Methods for reading integrated circuits and determining the distance or speed of an object

Abstract

A method for reading out an integrated circuit and determining the distance or speed of an object is provided. The readout integrated circuit includes: a balanced PIN photodiode configured to receive an optical signal and convert the optical signal into a current signal; an optical mixer configured to receive a current signal from the balanced PIN photodiode and convert the current signal into a mixed signal of high frequency and low frequency; a transimpedance amplifier configured to receive the converted current signal from the optical mixer and convert the converted current signal into a voltage signal; a comparator configured to receive the voltage signal and generate a pulse signal from the voltage signal; a master counter configured to receive a master signal corresponding to the pulse signal and count the number of pulses to generate master counter data; a reference counter configured to receive a reference signal and count the number of pulses to generate reference counter data; and an arithmetic logic unit configured to receive the master counter data and the reference counter data and calculate depth information corresponding to the distance to the target.

Description

[0001] This application claims priority and benefit to U.S. Provisional Application No. 63 / 051,542, filed July 14, 2020, entitled “A Novel Readout Architecture for FMCW LiDAR”, and U.S. Application No. 17 / 011,813, filed September 3, 2020, the entire contents of which are incorporated herein by reference. Technical Field

[0002] One or more aspects of embodiments of this disclosure generally relate to LiDAR systems. Background Technology

[0003] LiDAR is a portmanteau of light and radar and can mean "light detection and ranging" or "laser imaging, detection and ranging," and refers to a method for measuring the distance and / or velocity of a target or object by illuminating it with light (e.g., a laser) from one or more sources and by measuring the reflection of the light leaving the target using one or more sensors.

[0004] For example, the difference in return time (e.g., the amount of time between the emission of light and the detection of the partial reflection of light) and / or the difference in wavelength (e.g., the difference between the wavelength of the emitted laser and the wavelength of the detected reflected laser) can also be used to determine the distance to a target (e.g., the distance from the light source or sensor to the target) and can also be used to create a digital three-dimensional representation of one or more parts of the target that reflect the light.

[0005] The information disclosed in this background section is only intended to enhance the understanding of the background of the disclosure and may therefore contain information that does not form prior art. Summary of the Invention

[0006] The embodiments described herein provide improvements to LiDAR technology, including improvements to the readout architecture of readout integrated chips used in frequency modulated continuous wave (FMCW) LiDAR systems.

[0007] According to embodiments of this disclosure, an FMCW is provided. The readout integrated circuit of the LiDAR system includes: a balanced PIN photodiode configured to receive an optical signal and convert the optical signal into a current signal; an optical mixer configured to receive a current signal from the balanced PIN photodiode and convert the current signal into a mixed signal of high frequency and low frequency; a transimpedance amplifier configured to receive the converted current signal from the optical mixer and convert the converted current signal into a voltage signal, the voltage signal including a low-frequency sine wave after high frequency filtering; a comparator configured to receive the voltage signal from the transimpedance amplifier and generate a pulse signal from the voltage signal; a master counter configured to receive a master signal corresponding to the pulse signal generated by the comparator and count the number of pulses of the master signal during a specific time period to generate master counter data; a reference counter configured to receive a reference signal and count the number of pulses of the reference signal during a time period to generate reference counter data; and an arithmetic logic unit configured to receive the master counter data and the reference counter data and calculate depth information corresponding to the distance to the target based on the master counter data and the reference counter data.

[0008] The readout integrated circuit may further include: a main phase-locked loop (PLL) configured to receive a pulse signal from a comparator and multiply it by the frequency of the pulse signal to generate a main signal; and a reference phase-locked loop configured to amplify a reference PLL signal to generate a reference signal having a reference frequency corresponding to a reference distance.

[0009] The comparator can also be configured to compare the master signal with a reference signal.

[0010] The arithmetic logic unit can be configured to calculate depth information by multiplying the reference distance by the ratio of the reference counter data and the master counter data.

[0011] The readout integrated circuit may further include a frame memory, which is configured to: receive master counter data; receive depth information from an arithmetic logic unit; and store the depth information.

[0012] The arithmetic logic unit can also be configured to calculate speed information by: receiving depth information from a frame memory, the depth information including first depth information calculated for a first memory frame and second depth information calculated for a second memory frame; calculating the difference in depth corresponding to the difference between the first depth information and the second depth information; and dividing the difference in depth by a time period corresponding to the time between the first memory frame and the second memory frame.

[0013] The comparator can also be configured to compare the master counter data with the reference counter data.

[0014] According to another embodiment of this disclosure, a method for determining the distance or speed of an object is provided, the method comprising: receiving a waveform signal corresponding to the target; generating a pulse signal from the received waveform signal; resetting a master counter and a reference counter; after a first time period since the reset of the master counter and the reference counter has elapsed, starting a master count using the master counter and starting a reference count using the reference counter; continuing the master count and the reference count in a second time period; maintaining the last master value of the master counter and the last reference value of the reference counter; calculating the ratio of the last master value to the last reference value; and multiplying a reference distance by the ratio.

[0015] The method may also include receiving waveform signals from the output of an optical mixer.

[0016] The first time period can correspond to the detection range.

[0017] The second time period can correspond to the flexible programming time period.

[0018] The method may further include generating a beam toward the target to cause the target to scatter the beam, and receiving the scattered beam as a waveform signal corresponding to the target.

