Technique for compensating Doppler broadening by a mirror in a coherent LIDAR system using matched filtering

Abstract

A LiDAR system samples a received signal including a first frequency waveform and converts the received signal to the frequency domain. A matched filter is selected that includes a second frequency waveform having a set of coefficients that matches the first frequency waveform. The set of coefficients is updated according to a set of indices. The received signal is filtered with the matched filter to generate a filtered received signal. Range information and velocity information are extracted from the filtered received signal.

Description

Technical Field

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 093,599, filed Oct. 19, 2020, and U.S. Patent Application No. 17 / 354,324, filed Jun. 22, 2021, under 35 U.S.C. § 119(e), the entire contents of which are incorporated herein by reference.

[0002] The present disclosure generally relates to optical detection and ranging (LIDAR) systems, and for example, to techniques for compensating for Doppler spread by mirrors in coherent LIDAR systems.

Summary of the Invention

Problems to be Solved by the Invention

[0003] Conventional frequency-modulated continuous-wave (FMCW) LIDAR systems have phase impairments such as laser phase noise, circuit phase noise, flicker noise emitted by laser drive electronics, temperature / weather drift, and chirp plate offset. Scanning FMCW LIDAR systems may use a moving scanning mirror to steer the optical beam and scan the target or target environment. To achieve a wide field of view and high frame rate, the scanning mirror has a high angular velocity. The high mirror angular velocity may cause several impairments. For example, the Doppler shift due to the mirror may widen the bandwidth of the received signal. The received signal strength may decrease, and as a result, the detection probability may decrease. Therefore, ranging, velocity, and reflectivity measurement errors may increase.

Means for Solving the Problems

[0004] The present disclosure describes various examples related to methods of processing received signals in LIDAR systems, without limitation.

[0005] In some examples, disclosed herein is, for example, a method of processing a received signal by a matched filter to compensate for Doppler spread by a mirror. The received signal is filtered by a matched filter based on the expected shape or waveform of the received signal. For example, the received signal in the frequency domain (or "input spectrum") is filtered by a matched filter aimed at matching the power spectral density (PSD) of the expected received signal. The filter coefficients may be constant (e.g., obtained from theoretical simulations or modeling), or may be updated according to major factors such as the angular velocity of the mirror, the position of the mirror, the geometry of the scanner, the target, the scene, etc. In this method, detection is performed at the point where the SNR is maximized, enabling more accurate frequency and energy measurements.

[0006] In some examples herein, a method in a LIDAR system is disclosed. Sample a received signal in a LIDAR system and convert the received signal including a first frequency waveform into the frequency domain. Select a matched filter including a second frequency waveform having a series of coefficients that match the first frequency waveform; update the series of coefficients according to a series of indicators; filter the received signal by the matched filter to generate a filtered received signal; and further extract distance information and velocity information from the filtered received signal.

[0007] In some examples herein, a LIDAR system is disclosed. A LIDAR system includes a memory and a processing device or processor operably connected to the memory. The processing device or processor samples a received signal in the LIDAR system and converts the received signal including a first frequency waveform into the frequency domain. The processing device or processor further selects a matched filter including a second frequency waveform having a series of coefficients that match the first frequency waveform. The processing device or processor further updates a series of coefficients according to a series of indicators, filters the received signal by the matched filter, and generates a filtered received signal. The processing device or processor further extracts distance information and velocity information from the filtered received signal.

[0008] In some examples of this specification, a non-transitory machine-readable medium is disclosed. The non-transitory machine-readable medium has instructions stored therein, and when these instructions are executed by a processing device or processor of a light detection and ranging (LIDAR) system, the processing device or processor is caused to sample a received signal in the LIDAR system and convert the received signal including a first frequency waveform into the frequency domain. The processing device or processor further selects a matched filter including a second frequency waveform having a series of coefficients that match the first frequency waveform. The processing device or processor further updates the series of coefficients according to a series of indicators and filters the received signal by the matched filter to generate a filtered received signal. The processing device or processor further extracts distance information and velocity information from the filtered received signal.

[0009] These and other aspects of the disclosure will become apparent from the following detailed description when read in conjunction with the accompanying drawings, which are briefly described below. The disclosure includes any combination of two, three, four, or more features or elements, whether or not the features or elements specified in the disclosure are explicitly combined or otherwise described in the specific exemplary implementations described herein. The disclosure is intended to be read as a whole, and in any aspect or example of the disclosure, separable features or elements should be considered combinable unless the context of the disclosure clearly indicates otherwise.

