on the LIDAR chip and serves as the first LIDAR input signal, as described in connection with FIG. 1C. A second portion of the system return signal is directed to a polarization rotator 122, which outputs a second LIDAR input signal that is directed to a second input waveguide 76 on the LIDAR chip and serves as the second LIDAR input signal.

[0071] The beam splitter 120 can be a polarizing beam splitter. An example of a polarizing beam splitter is configured so that a first portion of the system return signal has a first polarization state but is free or substantially free of a second polarization state, and a second portion of the system return signal has a second polarization state but is free or substantially free of the first polarization state. The first and second polarization states can be linear polarization states, and the second polarization state can be different from the first polarization state. For example, the first polarization state can be TE and the second polarization state can be TM, or the first polarization state can be TM and the second polarization state can be TE. In some cases, the laser light source can be linearly polarized so that the LIDAR output signal has the first polarization state. Suitable beam splitters include, but are not limited to, Wollaston prisms and MEMS-based polarizing beam splitters.

[0072] The polarization rotator can 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. For example, the polarization rotator 122 shown in FIG. 3 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. As a result, the second LIDAR input signal has the first polarization state but does not have substantially or substantially does not have the second polarization state. Thus, the first LIDAR input signal and the second LIDAR input signal each have the same polarization state (the first polarization state in this example). Despite carrying light of the same polarization state, the first LIDAR input signal and the second LIDAR input signal are associated with different polarization states as a result of the use of the polarizing beam splitter. For example, the first LIDAR input signal carries reflected light with the first polarization state, and the second LIDAR input signal carries reflected light with the second polarization state. As a result, the first LIDAR input signal is associated with a first polarization state and the second LIDAR input signal is associated with a second polarization state.

[0073] Because the first LIDAR input signal and the second LIDAR carry light of the same polarization state, the comparison signal resulting from the first LIDAR input signal has the same polarization angle as the comparison signal resulting from the second LIDAR input signal.

[0074] Suitable polarization rotators include, but are not limited to, polarization-maintaining fiber rotators, Faraday rotators, half-wave plates, MEMS-based polarization rotators, and integrated optics polarization rotators using asymmetric y-branchers, Mach-Zehnder interferometers, and multimode interference couplers.

[0075] Because the outgoing LIDAR signal is linearly polarized, the first reference signal can have the same linear polarization state as the second reference signal. Additionally, the components of the LIDAR adapter can be selected so that the first reference signal, the second reference signal, the comparison signal, and the second comparison signal each have the same polarization state. In the example disclosed in connection with FIG. 3, the first comparison signal, the second comparison signal, the first reference signal, and the second reference signal can each have light of a first polarization state.

[0076] As a result of 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 each result from combining a reference signal and a comparison signal of the same polarization state and provide a desired beat between the reference signal and the comparison signal. For example, the composite signal may be the result of combining the first reference signal and the first comparison signal of a first polarization state and excluding or substantially excluding light of a second polarization state, or the result of combining the first reference signal and the first comparison signal of a second polarization state and excluding or substantially excluding light of the first polarization state. Similarly, the second composite signal may include the second reference signal and the second comparison signal of the same polarization state, thus providing a desired beat between the reference signal and the comparison signal. For example, the second composite signal may be the result of combining a second reference signal of a first polarization state with a second comparison signal and excluding or substantially excluding light of the second polarization state, or the second composite signal may be the result of combining a second reference signal of a second polarization state with a second comparison signal and excluding or substantially excluding light of the first polarization state.

[0077] The above configuration results in LIDAR data for a single sample area of ​​the field of view generated from multiple different composite signals (i.e., a first composite signal and a second composite signal) from the sample area. In some examples, determining the LIDAR data for the sample area includes electronic circuitry combining the LIDAR data from the different composite signals (i.e., the first composite signal and the second composite signal). Combining the LIDAR data can include taking the mean, median, or mode of the LIDAR data generated from the different composite signals. For example, the electronic circuitry can average a distance between the LIDAR core and a reflecting object determined from a composite signal having a distance determined from the second composite signal, and / or the electronic circuitry can average a radial velocity between the LIDAR core and a reflecting object determined from a composite signal having a radial velocity determined from the second composite signal.

[0078] In some examples, determining LIDAR data for the sample area includes electronic circuitry identifying one or more composite signals (i.e., the composite signal and / or the second composite signal) as the source of the most representative LIDAR data (representative LIDAR data). The electronic circuitry can then use the LIDAR data from the identified composite signals as the representative LIDAR data for further processing. For example, the electronic circuitry can identify a signal (the composite signal or the second composite signal) having a larger amplitude as having the representative LIDAR data and use the LIDAR data from the identified signal for further processing by the LIDAR core. In some examples, the electronic circuitry combines identifying the composite signal with the representative LIDAR data with combining LIDAR data from different LIDAR signals. For example, the electronic circuitry can identify each composite signal with an amplitude above an amplitude threshold as having the representative LIDAR data, and if two or more composite signals are identified as having the representative LIDAR data, the electronic circuitry can combine the LIDAR data of each identified composite signal. If one composite signal is identified as having representative LIDAR data, the electronics can use the LIDAR data from that composite signal as the representative LIDAR data. If none of the composite signals are identified as having representative LIDAR data, the electronics can discard the LIDAR data for the sample areas associated with those composite signals.

[0079] Although Figure 3 is described with reference to components arranged such that the first comparison signal, the second comparison signal, the first reference signal, and the second reference signal each have a first polarization state, other configurations of the components of Figure 3 can be arranged such that the composite signal is the result of combining the reference signal and the comparison signal with the same linear polarization state, and the second composite signal is the result of combining the reference signal and the comparison signal with the same linear polarization state. For example, beamsplitter 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 output LIDAR signal has a second polarization state. In this example, the first LIDAR input signal and the second LIDAR input signal each have a second polarization state.

[0080] 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, such that 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 electronic circuitry can process each composite signal so that the LIDAR core compensates for changes in the polarization state of the LIDAR output signal in response to reflections of the LIDAR output signal.

[0081] The LIDAR adapter of FIG. 3 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 at the facet 52 of the second comparison waveguide 50. The LIDAR adapter also includes one or more redirecting components 124, such as mirrors and prisms. FIG. 3 illustrates a LIDAR adapter with a mirror as the redirecting component 124 that redirects the second portion of the system return signal from the circulator 100 to the facet 52 of the second comparison waveguide 50 and / or the third lens 1266.

[0082] If the LIDAR core includes a LIDAR chip and a LIDAR adapter, the LIDAR chip, electronics, and LIDAR adapter can be disposed on a common mount. Suitable common mounts include, but are not limited to, glass, metal, silicon, and ceramic plates. As an example, FIG. 4 is a plan view of a LIDAR core having the LIDAR chip of FIG. 1A, the local electronics 32, and the LIDAR adapter of FIG. 2 mounted on a common support 140. While the local electronics 32 is shown as being disposed on the common support, all or part of the electronics can be disposed outside the common support. If the light source 4 is disposed outside the LIDAR chip, the light source can be disposed on the common support 240 or outside the common support 140. Suitable approaches for attaching the LIDAR chip, electronics, and / or LIDAR adapter to the common support include, but are not limited to, epoxy, solder, and mechanical clamps.

[0083] 5A-5C illustrate examples of signal processors 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. The signal processors receive a comparison signal from a comparison waveguide 196 and a reference signal from a reference waveguide 198. The comparison waveguide 18 and reference waveguide 20 shown in FIGS. 1A and 1B can function as the comparison waveguide 196 and reference waveguide 198, the comparison waveguide 18 and first reference waveguide 42 shown in FIG. 1C can function as the comparison waveguide 196 and reference waveguide 198, or the second comparison waveguide 50 and second reference waveguide 44 shown in FIG. 1C can function as the comparison waveguide 196 and reference waveguide 198.

[0084] The signal processing section includes a second splitter 200 that splits 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 coupling section 211. The second comparison waveguide 208 carries a second portion of the comparison signal to a second signal coupling section 212.

[0085] The signal processing section includes a first splitter 202 that splits a reference signal carried in the reference waveguide 196 into 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 coupling section 211. The second reference waveguide 208 carries a second portion of the reference signal to a second signal coupling section 212.

[0086] The second signal combiner 212 combines the second portion of the comparison signal and the second portion of the reference signal into a second composite signal, which beats between the second portion of the comparison signal and the second portion of the reference signal due to the frequency difference between the second portion of the comparison signal and the second portion of the reference signal.

[0087] The second signal combiner 212 also splits the resulting second composite signal into a first auxiliary detection waveguide 214 and a second auxiliary detection waveguide 216. The first auxiliary detection 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 detection 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).

[0088] In some cases, the second signal combining unit 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., part of the second portion of the comparison signal) is out of phase with the portion of the comparison signal in the second portion of the second composite signal (i.e., part of the second portion of the comparison signal), by 180°, but the portion of the reference signal in the second portion of the second composite signal (i.e., part of the second portion of the reference signal) is not out of phase with the portion of the reference signal in the first portion of the second composite signal (i.e., part of the second portion of the reference signal). Alternatively, the second signal combiner 212 divides the second composite signal so that the reference signal portion in the first portion of the second composite signal (i.e., part of the second portion of the reference signal) is 180° out of phase with the reference signal portion in the second portion of the second composite signal (i.e., part of the second portion of the reference signal), but the comparison signal portion in the first portion of the second composite signal (i.e., part of the second portion of the comparison signal) is not out of phase with the comparison signal portion in the second portion of the second composite signal (i.e., part of the second portion of the comparison signal). Examples of suitable optical sensors include germanium photodiodes (PDs) and avalanche photodiodes (APDs).

[0089] The first signal combiner 211 combines the first portion of the comparison signal and the first portion of the reference signal into a first composite signal, and the first composite signal beats between the first portion of the comparison signal and the first portion of the reference signal due to a frequency difference between the first portion of the comparison signal and the first portion of the reference signal.

[0090] The first signal combiner 211 also splits the first composite signal into a first detection waveguide 221 and a second detection waveguide 222. The first detection waveguide 221 carries a first portion of the first composite signal to a first optical sensor 223, which converts a first portion of the second composite signal into a first electrical signal. The second detection waveguide 222 carries a second portion of the second composite signal to a second optical sensor 224, which converts a second portion of the second composite signal into a second electrical signal. Examples of suitable optical sensors include germanium photodiodes (PDs) and avalanche photodiodes (APDs).

[0091] In some cases, the signal combining unit 211 divides the first composite signal so that the portion of the comparison signal included in the first portion of the composite signal (i.e., part of the first portion of the comparison signal) is out of phase with the portion of the comparison signal in the second portion of the composite signal (i.e., part of the first portion of the comparison signal) by 180°, but the portion of the reference signal in the first portion of the composite signal (i.e., part of the first portion of the comparison signal) is not out of phase with the portion of the reference signal in the second portion of the composite signal (i.e., part of the first portion of the reference signal). Alternatively, the signal combining unit 211 divides the composite signal so that the portion of the reference signal in the first portion of the composite signal (i.e., part of the first portion of the reference signal) is out of phase with the portion of the reference signal in the second portion of the composite signal (i.e., part of the first portion of the reference signal), but the portion of the comparison signal in the first portion of the composite signal (i.e., part of the first portion of the comparison signal) is not out of phase with the portion of the comparison signal in the second portion of the composite signal (i.e., part of the first portion of the comparison signal).

[0092] When the second signal combiner 212 divides the second composite signal such that the comparison signal portion in the first portion of the second composite signal is shifted 180° in phase with the comparison signal portion in the second portion of the second composite signal, the signal combiner 211 also divides the composite signal such that the comparison signal portion in the first portion of the composite signal is shifted 180° in phase with the comparison signal portion in the second portion of the composite signal. When the second signal combiner 212 divides the second composite signal such that the reference signal portion in the first portion of the second composite signal is shifted 180° in phase with the reference signal portion in the second portion of the second composite signal, the signal combiner 211 also divides the composite signal such that the reference signal portion in the first portion of the composite signal is shifted 180° in phase with the reference signal portion in the second portion of the composite signal.

[0093] The first reference waveguide 210 and the second reference waveguide 208 are configured to provide a phase shift between the first portion of the reference signal and the 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. As an example, one reference signal portion can be an in-phase component and the other a quadrature component. Thus, one reference signal portion 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 constructed so that the first reference signal portion is a cosine function and the second reference signal portion is a sine function. Thus, the reference signal portion in the second composite signal is out of phase with respect to the reference signal portion in the first composite signal, while the comparison signal portion in the first composite signal is out of phase with respect to the comparison signal portion in the second composite signal.