[0019] The method may further include calculating speed information by: receiving depth information, the depth information including first depth information calculated for a first memory frame and second depth information calculated for a second memory frame; calculating the depth difference corresponding to the difference between the first depth information and the second depth information; and dividing the depth difference by a time period corresponding to the time between the first memory frame and the second memory frame.

[0020] The method may also include calculating depth information by multiplying the reference distance by the ratio of the master count to the reference count.

[0021] According to another embodiment of this disclosure, a non-transitory computer-readable medium implemented on a readout integrated circuit of an FMCW LiDAR system is provided. The non-transitory computer-readable medium has computer code that, when executed on a processor, implements a method for determining the distance or velocity of an object. The method includes: receiving a waveform signal corresponding to the target; generating a pulse signal from the received waveform signal; resetting a master counter and a reference counter; after a first time period since the reset has elapsed, starting a master count using the master counter and a reference count using the reference counter; continuing the master count and reference count in a second time period; maintaining the last master value of the master counter and the last reference value of the reference counter; calculating the ratio of the last master value to the last reference value; and multiplying a reference distance by the ratio.

[0022] When the computer code is executed on the processor, it can be further implemented as a method to determine the distance or speed of an object by receiving waveform signals from the output of an optical mixer.

[0023] The first time period corresponds to the detection range, while the second time period corresponds to the flexible programming time period.

[0024] When the computer code is executed on the processor, it can be further implemented as a method to determine the distance or speed of an object by generating a beam of light toward the target so that the target scatters the beam of light and receiving the scattered beam of light as a waveform signal corresponding to the target.

[0025] When the computer code is executed on a processor, it can further implement a method for determining the distance or speed of an object by calculating speed information via the following operations: receiving depth information, including first depth information calculated for a first memory frame and second depth information calculated for a second memory frame; calculating a difference in depth corresponding to the difference between the first depth information and the second depth information; and dividing the difference in depth by a time period corresponding to the time between the first memory frame and the second memory frame.

[0026] When the computer code is executed on the processor, it can be further implemented to determine the distance or velocity of an object by multiplying the depth information by the ratio of the reference distance to the master count and the reference count.

[0027] Therefore, the systems and methods of some embodiments of this disclosure are able to calculate the range of a target while omitting circuitry elements used to perform transformations on signals that calculate depth / distance / range. Attached Figure Description

[0028] Non-limiting and non-exhaustive embodiments of this invention are described with reference to the following drawings, wherein, unless otherwise stated, the same reference numerals denote the same parts throughout the various views.

[0029] Figure 1 The diagram illustrates a block diagram depicting a LiDAR system according to some embodiments of the present disclosure;

[0030] Figure 2 A block diagram depicting the readout architecture of a frequency modulated continuous wave (FMCW) LiDAR system is shown.

[0031] Figure 3 A block diagram depicting the readout architecture of a frequency modulated continuous wave (FMCW) LiDAR system according to some embodiments of the present disclosure is shown;

[0032] Figure 4 Examples of various signals of simulated ROIC corresponding to targets at different distances in readout architectures according to some embodiments of this disclosure are shown; and

[0033] Figure 5 A flowchart illustrating a method for determining the distance of a target from a LiDAR system according to some embodiments of the present disclosure is shown.

[0034] Throughout the various views in the accompanying drawings, corresponding reference characters indicate the corresponding components. Those skilled in the art will understand that the elements in the drawings are shown for simplicity and clarity and are not necessarily drawn to scale. For example, the dimensions of some elements, layers, and regions in the drawings may be exaggerated relative to other elements, layers, and regions to aid in clarity and understanding of the various embodiments. Furthermore, common but well-understood elements and components not relevant to the description of the embodiments may not be shown to facilitate less obstruction of the views of these various embodiments and to make the description clearer. Detailed Implementation

[0035] The features of the inventive concept and the methods for implementing it can be more readily understood by referring to the accompanying drawings and detailed description of the embodiments. Hereinafter, embodiments will be described in more detail with reference to the accompanying drawings. However, the described embodiments can be implemented in various different forms and should not be construed as being limited to the embodiments shown herein. Rather, these embodiments are provided as examples so that this disclosure will be thorough and complete, and will fully convey aspects and features of the inventive concept to those skilled in the art. Therefore, treatments, elements, and techniques unnecessary for a full understanding of the aspects and features of the inventive concept by those skilled in the art are not described.

[0036] Unless otherwise stated, the same reference numerals denote the same elements throughout the drawings and text description, and therefore their descriptions will not be repeated. Furthermore, components unrelated to the description of the embodiments may be omitted to make the description clearer. In the drawings, the relative dimensions of elements, layers, and regions may be exaggerated for clarity.

[0037] In the detailed description, numerous specific details are set forth for illustrative purposes to provide a thorough understanding of the various embodiments. However, it is clear that various embodiments may be practiced without these specific details or with one or more equivalent arrangements. In other instances, well-known structures and apparatuses are shown in block diagram form to avoid unnecessarily obscuring the various embodiments.

[0038] It will be understood that although the terms “first,” “second,” “third,” etc., may be used herein to describe various elements, components, regions, layers, and / or portions, these elements, components, regions, layers, and / or portions should not be limited by these terms. These terms are used to distinguish one element, component, region, layer, or portion from another element, component, region, layer, or portion. Therefore, without departing from the spirit and scope of this disclosure, the first element, first component, first region, first layer, or first portion described below may be referred to as a second element, second component, second region, second layer, or second portion.