[0010] Accordingly, it is to be understood that the summary is provided to summarize some examples and to provide a basic understanding of some aspects of the disclosure, and is provided without limiting or narrowing the scope or spirit of the disclosure. Other examples, aspects, and advantages will become apparent from the following detailed description when considered in conjunction with the accompanying drawings that illustrate the principles of the described embodiments.

Brief Description of the Drawings

[0011] To clarify the various aspects of the present invention, the drawings referred to in the following detailed description (embodiments) are shown. The same reference numerals in the drawings denote the same elements.

[0012]

Figure 1A

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Figure 1B

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Figure 2

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Figure 3A

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Figure 3B

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DETAILED DESCRIPTION OF THE INVENTION

[0020] Various embodiments and aspects of the present disclosure will be described with reference to the following detailed description, and various embodiments will be described with the accompanying drawings. The following description and drawings are illustrative of the present disclosure and should not be construed as limiting the present disclosure. A number of specific details are described to provide a complete understanding of the various embodiments of the present disclosure. However, in some cases, well-known or conventional content is not described in order to provide a concise consideration of the embodiments of the present disclosure.

[0021] The LIDAR system described herein can be implemented in any sensing market such as transportation, manufacturing, measurement, medical, virtual reality, augmented reality, and security systems, but is not limited thereto. According to some embodiments, the above-described LIDAR system is implemented as part of an automatic driving assistance system or the front end of a frequency-modulated continuous wave (FMCW) device that assists in spatial recognition of an autonomous vehicle.

[0022] FIG. 1 shows a LIDAR system 100 according to an exemplary embodiment of the present disclosure. The LIDAR system 100 includes any one or more of a number of components, but may include fewer components or additional components than shown in FIG. 1. According to some embodiments, one or more of the components described herein with respect to the LIDAR system 100 can be implemented on a photonics chip. The optical circuit 101 includes a combination of active optical components and passive optical components. In some examples, the active optical components have optical beams of different wavelengths and include one or more optical amplifiers, one or more photodetectors, and the like.

[0023] The free space optics 115 includes one or more optical waveguides for transmitting an optical signal and routing the optical signal to appropriate input / output ports of the active optical circuit for operation. The free space optics 115 includes one or more optical components such as taps, wavelength division multiplexers (WDMs), splitters / combiners, polarization beam splitters (PBSs), collimators, couplers, and the like. In one aspect, the free space optics 115 includes components for converting the polarization state and guiding the received polarization to a photodetector, for example, using a PBS. The free space optics 115 may further include a diffraction element for deflecting optical beams having different frequencies at different angles.

[0024] The LIDAR system 100 of this embodiment includes an optical scanner 102 having one or more scanning mirrors. These scanning mirrors are rotatable along an axis (e.g., the slow axis) that is orthogonal or substantially orthogonal to the fast axis of the diffraction element in order to direct an optical signal that scans the environment according to a scanning pattern. For example, the scanning mirror is rotatable by one or more galvanometers. Objects within the target environment may scatter the incident light into a return light beam or a target return signal. Also, the optical scanner 102 may collect the return light beam or the target return signal, which may be returned to the optical circuit components of the optical circuit 101. For example, the return light beam is directed towards a photodetector by a polarization beam splitter. Note that the optical scanner 102 may include, in addition to mirrors and galvanometers, a quarter-wave plate, a lens, an anti-reflection coated optical window, and the like.

[0025] The LIDAR system 100 is provided with a LIDAR control device 110 to control and support the optical circuit 101 and the optical scanner 102. The LIDAR control device 110 includes a processing device necessary for the LIDAR system 100. In one aspect, the processing device is one or more general-purpose processing devices such as a microprocessor or a central processing unit. More specifically, it is a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, or a processor implementing another instruction set, or a processor implementing a combination of instruction sets. Further, the above processing device may be one or more special-purpose processing devices such as an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), or a network processor.

[0026] In one aspect, the LIDAR control device 110 is provided with a signal processing unit 112 such as a digital signal processor (DSP). Thereby, the LIDAR control device 110 outputs a digital control signal for controlling the optical driver 103. The digital control signal is converted into an analog signal via the signal conversion unit 106. For example, the signal conversion unit 106 includes a digital / analog converter. The optical driver 103 supplies a drive signal to the active optical components of the optical circuit 101 and drives light sources such as lasers and amplifiers. In one aspect, a plurality of optical drivers 103 and signal conversion units 106 may be provided to drive a plurality of light sources.