[0094] The first optical sensor 223 and the second optical sensor 224 can be connected as a balanced detector, and the first auxiliary optical sensor 218 and the second auxiliary optical sensor 220 can also be connected as a balanced detector. For example, FIG. 5B provides a schematic of the relationship between the electronic circuitry, the first optical sensor 223, the second optical sensor 224, the first auxiliary optical sensor 218, and the second auxiliary optical sensor 220. Although symbols for photodiodes are used to represent the first optical sensor 223, the second optical sensor 224, the first auxiliary optical sensor 218, and the second auxiliary optical sensor 220, one or more of these sensors can have other configurations. In some cases, all of the components shown in the schematic diagram of FIG. 5B are included on the LIDAR chip. In some cases, the components shown in the schematic diagram of FIG. 5B are distributed between the LIDAR chip and electronic circuitry located off the LIDAR chip.

[0095] The electronic circuitry connects the first and second optical sensors 223 and 220 as a first balanced detector 225 and the first and second auxiliary optical sensors 218 and 220 as a second balanced detector 226. Specifically, the first and second optical sensors 223 and 224 are connected in series. The electronic circuitry also connects the first and second auxiliary optical sensors 218 and 220 in series. The first and second balanced detectors communicate with a first data line 228 carrying the output from the first balanced detector as a first data signal. The second and second balanced detectors communicate with a second data line 232 carrying 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. Thus, the first data signal includes contributions from a first waveform and a second waveform, and the second data signal is a composite of the first and second waveforms. A portion of the first waveform in the first data signal is out of phase with a portion of the first waveform in the first data signal, while a portion of the second waveform in the first data signal is in phase with a portion of the second waveform in the first data signal. For example, the second data signal has a portion of the reference signal that is out of phase with a different portion of the reference signal included in the first data signal. Additionally, the second data signal has 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 and second data signals beat as a result of the beat between the comparison signal and the reference signal, i.e., the beat in the first composite signal and the beat in the second composite signal.

[0096] The local electronics 32 includes a beat frequency detector 238 configured to detect the beat frequency of the composite signal. The beat frequency detector 238 can perform a mathematical transform on the first and second data signals. For example, the mathematical transform can be a complex Fourier transform with the first and second data signals as inputs. Because the first data signal is the in-phase component and the second data signal is its quadrature component, the first and second data signals together act as a complex data signal, with the first data signal being the real component of the input and the second data signal being the imaginary component of the input.

[0097] The beat frequency detector 238 includes a first analog-to-digital converter (ADC) 264 that receives the first data signal from the first data line 228. The first analog-to-digital converter (ADC) converts the first data signal from analog to digital format and outputs a first digital data signal. The beat frequency detector 238 includes a second analog-to-digital converter (ADC) 266 that receives the second data signal from the second data line 232. The second analog-to-digital converter (ADC) 226 converts the second data signal from analog to digital format 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. Thus, the first digital data signal and the second digital data signal act together as a complex signal, with the first digital data signal acting as the real component of the complex signal and the second digital data signal acting as the imaginary component of the complex data signal.

[0098] The beat frequency detector 238 includes a converter 268 that receives a complex data signal. For example, the converter 268 receives a first digital data signal as an input from a first analog-to-digital converter (ADC) 264 and a second digital data signal as an input from a second analog-to-digital converter (ADC) 266. The converter 268 can be configured to perform a mathematical transform on the complex signal to convert it from the time domain to the frequency domain. The mathematical transform can be a complex transform, such as a complex Fast Fourier Transform (FFT). A complex transform, such as a complex Fast Fourier Transform (FFT), provides an unambiguous solution for the frequency shift of the LIDAR input signal relative to the LIDAR output signal caused by the radial velocity between the reflecting object and the LIDAR tip. The electronic circuitry utilizes one or more frequency peaks output from the converter 268 for further processing to generate LIDAR data (e.g., the distance and / or radial velocity between the reflecting object and the LIDAR tip or LIDAR core). The local electronics 32 may include a peak detector (not shown) that identifies the beat frequency of one or more frequency peaks.

[0099] The local electronics 32 may include an auxiliary LIDAR data generator 269 configured to receive the beat frequency from the converter 268. The auxiliary LIDAR data generator 269 is configured to generate auxiliary LIDAR data for the sample area. The LIDAR data for the sample area includes values ​​for line-of-sight velocity and / or separation distance between the LIDAR system and objects 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 auxiliary LIDAR data generator 269 calculates LIDAR data to serve as auxiliary LIDAR data. For example, in some cases, the auxiliary LIDAR data generator 269 calculates line-of-sight velocity and / or separation distance between the LIDAR system and objects in the sample area as auxiliary LIDAR data. As described below, other examples of auxiliary LIDAR data that can be calculated by the auxiliary data generator include, but are not limited to, potential solutions for the LIDAR data for the sample area, and potential line-of-sight velocity magnitude indicators and / or velocity magnitude indicators for the sample area. The converter 268 and / or auxiliary LIDAR data generator 269 can perform the attribution functions using firmware, hardware, software, or a combination thereof.

[0100] While Figure 5A shows a signal combiner that combines a portion of the reference signal with a portion of the comparison signal, the signal processor can include a single optical combining component that combines the reference signal and the comparison signal to form a composite signal. As a result, at least a portion of the reference signal and at least a portion of the comparison signal can be combined to form the composite signal. The combined portion of the reference signal can be the entire reference signal or a portion of the reference signal, and the combined portion of the comparison signal can be the entire comparison signal or a portion of the comparison signal.

[0101] The electronic circuitry adjusts the frequency of the system output signal over time. The system output signal has a frequency versus time pattern over a repeating period. Figure 5C shows an example of a suitable frequency versus time pattern for the system output signal. The base frequency (f0) of the system output signal can be the frequency of the system output signal at the start of the period.

[0102] FIG. 5C shows the frequency of the system output signal for a sequence of two periods, labeled Period j and Period j+1. For example, the frequency versus time pattern repeats in each of the periods shown in FIG. 5C. The periods shown do not have rearrangement periods and / or rearrangement periods are not spaced between periods. As a result, FIG. 5C shows the results of successive scans.

[0103] Each period has M data periods, each associated with a period index m and labeled DPm. In the example of FIG. 5C, each period has three data periods, labeled DPm, with m=1 and 2. In some cases, as shown in FIG. 5C, the frequency versus time pattern is the same for corresponding data periods in different periods. Corresponding data periods are data periods with the same period index. As a result, each of the data periods DP1 can be considered a corresponding data period, and the associated frequency versus time pattern is the same in FIG. 5C. At the end of a period, the electronic circuitry returns the frequency to the same frequency level that started the previous period.

[0104] During the data period DPm, the electronic circuitry operates the light source so that the frequency of the system output signal varies at a linear rate (chirp rate) αm, where α2 = -α1 in Figure 5C.

[0105] FIG. 5c labels sample areas, each associated with a sample area index k and labeled SRk. FIG. 5c labels sample areas SRk-1 through SRk+1. Each sample area is illuminated with a system output signal during the data period shown in FIG. 5c associated with the sample area. For example, sample area SRk+1 is illuminated by a system output signal during the data period labeled DP2 in period j+1 and the data period labeled DP1 in period j+1. Thus, the sample area labeled SRk+1 is associated with the data periods labeled DP1 and DP2 in period j+1. Sample area index k can be assigned with respect to time. For example, the sample areas can be illuminated by the system output signal in the sequence indicated by index k. As a result, sample area SR10 can be illuminated after sample area SR9 and before sample area SR11.

[0106] The frequency output from the complex Fourier transform represents the beat frequencies of the composite signal, each having a comparison signal that beats relative to a reference signal. 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 frequency determined from DP1 during illumination of sample area SRk can be combined with the beat frequency determined from DP2 during illumination of sample area SRk to determine LIDAR data for sample area SRk. As an example, during a data period in which the electronic circuitry increases the frequency of the outgoing LIDAR signal during the data period, such as occurs in data period DP1 of FIG. 5C, the following equation applies: fub=-fd+αuτ, where fub is the frequency provided by the converter 268, fd represents the Doppler shift (fd=2Vkfc / c), where fc represents the optical frequency (f0), c represents the speed of light, Vk represents the radial velocity between the reflecting object and the LIDAR core, where the direction from the reflecting object towards the chip is assumed to be the positive direction, and c is the speed of light, and αu represents the chirp rate (αm) for the data period, where the frequency of the system output signal increases with time (α1 in this case). The radial velocity may be a relative radial velocity because both the LIDAR core and the object may be moving, or the LIDAR core and / or the object may be stationary.

[0107] During a data period in which the frequency of the outgoing LIDAR signal decreases, such as occurs in data period DP2 of FIG. 5C, the following equation applies: f = -f -ατ, where f is the frequency provided by the converter 268, and α represents the chirp rate (α) for the data period, where the frequency of the system output signal increases with time (in this case, α). In these two equations, f and τ are unknowns. These equations can be solved for the two unknowns. An electronic circuit such as the auxiliary LIDAR data generator 269 can calculate the radial velocity (V) for sample region k from the Doppler shift (V = c × f / (2fc)) and / or the separation distance (R) for sample region k from c × τ / 2.

[0108] When the LIDAR core has a signal processor configured as disclosed in the content of Figures 5A-5C and the control circuitry is configured to calculate the radial velocity and distance between the LIDAR core and an object for each sample area, the LIDAR core is suitable for use as a range and velocity core. However, the LIDAR core can also have a signal processor configured as disclosed in the content of Figures 5A-5B and the electronic circuitry can be configured to calculate the radial velocity without calculating the distance. In these examples, the LIDAR core is suitable for use as a velocity core.

[0109] In an example of a velocity core, the electronic circuitry can operate the light source 4 such that the system output signal having a frequency that is a function of time as disclosed in the content of FIG. 5C is replaced by a system output signal whose frequency is not a function of time. For example, the frequency of the system output signal can be constant during each data period shown in FIG. 5C. In some cases, the system output signal can be continuous wave (CW). For example, the outgoing LIDAR signal, and thus the system output signal, can be non-chirped continuous wave (CW). As an example, the outgoing LIDAR signal, and thus the system output signal, can be represented by 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.

[0110] Because the frequency of the system output signal is constant, changes in the distance between the reflecting object and the LIDAR tip do not cause a change in the frequency of the LIDAR input signal. As a result, the separation distance does not contribute to the shift in the frequency of the LIDAR input signal relative to the frequency of the LIDAR output signal. Therefore, the effect of separation distance has been eliminated, or nearly eliminated, from the shift in the frequency of the LIDAR input signal relative to the frequency of the LIDAR output signal.

[0111] The speed core can include a signal processor configured as disclosed in the context of Figures 5A and 5B. As discussed above in the context of Figure 5B, a first analog-to-digital converter (ADC) 264 receives the first data signal 228 and outputs a first digital data signal. A second analog-to-digital converter (ADC) 266 receives the second data signal 228 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 first data signal. Thus, the first digital data signal and the second digital data signal consistently function as a composite signal, with the first digital data signal functioning as the real part of the composite data and the second digital data signal functioning as the imaginary part of the composite data.

[0112] The transform unit 268 receives the complex data signal. The transform unit 268 can be configured to perform a mathematical transform on the complex signal to convert it from the time domain to the frequency domain. The mathematical transform can be a complex transform, such as a complex Fast Fourier Transform (FFT). A complex transform, such as a complex Fast Fourier Transform (FFT), provides an explicit solution for the frequency shift of the LIDAR input signal relative to the LIDAR output signal caused by the radial velocity between the reflecting object and the LIDAR tip. The frequency shift provided by the transform unit 268 does not have an input from the frequency shift due to the separation distance between the reflecting object and the LIDAR tip, and due to the complex nature of the velocity data signal, the output of the transform unit 268 can be used to calculate the radial velocity between the reflecting object and the LIDAR tip. In some cases, electronic circuitry such as an auxiliary LIDAR data generator can approximate the radial velocity (v) between a reflecting object and the LIDAR chip using Equation 4: v = c × fd / (2 × fc), where fd is approximated as the peak frequency output from the converter 268, c is the speed of light, and fc represents the frequency of the LIDAR output signal. As a result, multiple data periods and / or chirps are not required for the velocity core to calculate the radial velocity.

[0113] The first digital-to-analog 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 digital-to-analog 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 continuous waves for the first and second data signals, the effect of the distance between the reflecting object and the LIDAR chip is effectively removed from the composite signal and the resulting beat of the electrical signal. Therefore, the beat frequency of the composite signal is reduced, and the required sampling rate is reduced. In some cases, the illumination distance and the sampling rate of the analog-to-digital converter in the velocity core can be on the order of 4 GSPS. In some cases, the sampling rate of the analog-to-digital converter in the velocity core can be on the order of 400 MSPS.

[0114] 5A and 5B are disclosed in the context of a complex data signal, a real data signal can be used. As a result, the signal processing units of FIG. 5A and 5B can be modified to eliminate components associated with the second data signal, and the transform unit 268 can be configured to perform a real Fourier transform (FFT). Thus, the signal processing unit can include a single signal combiner 211 and a single analog-to-digital converter (ADC).