[0039] The terminology used herein is for the purpose of describing some embodiments only and is not intended to limit this disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. It will also be understood that the terms “comprising,” “having,” and “including” as used in this specification indicate the presence of the stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items.

[0040] As used herein, the terms “substantially,” “approximately,” “approximately,” and similar terms are used as approximate terms rather than terms of degree and are intended to take into account the inherent biases of measured or calculated values ​​that will be recognized by those skilled in the art. Taking into account the measurement in question and the errors associated with the measurement of a particular quantity (i.e., the limitations of the measurement system), “approximately” or “approximately” as used herein includes the stated value and indicates that it is within an acceptable range of deviation for a particular value as determined by those skilled in the art. For example, “approximately” may mean within one or more standard deviations, or within ±30%, 20%, 10%, or 5% of the stated value. Furthermore, the word “may” as used in describing embodiments of this disclosure means “one or more embodiments of this disclosure.”

[0041] When a particular embodiment can be implemented differently, the specific order of processing can be executed differently from the order in which they are described. For example, two consecutively described processes can be executed substantially simultaneously or in the reverse order of their description.

[0042] Electronic or electrical devices and / or any other related devices or components according to embodiments of the present disclosure described herein can be implemented using any suitable hardware, firmware (e.g., application-specific integrated circuits), software, or a combination of software, firmware, and hardware. For example, various components of such devices may be formed on a single integrated circuit (IC) chip or multiple separate IC chips. Furthermore, various components of such devices may be implemented on flexible printed circuit films, tape-and-carrier packages (TCPs), printed circuit boards (PCBs), or formed on a substrate.

[0043] Furthermore, the various components of these devices may be processes or threads running on one or more processors in one or more computing devices, which execute computer program instructions and interact with other system components to perform the various functions described herein. The computer program instructions are stored in memory, which may be implemented in the computing device using standard memory devices, such as random access memory (RAM). The computer program instructions may also be stored in other non-transitory computer-readable media, such as CD-ROMs, flash drives, etc. Moreover, those skilled in the art will recognize that, without departing from the spirit and scope of the embodiments of this disclosure, the functions of various computing devices may be combined or integrated into a single computing device, or the functions of a particular computing device may be distributed across one or more other computing devices.

[0044] Unless otherwise defined, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which the inventive concept pertains. It will also be understood that, unless expressly defined herein, terms (such as those defined in a general dictionary) shall be interpreted as having the same meaning as they have in the relevant field and / or the context of this specification, and shall not be interpreted in an idealized or overly formalized sense.

[0045] As described above, LiDAR systems can be used to determine the depth of a target relative to the LiDAR system (e.g., the distance of the target from the LiDAR system) and / or velocity. Some embodiments of this disclosure provide improvements to LiDAR technology by omitting other components that can be used in a LiDAR system, thereby increasing the speed and accuracy of the LiDAR system and potentially reducing the associated manufacturing costs.

[0046] Figure 1 A block diagram depicting a LiDAR system according to some embodiments of the present disclosure is shown.

[0047] Reference Figure 1The LiDAR system 100 includes a light source 110, a reflector 115, a scanner 120, a receiver 140, and a controller 150. The LiDAR system 100 may be referred to as a laser ranging system, a lidar system, or a laser detection and ranging system.

[0048] In some embodiments, the LiDAR system 100 may be configured to sense, identify, or determine the distance to one or more targets 130 within its field of view (FOR). As an example, the LiDAR system 100 may determine the distance to a target 130, wherein all or part of the target 130 is contained within the field of view (FOR) of the LiDAR system 100. All or part of the target 130 contained within the FOR of the LiDAR system 100 may mean that the FOR overlaps with, includes, or surrounds at least a portion of the target 130. In some embodiments, the target 130 may include all or part of an object that is moving or stationary relative to the LiDAR system 100.

[0049] Light source 110 may correspond to a laser for generating an output beam 125 having an operating wavelength (e.g., a wavelength in the electromagnetic spectrum). Output beam 125 may be referred to as an optical signal, laser beam, light beam, optical beam, emitted beam, emitted light, or simply a beam. In some embodiments, LiDAR system 100 is a frequency-modulated continuous wave (FMCW) LiDAR system. Therefore, output beam 125 may be an FMCW laser; however, it should be noted that in other embodiments, output beam 125 may be pulsed or otherwise modulated. Output beam 125 may be directed toward a target 130 at a distance D from LiDAR system 100. Before being directed to target 130, output beam 125 may pass through or through a mirror 115 (e.g., mirror 115 may include an aperture, slot, or stop through which output beam 125 passes).

[0050] After passing through or over mirror 115, the output beam 125 can also pass through scanner 120. Scanner 120 can be configured to scan the output beam 125 across a region of interest (e.g., FOR) of LiDAR system 100. Scanner 120 may include one or more scanning mirrors configured to pivot, rotate, oscillate, or move at an angle about one or more axes of rotation. Thus, the output beam 125 can be reflected by the scanning mirrors, and the reflected output beam 125 can be scanned at a corresponding angle as the scanning mirrors pivot or rotate. For example, the scanning mirrors can be configured to periodically pivot back and forth, thereby scanning the output beam 125 back and forth.