[0027] The LIDAR control device 110 is also configured to output a digital control signal to the optical scanner 102. The motion control device 105 can control the galvanometer of the optical scanner 102 based on the control signal received from the LIDAR control device 110. Specifically, using a digital / analog converter, the coordinate routing information from the LIDAR control device 110 can be converted into a signal processable by the galvanometer of the optical scanner 102. In one aspect, the motion control device 105 can also send back to the LIDAR control device 110 information regarding the position or operation of the components of the optical scanner 102. Specifically, using an analog / digital converter, the information regarding the position of the galvanometer can be sequentially converted into a signal processable by the LIDAR control device 110.

[0028] The LIDAR control device 110 is further configured to analyze the input digital signal. In this regard, the LIDAR system 100 is provided with a photoreceiver 104 for measuring one or more beams received by the optical circuit 101. Specifically, the reference beam receiver as the photoreceiver 104 measures the amplitude of the reference beam from the active optical component, and an analog / digital converter converts the signal from the reference beam receiver into a signal processable by the LIDAR control device 110. Also, the target receiver as the optical receiver 104 measures an optical signal that carries information regarding the distance and velocity of a target in the form of a beat frequency modulated optical signal. In this case, the reflected beam of the optical signal may be mixed with a signal from a local oscillator. The optical receiver 104 can be provided with a high-speed analog / digital converter that converts a signal from the target receiver into a signal processable by the LIDAR control device 110. In one aspect, the signal from the optical receiver 104 can be subject to signal conditioning by the signal conditioning unit 107 before being received by the LIDAR control device 110. For example, the signal from the optical receiver 104 may be supplied to an operational amplifier of the signal conditioning unit 107 for amplification of the return signal, and the signal amplified by the operational amplifier may be supplied to the LIDAR control device 110.

[0029] In some applications, the LIDAR system 100 can additionally be provided with one or more imaging devices 108 configured to capture an image of the environment, a global positioning system (GPS) 109 configured to provide the geographical location of the system, or other sensor inputs. Also, the LIDAR system 100 can be provided with an image processing device 114. In this case, the image processing device 114 can be configured to receive an image and a geographical location from the imaging device 108 and the global positioning system (GPS) 109, and transmit the image and the location or information related thereto to the LIDAR control device 110 or other systems connected to the LIDAR system 100.

[0030] In the operation according to some embodiments, the LIDAR system 100 is configured to simultaneously measure distance and velocity in two dimensions using a non-degenerate optical light source. This function enables real-time long-range measurement of the distance, velocity, azimuth angle, and elevation angle of the surrounding environment.

[0031] In some examples, the scan process is initiated from the optical driver 103 and the LIDAR control device 110. The LIDAR control device 110 instructs the optical driver 103 to modulate one or more light beams respectively, and these modulation signals are transmitted through the passive optical circuit of the optical circuit 101 to the collimator of the free space optical system 115. The collimator guides the modulation signals to the optical scanner 102, and the optical scanner 102 scans the environment in a predefined pattern defined by the motion control device 105. The optical circuit 101 may be provided with a polarization wavelength plate (PWP) that converts the polarization state of light when the light exits the optical circuit 101. In one aspect, the polarization wavelength plate may be a quarter-wave plate or a half-wave plate. A part of the polarized light beam may be reflected back to the optical circuit 101. For example, the lens system or collimation system used in the LIDAR system 100 may have natural reflection characteristics or a reflective coating, whereby a part of the light beam is reflected back to the optical circuit 101.

[0032] The optical signal reflected from the environment is sent through the optical circuit 101 to the receiver (optical receiver 104). At this time, since the polarization state of the light has been converted, it is reflected by the polarization beam splitter together with a part of the polarized light reflected back to the optical circuit 101. As a result, the reflected optical signal does not return to the same optical fiber or waveguide as the light source, but is reflected to different optical receivers respectively. These signals interfere with each other to generate a synthesized signal. Each beam signal returning from the target generates a time-shifted waveform, and the beat frequency measured by the optical receiver (photodetector) is generated by the time phase difference between these two waveforms. Then, the synthesized signal can be reflected to the optical receiver 104.

[0033] The analog signal received by the optical receiver 104 is converted into a digital signal by an ADC (analog / digital converter). Next, the digital signal is transmitted to the LIDAR control device 110. The signal processing unit 112 of the device receives the digital signals and processes them. In one aspect, the signal processing unit 112 receives position data from the motion control device 105 and a galvanometer (not shown), and receives image data from the image processing device 114. Thereby, the signal processing unit 112 can generate a 3D point cloud having information on the distance and speed of points in the environment when the optical scanner 102 scans additional points. The signal processing unit 112 may also superimpose the 3D point cloud on the image data to determine the speed and distance of surrounding objects. This system may further process satellite-based navigation position data to provide accurate global position information.