[0115] A LIDAR system can have one or more range and velocity cores and one or more velocity cores. By way of example, FIG. 6A shows a LIDAR system having multiple different cores on a common support 140. Each LIDAR core can be constructed as disclosed in the context of FIGS. 1A through 5 or can have an alternative construction. One or more of the LIDAR cores can have a velocity core, and one or more of the LIDAR cores can have a range and velocity core. For illustrative purposes, the LIDAR cores of the LIDAR system of FIG. 6A have one range and velocity core 270 and three velocity cores 272.

[0116] Each LIDAR core outputs a different system output signal. The system output signals are received by a redirecting component 274, which redirects the system output signal. Suitable redirecting components 274 include, but are not limited to, convex lenses and concave mirrors. The system output signals output from the collimator 274 are received by one or more beam steering components 276, which output the system output signals. The direction in which the system output signals travel away from the LIDAR system is labeled d2 in FIG. 6A. The electronic circuitry can operate the one or more beam steering components 276 to steer each system output signal to a different sample region of the field of view. As evident from the arrows labeled A and B in FIG. 6A, the one or more beam steering components 276 can be configured so that the electronic circuitry can steer the system output signals in two or three dimensions. As a result, the one or more beam steering components 276 can function as a beam steering mechanism actuated by electronic circuitry 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, a movable mirror, a MEMS mirror, an optical phased array (OPA), an optical grating, and a movable optical grating. In some cases, the redirecting component 274 and / or the one or more beam steering components 276 are configured to steer the system output signal to be parallel or nearly parallel as it moves away from the LIDAR system. Additionally or alternatively, the LIDAR system can include one or more collimating optical components (not shown) that steer the system output signal to be parallel or nearly parallel as it moves away from the LIDAR system.

[0117] As described above, the sampling rate for the ADC of the speed core can be lower than the sampling rate for the ADC of the range and speed core. In some cases, the LIDAR assembly includes a speed core with an ADC sampling rate greater than 100, 200, or 300 MSPS (megasamples per second) and less than 500, 800, or 1000 MSPS, and / or a range and speed core with an ADC sampling rate greater than 1, 2, or 3 GSPS (gigasamples per second) and less than 5, 8, or 10 GSPS. The ratio of the sampling rate for the ADC of one or more speed cores to the sampling rate for the ADC of one or more range and speed 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 speed core can be a core with a smaller bandwidth than the range and speed core. By way of example, a speed-core photodetector can be used in conjunction with a transimpedance amplifier (TIA) that converts a current to a voltage for the resulting data signal output from the photodetector. For example, FIG. 5B shows transimpedance amplifiers 282 selectively positioned along the first data line 282 and the second data line 232 to convert a current to a voltage for the first data signal and a current to a voltage for the second data signal. One or more speed-core transimpedance amplifiers (TIAs) and associated circuitry can be configured to operate at one or more throw distances and with a smaller bandwidth than the speed-core transimpedance amplifiers (TIAs) and associated circuitry. In some cases, the LIDAR assembly has one or more velocity cores operating in a bandwidth region greater than 0.1 Gz, 0.2 Gz, or 0.3 Gz and less than 0.5 Gz, 1 Gz, or 2 Gz, and one or more range and velocity cores operating in a bandwidth region greater than 0.5 Gz, 1 Gz, or 1.5 Gz and less than 2 Gz, 3 Gz, or 5 Gz.In some cases, the ratio of the bandwidth for one or more range and velocity cores to the bandwidth for one or more velocity cores is greater than 2:1, 4:1, or 8:1 and less than 10:1, 15:1, or 20:1. Reducing the bandwidth requirements for the velocity cores relative to the range and velocity cores allows the velocity cores to operate at lower frequencies and reduces costs associated with the velocity core components. In some cases, the LIDAR assembly has one or more range and velocity cores with TIAs operating in a bandwidth range greater than 0.1 Gz, 0.2 Gz, or 0.3 Gz and less than 0.5 Gz, 1 Gz, or 2 Gz, and one or more range and velocity cores with TIAs operating in a bandwidth range greater than 0.5 Gz, 1 Gz, or 1.5 Gz and less than 2 Gz, 3 Gz, or 5 Gz. In some cases, the ratio of the bandwidth for the TIA of one or more irradiation distance and velocity cores to the bandwidth for the TIA of one or more velocity cores is greater than 2:1, 4:1, or 8:1 and less than 10:1, 15:1, or 20:1.

[0118] FIG. 6B illustrates the relationship between the data period disclosed in FIG. 5C and the field of view for the LIDAR system. For illustrative purposes, only the system output signals for the projection distance and velocity core C1 are shown. The field of view is defined by a set of sample areas labeled SRk-1 to SRk+1. The illustrated system output signals are scanned in the direction of the solid line labeled "Scan." The system output signals are scanned through a series of sample areas (SRk-1 to SRk+1). The set of sample areas scanned by the system output signals forms the field of view for the LIDAR system. Objects in the field of view can change over time. As a result, the location of the sample areas is determined relative to the LIDAR system, rather than relative to the environment in which the LIDAR system is located. In some cases, the sample areas can be defined to be positioned within a certain range of angles relative to the LIDAR system. The dotted line labeled "Scan" in FIG. 6B indicates that the scanning of the sample areas can be repeated for multiple scan periods. Thus, each scan cycle can scan the system output signal through the same sample area as the object in the field of view moves or changes. The sample area of ​​the field of view can be scanned in the same sequence during different scan cycles, or in different sequences for different scan cycles.

[0119] The portion of each sample region corresponding to one data period is labeled DP1 or DP2 in Figure 6B. As can be seen from Figure 5C, the chirp rate of the system output signal from core C1 during data period DP1 is α1, and the chirp rate of the system output signal from core C1 during data period DP2 is α2. As mentioned above, the system output signals from rate cores C2-C4 do not have to be chirped, but may have a constant frequency.

[0120] Each sample area has a dotted line labeled Lk. The dotted line labeled Lk can function as a position reference line for sample area k. FIG. 6B has position reference lines labeled Lk-1 through Lk+1. In FIG. 6B, each position reference line (Lk) is drawn along the longitudinal axis of the sample area having sample area index k.

[0121] FIG. 6B shows multiple orientation angles labeled θk, where k represents sample region index k. The orientation angle θk can measure the angular orientation of the sample region SRk relative to the LIDAR system. In some cases, as shown in FIG. 6B, the orientation angle θk can be measured with respect to a position reference line Lk. As a result, the orientation angle θk can measure the angular orientation of the position reference line Lk. Because FIG. 6B shows a LIDAR system with a two-dimensional field of view, one angle (θk) can define the angular orientation of the sample region SRk relative to the LIDAR system; however, the field of view is typically three-dimensional. As a result, the LIDAR system can use more than one angle and / or other variables to define the orientation of the sample region relative to the LIDAR system.

[0122] FIG. 6C shows an object in the field of view disclosed in the context of FIG. 6B. For example, a positioned object is positioned in the field of view of a LIDAR system. Each position reference line (Lk) extends a distance Rk from the LIDAR system to a field location labeled flk. The distance Rk represents a value that the illumination range and velocity core electronics determines for the distance between the LIDAR system and the object as a result of the system output signal transmitted while illuminating the sample area SRk. As a result, the field location labeled flk represents a location along the position reference line (Lk) where the electronics determines that the surface of the object reflecting the system output signal is located. The collection of field locations in the field of view functions as a point cloud.

[0123] The field position (flk) associated with the distance Rk can also be associated with a radial velocity Vk, where k represents the sample region index, which can be the radial velocity generated by the electronic circuitry for the sample region having the sample region index k.

[0124] The one or more direction angles (θ) and distances R associated with each field position (flk) can effectively function as polar or spherical coordinates. As a result, the electronic circuitry can convert the coordinates of the field positions (flk) into a coordinate system having, but not limited to, Cartesian coordinates. By way of example, FIG. 6D shows an example of multiple different field positions in the sample area of ​​the irradiation distance and velocity core C1. Furthermore, the axes of the Cartesian coordinate system are transposed in the field of view. As a result, the position of the field positions (flk) is also shown with respect to the Cartesian coordinate system. The electronic circuitry can selectively use the direction angles (θ) and distances R associated with each field position (flk) to convert the field positions (flk) to other coordinate systems.

[0125] In some cases, a field location (flk) does not appear in all or part of a sample region. For example, if an object does not appear in a sample region (SRk), a beat frequency will generally not be generated and LIDAR data will not be generated for the sample region. As a result, some of the sample region indices may not be associated with a field location (flk).

[0126] If the core is a throw distance and velocity core, all or a portion of the sample area illuminated by the core (throw distance and velocity sample area, RV sample area) can be associated with a field position, coordinate, distance Rk, and radial velocity Vk, respectively. In contrast, if the core is a velocity core, all or a portion of the sample area illuminated by the core (velocity sample area, V sample area) can be associated with a field position, coordinate, and radial velocity Vk, respectively. Figure 6B shows the coordinates as two-dimensional Cartesian coordinates (x, y), although three-dimensional coordinates and / or other coordinate systems are also possible. In some cases, the coordinates are polar or spherical coordinates of the field position (flk).

[0127] FIG. 7 is a two-dimensional diagram of a field of view for a LIDAR system. For example, FIG. 7 can represent a projection of a three-dimensional field of view onto a two-dimensional plane. The field of view has multiple rectangles, each of which can represent the projection of one sample area in the field of view onto the plane. The sample areas are represented as rectangles for illustrative purposes and can have other geometric shapes. The sample areas are each labeled SRk, where k is 1 to 30.

[0128] Each sample area is labeled Ci, where i is a core index that identifies the core that illuminated the sample area. The core index is a natural number ranging from i=1 to i=M, where M is the number of system output signals output by the LIDAR system. The label Ci indicates which system output signal illuminated the sample area. For example, the sample area labeled C1 was illuminated by the illumination distance and velocity labeled C1 in FIG. 6A. Therefore, the sample area labeled C1 is an RV sample area. In contrast, the sample area labeled C2 was illuminated by the velocity core labeled C2, the sample area labeled C3 was illuminated by the velocity core labeled C3, and the sample area labeled C4 was illuminated by the velocity core labeled C4. Consequently, the sample areas labeled C2-C4 are V sample areas.

[0129] FIG. 7 has an arrow labeled A. The arrow indicates the sequence in which the system output signal is scanned through the field of view. In addition, a sample region index (k) is assigned to the sample regions in time order. Thus, the sample regions labeled C2 and SR11 are scanned by rate core C1 before the sample regions labeled C2 and SR12 are scanned by rate core C2.

[0130] The LIDAR system includes electronics configured to operate the LIDAR system. The electronics can include local electronics 32 from one or more cores and common electronics 280. The common electronics 280 can be located on the common support 140 as shown in FIG. 6A or can be located remotely from the common support 140. The common electronics 280 can be in the same physical location and / or housing as the local electronics associated with the different cores, or can be in a different location and / or housing than the local electronics 32 associated with the different cores.

[0131] The common electronics unit 280 can be in electrical communication with local electronics units 32 associated with different cores. For example, the common electronics unit 280 can have a LIDAR data generator 291 in electrical communication with local electronics units 32 from different cores. Figure 8 shows the common electronics unit 280 having a LIDAR data generator 291 configured to receive auxiliary LIDAR data generated by the auxiliary LIDAR data generator 269 of a different core.

[0132] Electrical communication between the common electronics 280 and the local electronics 32 associated with different cores allows the common electronics 280 to access auxiliary LIDAR data generated from the different cores. For example, the common electronics 280 can access the throw distance and / or velocity calculated for a sample area by the local electronics 32 associated with the throw distance and velocity core, and / or the velocity calculated for a sample area by the local electronics 32 associated with the velocity core. The LIDAR data generator 291 can combine the auxiliary LIDAR data generated by the different cores to calculate LIDAR data for a single sample area. Additionally or alternatively, the LIDAR data generator 291 can combine LIDAR data generated for different sample areas by the same core to calculate LIDAR data for a single sample area.

[0133] The auxiliary LIDAR data generated by the electronic circuitry for a sample area can include separated LIDAR data and shared LIDAR data. The separated LIDAR data can be LIDAR data calculated by the local electronic circuitry for a sample area, where one or more beat frequencies used to calculate the separated LIDAR data result from illumination of that sample area by the system output signal. As a result, illumination of other sample areas by the system output signal is not required to calculate the separated LIDAR data for the sample area. As a result, the radial velocity Vk for the V sample area of ​​sample area index k can be calculated without illuminating another sample area with the system output signal. However, the LIDAR data generator 291 can combine separated LIDAR data and / or shared LIDAR data resulting from illumination of different cores and / or different sample areas to approximate the shared LIDAR data. As a result, shared LIDAR data for a sample area can be calculated by combining beat frequencies resulting from illumination of different sample areas. As an example, the throw distance (Rk) for a V sample area can be calculated by combining beat frequencies from multiple different sample areas. Thus, the throw distance (Rk) calculated for a V sample area can be shared LIDAR data, while the radial velocity (Vk) for the same V sample area can be separate LIDAR data. In contrast, both the throw distance (Rk) and the radial velocity (Vk) for a V sample area can be separate LIDAR data.