[0051] After passing through scanner 120, once the output beam 125 reaches target 130, target 130 may scatter or otherwise reflect at least a portion of the light from the output beam 125, and some of the scattered or reflected light may return as one or more input beams 135 toward LiDAR system 100 as received optical signals. Typically, a relatively small portion of the light from output beam 125 returns to LiDAR system 100 as input beam 135. The input beam 135 may then return while passing through scanner 120 and may then be reflected by mirror 115 to be directed to receiver 140.

[0052] In addition to mirror 115, LiDAR system 100 may also include one or more optical components (e.g., lenses, mirrors, or filters) configured to reflect, focus, filter, shape, modify, redirect, guide, collimate, or combine light generated or received by LiDAR system 100 (e.g., configured to guide or focus output beam 125 or input beam 135). As an example, LiDAR system 100 may include one or more lenses to focus input beam 135 onto a photodetector of receiver 140. In some embodiments, mirror 115 may provide output beam 125 and input beam 135 substantially coaxial, such that the two beams travel along approximately the same optical path (e.g., substantially parallel to each other and traveling in opposite directions). Thus, mirror 115 and other corresponding components may guide input beam 135 to receiver 140.

[0053] Receiver 140 may be referred to as a photodetector, optical receiver, optical sensor, detector, photodetector, or optical detector. Receiver 140 may include one or more avalanche photodiodes (APDs), single-photon avalanche photodiodes (SPADs), PN photodiodes (PDs), and / or PIN photodiodes (e.g., such as...). Figure 3 The balanced PIN PD340 shown is an example. Receiver 140 may include electronic circuitry for performing signal modification and analysis. Receiver 140 may include a transimpedance amplifier (TIA) (e.g., hereinafter referred to as...). Figure 2 and Figure 3 The TIA (described as 265, 365) converts the received photocurrent generated in response to the received optical signal into a voltage signal. The voltage signal can be used to determine one or more optical characteristics of the input beam 135 and can be used to generate a digital output signal / electrical signal 145, which is sent to the controller 150 for processing or analysis (e.g., determining the time-of-flight value corresponding to the received optical pulse).

[0054] Therefore, after being reflected by mirror 115, receiver 140 can receive and detect photons from input beam 135. Receiver 140 can then generate and output current or voltage pulses as electrical signals 145 representing input beam 135, and can send electrical signals 145 to controller 150 (e.g., which may be referred to below). Figure 2 and Figure 3 The ROIC 250, 350 described may include a portion of the following references. Figure 2 and Figure 3 (Description of the ROIC 250 and 350 controllers).

[0055] The controller 150 may include a processor, computing system, or other suitable circuitry, and may be configured to analyze one or more characteristics of the electrical signal 145 from the receiver 140 to determine one or more characteristics of the target 130 (such as the target's distance or velocity relative to the LiDAR system 100). This may be accomplished, for example, by analyzing the time of flight of the light common to the transmitted output beam 125 and the received input beam 135.

[0056] The time of flight T represents the round-trip flight time of the emitted light beam or pulse from LiDAR system 100 to target 130 and back. The time of flight T can be used to calculate the distance / range / depth D from target 130 to LiDAR system 100, where distance D can be expressed as D = c × T / 2, and c is the speed of light.

[0057] The controller 150 may also be electrically or communicatively integrated with the light source 110, the reflector 115, and the scanner 120. The controller 150 may receive electrical trigger pulses or edges due to the light source 110, wherein each pulse or edge corresponds to the emission of a light pulse by the light source 110. The controller 150 may also control the light source 110 to generate and / or adjust the output beam 125. As further described below, the controller 150 may determine the time-of-flight value of the light pulse based on timing information associated with when the output beam 125 is emitted by the light source 110 and when the input beam 135 is detected by the receiver 140. Therefore, the controller 150 may include circuitry performing signal amplification, sampling, filtering, signal conditioning, analog-to-digital conversion, time-to-digital conversion, pulse detection, threshold detection, rising edge detection, or falling edge detection.

[0058] In some embodiments, one or more LiDAR systems 100 may be integrated into a vehicle (e.g., as part of an advanced driver assistance system (ADAS) to assist the driver in operating the vehicle, or as part of an autonomous vehicle driving system). For example, the LiDAR system 100 may be part of an ADAS that provides information or feedback to the driver (e.g., warns the driver of potential problems or hazards) or automatically controls one or more functions of the vehicle (e.g., by controlling the braking or steering systems) to avoid a collision or accident. The LiDAR system 100 may provide information about the surrounding environment to the autonomous vehicle's driving system. The autonomous vehicle driving system may be configured to guide the autonomous vehicle using the environment around it and may include one or more computing systems that receive information about the surrounding environment from the LiDAR system 100, analyze the received information, and provide control signals to the vehicle's driving system and actuators (e.g., steering wheel, accelerator, brake, or turn signals).

[0059] Figure 2 A block diagram depicting the readout architecture of a frequency modulated continuous wave (FMCW) LiDAR system is shown.

[0060] Reference Figure 2 FMCW LiDAR system (e.g., Figure 1 The readout architecture 200 of the LiDAR system 100 may include a receiver implemented as a LiDAR system (e.g., Figure 1 The receiver 140) includes a balanced PIN PD 240, and may also include a controller implemented as a LiDAR system (e.g., Figure 1 The controller 150 includes a readout integrated circuit (ROIC) 250. ROIC 250 can be used in conjunction with a memory (PC) 260. ROIC 250 may include a TIA 265, an analog-to-digital controller (ADC) block 270 (e.g., an ultra-high-speed, high-resolution ADC block 270), a fast Fourier transform (FFT) block 280 (e.g., a 2D FFT block), and a phase-locked loop (PLL) block 290 in relevant sections.