[0034] FIG. 1B is a block diagram showing an example of a matched filtering module 130 of a LIDAR system according to an embodiment of the present disclosure. Referring to FIGS. 1A and 1B, the signal processing unit 112 includes a matched filtering module 130. Although the matched filtering module is depicted as being present within the signal processing unit 112, it should be noted that the embodiments of the present disclosure are not so limited. For example, in one embodiment, the matched filtering module 130 may be present in a computer memory (e.g., RAM, ROM, flash memory, etc.) within the system 100 (e.g., the LIDAR control system 110). Scanning FMCW LIDAR system 100 uses a moving scanning mirror (e.g., included in optical scanner 102) to steer the optical beam and scan the target or target environment. Objects within the target environment scatter the incident light into a return optical beam or target return signal. Optical scanner 102 collects the return optical beam or target return signal. The target return signal is mixed with a second signal from a local oscillator to generate a beat frequency that is distance-dependent. The beat frequency measured by the optical receiver (photodetector) is generated by the temporal phase difference between the two waveforms. In one embodiment, the beat frequency is digitized by an analog-to-digital converter (ADC) within a signal conditioning unit such as signal conditioning unit 107 of LIDAR system 100. In one embodiment, the digitized beat frequency signal is received by signal processing unit 112 of LIDAR system 100 and then digitally processed in signal processing unit 112. Signal processing unit 112, which includes a matched filtering module 130, processes the received signal to extract target distance information and velocity information.

[0035] Matched filtering module 130 includes, but is not limited to, a sampling module 121, a conversion module 122, a selection module 123, a coefficient module 124, and a filtering module 125. In some embodiments, matched filtering module 130 receives signals from optical receiver 104 or signal conditioning unit 107. Sampling module 121 is configured to sample the received signal in the LIDAR system. Conversion module 122 is configured to convert the received signal into the frequency domain, where the received signal has a first frequency waveform. Selection module 123 is configured to select a matched filter, which includes a second frequency waveform having a series of coefficients for matching the first frequency waveform. The second frequency waveform has the expected first frequency waveform of the received signal. For example, the received signal is a beat frequency generated from the mixing of a target return signal and a local oscillator signal, and the second frequency waveform is determined based on a simulation (model) or measurement result of the received signal. The coefficient module 124 is configured to update a series of coefficients based on a series of indicators. The filtering module 125 is configured to filter the received signal by a matched filter and generate a filtered received signal. The signal processing unit is configured to extract target distance information and velocity information from the filtered received signal. The matched filtering module 130 may include other modules. Some or all of the modules 121 - 125 are implemented by software, hardware, or a combination thereof. For example, these modules are loaded into memory and executed by one or more processors. Some of the modules 121 - 125 may be integrated together as an integrated module.

[0036] FIG. 2 is a time - frequency diagram 200 of an FMCW scanning signal 201 that can be used for a LIDAR system, such as the LIDAR system 100, to scan a target environment in one embodiment. In this example, the FMCW scanning signal 201 labeled as f FM (t) is a sawtooth waveform (sawtooth "chirp") having a chirp bandwidth Δf C and a chirp period T C . The slope of the sawtooth is k = (Δf C / T C ). FIG. 2 also shows a target return signal 202 in one embodiment. f FM(The target return signal 202, indicated by (t - Δt), is a time-delayed version of the FMCW scanning signal 201, where Δt is the round-trip time between the target irradiated by the FMCW scanning signal 201. This round-trip time is given by Δt = 2R / v. Here, R is the distance to the target, and v is the speed of light c, the speed of the light beam. Therefore, the distance R to the same target can be calculated as R = c(Δt / 2). When the target return signal 202 is optically mixed with the FMCW scanning signal, a distance-dependent difference frequency (the "beat frequency") Δf R (t) is generated. The beat frequency Δf R (t) is linearly related to the time delay Δt by the slope k of the sawtooth. That is, ΔfR(t) = kΔt. Since the distance R to the target is proportional to Δt, the distance R to the target can be calculated as R = (c / 2)(Δf R (t) / k). That is, the distance R is linearly related to the beat frequency Δf R (t). The beat frequency Δf R (t) is generated, for example, as an analog signal by the optical receiver 104 of the LIDAR system 100. This beat frequency is digitized, for example, by an analog-to-digital converter (ADC) within the signal conditioning unit 107 of the LIDAR system 100. The beat frequency signal digitized in this way is digitally processed by a signal processing unit (e.g., signal processing unit 112) within the LIDAR system 100. Note, however, that if the target has a relative velocity with respect to the LIDAR system 100, the target return signal 202 generally includes a frequency offset (Doppler shift). Since the Doppler shift is detected separately and used to correct the frequency of the return signal, the Doppler shift is not shown in Figure 2 for simplicity and ease of explanation. Also, it should be noted that the sampling frequency of the ADC is determined to be the highest beat frequency that can be processed by the system without generating aliasing. Generally, the highest frequency that can be processed is half of the sampling frequency (i.e., the "Nyquist limit"). For example, but not limited to, when the sampling frequency of the ADC is 1 gigahertz, the highest beat frequency (Δf Rmax ) that can be processed without aliasing is 500 megahertz. This limit is determined by the maximum target distance R max =(c / 2)(Δf Rmax / k) and can be adjusted by changing the slope k of the sawtooth. In one example, the data samples from the ADC may be continuous, but the subsequent digital processing described later can be divided into "time segments" that can be associated with a predetermined periodicity of the LIDAR system 100. For example, but not limited to, the time segment corresponds to the number of chirp periods T C or the number of rotations in the azimuth direction by the aforementioned optical scanner.