[0134] An example of calculating shared LIDAR data is calculating the throw distance (Rk) for a target V sample region by interpolating or extrapolating the coordinates of the field position for the V sample region from the coordinates of the field position associated with the RV sample region. If the coordinates are polar or spherical, the throw distance (distance) (Rk) for the target V sample region k can be extracted directly from the coordinates. Alternatively, the throw distance (distance) (Rk) for the V sample region k can be calculated from the coordinates. For example, if the coordinates are Cartesian, the coordinates can be converted to polar or spherical coordinates, and the desired throw distance can be extracted. In some applications of LIDAR systems, the desired data for the V sample region is the coordinates of the field position for the sample region, rather than the throw distance. As a result, in some applications, the throw distance is not calculated for all or part of the V sample region for which coordinates are calculated. The throw distance and / or coordinates estimated for the V sample region can serve as position data for the V sample region. Thus, interpolation and extrapolation provide estimates of object position data for the target sample region. Interpolation or extrapolation is performed with respect to coordinates and / or throw distances from multiple RV sample regions. The field locations of the RV sample regions from which position data for the V region is calculated serve as known points in the interpolation or extrapolation algorithm.

[0135] The LIDAR data generator 291 can identify sample regions of interest whose coordinates and / or throw distances are to be interpolated or extrapolated, and can identify potential sample regions having potential data points whose coordinates and / or throw distances are to be interpolated or extrapolated. As an example, FIG. 9 shows the field of view from FIG. 7, with the sample region labeled SR6 for core C4 identified as the sample region of interest. The potential data points have field locations of RV sample regions physically located near the sample region of interest. Because the core labeled C1 is the only throw distance and velocity core for the LIDAR system of FIG. 6A, each potential data point is labeled C1.

[0136] The LIDAR data generator 291 can apply an identification algorithm to identify potential data points. The identification algorithm can associate a particular group of RV sample areas with each of different possible target sample areas. The association can be specific to each possible target sample area, or general to multiple different possible target sample areas. As an example of a specific association, the identification algorithm can associate the group of potential data points shown in FIG. 9 with the specific target sample area shown in FIG. 9. As an example of a general association, the identification algorithm can associate the pattern of potential data points shown in FIG. 9 with multiple different target sample areas, each located in the same row of sample areas as the target sample area of ​​FIG. 9.

[0137] In another example of a suitable identification algorithm, potential data points can be identified by applying an identification criterion to the target sample region and adjacent RV sample regions. For example, each RV sample region in the target sample region with a field position Rfl can be identified as a potential data point with Rfl being a constant.

[0138] The LIDAR data generator 291 can compare the LIDAR data of the potential data points to one or more criteria to determine which potential data points are suitable for use as known data points. In some cases, the one or more criteria can 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 can compare the LIDAR data associated with the sample region of interest and the data associated with each of the potential data points to one or more velocity criteria to determine which potential data points are suitable for use as known data points.

[0139] The velocity criterion can be selected such that the criterion is met if it is likely that the same object is located in the target sample region and the sample region associated with the potential data point. If an object is located in the target sample region and the sample region associated with the potential data point, the radial velocity calculated for these sample regions may be the same or similar. For example, applying the velocity criterion can include comparing a variable that is a function of the radial velocity calculated for the target sample region and the velocity associated with the potential data point to a threshold. The threshold can be a constant or a function of the radial velocity calculated for the target sample region and / or the radial velocity calculated for the potential data point. For example, the difference between the radial velocity associated with the target sample region and the radial velocity associated with the potential data point can be compared to a velocity threshold. If the difference is less than the velocity threshold, the velocity criterion is met, but if the difference is greater than or equal to the velocity threshold, the velocity criterion is not met. Another example of applying the velocity criterion is comparing the percentage change from the radial velocity associated with the target sample region to the radial velocity associated with the potential data point to a velocity threshold. If the difference is less than the speed threshold, the speed criterion is met, but if the difference is greater than or equal to the speed threshold, the speed criterion is not met.

[0140] Potential data points that meet one or more criteria are flagged as known data points, while potential data points that do not meet one or more criteria are not flagged as known data points. For example, the field locations of RV sample regions labeled with F in FIG. 9 can be flagged as known data points, while field locations of RV sample regions not labeled with F are not flagged as known data points. The LIDAR data generator 291 uses coordinates associated with known data points in an interpolation or extrapolation algorithm to estimate coordinates of the field locations of the target sample region. In contrast, potential data points that are not flagged as known data points are not used in the interpolation or extrapolation algorithm. As a result, in some cases, the number of known data points used in the interpolation or extrapolation algorithm varies depending on the radial velocity calculated for the potential data points.

[0141] Suitable interpolation algorithms include, but are not limited to, piecewise constant interpolation, linear interpolation, polynomial interpolation, spline interpolation, interpolation by function approximation, and Gaussian interpolation. Suitable extrapolation algorithms include, but are not limited to, linear extrapolation, polynomial extrapolation, conic extrapolation, and French curve extrapolation.

[0142] FIG. 10 is a process flow for generating throw distance data for a sample area illuminated by a velocity core of a LIDAR system having throw distance and velocity cores.

[0143] In processing block 300, local electronics for each core generate separate LIDAR data for the sample areas scanned by that core. For example, the auxiliary LIDAR data generator 269 for the velocity core calculates a radial velocity for each V sample area scanned by the core. Additionally, the auxiliary LIDAR data generator 269 for the throw range and velocity core calculates a throw range and a radial velocity for each RV sample area scanned by the RV core. As described above, one or more azimuth angles (θ) associated with a sample area and the throw range or distance R calculated for the sample area effectively function as polar or spherical coordinates of the field location of that sample area. Alternatively, the local electronics can selectively convert the polar or spherical coordinates to other coordinates. Thus, the auxiliary LIDAR data generator 269 associated with each throw range and velocity core can calculate the radial velocity and coordinates of the field location associated with the RV sample area scanned by that core.

[0144] In processing block 302, the LIDAR data generator 281 can identify one of the V sample regions to serve as a target sample region for which coordinates and / or throw distances are to be estimated. The field location of the target sample region can serve as the target field location.

[0145] From process block 302, the LIDAR data generator 281 may proceed to process block 304. In process block 304, the LIDAR data generator 281 may execute an identification algorithm to identify RV sample areas having field locations that may be suitable to serve as known data points. The identified RV sample areas and / or field locations serve as potential data points.

[0146] From process block 304, the LIDAR data generator 281 may proceed to process block 306. In process block 306, the LIDAR data generator 281 may initialize the identified potential data points and / or RV sample regions having the identified potential data points. For example, the LIDAR data generator 281 may flag each of the identified potential data points and / or sample regions having the identified potential data points as not being known data points.

[0147] From process block 306, the LIDAR data generator 281 can proceed to process block 308. In process block 308, the LIDAR data generator 281 compares the radial velocity associated with the target field location (or, more or less, V sample area) and the radial velocity associated with one potential data point of interest (or potential RV sample area) to one or more velocity criteria to determine whether the same object is likely located in the sample area associated with the target field location and in the sample area associated with the potential field location. This comparison can be repeated until each potential data point serves as a potential data point of interest, until a predetermined number of potential data points serve as potential data points of interest, or until a predetermined number of potential data points meet one or more velocity criteria. The LIDAR data generator 281 can flag each data point that potentially meets one or more velocity criteria as a known data point.

[0148] From process block 308, the LIDAR data generator 281 may proceed to process block 310. In process block 310, the LIDAR data generator 281 may interpolate or extrapolate coordinates of the target field location from the coordinates of the known data points. Potential data points that are not flagged as known data points are not used in the interpolation or extrapolation.

[0149] In some cases, the coordinate interpolation or extrapolation includes interpolating or extrapolating a throw distance associated with the object field position. For example, if the coordinate interpolation or extrapolation is performed in polar or spherical coordinates, the throw distance is one of the coordinate variables. Alternatively, the throw distance can be calculated from the coordinates of the object field position. When the throw distance is determined for the object field position flk, the throw distance can function as a distance Rk for the V sample region SRk. As a result, the V sample region SRk can be associated with a line of sight velocity Vk. This allows the V sample region serving as the object sample region to be associated with the field position, the estimated range Rk, and the line of sight velocity Vk.

[0150] From processing block 310, the LIDAR data generator 281 proceeds to decision block 312 where a determination is made as to whether the desired number of V sample areas have served as sample areas of interest. It may be desirable for all or a portion of the sample areas in the field of view of the LIDAR system to serve as sample areas of interest. In some cases, each of the V sample areas in the field of view of the LIDAR system will serve as a sample area of ​​interest. As a result, in some cases, the common electronics may determine whether each of the V sample areas in the field of view of the LIDAR system have served as a sample area of ​​interest. If the determination is negative, the common electronics may return to processing block 302.

[0151] If the determination at decision block 310 is affirmative, the LIDAR data generator 281 obtains estimated range (Rk) values ​​for all or a portion of the V sample regions. The estimated range (Rk) values ​​are estimated from the beat frequency of a composite signal resulting from illuminating multiple different sample regions with the system output signal. As a result, the estimated range (Rk) values ​​can be considered shared LIDAR data. The estimated range (Rk) values ​​for the V sample regions can be added to the separate LIDAR data for the RV regions and the separate LIDAR data for the V region to provide LIDAR data for the LIDAR system's field of view. As a result, all or a portion of the V sample regions of the LIDAR system's field of view are associated with a field position, an estimated range Rk, and a radial velocity Vk. Similarly, all or a portion of the RV sample regions of the LIDAR system's field of view are associated with a field position, an estimated range Rk, and a radial velocity Vk.

[0152] If the determination at decision block 310 is affirmative, the common electronics 280 proceeds from decision block 312 to processing block 314. In processing block 314, the common electronics can further process the LIDAR data related to the field of view of the LIDAR system. The further processing is a function of the application of the LIDAR system. Examples of further processing applications include, but are not limited to, image generation, autonomous vehicle control, point cloud generation, object recognition, and statistical analysis. The further processing can use all or a portion of the throw distance, line of sight velocity, and field position associated with the V sample region and associated with the RV sample region in the field of view of the LIDAR system.

[0153] The above-described LIDAR core structures are exemplary, and other LIDAR core structures can be used. For example, FIGS. 11A through 11C show examples of LIDAR cores suitable for use as velocity cores. FIG. 11A shows a plan view of the LIDAR core of FIG. 1A modified to include a frequency shifter 298 disposed along the utility waveguide 12. Electronic circuitry can activate the frequency shifter 298 to create a frequency offset between the LIDAR output signal and the reference signal. Because the system output signal includes or consists of light from the LIDAR output signal, a frequency offset also exists 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 can be integrated into the LIDAR chip or LIDAR core, or it can be a separate electro-optical component attached to the LIDAR chip or LIDAR core using techniques such as flip-chip mounting.

[0154] The LIDAR core of FIG. 11A can provide a clear solution for the beat frequency without the second data signal and therefore without the imaginary component of the composite signal. As a result, the signal processor used in combination with the LIDAR core of FIG. 11A does not need to generate the second composite signal. Therefore, the signal processor used in combination with the LIDAR core of FIG. 11A can be used with the signal processor of FIG. 5A, modified to exclude the components necessary to generate and process the second composite signal, as shown in FIG. 11B. Similarly, the relationship between the electronic circuitry, the first optical sensor 223, and the second optical sensor 224 can be established as disclosed in the content of FIG. 5B, but excluding the first auxiliary optical sensor 218 and the second auxiliary optical sensor 220, as shown in FIG. 11C. As can be seen from FIG. 1C, the converter 268 receives the first data signal but not the second data signal. As a result, the first data signal functions as the real data signal received by the converter 268. A LIDAR core having a converter 268 that receives a real data signal can be considered a real data signal LIDAR core.

[0155] The beat frequency detector 238 includes a converter 268 that receives as an input a first digital data signal from a first analog-to-digital converter (ADC) 264. The converter 268 can be configured to perform a mathematical transform on the first digital data signal to convert it from the time domain to the frequency domain. The mathematical transform can be a real transform, such as a Fourier transform. The local electronics uses one or more frequency peaks output from the converter 268 for further processing to generate LIDAR data (distance between a reflecting object and the LIDAR tip or LIDAR core, and / or radial velocity). The local electronics 32 can include a peak detector (not shown) that identifies the beat frequency of the one or more frequency peaks. The converter 268 and / or the auxiliary LIDAR data generator 269 can perform the attribution function using firmware, hardware, software, or a combination thereof.