[0061] The balanced PIN PD 240 can receive an input beam (e.g., Figure 1 The photons corresponding to the input beam 135 can then be converted into an electric current as a signal 245 (e.g., Figure 1The TIA 265 can then receive signal 245 and convert the current of signal 245 into a voltage signal (e.g., TIA signal 267) to be sent to ADC block 270. ADC block 270 then converts the TIA signal 267 received from TIA 265 into a data stream (e.g., data signal 285), such that each pixel or voxel detected by balanced PIN PD 240 (e.g., a single sample or data point on a regularly spaced 3D grid) can be converted into one or more corresponding data values. Subsequently, FFT block 280 can perform a transformation (e.g., FFT) on the data values ​​of data signal 285 received from ADC block 270 to calculate depth information corresponding to the target of the reflected or scattered input beam 135. Finally, the depth value indicated in the depth signal 287 from FFT block 280 and the data value from the data signal 285 from ADC block 270 are sent to memory 260 via two corresponding lines from ADC block 270 to memory 260 and from FFT block 280 to memory 260, thereby enabling the calculation of the target (e.g., using the data signal 285 and the depth signal 287) using the data signal 285 and the depth signal 287. Figure 1 The target is both the depth and speed (130).

[0062] Advanced Driver Assistance Systems (ADAS) and autonomous driving applications can utilize high-resolution and high-quality range / depth / distance information to enable LiDAR systems to "see" further (e.g., with a longer target detection range) and to detect or identify targets more quickly and easily, thereby reducing the risk associated with a vehicle using a LiDAR system colliding with or avoiding one or more targets. Furthermore, low-power operation of LiDAR systems can be implemented using ADAS or autonomous driving systems. Therefore, the specifications of the ROIC 250 can take into account receiver bandwidth (e.g., on the order of several hundred MHz or more), ADC resolution and detection capability, low noise (e.g., a signal-to-noise ratio (SNR) of 12 dB or higher, and / or a low-noise amplifier (LNA) used as a TIA), power consumption, chip-level direct Fourier transform (DFT) performance, and other radio frequency (RF) processing.

[0063] However, target analysis in 3D systems typically consumes a relatively large amount of power. Furthermore, LiDAR systems capable of calculating target depth using direct time-of-flight (dToF) methods combined with single-photon avalanche diodes (SPADs) as receivers may face difficulties due to various sources of environmental noise. Therefore, Figure 2 The implementation of the readout architecture 200 may have obstacles associated with the ADC block 270 and the FFT block 280.

[0064] For example, the 2D FFT block 280 may require a relatively large amount of space on the ROIC 250 and may consume a relatively large amount of power over several frames to detect depth and velocity information. Note that the readout architecture 200 in the FMCW LiDAR system can determine depth and velocity simultaneously using the 2D FFT block 280. Furthermore, when determining depth and velocity information, there may be hysteresis associated with the operation of the FFT block 280.

[0065] As another example, ADC block 270 can operate on the order of GHz (e.g., it may have a sampling rate of some GHz) to achieve medium to high resolution, and readout architecture 200 may attempt to isolate signal noise and crosstalk associated with other blocks of ROIC 250. This is achieved through a high-speed, low-jitter phase-locked loop (PLL) block 290 and a high-sensitivity bias circuit 292 to support the high-speed operation of ADC block 270 (e.g., PLL block 290 can be used as a clock for ADC block 270 and FFT block 280, and can operate on the order of GHz). As a result, due to the high sensitivity level of each block, readout architecture 200 may not be effectively integrated with optical PLL blocks (OPLL).

[0066] Therefore, as referred to below Figure 3 and Figure 4 The described existence and solution Figure 2 The above-mentioned problems and limitations of the readout architecture 200 are associated with some of the benefits of the new readout architecture.

[0067] Figure 3 A block diagram depicting the readout architecture of a frequency modulated continuous wave (FMCW) LiDAR system according to some embodiments of the present disclosure is shown.

[0068] Reference Figure 3 With the readout architecture of LiDAR systems (e.g., Figure 2 Various problems associated with the readout architecture 200 can be solved or eliminated. For example, with Figure 2 The ambient noise associated with the readout architecture 200 can be effectively eliminated by removing interference additionally caused by other LiDAR systems and / or other light sources, using the modulated signal (e.g., the FMCW signal) of the FMCW LiDAR system (e.g., LiDAR system 100) according to embodiments of this disclosure. This can be achieved by providing an omitted... Figure 2 The readout architecture 200 consists of a high-speed ADC block 270 and a 2D FFT block 280 (typically a relatively noise-sensitive block) and a low-power readout architecture 300, which is implemented by replacing the omitted blocks with a comparator 380 and one or more counters 395.

[0069] The readout architecture 300 of the LiDAR system may be included in the relevant section as a receiver (e.g., Figure 1 The receiver 140 comprises a balanced PIN PD 340, a ROIC 350, and a memory (or frame memory) (PC) 360. The ROIC 350 includes a TIA 365, a comparator 380, a main PLL block (PLL_i) 390i, a reference PLL block (PLL_r) 390r, a main counter block (CNT_i) 395i, a reference counter block (CNT_r) 395r, and a depth and / or depth / velocity block 375 for calculating depth and / or velocity (e.g., depth / velocity 375). Figure 2 Unlike the ROIC 250, the ROIC 350 in this example omits overly sensitive blocks (e.g., ADC block 270 and FFT block 280) while still efficiently calculating the depth and velocity of the target.