[0037] FIG. 3A is a diagram 300a showing an example of the received signal power spectral density (PSD) when the scanning mirror is slow in the LIDAR system. FIG. 3B is a diagram showing an example of the received signal power spectral density (PSD) when the scanning mirror is fast in the LIDAR system. A scanning LIDAR system (e.g., FMCW LIDAR) uses a moving scanning mirror to steer the optical beam and scan the target or target environment. To achieve a wide field of view and a high frame rate, the scanning mirror has a high angular velocity. In some situations, the high mirror angular velocity may cause some obstacles. For example, the Doppler shift caused by the mirror may increase the bandwidth of the received signal. Therefore, in these situations, the received signal strength may decrease, resulting in a decrease in the detection probability and an increase in errors related to distance, speed, and reflectivity measurements.

[0038] Referring to FIGS. 3A and 3B, a moving scanning mirror (e.g., the scanning mirror included as part of the system 100 of FIG. 1) induces a Doppler shift in the outgoing and incoming light beams, which may result in a target return signal. As depicted in FIG. 3A, when the scanning mirror is moving at a low mirror speed (e.g., <5kdeg / s), the Doppler due to the mirror has little impact on the signal quality. The peak value 302a is detected in the PSD 301a of the received signal. The received signal may have a random realization value 305a, which is relatively small. The received signal has an appropriate range of frequency measurement error 303a and an appropriate range of power measurement error 304a.

[0039] As depicted in FIG. 3B, when the scanning mirror is moving at a high mirror speed (>5kdeg / s), there is a significant spread in the signal power spectral density (PSD) 301b. As a result, the energy of the measured signal may be on average lower. Therefore, there is a possibility that the detection probability may consequently decrease. The measurement error of the frequency 303b and / or the measurement error of the energy 304b may increase due to the randomness of the signal (e.g., the random realization value 305b).

[0040] FIG. 4 is a diagram 400 illustrating an example of a matched filter of a LIDAR system according to an embodiment of the present disclosure. Embodiments of the present disclosure provide a plurality of approaches to counteract Doppler spread due to the mirror. For example, in embodiments of the present disclosure, techniques in the frequency domain or techniques in the time domain can be employed. As one approach in the frequency domain technique, there is matched filtering in the frequency domain. In this approach, the received signal is filtered by a matched filter in the frequency domain, and the matched filter includes the shape or waveform of the received signal expected in the frequency domain. The frequency waveform of the expected received signal is determined based on a theoretical model, simulation, or measurements from predetermined conditions (e.g., conditions determined in a laboratory environment or a test environment, artificial intelligence,... etc.).

[0041] Referring to FIG. 4, a received signal 401 in the frequency domain, for example an input spectrum, is input to a matched filter 402. The received signal 401 may include a first frequency waveform that may be an unknown waveform, for example at the start of a matched filtering process. The matched filter 402 can include a second frequency waveform that may be the frequency waveform of the expected received signal. In some embodiments, the second frequency waveform has a series of coefficients for matching or approximating the first frequency waveform. In some embodiments, the second frequency waveform is an expected value, an estimated value, or an approximate value of the first frequency waveform determined based on a theoretical model or experimental measurement. In some embodiments, the second frequency waveform is determined based on a model or simulation or measurement of a LIDAR system, for example, an optical subsystem of a LIDAR system.

[0042] In one embodiment, the second frequency waveform is based on an estimated value of the power spectral density (PSD) function of the received signal. For example, the matched filter 402 includes the expected received signal PSD. The matched filter 402 is configured to compare the expected received signal PSD with the first frequency waveform to determine if they match.