[0156] The local electronics 32 can include an auxiliary LIDAR data generator 269 configured to receive the beat frequency from the converter 268. The auxiliary LIDAR data generator 269 is configured to generate auxiliary LIDAR data for the sample area. The LIDAR data for the sample area includes values ​​for line-of-sight velocity and / or separation distance between the LIDAR system and objects 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 auxiliary LIDAR data generator 269 calculates LIDAR data to serve as auxiliary LIDAR data. For example, in some cases, the auxiliary LIDAR data generator 269 calculates line-of-sight velocity and / or separation distance between the LIDAR system and objects in the sample area as auxiliary LIDAR data. As described below, other examples of auxiliary LIDAR data the auxiliary data generator can calculate include, but are not limited to, potential solutions for the LIDAR data for the sample area and indicators of potential line-of-sight velocity magnitudes for the sample area.

[0157] Different cores having local electronics 32 configured as disclosed in the context of Figure 11C can be in electrical communication with common electronics 280 as disclosed in the context of Figure 8. Alternatively, one or more cores having local electronics 32 configured as disclosed in the context of Figure 11C and one or more cores having local electronics configured as disclosed in the context of Figure 5B can be in electrical communication with common electronics 280 as disclosed in the context of Figure 8.

[0158] The system output signal from the LIDAR core of FIG. 11A can be continuous wave (CW). For example, the outgoing LIDAR signal, and therefore the system output signal, can be chirp-free continuous wave (CW). As an example, the outgoing LIDAR signal, and therefore the system output signal, can be expressed by 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 electronics, such as the auxiliary LIDAR data generator 269, can approximate the line-of-sight velocity (v) between the reflecting object and the LIDAR chip using Equation 5: v=c*fft / (2*(fc±fos)), where fft represents the peak frequency output from the transform 268, c is the speed of light, fc represents the frequency of the LIDAR output signal, and therefore the system output signal, and fos represents the offset between the frequency of the system output signal and a reference signal. In many cases, fc>>fos, and the equation for radial velocity can be approximated as v=c*fft / (2*fc). As a result, multiple data periods and / or chirping are not required to generate the radial velocity.

[0159] When used in combination with the signal processing section of FIG. 11B and the local electronics of FIG. 11C to provide a real data signal core, the LIDAR core shown in any of FIGS. 1A through 1C can operate as a range and velocity core. For example, the frequency versus time pattern of FIG. 5C can represent a frequency versus time pattern suitable for use with a real data signal core constructed according to FIG. 1A operated as a range and velocity core. In this example, the frequency peaks output from the Fourier transform represent beat frequencies of a composite signal having a comparison signal that each beats relative to a reference signal. However, the real Fourier transform outputs positive and negative beat frequencies of the same magnitude. It can be ambiguous which beat frequency represents the correct value for the composite signal's beat frequency. As a result, there are multiple possible solutions for LIDAR data regarding the RV sample area illuminated by the system output signal from a LIDAR core constructed according to FIGS. 1A through 11C and operated as a range and velocity core.

[0160] Beat frequencies from two or more different data periods associated with the same sample area can be combined to generate potential LIDAR data solutions for the RV sample area illuminated by system output signals from a LIDAR core constructed according to any of Figures 1A-1C and operated as an illumination range and velocity core. For example, beat frequencies determined from DP1 while illuminating sample area SRk can be combined with beat frequencies determined from DP2 while illuminating sample area SRk to determine potential LIDAR data solutions for the RV sample area.

[0161] As mentioned above, the beat frequency of the composite signal during the data period when the frequency of the outgoing LIDAR signal increases can be represented by fub, and the beat frequency of the composite signal during the data period when the frequency of the outgoing LIDAR signal decreases can be represented by fdb. The contribution of the throw distance between the LIDAR system and the object to the beat frequency can be represented by fr, where fr = 2 * αu * Rk / c, where αu represents the chirp rate (αm) (in this case, α1) of the data period when the frequency of the system output signal increases with time, Rk represents the distance between the LIDAR system and the object at sample region SRk, and c represents the speed of light. The Doppler effect contribution to these beat frequencies can be represented by fd = 2Vkfc / c, where fc represents the fundamental frequency (f0), and Vk is the radial velocity between the reflecting object at sample region k and the LIDAR system, with the radial velocity assumed to be positive if the object is moving toward the LIDAR system.

[0162] There are three possible LIDAR data solutions for combinations of fr and fd values ​​relative to the RV sample domain. For example, fr = (fub + fdb) / 2 and fd = (fdb - fub) / 2 can serve as a first solution. A second solution can be fr = (fdb - fub) / 2 and fd = (fdb + fub) / 2. A third solution can be fr = (fub - fdb) / 2 and fd = - (fdb + fub) / 2. As previously mentioned, the real Fourier transform outputs positive and negative beat frequencies of equal magnitude. As a result, in these LIDAR data solutions, fub represents the magnitude of the peak frequency output from the transform unit 268, and fdb represents the magnitude of the peak frequency output from the transform unit 268. As previously mentioned, the values ​​of fr and fr are directly related to the radial velocity (Vk) and throw distance (Rk) for the RV sample region by fd=2Vkfc / c and fr=2*αu*Rk / c, respectively. As a result, each potential LIDAR data solution for the RV sample region SRk can have all or some of the components selected from the group consisting of a value of fr, a value of fd, a value of the radial velocity (Vk), and a value of the throw distance (Rk). In some cases, each potential LIDAR data solution has at least a possible value of fr and a possible value of fd. In some cases, each potential LIDAR data solution has at least a possible value of the radial velocity (Vk) and a possible throw distance (Rk) for the RV sample region SRk.

[0163] FIG. 12A illustrates an example process flow that the common electronics can use to identify a correct LIDAR data solution for a target RV sample region. In process block 320, multiple potential LIDAR data solutions are calculated. For example, the auxiliary LIDAR data generator 269 can calculate potential f values ​​and / or potential throw distance (Rk) values ​​for a first solution, a second solution, and a third solution. In process block 321, the auxiliary LIDAR data generator 269 can identify candidate LIDAR data solutions from among the potential LIDAR data solutions. For example, the electronics can identify candidate f values ​​from among the potential f values ​​and / or candidate Rk values ​​from among the potential Rk values. The Rk value is, by definition, positive. As a result, the f value is also positive. However, the f value from the second solution is the negative of the f value from the third solution. As a result, the potential f and / or Rk values ​​have one or more negative values. Possible negative fr and / or Rk values ​​can be excluded from the candidate pool. As a result, each possible positive fr value serves as a candidate fr value. Additionally, or alternatively, each possible positive Rk value serves as a candidate Rk value.

[0164] In processing block 322, the LIDAR data generator 281 identifies a correct solution. For example, if each of the potential LIDAR data solutions does not already have a radial velocity (Vk), then the radial velocity (Vk) can be calculated for each solution using the value of fd associated with the solution and fd=2Vkfc / c. The Vk results from the different solutions can be compared with the radial velocity results from one or more V sample regions to identify the correct Vk result. The LIDAR data solution with the identified Vk result can be selected as the correct LIDAR data solution. Thus, the Vk value of the selected LIDAR data solution can be selected as the correct Vk and Rk values.

[0165] In processing block 323, the LIDAR data generator 281 can determine LIDAR data for the RV sample region associated with sample region index k. For example, if the selected potential LIDAR data solution does not already have a throw distance (Rk), the throw distance (Rk) can be calculated for the selected LIDAR data solution using the value of f associated with the selected LIDAR data solution and f = 2 * αu * Rk / c. The Vk and Rk values ​​associated with the selected LIDAR data solution can serve as shared LIDAR data for the RV sample region SRk. Thus, the LIDAR data for the RV sample region associated with sample region index k will have or consist of the Vk and Rk values ​​selected in processing block 322.

[0166] A LIDAR system can have one or more range and velocity cores that are real data signal cores, and one or more velocity cores that are real data signal cores. By way of example, FIG. 12B shows a LIDAR system having multiple different real data signal cores on a common support 140. One or more of the LIDAR cores can be velocity cores constructed as disclosed in the context of FIGS. 11A-11C, and one or more of the LIDAR cores can be range and velocity cores constructed as disclosed in the context of FIGS. 1A-1C with the signal processing section of FIG. 11B in combination with the electronic circuitry of FIG. 11C. For illustrative purposes, the LIDAR core of the LIDAR system of FIG. 12B has two velocity cores 325 constructed as disclosed in the context of FIGS. 11A-11C, and also has a range and velocity core 324 constructed as disclosed in any of FIGS. 1A-1C with the signal processing section of FIG. 11B in combination with the electronic circuitry of FIG. 11C. Throw distance and velocity cores 324 are alternated with velocity cores 325 .

[0167] FIG. 12C is a two-dimensional view of the field of view for the LIDAR system of FIG. 12B. For example, FIG. 12C can represent the projection of a three-dimensional field of view onto a two-dimensional plane. The field of view has multiple rectangles, each of which can represent the projection of one sample area in the field of view onto the plane. The sample areas are shown as rectangles for illustrative purposes but can also have other shapes. The sample areas are labeled SRk, where k ranges from 1 to 30.

[0168] Each sample area is labeled Ci, where i is a core index that identifies the core that illuminates the sample area. The core index is a natural number that can extend from i=1 to i=M, where M is the number of system output signals output by the LIDAR system. The label Ci indicates which system output signal illuminates the sample area. For example, the sample area labeled C1 in FIG. 12B is illuminated by the illumination distance and velocity core labeled C1, and the sample area labeled C3 in FIG. 12B is illuminated by the illumination distance and velocity core labeled C3. Therefore, the sample areas labeled C1 and C3 are RV sample areas. In contrast, the sample area labeled C2 is illuminated by the velocity core labeled C2, and the sample area labeled C4 is illuminated by the velocity core labeled C4. Consequently, the sample areas labeled C2 and C4 are V sample areas.

[0169] FIG. 12C has an arrow labeled A. The arrow indicates the sequence in which the system output signal is scanned through the field of view. In addition, a sample region index (k) is assigned to the sample regions in chronological order. Thus, sample regions labeled C2 and SR11 were scanned by velocity core C1 before sample regions labeled C2 and SR12 were scanned by velocity core C2.

[0170] The local electronics 32 can be local electronics in that they are specific to each core of the LIDAR system. In addition to the local electronics 32, the LIDAR system can have a common electronics 280. The common electronics 280 can be located on the common support 140, as shown in FIG. 12C , or can be located remotely from the common support 140. The common electronics 280 can be in the same physical location and / or housing as the electronics associated with the different cores, or can be in a different location and / or housing than the local electronics 32 associated with the different cores.

[0171] The LIDAR data generator 281 can combine potential LIDAR data solutions with separated LIDAR data from one or more V sample regions to select a correct LIDAR data solution, as disclosed in the context of Figure 12A. In some cases, the RV sample region associated with a potential LIDAR data solution and one or more V sample regions can be illuminated by a system output signal with light from the same core or from different cores.

[0172] To identify a potentially correct LIDAR data solution, the potential LIDAR data solution for the target RV sample area can be compared to the radial velocity calculated for one or more V sample areas, each of which serves 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, electronic circuitry can identify the target RV sample area for which the correct LIDAR data solution will be identified. FIG. 12D shows the field of view from FIG. 12C in which the RV sample area labeled SR15 and illuminated by the system output signal having light from velocity core C4 has been identified as the target RV sample area.

[0173] One or more V sample areas can each be identified as a reference V sample area. The LIDAR data solution for the target RV sample area can be compared to the radial velocity (Vk) calculated for each of the one or more reference V sample areas to identify the correct LIDAR data solution for the target RV sample area from among the possible LIDAR data solutions for the target RV sample area. In some cases, the V sample area physically closest to the target RV sample area can be identified as the unique reference V sample area. As an example, in FIG. 12D , the V sample area labeled SR5 and illuminated by the system output signal with light from velocity core C1 is identified as the unique reference V sample area.

[0174] The LIDAR data generator 281 can use one or more solution identification criteria to identify a correct LIDAR data solution for the target RV sample region from among potential LIDAR data solutions for the target RV sample region. An example of a solution identification criteria includes an approximate velocity criterion that identifies a potential LIDAR data solution having a radial velocity closest to the radial velocity of one or more reference V sample regions as the correct LIDAR data solution. For example, the V sample region physically closest to the target RV sample region can be identified as the unique reference V sample region, and the potential LIDAR data solution having a radial velocity V closest to the radial velocity of the one or more reference V sample regions can be selected as the correct LIDAR data solution for the target RV sample region. Thus, the radial velocity V and range R associated with the LIDAR data solution can serve as the LIDAR data for the target RV sample region.

[0175] The LIDAR data generator 281 can apply other identification criteria in addition to or instead of the approximate velocity criterion. Another example of an identification criterion can be a range criterion that the radial velocity Vk for the identified reference V sample region falls within a range of radial velocity values. Examples of suitable ranges of radial velocity values ​​include, but are not limited to, the radial velocity of the target RV sample region + / - 10%, 20%, or . If the radial velocity (Vk) for one of the identified reference V sample regions falls outside the range of radial velocity values, the reference V sample region can be removed from the identified reference V sample regions. If none of the identified reference V sample regions has a radial velocity within the range of radial velocity values, the LIDAR data for the target RV sample region can be classified as unusable. In some cases, the LIDAR data generator 281 applies both a range criterion and an approximate velocity criterion to the target RV sample region.