[0070] The LiDAR system in this example can output an output beam (e.g., by using a linearly frequency-modulated signal (chirping signal) that changes the frequency of the output beam 125) to produce an output beam. Figure 1 The output beam is 125. Then, the target (e.g., Figure 1 The target 130) can scatter or reflect the output beam 125, thereby causing the input beam (e.g., Figure 1 The input beam 135 is returned to the LiDAR system (e.g., to the balanced PIN PD 340).

[0071] Therefore, the balanced PIN PD 340 can detect photons of the input beam 135 as a linear frequency modulated signal. The balanced PIN PD 340 can then convert the photons into an electric current to transmit a signal (e.g., current as an electrical signal or digital output signal) 345 to the ROIC 350, which can function alone or in conjunction with the frame memory 360 as... Figure 1 The controller 150 operates. The electrical signal 345 from the balanced PIN PD 340 can be considered to have a β frequency corresponding to the linear modulation frequency of the input beam 135. The electrical signal 345 can then be directly received by the TIA 365; however, it should be noted that in other embodiments, the readout architecture 300 may include an optical mixer between the balanced PIN PD 340 and the TIA 365. The optical mixer can convert the frequency of the electrical signal 345 from the balanced PIN PD 340. For example, the optical mixer can convert the electrical signal 345 into a mixed signal of low and high frequencies.

[0072] The TIA 365 is a current-to-voltage converter and can be used with one or more operational amplifiers. The TIA 365 can be used to amplify the current output corresponding to the received electrical signal 345 to a usable voltage (e.g., to a suitable voltage to be used by comparator 380). The TIA 365 can be used because the balanced PIN PD 340 can have a more linear current response than its voltage response (e.g., the current response of the balanced PIN PD 340 can be approximately 1% nonlinear or better over a wide range of optical inputs). The TIA 365 presents a low impedance to the balanced PIN PD 340 and isolates the balanced PIN PD 340 from the output voltage of the TIA 365. In some embodiments, the TIA 365 can be a large-value feedback resistor. The gain, bandwidth, input offset current, and input offset voltage of the TIA 365 can be customized according to the receiver used with it (e.g., ...). Figure 1 The type of receiver (140) varies.

[0073] Therefore, the TIA 365 can receive electrical signal 345 and convert it into voltage. It should be noted that... Figure 2 Unlike the TIA 265, the TIA 365 in this example does not require a low-noise amplifier because the ROIC 350 is capable of effectively separating noise from the various signals associated with it. After converting the electrical signal 345 into a voltage and / or amplifying the current output of the electrical signal 345, the TIA 365 can transmit a TIA signal 367 (e.g., as a relatively small analog signal) to the comparator 380. In embodiments where the readout architecture 300 may include an optical mixer between the balanced PIN PD 340 and the TIA 365, the TIA signal 367 output by the TIA 365 may include a low-frequency sine wave after high frequencies have been filtered out.

[0074] Comparator 380 can then convert the TIA signal 367 from TIA 365 into a pulse signal 385. The pulse signal 385 from comparator 380 is then transmitted as data valid for signal processing. The data indicated by the pulse signal 385 can then be transmitted to the main PLL block 390i, which can be supported by bias circuitry 392.

[0075] Subsequently, the main PLL block 390i and / or the main counter block 395i, which can be implemented as part of an arithmetic logic unit (ALU), can count the frequency of the pulse signal 385 and send the count as a count signal 387a to the depth / velocity block 375. For example, the main PLL block 390i can generate a main signal by multiplying by the frequency of the pulse signal 385. The main counter block 395i can count the number of pulses of the main signal over a specific time period to generate main counter data (e.g., count signal 387a). The reference PLL block 390r (e.g., in conjunction with the reference counter block 395r) can be used to count the reference target frequency (e.g., the frequency of the pulse signal associated with the reference target at the reference distance) and send the count as a reference count signal 387b to the depth / velocity block 375. For example, the reference PLL block 390r can amplify the reference PLL signal to generate a reference signal having a reference frequency (e.g., the reference target frequency) corresponding to the reference distance. The reference counter block 395r can count the number of pulses of the reference signal during the time period used to receive the reference signal and generate reference counter data (e.g., reference count signal 387b). The depth / velocity block 375 is capable of performing simple multiplication and division to enable the calculation of the target's depth and / or velocity relative to the LiDAR system based on the count signal 387a. The depth / velocity block 375 can be an arithmetic logic circuit or can be implemented as part of an arithmetic logic circuit.

[0076] Therefore, the main PLL block 390i, combined with the main counter block 395i and the depth / velocity block 375, can be used to multiply by the beat frequency to enable the use of the direct time-of-flight (dToF) method to calculate the target (e.g., Figure 1 The depth of the target (130). However, it should be noted that in other embodiments, the main PLL block 390i may be omitted, and the pulse signal 385 output by the comparator 380 may be sent to the main counter block 395i and may be used alone to generate a count for a given time frame.

