Calibration method of time-of-flight ranging laser radar

Abstract

The invention discloses a calibration method of a time-of-flight ranging laser radar, which comprises the following steps of: calibrating a receiving end detector without a lens, irradiating by using uniform light with constant power, recording charge quantity code values under different modulation phases at fixed integral time, and completing calibration; thirdly, calibrating the laser radar module, namely adjusting a digital output result to be close to zero under a dark condition, ensuring that pixel outputs are consistent under the same light intensity, eliminating dead pixels, correcting lens distortion and determining a focusing distance; then, by moving the positions of the test card in two directions, adjusting the positions and gradients of the lens and the detector, and ensuring that the image definition is consistent and is positioned in the center of a field of view; in addition, Fourier series is used for fitting the error between the measured distance and the actual distance, and correction is carried out; and finally, second-order linear fitting is carried out on the measured distance and temperature data, and temperature correction is carried out according to a fitting curve, so that the distance measurement accuracy and stability of the laser radar module are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of laser radar, and in particular to a calibration method for a time-of-flight ranging laser radar. Background Art

[0002] i-ToF (Indirect Time-of-Flight) LiDAR, as a new generation of LiDAR technology, has a significantly different working principle from the 2D imaging system. It is a transceiver system that measures distance by emitting laser pulses and receiving the reflected signal. Due to this characteristic, the error source is not only limited to the transmitting end, but also to the receiving end. Therefore, in order to improve the precision and accuracy of ranging, in addition to the conventional camera internal parameters, external parameters and distortion calibration, it is also necessary to calibrate parameters such as ranging accuracy, ranging accuracy and temperature drift. At present, there are only calibration methods for parameter indicators, and the calibration process of dual-frequency all-solid-state i-ToF LiDAR is a complex and delicate process involving multiple steps and multiple aspects of calibration. Therefore, how to improve the ranging precision and accuracy of LiDAR through a complete set of calibration processes is a technical problem that needs to be solved urgently. Summary of the invention

[0003] In order to overcome the above-mentioned deficiencies in the prior art, the present invention provides a calibration method for a time-of-flight ranging laser radar, which can significantly improve ranging accuracy, optimize frequency selection, enhance system adaptability, and reduce testing costs.

[0004] The present invention is implemented by the following technical solutions:

[0005] A calibration method for a time-of-flight ranging laser radar, comprising:

[0006] Calibrate a receiving-end detector without a lens installed, illuminate the receiving-end detector with uniform light of constant power, obtain charge quantity code values ​​of the receiving-end detector at different modulation phases under a fixed integration time, and complete the calibration of the receiving-end detector according to the charge quantity code values ​​at different modulation phases;

[0007] Calibrate the laser radar module, make the digital output result of each pixel in the receiving end detector close to zero under the condition of no light, make the output of any two pixels in the receiving end detector consistent under the condition of the same incident light intensity, remove bad pixel pixels, import the lens distortion file to correct the lens distortion, move the position of the light diffuser from the lens to the pre-obtained focus position to ensure that the light diffuser is parallel to the optical platform and then output the focus distance of the laser radar module lens, move the test card in the first direction and the second direction respectively so that the rays of the test card in the third direction just pass through the center position of the laser radar module lens in the first direction and the second direction respectively, and then move the lens in the third direction to make the obtained image clear, adjust the position of the receiving end detector so that the image is in the center of the field of view, and adjust the inclination of the lens so that the image clarity at the four positions is consistent;

[0008] The error between the measured distance and the actual distance is fitted using the Fourier series, and the measured distance is corrected according to the function obtained by fitting;

[0009] A second-order linear fit is performed on the measured distance and temperature data, and the measured distance is temperature corrected according to a curve obtained by the fitting.

[0010] The charge quantity code values ​​under different modulation phases complete the calibration of the receiving end detector, including: obtaining the charge quantity code value curve of the same pixel under the different modulation phases within the fixed integration time; fitting the charge quantity code value curve through a first-order curve function so that the linear deviation between the first-order curve function and the charge quantity code value curve is minimized; traversing all pixels of the receiving end detector to obtain the fitting curve coefficients of all pixels.

[0011] The fitting curve coefficients include an equivalent conversion efficiency correction coefficient and a background noise voltage code value, wherein the equivalent conversion efficiency correction coefficient is a ratio of the mode of the equivalent conversion efficiency at different modulation phases at different integration times to the equivalent conversion efficiency at different modulation phases;

[0012] The equivalent conversion efficiency is the ratio of the actual charge quantity code obtained by irradiating the receiving end detector without the lens with uniform light through the integrating sphere under different modulation phases to the ideal photogenerated electron digital value;

[0013] The background noise voltage code value is the vertical axis intercept of the charge quantity code value curve.