[0176] Figure 12E shows a process flow for an exemplary process for generating LIDAR data representing a sample area illuminated by a LIDAR system having a real data signal core, such as the LIDAR system shown in Figure 12B. At process block 326, the field of view for the LIDAR system is scanned.

[0177] In processing block 327, separate LIDAR data for each V sample area can be calculated. As described above, separate LIDAR data for a sample area is LIDAR data that can be calculated without using a composite signal that results from illuminating different sample areas with the system output signal. For example, to generate the separate LIDAR data, the auxiliary LIDAR data generator 269 for each velocity core can calculate a radial velocity for each of the V sample areas illuminated by the velocity core.

[0178] In processing block 328, the auxiliary LIDAR data generator 269 for each throw distance and velocity core can calculate potential LIDAR data solutions for each RV sample area illuminated by one throw distance and velocity core. For example, the auxiliary LIDAR data generator 269 for each throw distance and velocity core can calculate potential LIDAR data solutions for the RV sample area illuminated by one throw distance and velocity core, as disclosed in the context of FIG. 12A.

[0179] In processing block 329, a correct LIDAR data solution can be selected for each RV sample region illuminated by each illumination distance and velocity core. For example, the LIDAR data generator 281 can select a correct LIDAR data solution for the RV sample region from among the possible LIDAR data solutions, as disclosed in the context of FIG. 12A. The radial velocity (Vk) and range (Rk) associated with the selected LIDAR data solution can be considered shared LIDAR data that serves as all or part of the LIDAR data for the target RV sample region SRk.

[0180] The LIDAR data for the RV sample areas can serve as the throw distance and radial velocity for each RV sample area scanned by the RV core in processing block 300 of FIG. 10. Thus, the auxiliary LIDAR data generator 269 or the LIDAR data generator 281 can calculate the radial velocity and coordinates of the field location associated with the RV sample area scanned by those cores, as disclosed in processing block 300. In addition, the separate LIDAR data for the V sample areas can serve as the radial velocity for each V sample area scanned by the V core in processing block 300. As a result, the remainder of the process shown in FIG. 10 can be performed to interpolate and / or extrapolate the throw distance (Rk) for each V sample area illuminated by the velocity core, as the case may be. For example, in processing block 310, the LIDAR data generator 281 can combine throw distance data (Rk) of LIDAR solutions selected from different RV sample areas to approximate the throw distance data (Rk) for each V sample area illuminated by one velocity core. For example, the LIDAR data generator 281 may interpolate and / or extrapolate throw distance data (Rk) for each V sample region from coordinates and / or throw distance data (Rk) from different RV sample regions, as described above. The LIDAR data for the sample regions of the field of view may comprise or consist of LIDAR data for the RV sample regions, separate LIDAR data for each V sample region (Vk), and approximate throw distance data (Rk) for each V sample region.

[0181] Although the fields of view shown in Figures 7 and 12B depict the sample areas as spaced apart from one another, the sample areas can partially or completely overlap. For example, all or a portion of the V sample area can partially or completely overlap with or be partially or completely overlapped by the RV sample area. As a result, all or a portion of the sample area can be simultaneously illuminated by a system output signal having light from the RV core and by a system output signal having light from the V core.

[0182] Although the LIDAR system of Figure 12B is disclosed as having real data signal cores with velocity cores constructed as disclosed in the content of Figures 11A-11C, some of the cores can be complex data signal cores. For example, the velocity cores can be constructed as disclosed in any of Figures 1A-5C. Throw distance and velocity cores 324 alternate with velocity cores 325.

[0183] The real data signal core disclosed in FIGS. 11A-11C and functioning as a V-core includes a frequency shifter. However, the frequency shifter can be eliminated. For example, the velocity core of FIG. 12B can be configured as disclosed in any of FIGS. 1A-1C using the signal processing section of FIG. 11B in combination with the electronic circuitry of FIG. 11C to provide a real data signal core that can operate as a V-core. For example, the system output signal can be continuous wave (CW). By way of example, the outgoing LIDAR signal, and therefore the system output signal, can be non-chirped continuous wave (CW). In some cases, the outgoing LIDAR signal, and therefore the system output signal, can be expressed by 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 the positive and negative beat frequencies that have the same magnitude. For example, a real Fourier transform can output frequency peaks at beat frequency values ​​fd and −fd, where fd represents the Doppler frequency shift and can be expressed as fd=2Vkfc / c, where fc represents the continuous wave frequency, c represents the speed of light, and Vk is the radial velocity between the LIDAR system and the reflecting object at sample area SRk, assuming the direction from the reflecting object toward the LIDAR system is the positive direction. Because it may be ambiguous which beat frequency represents the correct value for the beat frequency of the composite signal, there are two possible radial velocity solutions: one at Vk and one at −Vk. As a result, there are multiple possible solutions for the radial velocity for a V sample area illuminated by a system output signal from a real data signal core constructed as disclosed in any of FIGS. 1A-1C.

[0184] FIG. 13A illustrates an example process flow that the electronic circuitry can use to identify a correct radial velocity solution for the V sample region SRk when a LIDAR data solution is available from the RV sample region. In process block 340, the auxiliary LIDAR data generator 269 calculates a velocity magnitude indicator from the radial velocity indicator for the sample region SRk. The magnitude of the potential radial velocity indicator indicates the magnitude of the radial velocity between the LIDAR system and an object in the V sample region SRk. For example, the magnitude of the potential radial velocity indicator sets the magnitude of the radial velocity. As a result, the radial velocity indicator can be calculated as a value of the radial velocity (Vk) given by fd = 2Vkfc / c, where fd can represent either of the peak frequencies output from the Fourier transform. Either the beat frequency (fd) or the Doppler frequency shift (fd) can also function as a radial velocity indicator, since any Doppler frequency shift fd is directly related to the magnitude of the radial velocity by |fd| = |2Vkfc / c|. The auxiliary LIDAR data generator 269 can identify the magnitude of the radial velocity indicator as the velocity magnitude indicator.

[0185] In processing block 342, the LIDAR data generator 281 can identify the direction of the radial velocity indicator for the V sample region SRk. For example, the velocity magnitude indicator for the V sample region SRk can be compared to a comparative 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, if the velocity magnitude indicator for the V sample region SRk matches a potential radial velocity magnitude from an adjacent RV sample region, it is likely that system output signals illuminating different sample regions were incident on the same object. As a result, the direction of the potential radial velocity solution that matched with the velocity magnitude indicator is assigned to the velocity magnitude indicator to provide a radial velocity indicator. Thus, the directional radial velocity indicator has the magnitude of the velocity magnitude indicator and the direction of the comparative component from the matched LIDAR data solution. As an example, if the radial velocity indicator for the V sample region SRk provides a velocity magnitude indicator of 20 mph and a radial velocity (Vk) calculation matches the potential radial velocity solution of 20 mph, the negative value of the potential radial velocity solution is assigned to the velocity magnitude indicator to provide a directional radial velocity indicator value of −20 mph.

[0186] In processing block 344, the LIDAR data generator 281 can determine the radial velocity of the V sample region SRk. If the velocity magnitude indicator is the magnitude of the radial velocity calculation, the directional radial velocity indicator can function as the radial velocity for the sample region SRk. If the velocity magnitude indicator is a magnitude other than the radial velocity calculation, the radial velocity can be calculated from the directional radial velocity indicator. For example, if the velocity magnitude indicator is the magnitude of any beat frequency (fd), the radial velocity (Vk) can be calculated from Cfd=2Vkfc / c, where Cfd represents the directional radial velocity indicator.

[0187] One or more LIDAR cores in the LIDAR system of Figure 12B can be configured as disclosed in the subject matter of Figures 1A-1C using the signal processing section of Figure 11B in combination with the electronic circuitry of Figure 11C and can operate as range and velocity cores, while one or more LIDAR cores in a LIDAR system can be configured as disclosed in any of Figures 1A-1C using the signal processing section of Figure 11B in combination with the electronic circuitry of Figure 11C and can operate as V-cores. By way of example, Figure 13B shows a LIDAR system having multiple different real data signal cores on a common support 140. One or more of the LIDAR cores can be velocity cores constructed as disclosed in any of Figures 1A-1C using the signal processing section of Figure 11B in combination with the electronic circuitry of Figure 11C, and one or more of the LIDAR cores can be throw distance and velocity cores constructed as disclosed in the subject matter of Figures 1A-1C using the signal processing section of Figure 11B in combination with the electronic circuitry of Figure 11C. For illustrative purposes, the LIDAR cores of the LIDAR system of Figure 13B have two velocity cores 325 and two throw distance and velocity cores 324. The throw distance and velocity cores 324 alternate with the velocity cores 325.

[0188] FIG. 13C is a two-dimensional view of the field of view for the LIDAR system of FIG. 13B. For example, FIG. 13C can represent a projection of a three-dimensional field of view onto a two-dimensional plane. The field of view has multiple rectangles, each of which can represent the projection of one of the sample regions in the field of view onto the plane. The sample regions are shown as rectangles for illustration purposes and can have other shapes. The sample regions are each labeled SRk, where k ranges from 1 to 30.

[0189] Each sample area is labeled with a core index Ci, where i is a core index that identifies the core that illuminates the sample area. The core index is a natural number that can range from i=1 to i=M, where M is the number of system output signals output by the LIDAR system. The label Ci indicates which system output signal illuminates the sample area. For example, the sample area labeled C1 is illuminated by the illumination distance and velocity core labeled C1 in FIG. 13B, and the sample area labeled C3 is illuminated by the illumination distance and velocity core labeled C3 in FIG. 13B. Therefore, the sample areas labeled C1 and C3 are RV sample areas. In contrast, the sample area labeled C2 is illuminated by the velocity core labeled C2, and the sample area labeled C4 is illuminated by the velocity core labeled C4. As a result, the sample areas labeled C3 and C4 are V sample areas.

[0190] FIG. 13C has an arrow labeled A. The arrow indicates the sequence in which the system output signal is scanned through the field of view. In addition, a sample region index (k) is assigned to the sample regions in chronological order. Thus, the sample regions labeled C2 and SR11 were scanned by velocity core C1 before the sample regions labeled C2 and SR12 were scanned by velocity core C2.

[0191] The local electronics 32 can be local electronics in that they are unique to each core on the LIDAR system. In addition to the local electronics 32, the LIDAR system can have common electronics 280. The common electronics 280 can be located on the common support 140, as shown in FIG. 13C, or can be located remotely from the common support 140. The common electronics 280 can be in the same physical location and / or housing as the local electronics associated with different cores, or can be in a different location and / or housing than the local electronics 32 associated with different cores.

[0192] The common electronics can be in electrical communication with the local electronics 32 associated with the different cores, as disclosed in the context of Figure 8. As a result, the common electronics 280 can access LIDAR data generated by the different cores. For example, the common electronics 280 can access auxiliary LIDAR data calculated by the local electronics 32 for the sample area.

[0193] The electronic circuitry can combine potential LIDAR data solutions with radial velocity indicators and / or velocity magnitude indicators from one or more V sample regions to identify the correct LIDAR data for the RV and V sample regions of the field of view.

[0194] To identify the likely correct LIDAR data solution for the RV sample area and the correct direction for the radial velocity indicator, the electronic circuitry can compare the likely LIDAR data solution for the target RV sample area and the radial velocity magnitude indicator for one or more V sample areas, each of which serves as a reference V sample area.

[0195] All or part of the reference V sample area and the target RV sample area can be illuminated by the same core or different cores. For example, an electronic circuitry such as the LIDAR data generator 281 can identify the target RV sample area for which one of the correct LIDAR data solutions will be identified. Figure 13D shows the field of view of Figure 13C in which the RV sample area labeled SR15 and illuminated by the system output signal with light from velocity core C4 has been identified as the target RV sample area.

[0196] The LIDAR data generator 281 can identify one or more V sample regions as reference V sample regions. The LIDAR data generator 281 can compare potential LIDAR data solutions for the target RV sample region with the 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 the potential LIDAR data solutions for the target RV sample region. In some cases, the V sample region physically closest to the target RV sample region is identified as the unique reference V sample region. As an example, in FIG. 13D , the V sample region labeled SR5 and illuminated by the system output signal with light from velocity core C1 is identified as the unique reference V sample region.