[0077] For example, by counting the beat frequencies of pulse signal 385, the counting frequency can be converted into a digital signal (e.g., using a frequency-to-digital (F2D) converter) to determine depth / range / distance information associated with the target. A smaller distance (or phase difference) between the input frequency of input beam 135 and the output frequency of output beam 125 corresponds to a longer delay, resulting in higher frequencies and higher counts. Therefore, the distance from the LiDAR system to the target can be determined by counting the beat pulses of pulse signal 385 in the time domain.

[0078] In some embodiments, the readout architecture 300 may be adapted for high-resolution depth information. Therefore, as the target distance from the LiDAR system increases, the count associated with the beat frequency of the pulse signal 385 can be larger. Thus, according to some embodiments, a reference target at a reference distance associated with the reference count can be used to calculate the depth information associated with the target.

[0079] For example, a reference PLL block 390r (e.g., in conjunction with a reference counter block 395r) can be used to count the frequency of a reference target (e.g., the frequency of a pulse signal associated with a reference target at a reference distance), and the count can be sent as a reference count signal 387b to the depth / velocity block 375. For example, the reference PLL block 390r can amplify the reference PLL signal to generate a reference signal having a reference frequency (e.g., the reference target frequency) corresponding to the reference distance. The reference counter block 395r can count the number of pulses of the reference signal during the time period of receiving the reference signal and generating reference counter data (e.g., reference count signal 387b). Thereafter, the depth information associated with the target can be calculated as shown in Equation 1 below.

[0080] Equation 1

[0081] D = RD × CNT_i / CNT_r

[0082] Where D is the calculated distance to the target, RD is the reference distance to the reference target, CNT_i is the count associated with the distance to the target determined by the main PLL block 390i and / or the main counter block 395i (e.g., count signal 387a), and CNT_r is the count associated with the reference distance to the reference target determined by the reference PLL block 390r and / or the reference counter block 395r (e.g., reference count signal 387b).

[0083] Therefore, the resolution, accuracy, and noise of the readout architecture 300 can depend on the speed of the main PLL block 390i and the length of the counting time, where a longer counting time enables the readout architecture to be more accurate and have a higher resolution.

[0084] Furthermore, a single frame memory 360 can be used to calculate velocity information. For example, a depth / velocity block 375 can transmit depth information in a signal transmitted to the frame memory 360. The frame memory 360 can then store the depth information, and subsequently use the depth information corresponding to the distance to the target at a first time, new depth information corresponding to the distance to the target at a second time, and the time difference between the first and second times to calculate the velocity of the target. The stored depth information and / or the calculated velocity can be transmitted to the ROIC (e.g., ROIC 350) via a signal (e.g., I2C). It should be noted that the main PLL block 390i, the reference PLL block 390r, the main counter block 395i, the reference counter block 395r, the depth / velocity block 375, and / or the frame memory 360 can be implemented by an ALU, but this disclosure is not limited thereto.

[0085] For example, the velocity information associated with the target can be calculated as shown in Equation 2 below.

[0086] Equation 2

[0087] V = avg[(distance_i+1–distance_i) / tunit] or when tunit equals 1 second, V = avg(distance_i+1–distance_i).

[0088] Where V is the velocity, distance_i is the distance of the target at the first time, distance_i+1 is the distance of the target at the second time, "tunit" depends on the linear frequency modulation timing of the linear frequency modulation signal corresponding to the input beam, "tunit" is the time difference between the first and second times, and avg represents the average value.

[0089] Figure 4 Examples of various signals of the simulated ROIC corresponding to targets at different distances are shown in some embodiments of this disclosure.

[0090] Reference Figure 4 ROIC can correspond to Figure 3 The ROIC 350. For example, sending a Tx linear frequency modulated signal 425 can correspond to the output beam (e.g., Figure 1The output beam 125) signal. As indicated by the counter, the Tx linear frequency modulated signal 425 may have a frequency of about 2 microseconds, but this disclosure is not limited thereto. Therefore, the main PLL block 390i and / or the main counter block 395i can generate a first signal 487a1 corresponding to a first target distance of 150 meters, and can generate a second signal 487a2 corresponding to a second target distance of 15 meters, while the reference PLL block 390r and / or the reference counter block 395r can generate a reference signal 487b corresponding to a reference distance to a reference target. Figure 4 As shown, the count value corresponding to the first signal 487a1 can be approximately 3510, the count value corresponding to the second signal 487a2 can be approximately 130, and the count value of the reference signal 487b can be approximately 352.

[0091] Figure 5 A flowchart illustrating a method for determining the distance of a target from a LiDAR system according to some embodiments of the present disclosure is shown.

[0092] Reference Figure 5 In S501, LiDAR systems (e.g., Figure 1 The LiDAR system 100 can receive signals from targets (e.g., Figure 1 The waveform signal corresponding to target 130). For example, Figure 3 The balanced PIN PD 340 shown can receive waveform signals. According to some embodiments, a LiDAR system can receive waveform signals by generating a beam toward a target to cause the target to scatter the beam (e.g., by using...). Figure 1 The light source 110 and scanner 120 generate an output beam 125, and receive the scattered beam as a waveform signal corresponding to the target (e.g., by using...). Figure 1 The scanner 120, mirror 115 and receiver 140 receive the input beam 135 and the waveform signal from the output of the optical mixer (i.e. the output of the optical mixer).