[0014] The formula for the ideal photogenerated electron digital value is as follows:

[0015] Among them, P pixel_signal is the light power incident on the pixel, λ is the wavelength, c is the speed of light, h is Planck's constant, Tint is the integration time.

[0016] The method of removing bad pixels includes: collecting the charge quantity code values ​​output by all pixels of the receiving end detector in a light-free environment, and calculating the standard deviation and mean of the charge quantity code values, calculating the absolute value of the difference between the charge quantity code values ​​of all pixels and the mean, and judging whether the absolute value is greater than a preset threshold, wherein the preset threshold is a multiple of the standard deviation; if so, judging that the pixel is a bad pixel, and removing the pixel.

[0017] The test card is moved in the first direction and the second direction respectively so that the rays of the test card in the third direction just pass through the center positions of the laser radar module lens in the first direction and the second direction respectively, and then the lens is moved in the third direction to make the obtained image clear, and the position of the detector at the receiving end is adjusted so that the image is in the center position of the field of view, including: marking the center positions of the axes of the test card in the first direction, the second direction and the third direction through the rays of the third direction of the level, moving the axis of the first direction of the three-axis displacement stage so that the rays of the third direction just pass through the center position of the first direction axis of the lens, and fixing the position of the first direction axis of the three-axis displacement stage; marking the center position of the second direction axis of the test card through the rays of the third direction of the level, moving the second direction axis of the three-axis displacement stage so that the rays of the third direction just pass through the center position of the second direction axis of the lens, and fixing the position of the second direction axis of the three-axis displacement stage.

[0018] Adjusting the position of the receiving end detector so that the image is located at the center of the field of view includes: when the image is not located at the center of the field of view, moving the receiving end detector in the opposite direction of the image deviating from the center of the field of view.

[0019] The adjusting the inclination of the lens so that the image clarity at four positions is consistent includes: adjusting the rotation angle of the lens in the opposite direction of the image clarity direction.

[0020] The error between the measured distance and the actual distance is fitted using the Fourier series, and the measured distance is corrected according to the function obtained by fitting, including: setting the laser radar module to be measured and the reflectivity plate at a fixed distance, and calibrating the fixed distance;

[0021] Obtain two curves of ideal distance measurement and actual distance measurement at a first demodulation frequency, obtain an error curve between the ideal distance measurement and the actual distance measurement, and use Fourier series to fit the error curve at the first frequency;

[0022] According to the unambiguous distance formula of dual-frequency ranging, a second demodulation frequency that meets the conditions is selected, and two curves of ideal ranging and actual ranging are obtained at the second demodulation frequency, and an error curve between the ideal ranging and actual ranging is obtained. The error curve at the second frequency is fitted using Fourier series, and the second frequency corresponding to the minimum value of the peak value of the error curve after the error is eliminated is obtained as the second frequency of dual-frequency ranging.

[0023] A second-order linear fit is performed on the measured distance and temperature data, and the measured distance is temperature corrected according to the curve obtained by fitting, including: placing the laser radar module in an incubator with low-reflectivity baffles on all sides; adjusting the temperature of the incubator according to a preset temperature step to obtain a curve of the measured distance and temperature, and performing a second-order linear fit on the curve of the measured distance and temperature.

[0024] The present invention is directed to a dual-frequency ranging error calibration and compensation method for an i-ToF (indirect time of flight) laser radar system, which achieves accurate correction of the system ranging error and significantly improves the accuracy and stability of ranging. The following are the beneficial effects of the present invention:

[0025] 1. Improved ranging accuracy: By fitting the residual curve using Fourier series, the present invention can accurately identify and compensate for the swing error, thereby significantly improving the ranging accuracy.

[0026] 2. Optimized dual-frequency ranging frequency selection: Based on the unambiguous distance formula of dual-frequency ranging, the present invention scientifically selects multiple groups of qualified second demodulation frequencies f2, and selects the optimal dual-frequency ranging frequency by comparing the peak-to-peak value of the residual curve. This method not only simplifies the frequency selection process, but also ensures the accuracy and stability of dual-frequency ranging.

[0027] 3. Enhanced system adaptability: The method proposed in the present invention is not only applicable to specific i-ToF lidar systems, but can also be widely used in other similar ranging systems. By adjusting the parameters in the calibration process, it can flexibly adapt to the needs of different systems, improving the versatility and practicality of the method.