[0197] The LIDAR data generator 281 can use one or more solution discrimination criteria to identify a correct LIDAR data solution for the target RV sample region and / or a correct direction for the direction of the radial velocity indicator for the reference V sample region from among the potential LIDAR data solutions for the target RV sample region. An example of a discrimination criterion includes an approximate magnitude velocity criterion that provides a match between the velocity magnitude indicator for the reference V sample region SRk and a comparison component of the LIDAR data solution for the target RV sample region. For example, the potential LIDAR data solutions for the reference V sample region have a component that is equivalent to the radial velocity indicator and serves as a comparison component that can be compared to the velocity magnitude indicator. For example, if the velocity magnitude indicator is the magnitude of the radial velocity calculation, each potential LIDAR data solution for the reference V sample has a value of radial velocity (Vk) that serves as a comparison component. As another example, if the velocity magnitude indicator is the magnitude of the Doppler frequency shift, each potential LIDAR data solution for the reference V sample has a value of fd that can serve as a comparison component. The LIDAR data solution having a comparative component with a magnitude closest to the velocity magnitude indicator for the target RV sample region and for the reference V sample region can be selected as the correct LIDAR data solution for the target RV sample region. Thus, the radial velocity Vk and range Rk associated with the selected LIDAR data solution can serve as the LIDAR data for the target RV sample region. Additionally, the direction of the comparative component of the selected LIDAR data solution can serve as the direction of the radial velocity indicator for the reference V sample region associated with the radial velocity indicator. As a result, the direction of the comparative component of the selected LIDAR data solution is assigned to the radial velocity 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 (positive or negative) of the comparative component of the selected LIDAR data solution.For example, if the radial velocity indicator is a radial velocity (Vk) calculation that provides a velocity magnitude indicator of 20 mph, and the comparison component of the selected LIDAR data solution has a value of -20 mph, then the negative value of the comparison component is assigned to the velocity magnitude indicator to provide a directional radial velocity indicator value of -20 mph.

[0198] The LIDAR data generator 281 can apply other solution discrimination criteria in addition to or instead of the approximate velocity magnitude criterion. Another example of a discrimination criterion can be a range criterion in which the comparison component of each LIDAR data solution for the target sample region has a value within a range of the comparison component's values. In some cases, the magnitude range of the comparison component's values ​​includes, but is not limited to, the value of the velocity magnitude indicator of the reference V sample region plus or minus 10%, 20%, or 30% of the velocity magnitude indicator of the reference V sample region. In some cases, the magnitude range of the comparison component's values ​​includes, but is not limited to, the value of the velocity magnitude indicator of the reference V sample region plus or minus a constant value. If the magnitude of the comparison component's value for the target RV sample region falls outside the range, the LIDAR data solution having the comparison component's value can be removed from the list of possible LIDAR data solutions. If none of the LIDAR data solutions for the target RV sample region are within the range, the target RV sample region LIDAR data can be classified as unusable. In some cases, the LIDAR data generator 281 applies both a range criterion and an approximate velocity magnitude criterion to the target RV sample region.

[0199] 13E shows an example of a process flow that the LIDAR data generator 281 may use to identify the correct LIDAR data solution for the RV sample region of interest and to determine the correct radial velocity for the reference V sample region. In process block 346, the LIDAR data generator 281 identifies the RV sample region of interest. 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 RV sample region of interest is identified as the only reference V sample region.

[0200] In processing block 347, the LIDAR data generator 281 can access potential LIDAR data solutions calculated by the auxiliary LIDAR data generator for the RV sample region of interest, as disclosed in the context of FIG. 12A . For example, the LIDAR data generator 281 electronics can access potential values ​​for f and / or potential values ​​of throw distance (R) for the first, second, and third solutions. In processing block 348, the LIDAR data generator 281 can identify candidate LIDAR data solutions from among the potential LIDAR data solutions. For example, the LIDAR data generator 281 can identify candidate f values ​​from among the possible f values ​​and / or candidate R values ​​from among the possible R values. The R value is positive by definition. As a result, the f value is also positive. However, the f value from the second solution is the negative of the f value from the third solution. As a result, the potential f values ​​and / or R values ​​have one or more negative values. Possible negative fr and / or Rk values ​​can be eliminated from the pool of candidates. As a result, each possible positive fr value can serve as a candidate fr value. Additionally, or alternatively, each possible positive Rk value can serve as a candidate Rk value.

[0201] In processing block 349, the LIDAR data generator 281 can identify the correct solution. The radial velocity (Vk) component and / or the fd component of each LIDAR data solution can serve as the comparison component for the LIDAR data solution. The component that serves as the comparison component can be determined by the velocity magnitude indicator. For example, as described above, if the velocity magnitude indicator is the magnitude of the radial velocity calculation, each potential LIDAR data solution for the reference V sample area has a value of radial velocity (Vk) that can serve as the comparison component, while if the velocity magnitude indicator is the magnitude of Doppler frequency, each potential LIDAR data solution for the reference V sample area has a value of fd that can serve as the comparison component. If the value of radial velocity (Vk) serves as the comparison component and the potential LIDAR data solution does not already have a radial velocity (Vk) component, the radial velocity (Vk) can be calculated for each potential LIDAR data solution using the value of fd associated with the LIDAR data and fd = 2VkFc / c.

[0202] The LIDAR data generator 281 can compare the comparison components from different LIDAR data solutions with velocity magnitude indicators from one or more V sample regions using one or more solution identification criteria to identify a correct LIDAR data solution. The LIDAR data generator 281 can select the LIDAR data solution that has the identified comparison component as the correct LIDAR data solution.

[0203] In processing block 350, the LIDAR data generator 281 identifies LIDAR data for the target RV sample region associated with sample region index k. For example, if a component of a selected potential LIDAR data solution does not already have a throw distance (Rk), the throw distance (Rk) can be calculated for the selected LIDAR data solution using the value of f associated with the selected LIDAR data solution and f = 2 * αu * Rk / c. Additionally, if a component of a selected potential LIDAR data solution does not already have a radial velocity (Vk), the radial velocity (Vk) can be calculated for the selected LIDAR data solution using the value of fd associated with the selected LIDAR data solution and fd = 2Vkfc / c. The Vk and Rk values ​​associated with the selected LIDAR data solution can serve as shared LIDAR data for the target RV sample region SRk. Thus, the LIDAR data for RV associated with sample region index k can have or consist of the Vk and Rk values ​​selected in processing block 322.

[0204] In processing block 351, the LIDAR data generator 281 can determine a radial velocity for the reference V sample region. The direction of the radial velocity indicator can be identified. For example, the direction of the comparative component of the selected LIDAR data solution serves as the direction of the radial velocity indicator for the reference V sample region associated with the radial velocity indicator. As a result, the direction of the comparative component of the selected LIDAR data solution is assigned to the radial velocity indicator to provide a directional radial velocity indicator. Thus, the directional radial velocity indicator has the magnitude of the velocity magnitude indicator of the selected LIDAR data solution and the direction (positive or negative) of the comparative component. If the velocity magnitude indicator is the magnitude of the radial velocity calculation, the directional radial velocity indicator serves as the radial velocity (Vk) for the sample region SRk. If the velocity magnitude indicator is the magnitude of something other than the radial velocity calculation, the radial velocity can be calculated from the directional radial velocity indicator. For example, if the velocity magnitude indicator is the magnitude of any beat frequency (fd), then the radial velocity (Vk) can be calculated from Cfd=2Vkfc / c, where Cfd represents the directional radial velocity indicator.

[0205] Figure 13F shows a process flow for generating LIDAR data for a sample area illuminated by a LIDAR system having real data signal cores constructed as disclosed in the content of Figure 13B. In process block 352, electronic circuitry causes the field of view of the LIDAR system to be scanned by the system output signals of the different cores.

[0206] In processing block 353, one or more velocity core auxiliary LIDAR data generators calculate a velocity magnitude indicator for each V sample area. In processing block 354, one or more throw distance and velocity core auxiliary LIDAR data generators calculate potential LIDAR data solutions for each RV sample area illuminated by one throw distance and velocity core. For example, auxiliary LIDAR data generator 269 can calculate potential LIDAR data solutions for each RV sample area illuminated by one throw distance and velocity core.

[0207] In processing block 355, the LIDAR data generator 281 identifies an RV sample region of interest. 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 RV sample region of interest is identified as the only reference V sample region.

[0208] In processing block 356, the LIDAR data generator 281 identifies a correct LIDAR data solution for the RV sample region of interest. For example, the LIDAR data generator 281 can select a correct LIDAR data solution for the RV sample region from among the possible LIDAR data solutions, as disclosed in the content of FIG. 13E. The radial walking speed (Vk) and area (Rk) associated with the selected LIDAR data solution can be considered shared LIDAR data that serves as all or part of the LIDAR data for the RV sample region SRk of interest.

[0209] In processing block 358, the LIDAR data generator 281 can determine a radial velocity (Vk) for each V sample region. For example, the common electronics 280 can determine the radial velocity (Vk) for each V sample region as disclosed in the context of FIG. 13E.

[0210] Processing blocks 355 through 358 can be repeated until each RV sample area serves as a target RV sample area, or until a desired portion of the RV sample area serves as a target RV sample area, and until each V sample area serves as a reference V sample area, or until a desired portion of the V sample area serves as a reference V sample area. FIG. 13C illustrates a 1:1 ratio of V sample areas V 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. As a result, the flow illustrated in FIG. 13D can be completed for a field of view in which each RV sample area serves as a target sample area and each V sample area serves as a reference sample area for its associated RV sample area. In some cases, multiple V sample areas can serve as reference sample areas associated with an associated RV sample area. In these examples, the V sample area that serves as a reference sample area for its associated RV sample area may have a V sample area located closest or farthest from the associated target RV sample area.

[0211] Although Figures 12C and 13C each depict sample areas illuminated by different cores as spatially separated, adjacent sample areas can overlap completely or partially. By way of example, Figure 13G depicts a portion of the field of view of Figure 12C or 13C in which sample areas illuminated by different cores partially overlap, such that each V sample area is overlapped by a different RV sample area. In some cases, the V sample area positioned closest to the target RV sample area is the V sample area that overlaps most with the target RV sample area. Thus, a V sample area that serves as a reference sample area for an associated target RV sample area can have the V sample area that is most overlapped by the associated target RV sample area.

[0212] The LIDAR data for the RV sample areas can serve as the throw distance and radial velocity for each RV sample area scanned by the RV core in processing block 300 of FIG. 10. Accordingly, the auxiliary LIDAR data generator 269 or the LIDAR data generator 281 can calculate the radial velocity and coordinates of the field location associated with the RV sample areas scanned by those cores, as disclosed in processing block 300. In addition, the radial velocity determined for the V sample areas can serve as the radial velocity for each V sample area scanned by the V core in processing block 300. As a result, the remaining portion of the processing shown in FIG. 10 can be performed, in some cases, to interpolate and / or extrapolate the throw distance (Rk) for each V sample area illuminated by the velocity core. As an example, in processing block 330, the common electronics unit 280 can combine the throw distance data (Rk) of LIDAR data solutions selected from different RV sample areas to approximate the throw distance data (Rk) for each V sample area illuminated by one velocity core. For example, the common electronics 280 can interpolate and / or extrapolate throw distance data (Rk) for each V sample region from coordinates and / or throw distance data (Rk) from different RV sample regions, as disclosed above. The LIDAR data for the sample regions of the field of view can include or consist of LIDAR data for the RV sample regions, separate LIDAR data for each V sample region (Vk), and approximate throw distance data (Rk) for each V sample region.

[0213] Example 1

[0214] The LIDAR system has an n-dimensional field of view. Field location fl is located in RV sample region SR and is identified as a known data point with coordinate R = 10 m and angular orientation θ = 10°. Field location fl is located in RV sample region SR and is identified as a known data point with coordinate R = 16 m and angular orientation θ = 12°. Field location fl is selected as the field location of interest and is located in V sample region SR with angular orientation θ = 11°. The throw distance R for field location fl is interpolated from known data points fl and fl using linear interpolation to be R = 13 m, where R = R + (R - R) (θ - θ) / (θ - θ).

[0215] Suitable platforms for LIDAR chips include, but are not limited to, silica, indium phosphide, and silicon-on-insulator wafers. FIG. 14 shows a cross-sectional view of a portion of a chip constructed from a silicon-on-insulator wafer. A silicon-on-insulator (SOI) wafer has a buried layer 431 between a substrate 432 and an optically transmissive medium 434. In a silicon-on-insulator wafer, the buried layer 431 is silica, while the substrate 432 and optically transmissive medium 434 are silicon. The substrate 432 of an optical platform such as an SOI wafer can serve as the base for the entire LIDAR chip. For example, the optical components shown on the LIDAR chips of FIGS. 1A-1C can be located on top of and / or on the sides of the substrate 432.