[0093] In S502, the LiDAR system can generate pulse signals from the received waveform signals (e.g., such as...). Figure 3 As shown, TIA 365 and / or comparator 380 can generate pulse signals (385). For example, TIA 365 can convert a waveform signal into a voltage signal, and comparator 380 can convert a voltage signal into a pulse signal. Comparator 380 can compare the master signal with a reference signal. Optionally, comparator 380 can compare master counter data with reference counter data.

[0094] In the S503, the LiDAR system can reset the master counter and reference counter (e.g., Figure 3 The master counter block 395i and the reference counter block 395r can be reset.

[0095] In S504, the LiDAR system can begin main counting using the main counter and reference counting using the reference counter after a first time period has elapsed since the main counter and reference counter were reset. The first time period can correspond to the detection range.

[0096] In S505, the LiDAR system can continue master and reference counting in a second time period. This second time period can correspond to a flexible (e.g., predetermined or user-defined) programmed time period.

[0097] In S506, the LiDAR system can (e.g., by using...) Figure 3 The frame memory 360) holds the last master value of the master counter and the last reference value of the reference counter.

[0098] In the S507, the LiDAR system can (e.g., by using...) Figure 3 Calculate the ratio of the final master value to the final reference value for the depth and / or depth / velocity block 375.

[0099] In S508, the LiDAR system can (e.g., by using...) Figure 3 The depth and / or depth / velocity block 375) multiplies the reference distance by the ratio of the last master value to the last reference value.

[0100] According to some embodiments, in S509, the LiDAR system can (e.g., by using...) Figure 3 The depth and / or depth / velocity block 375 and frame memory 360 calculate velocity information by: receiving depth information, which includes first depth information calculated for a first memory frame and second depth information calculated for a second memory frame; calculating the depth difference corresponding to the difference between the first depth information and the second depth information; and dividing the depth difference by a time period corresponding to the time between the first memory frame and the second memory frame.

[0101] According to some embodiments, in S510, the LiDAR system can (e.g., by using...) Figure 3 The depth and / or depth / velocity block 375) calculates depth information by multiplying the reference distance by the ratio of the master count and the reference count.

[0102] The ROIC of various embodiments of this disclosure as described above (e.g., Figure 3The readout architecture 300 (ROIC 350) can be integrated with the OPLL on the same die. Therefore, the size of the LiDAR system employing the ROIC of the disclosed embodiments can be reduced. Furthermore, the ROIC of the disclosed embodiments enables the readout architecture to achieve ultra-low power, high-speed operation, and can extract depth and velocity information without unacceptable system latency. Additionally, the use of relatively complex FFT blocks (e.g., using one or more relatively simple counters) can be omitted while using relatively simple FFT blocks. Figure 2 The depth information is obtained by using the FFT block 280 of the ROIC 250. The readout architecture of the disclosed embodiments is also capable of calculating velocity information by using one or more relatively simple counters and a relatively small frame memory, which can store depth information and determine the difference in depth between two frames to determine both velocity information.

[0103] Therefore, embodiments of this disclosure provide readout architectures for use with LiDAR systems to improve the size, speed, and accuracy of LiDAR systems.

[0104] While this disclosure has been specifically shown and described with reference to some exemplary embodiments thereof, those skilled in the art will understand that various changes in form and detail may be made therein without departing from the spirit and scope of this disclosure as set forth in the appended claims and their equivalents.

Claims

1. A readout integrated circuit of a frequency modulated continuous wave lidar system, comprising: a balanced PIN photodiode configured to receive an optical signal and convert the optical signal to a current signal; an optical mixer configured to receive the current signal from the balanced PIN photodiode and convert the current signal to a mixed signal of a high frequency and a low frequency; a transimpedance amplifier configured to receive the converted current signal from the optical mixer and convert the converted current signal to a voltage signal, the voltage signal comprising a low frequency sinusoidal waveform after the high frequency is filtered out; a comparator configured to receive the voltage signal from the transimpedance amplifier and generate a pulse signal from the voltage signal; a master counter configured to receive a master signal corresponding to the pulse signal generated by the comparator and count a number of pulses of the master signal during a certain time period to generate master counter data; a reference counter configured to receive a reference signal having a reference frequency corresponding to a reference distance and count a number of pulses of the reference signal during a reference time period to generate reference counter data; and an arithmetic logic unit configured to receive the master counter data and the reference counter data and calculate depth information corresponding to a distance of a target by multiplying the reference distance with a ratio of the master counter data and the reference counter data.

2. The readout integrated circuit of claim 1, further comprising: a master phase-locked loop configured to receive the pulse signal from the comparator and multiply a frequency of the pulse signal to generate the master signal; and a reference phase-locked loop configured to amplify a reference phase-locked loop signal to generate the reference signal. The comparator is further configured to compare the master signal with the reference signal.

4. The readout integrated circuit of any one of claims 1 to 3, further comprising a frame memory configured to:

3. The readout integrated circuit of claim 2, wherein, receive the master counter data; receive the depth information from the arithmetic logic unit; and store the depth information. The arithmetic logic unit is further configured to calculate velocity information by: receiving the depth information from the frame memory, the depth information comprising first depth information calculated for a first memory frame and second depth information calculated for a second memory frame; 5. The readout integrated circuit according to claim 4, wherein, calculating a difference in depth corresponding to a difference between the first depth information and the second depth information; and dividing the difference in depth by a time period corresponding to a time between the first memory frame and the second memory frame. The comparator is further configured to compare the master counter data with the reference counter data. ​ ​ 6. The readout integrated circuit of claim 1, wherein, ​

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