[0043] In one embodiment, the filter coefficients 403 of the matched filter 402 are constant. For example, the filter coefficients 403 can be derived from theoretical simulations and modeling.

[0044] In one embodiment, the filter coefficients 403 are updated according to a series of indicators. For example, the filter coefficient 403 is updated according to major factors such as the angular velocity of the scanning mirror, the position of the scanning mirror, the geometry of the optical scanner, the size of the scanning mirror, the beam diameter, or the target. A series of indicators includes the angular velocity of the scanning mirror, the position of the scanning mirror, the geometry of the optical scanner, the size of the scanning mirror, the beam diameter, or the target. For example, the filter coefficient 403 is adapted or adjusted to better match the received signal. For example, the filter coefficient 403 is first determined from theoretical simulations or modeling and then dynamically updated or adapted based on factors such as the angular velocity of the scanning mirror, the position of the scanning mirror, the geometry of the optical scanner, or the target. For example, when the angular velocity of the scanning mirror increases, the filter coefficient 403 is updated to widen the bandwidth of the matched filter.

[0045] In one embodiment, the matched filter coefficient 403 is updated such that the matched filter bandwidth is proportional to the angular velocity of the scanning mirror, the size of the scanning mirror, and / or the beam diameter.

[0046] In one embodiment, a series of coefficients is updated based on changes in the hardware configuration or system operation. For example, update a series of coefficients based on an increase in mirror angular velocity or a change in the scan pattern.

[0047] In one embodiment, the filter coefficient 403 may be updated continuously, for example, every 1 millisecond, 1 second, 15 seconds, 30 seconds, or any value in between. As another example, update the filter coefficient 403 when a change is detected in factors such as the angular velocity of the scanning mirror, the position of the scanning mirror, the geometry of the optical scanner, or the target.

[0048] According to some embodiments, the matched filter 402 is configured based on the convolution of waveforms. For example, in certain situations, the matched filter 402 is configured to compare a received signal (e.g., a first frequency waveform) with an expected received signal (e.g., a second frequency waveform) to determine similarities therebetween. As an example, the matched filter 402 is configured to calculate the cross-correlation between the received signal PSD and the expected received signal PSD. For example, the maximum correlation value represents the peak value of the received signal.

[0049] If the second frequency waveform (known waveform) used for filtering is the complex conjugate of the received signal waveform which is an unknown waveform, the signal-to-noise ratio (SNR) and the detection probability are maximized by the matched filter 402. In one embodiment, the filtered received signal is input into a peak selection process to extract distance information and velocity information. A peak value search 404 is performed to detect the peak value from the received signal. Next, the target's distance information and velocity information are extracted based on the peak value in the received signal. Since detection 405 occurs at the point where the SNR is maximized, the method can provide more accurate frequency and energy measurements, thereby improving the accuracy in measuring the target's distance and velocity.

[0050] FIG. 5 is a diagram for explaining an example of a matched filter waveform according to an embodiment of the present disclosure. Different matched filter waveforms (e.g., the second frequency waveform) may be selected based on theoretical simulations or modeling, or may be selected empirically. As an example, the matched filter may include a Gaussian waveform 501. Here, M(f)=exp(-0.5(f / B) 2) is obtained. Here, B determines the filter bandwidth. As another example, the matched filter may include a sinc waveform 502. Here, M(f) = sinc(f / B) (where |f| ≤ B). Otherwise, M(f) = 0. Here, B determines the filter bandwidth. As yet another example, the matched filter may include a sinc-squared waveform 503. Here, M(f) = sinc 2 (f / B) (where |f| ≤ B). Otherwise, M(f) = 0. Here, B determines the filter bandwidth. As yet another example, the matched filter may include a rectangular waveform 504. Here, M(f) = 1 (where |f| ≤ B). Otherwise, M(f) = 0. Here, B determines the filter bandwidth. The above examples of the matched filter can be defined by the parameter B that determines the filter bandwidth. In one embodiment, the filter bandwidth is directly proportional to the angular velocity of the scanning mirror. The above examples of the matched filter are for illustrative purposes only, and there may be various other waveforms of the matched filter.

[0051] To implement in digital signal processing, discrete-frequency filter coefficients can be obtained by sampling continuous-frequency waveforms (e.g., 501 - 504).

[0052] FIG. 6 is a flowchart showing an example of a process 600 for processing a received signal in a LIDAR system according to an embodiment of the present disclosure. Process 600 is executed by processing logic including software, hardware, or a combination thereof. The software may be stored in a non-transitory machine-readable storage medium (e.g., on a memory device). For example, process 600 may be executed by a matched filtering module 130 within a signal processing unit 112 of a LIDAR system 100 as shown in FIGS. 1A - 1B. By this process, more accurate frequency and energy measurements are achieved, thereby improving the accuracy in measuring the distance and velocity of a target.