[0216] FIG. 14 labels the dimensions of a ridge waveguide. 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 due to the need to use higher levels of optical power than in other applications. 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 apply to straight or substantially straight sections of the waveguide, curved sections of the waveguide, and tapered sections of the waveguide. Therefore, these sections of the waveguide will be single-mode. However, in some cases, these dimensions apply to straight or substantially straight sections of the waveguide. Additionally or alternatively, the curved portion of the waveguide can have a reduced slab thickness to reduce optical loss in the curved portion of the waveguide. For example, the curved portion of the waveguide can have a ridge extending away from the slab region that is greater than 0.0 μm and less than 0.5 μm thick. While the above dimensions generally provide straight or substantially straight portions of the waveguide with a single-mode structure, they can result in tapered and / or curved portions that are multimode. Coupling between multimode geometries and single-mode geometries can be achieved using tapers that do not substantially excite higher-order modes. Thus, the waveguide can be configured such that signals carried in the waveguide are carried in single mode even when carried in a waveguide portion with multimode dimensions. The waveguide structure disclosed in connection with FIG. 6 is suitable for all or a portion of the waveguides of a LIDAR chip constructed according to FIGS. 1A-1C.

[0217] As described above, the electronic circuitry that operates the system includes local electronics 32 and common electronics 280. The distinction between local electronics and common electronics is used to denote the portion of the electronics associated with one core (local electronics) and the portion of the electronics associated with multiple cores (common electronics), respectively. While local electronics 32 and common electronics 104 are shown as being in different locations, local electronics 32 and common electronics 104 may be in a common location and / or in a common package. Furthermore, local electronics 32 and common electronics 104 may be integrated and need not refer to separate or distinct electronic components. Consequently, functions described as being performed by local electronics may be performed by common electronics, and / or functions described as being performed by common electronics may be performed by local electronics. Although certain components of the electronics, such as the auxiliary LIDAR data generator and the LIDAR data generator, are described above, the electronics may include additional components not shown. For example, the local electronics and / or portions of the local electronics may be configured to control the frequency of the system output signal, steering of the system output signal, and operation of frequency shifter 298.

[0218] Suitable electronic circuitry 32 and / or common electronic circuitry 104 may include, but are not limited to, analog electronic circuitry, application specific integrated circuits (ASICS), digital electronic circuitry, processors, microprocessors, digital signal processors (DSPs), field programmable gate arrays (FPGAs), computers, microcomputers, or any suitable combination thereof to perform the operation, control, and control functions described above, or may include a controller configured therewith. In some examples, the controller has access to a memory containing instructions to be executed by the controller during the performance of the operation, control, and control functions. While the electronic circuitry is illustrated as a single component in a single location, the electronic circuitry may include multiple distinct components that are separate from one another and / or located in different locations. Additionally, as discussed above, all or a portion of the disclosed electronic circuitry may be included on a chip with the electronic circuitry integrated therewith.

[0219] The optical sensor connected to the waveguide in the LIDAR chip can be a component separate 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, Japan, or InGaAs APDs (avalanche photodiodes) manufactured by Hamamatsu, located in Hamamatsu, Japan. These optical sensors can be centrally located on the LIDAR chip. Alternatively, all or a portion of the waveguide terminating in the optical sensor can terminate in a facet located at the edge of the chip, and the optical sensor can be attached to the edge of the chip beyond the facet so that the optical sensor receives light passing through the facet. The use of an optical sensor that is a component separate from the chip is suitable for all or a portion of the optical sensors selected from the group consisting of first auxiliary optical sensor 218, second auxiliary optical sensor 220, first optical sensor 223, and second optical sensor 224.

[0220] As an alternative to a light sensor that is a separate component, all or part of the light sensor can be integrated into the chip. For example, examples of light sensors coupled to ridge waveguides of chips constructed from silicon-on-insulator wafers can be found in Optical Express, Vol. 15, No. 21, pp. 13965-13971 (2007); U.S. Patent No. 8,093,080, issued January 10, 2012; U.S. Patent No. 8,242,432, issued August 14, 2012; and U.S. Patent No. 6,108,472, issued August 22, 2000, all of which are incorporated herein in their entireties. The use of a light sensor integrated into the chip is suitable for all or part of the light sensors selected from the group consisting of auxiliary light sensor 218, second auxiliary light sensor 220, first light sensor 223, and second light sensor 224.

[0221] The light source 4 connected to the utility waveguide 12 can be a laser chip separate from and attached to the LIDAR chip. For example, the light source 4 can be a laser chip attached to the chip using a flip-chip arrangement. Use of a flip-chip arrangement is preferred when the light source 4 is connected to a ridge waveguide of a chip constructed from a silicon-on-insulator wafer. Alternatively, the utility waveguide 12 can include an optical grating (not shown), such as a Bragg grating, that acts as a reflector for an external cavity laser. In these examples, the light source 4 can include a gain element separate from the LIDAR chip and attached to the LIDAR chip in a flip-chip arrangement. Examples of suitable interfaces between silicon-on-insulator wafer gain elements and ridge waveguides can be found in U.S. Patent No. 9,700,278, issued July 11, 2017, and U.S. Patent No. 5,991,484, issued November 23, 1999, which are incorporated herein in their entireties. If light source 4 comprises a gain element or laser chip, local electronics 32 can adjust the frequency of the emitted LIDAR signal by varying the level of current applied through the gain element or laser cavity.

[0222] The LIDAR systems described above include multiple optical components, such as a LIDAR chip, a LIDAR adapter, a light source, a light sensor, a waveguide, and an amplifier. In some examples, the LIDAR system includes one or more passive optical components in addition to or in place of the optical components shown. Passive optical components can be solid-state components that exclude moving parts. Suitable passive optical components include, but are not limited to, lenses, mirrors, optical gratings, reflective surfaces, splitters, demultiplexers, multiplexers, polarizers, polarization splitters, and polarization rotators. In some examples, the LIDAR system includes one or more active optical components in addition to or in place of the optical components shown. Suitable active components include, but are not limited to, optical switches, phase tuners, attenuators, steerable mirrors, steerable lenses, tunable demultiplexers, and tunable multiplexers.

[0223] Other embodiments, combinations, and modifications of the present invention will be readily apparent to those skilled in the art in view of these teachings. Accordingly, the present invention is limited only by the scope of the following claims, which include all such embodiments and modifications when viewed in conjunction with the above specification and accompanying drawings.

Claims

1. one or more cores each outputting a system output signal that illuminates a plurality of sample regions of the field of view; a core reference having an optical coupling portion configured to generate a composite signal that beats at a beat frequency; and an electronic circuit configured to determine the beat frequency of the composite signal using a real Fourier transform; 1. A LIDAR system comprising: The electronic circuit unit includes: configured to use a beat frequency of the composite signal to calculate a magnitude of a radial velocity indicator relative to a reference of the sample area illuminated by the system output signal output from the reference core; the radial velocity indicator indicates a radial velocity between the LIDAR system and an object in the reference sample region; The electronic circuit unit includes: configured to identify a direction of the radial velocity indicator, wherein the identification of the direction comprises a comparison of a magnitude of the radial velocity indicator with data calculated for a reference sample area selected from among the sample areas, the reference sample area being different from the reference sample area; LIDAR system.

2. the radial velocity indicator is a calculation of radial velocity relative to the reference sample area; 2. The system according to claim 1.

3. the radial velocity indicator is the beat frequency of the composite signal resulting from illumination of the reference sample area by one of the system output signals; 2. The system according to claim 1.

4. the data from the sample area of ​​interest comprises a plurality of possible LIDAR data solutions for the sample area of ​​interest; 2. The system according to claim 1.

5. each of the potential LIDAR data solutions for the target sample region has all or a portion of components selected from the group consisting of: a value for fr, a value for fd, a value for radial velocity, and a value for throw distance; The value of fd is the Doppler frequency shift, the value of fr is the frequency shift resulting from the distance between the system and objects in the sample region of interest; the value of the radial velocity indicates a radial velocity between the system and an object in the sample region of interest; the throw distance value indicates a throw distance between the system and an object in the sample area of ​​interest; A system according to claim 4.

6. the potential LIDAR data solutions have comparison components selected from values ​​of fd and values ​​of radial velocity; The value of fd is the Doppler frequency shift, the value of the radial velocity indicates a radial velocity between the system and an object in the sample region of interest; Comparing the magnitude of the radial velocity indicator with data calculated for one or more reference sample regions comprises comparing the magnitude of the radial velocity indicator with the comparison component. A system according to claim 4.

7. the electronic circuitry identifies the potential LIDAR solution with the comparison component having a magnitude closest to the magnitude of the radial velocity indicator. A system according to claim 6.

8. the electronic circuitry sets the direction of the radial velocity indicator to the same direction as the identified comparison component. A system according to claim 6.

9. the reference sample area and the target sample area at least partially overlap; 2. The system according to claim 1.

10. the reference sample area is the sample area closest to the target sample area; 2. The system according to claim 1.

11. the one or more cores are a plurality of cores, and the system output signal illuminating the sample area of ​​interest is different from the system output signal illuminating the sample area closest to the sample area of ​​interest. A system according to claim 10.

12. the electronic circuitry estimates a throw distance for the target sample area by interpolating between throw distances calculated for a plurality of different sample areas selected from among the sample areas illuminated by the system output signals from one or more cores.

2. The system according to claim 1.

13. the electronic circuitry calculates the beat frequency value using a real Fourier transform; 2. The system according to claim 1.

14. one or more cores each outputting a system output signal that illuminates a plurality of sample areas of the field of view; subject to said core having an optical coupling portion configured to generate a composite signal that beats at a beat frequency; and electronic circuitry configured to use the beat frequency values ​​of the composite signal to calculate a plurality of possible LIDAR data solutions for objects of interest in the sample region illuminated by the system output signal output from the target core; 1. A LIDAR system comprising: each of the potential LIDAR data solutions has a comparison component indicative of a value of radial velocity between the LIDAR system and an object in the sample region of interest; the electronic circuitry is configured to identify a correct one of the LIDAR data solutions, wherein identifying a correct LIDAR data solution comprises comparing the LIDAR data solution with data calculated for one or more reference sample areas selected from among the sample areas, the one or more reference sample areas being different from the target sample area; LIDAR system.

15. the comparison component is a calculation of a likely radial velocity for the sample region of interest; A system according to claim 14.

16. the comparison component is the beat frequency of the composite signal resulting from illumination of the reference sample area by one of the system output signals; A system according to claim 14.

17. the data from each of the one or more reference sample areas having a line of sight velocity indicator relative to the reference sample area, the line of sight velocity indicator indicative of a line of sight velocity between the LIDAR system and an object in the reference sample area; A system according to claim 14.

18. each of the potential LIDAR data solutions having a comparison component selected from a value of fd and a value of radial velocity; The value of fd is the Doppler frequency shift, the value of the radial velocity indicates a radial velocity between the system and an object in the sample region of interest; Comparing the comparison component with data calculated for one or more reference sample regions comprises comparing the magnitude of the radial velocity indicator with the magnitude of the comparison component.

18. A system according to claim 17.

19. the electronic circuitry identifies the potential LIDAR solution with the comparison component having a magnitude closest to the magnitude of the radial velocity indicator as the correct LIDAR solution.

19. A system according to claim 18.

20. the one or more sample areas is a single sample area; A system according to claim 14.

21. the one or more reference sample regions and the target sample region at least partially overlap; A system according to claim 14.

22. the one or more reference sample regions having one of the sample regions closest to the target sample region; A system according to claim 14.

23. the one or more cores are a plurality of cores, and the system output signal illuminating the sample area of ​​interest is different from the system output signal illuminating the sample area closest to the sample area of ​​interest.

23. A system according to claim 22.

24. the electronic circuitry estimates a throw distance for at least one of the one or more reference sample areas by interpolating between throw distances calculated for a plurality of different sample areas selected from among the sample areas illuminated by the system output signals from one or more cores. A system according to claim 14.

25. the electronic circuitry calculates the beat frequency value using a real Fourier transform; A system according to claim 14.

26. illuminating multiple sample areas of the field of view with system output signals from different cores; combining the optical signals to generate a composite signal that beats at the beat frequency; using the beat frequency value of the composite signal to calculate a magnitude of a radial velocity indicator relative to a reference of the sample area illuminated by the system output signal output from a reference core; the radial velocity indicator indicates a radial velocity between the LIDAR system and an object in the reference sample region; identifying a direction of the radial velocity indicator by comparing a magnitude of the radial velocity indicator with data calculated for an object of the sample region; the reference sample area is different from the target sample area; A method for operating a LIDAR system.

27. illuminating multiple sample areas of the field of view with system output signals from different cores; combining the optical signals to generate a composite signal that beats at the beat frequency; using the beat frequency values ​​of the composite signal to calculate a plurality of different possible LIDAR data solutions related to the subject of interest in the sample region; each of the potential LIDAR data solutions having a comparison component indicative of a value of radial velocity between the LIDAR system and an object in the sample region of interest; and identifying a correct one of the LIDAR data solutions by comparing the LIDAR data solution with data calculated for one or more reference sample areas selected from among the sample areas; the one or more reference sample regions are different from the target sample region; A method for operating a LIDAR system.

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