[0053] In block 601, the received signal is sampled by the LIDAR system and the received signal is converted to the frequency domain. Here, the received signal includes a first frequency waveform.

[0054] In block 602, a matched filter is selected. The matched filter includes a second frequency waveform having a series of coefficients that match the first frequency waveform. In one embodiment, the second frequency waveform is determined based on a model or simulation or measurement of the optical subsystem of the LIDAR system. In one embodiment, the second frequency waveform is determined based on an estimated value of the PSD of the received signal.

[0055] In one embodiment, selecting the matched filter includes selecting a rectangular waveform, a sinc waveform, a sinc-squared waveform, or a Gaussian waveform as the second frequency waveform. In one embodiment, the matched filter is composed of at least one of a sinc waveform, a sinc-squared waveform, a Gaussian waveform, or a rectangular waveform.

[0056] In block 603, a series of coefficients are updated according to a series of indicators. In one embodiment, the series of coefficients of the matched filter are updated according to at least one of the angular velocity of the scanning mirror, the position of the scanning mirror, the geometry of the optical scanner, or the target.

[0057] In one embodiment, the series of coefficients are updated such that the filter bandwidth is proportional to the angular velocity of the scanning mirror, the size of the scanning mirror, or the beam diameter. In one embodiment, the series of coefficients are updated based on changes in the hardware configuration or system operation including changes in the mirror angular velocity or the scan pattern.

[0058] In block 604, the received signal is filtered by the matched filter to generate a filtered received signal.

[0059] In block 605, distance information and velocity information are extracted from the filtered received signal. In one embodiment, the filtered received signal is input to a peak selection process to extract the distance information and velocity information. For example, the peak value of the filtered received signal is detected to extract the distance information and velocity information of the target.

[0060] In the foregoing description, for the sake of easy understanding of the embodiments of the present invention, a plurality of specific examples of specific systems, components, methods, etc. are shown. However, those skilled in the art can implement the present invention even without the description of these specific examples. Also, well-known components and methods may have their details omitted or may be shown in the form of simple block diagrams, which is for the purpose of facilitating the understanding of the present invention. Therefore, the disclosed content is merely illustrative, and even if one example is different from other examples, it is considered to be included within the scope of the present invention.

[0061] When the expressions "one embodiment" or "embodiments" are used in this specification, it means that the specific features, structures, or characteristics described in relation to those embodiments are included in at least one embodiment. Therefore, when the expressions "in one embodiment" or "in embodiments" appear in several places in this specification, they do not necessarily indicate the same embodiment.

[0062] Although the operations of the methods described herein are shown in a specific order, the order of operations of each method may be changed. Specific operations may be performed in reverse order, or at least some operations may be performed simultaneously with other operations. Instructions for different operations or auxiliary operations can be performed intermittently or alternately.

[0063] The description of the embodiments of the invention described above is not intended to be detailed and exhaustive, including the content described in the summary, nor is it limited to the disclosed specific forms. Specific embodiments and examples of the present invention are described herein for illustrative purposes, but various equivalent changes can be made within the scope recognized by those skilled in the art. The terms "example" or "exemplary" used herein are used to mean serving as an example, instance, or illustration. The aspects or designs described as "example" or "exemplification" in this specification should not necessarily be construed as more preferable or advantageous than other aspects or designs. Rather, the use of the terms "example" or "exemplification" is intended to represent the concept in a specific form. The term "or" used in this specification is intended to be construed as an inclusive "or" rather than an exclusive "or". That is, unless otherwise specified or clear from the context, the expression "X includes A or B" means any of the natural inclusive permutations. That is, when X includes A, when X includes B, or when X includes both A and B, in any of the aforementioned cases, the condition "X includes A or B" is satisfied. Furthermore, the articles "a" and "an" used in this specification and the appended claims are construed to mean "one or more" when the context does not clearly indicate the singular form, unless otherwise specified. Furthermore, when terms such as "first", "second", "third", "fourth" are used in this specification, these terms are used as identifiers for distinguishing different elements and do not necessarily indicate an order according to the numerical designation.

Claims

1. A method in a light detection and ranging (LiDAR) system (hereinafter referred to as a LiDAR system), comprising: sampling a received signal by the LiDAR system and converting the received signal including a first frequency waveform into a frequency domain; selecting a matched filter including a second frequency waveform having a filter coefficient including a filter bandwidth matching the first frequency waveform, the second frequency waveform being a sinc waveform, a sinc-squared waveform, a Gaussian waveform, or a rectangular waveform; updating the filter coefficient according to at least one of an angular velocity of a scanning mirror, a position of the scanning mirror, a geometry of an optical scanner, a size of the scanning mirror, a beam diameter, and a scanning pattern; filtering the received signal by the selected matched filter to generate a filtered received signal; further extracting distance information and velocity information from the received signal filtered by the matched filter; and a method including the above steps.

2. The method according to claim 1, wherein the filter coefficient is updated such that the filter bandwidth of the matched filter is proportional to at least one of the angular velocity of the scanning mirror, the size of the scanning mirror, or the beam diameter.

3. The method according to claim 1, wherein the second frequency waveform is determined based on an estimated value of a power spectral density function of the received signal.

4. The method according to claim 1, wherein the filter coefficient is updated based on a change in the angular velocity of the scanning mirror or a change in the scanning pattern.

5. The method according to claim 1, further comprising inputting the filtered received signal into a peak selection process to extract the distance information and the velocity information.

6. The method according to claim 1, wherein the second frequency waveform is determined based on a model or simulation or measurement of an optical subsystem of the LIDAR system. **Claim 7** An optical detection and ranging (LIDAR) system (hereinafter referred to as a LIDAR system), a memory, and a processor operably connected by the memory and executing the following, a LIDAR system comprising. Sampling a received signal in the LIDAR system and converting the received signal including a first frequency waveform into a frequency domain; Selecting a matched filter including a second frequency waveform having a filter coefficient including a filter bandwidth matching the first frequency waveform, the second frequency waveform being a sinc waveform, a sinc squared waveform, a Gaussian waveform or a rectangular waveform; Updating the filter coefficient according to at least one of an angular velocity of a scanning mirror, a position of the scanning mirror, a geometry of an optical scanner, a size of the scanning mirror, a beam diameter, and a scanning pattern; Filtering the received signal with the selected matched filter to generate a filtered received signal; Further, distance information and velocity information are extracted from the received signal filtered by the matched filter. **Claim 8** The LIDAR system according to claim 7, wherein the filter coefficient is updated such that the filter bandwidth of the matched filter is proportional to at least one of the angular velocity of the scanning mirror, the size of the scanning mirror, or the beam diameter. **Claim 9** The LIDAR system according to claim 7, wherein the second frequency waveform is determined based on an estimated value of a power spectral density function of the received signal. **Claim 10** The LIDAR system according to claim 7, wherein the filter coefficient is updated based on a change in the angular velocity of the scanning mirror or a change in the scan pattern.

11. The LIDAR system according to claim 7, wherein the processor operably coupled to the memory further includes inputting the filtered received signal into a peak selection process for extracting the distance information and the velocity information.

12. The LIDAR system according to claim 7, wherein the second frequency waveform is determined based on a model or simulation or measurement of an optical subsystem of the LIDAR system.

13. A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor of an optical detection and ranging (LIDAR) system (hereinafter referred to as the LIDAR system), cause the processor to perform the following. Sampling a received signal in the LIDAR system and converting the received signal including a first frequency waveform into a frequency domain; Selecting a matched filter including a second frequency waveform having a filter coefficient including a filter bandwidth matching the first frequency waveform, the second frequency waveform being a sinc waveform, a sinc-squared waveform, a Gaussian waveform, or a rectangular waveform; Updating the filter coefficient according to at least one of an angular velocity of a scanning mirror, a position of the scanning mirror, a geometry of an optical scanner, a size of the scanning mirror, a beam diameter, and a scanning pattern; Filtering the received signal by the selected matched filter to generate a filtered received signal; Further, extracting distance information and velocity information from the received signal filtered by the matched filter.

14. The non-transitory machine-readable medium according to claim 13, wherein the filter coefficient is updated such that the filter bandwidth of the matched filter is proportional to at least one of an angular velocity of the scanning mirror, a size of the scanning mirror, or a beam diameter.

15. The non - transitory machine - readable medium according to claim 13, wherein the second frequency waveform is determined based on an estimated value of the power spectral density function of the received signal. **Claim 16** The non - transitory machine - readable medium according to claim 13, wherein the filter coefficient is updated based on a change in the angular velocity of the scanning mirror or a change in the scan pattern. **Claim 17** The non - transitory machine - readable medium according to claim 13, wherein the processor operably connected to the memory further includes inputting the filtered received signal into a peak selection process for extracting the distance information and the velocity information. **Claim 18** The non - transitory machine - readable medium according to claim 13, wherein the second frequency waveform is determined based on a model or simulation or measurement of the optical subsystem of the LIDAR system.

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