[0028] 4. Reduced test costs: During the test process, the present invention effectively reduces the test costs by optimizing the temperature stabilization time and the number of data acquisitions. At the same time, the accuracy and reliability of the test results are ensured through precise temperature control and data acquisition processing.

[0029] In summary, the present invention proposes an efficient, accurate and universal dual-frequency ranging error calibration method for the i-ToF lidar system, which can significantly improve the ranging accuracy, optimize the frequency selection, enhance the system adaptability, and reduce the testing cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific implementation methods and drawings. Here, the exemplary implementation methods of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0031] As used herein, the term "including" and its variations mean open inclusion, i.e., "including but not limited to". Unless otherwise stated, the term "or" means "and / or". The term "based on" means "based at least in part on". The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0032] Figure 1 A schematic diagram of a flow chart of a calibration method for a time-of-flight ranging laser radar provided in a first embodiment of the present invention;

[0033] Figure 2 It is a schematic diagram of the Q value correction process;

[0034] Figure 3 It is a schematic diagram of collecting the number of electrons of four-phase signals when the duty ratios are inconsistent;

[0035] Figure 4 It is a schematic diagram of the positional relationship between the theoretical lens, the lens holder and the detector chip;

[0036] Figure 5 Schematic diagram of optical axis deviation caused by lens assembly;

[0037] Figure 6 Schematic diagram of lens and detector chip assembly deviation;

[0038] Figure 7 Schematic diagram of the position of the lens and detector chip after the active centering process;

[0039] Figure 8 This is a schematic diagram of the physical picture of the manual AA platform;

[0040] Fig. 9 This is a schematic diagram of the ideal optical axis and the test card position;

[0041] Fig.10 It is the schematic diagram of the swing error test system;

[0042] Fig.11 This is a schematic diagram of the phase delay method data acquisition board;

[0043] Fig.12 It is a schematic diagram of the comparison curve between theoretical distance and measured distance;

[0044] Fig.13 It is a schematic diagram of the error curve;

[0045] Fig.14 Schematic diagram of the residual curve after Waggling+FPPN elimination;

[0046] Fig.15 This is a schematic diagram of the temperature calibration test scenario;

[0047] Fig.16 This is a schematic diagram of the measured distance curve before and after temperature correction;

[0048] Fig.17 This is a schematic diagram of the curve of the measured distance affected by temperature;

[0049] Reference numerals:

[0050] Lens group 401;

[0051] Optical axis 402;

[0052] Mirror mount 403;

[0053] Focal length 404;

[0054] Depth of focus 405;

[0055] detector center 406;

[0056] Detector chip 407.

[0057] Optical axis 501;

[0058] Focal length 502;

[0059] Detector center 503;

[0060] Optical axis 601;

[0061] Focal length 602;

[0062] Optical axis 701;

[0063] UV glue 702;

[0064] Focal length 703;

[0065] Detector center 704;

[0066] Light homogenizing plate 801;

[0067] Transmissive ISO12233 resolution test chart 802;

[0068] XYZ three-axis and θ-axis translation stage 803;

[0069] Infrared light source 804;

[0070] Fixture and hardware board moving platform 805;

[0071] Computer 806;

[0072] Optical vibration isolation table 807;

[0073] Data transmission cable 808;

[0074] The calibrated i-ToF module 1901;

[0075] Receive and transmit light circuit 1902;

[0076] Light-absorbing paper tube 1903;

[0077] Incubator 1904;

[0078] Reflector 1905. DETAILED DESCRIPTION

[0079] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0080] The following describes the embodiments of the present disclosure through specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0081] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0082] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present disclosure. The drawings only show components related to the present disclosure rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0083] Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects described may be practiced without these specific details.

[0084] See also Figure 1 The first embodiment of the present invention provides a calibration method for a time-of-flight ranging laser radar, which can be executed by an electronic device to implement the following steps:

[0085] S101, calibrate the receiving-end detector without a lens installed, illuminate the receiving-end detector with uniform light of constant power, obtain the charge quantity code values ​​of the receiving-end detector at different modulation phases under a fixed integration time, and complete the calibration of the receiving-end detector according to the charge quantity code values ​​at different modulation phases.

[0086] In this embodiment, i-ToF uses continuous wave modulation and demodulation to obtain the time difference information between the transmitted wave and the returned wave. The phase information is calculated, and then the phase is converted into the change in flight time, and finally the round-trip flight distance of the light is calculated. In actual use, two sets of sampling signals with a phase difference of 180° can be used to demodulate the echo signal. This method is called the dual-phase method. There is also a solution to obtain the target distance using four phases of 0°, 90°, 180° and 270°.

[0087] When using multiple phases to sample the signal, the ideal received waveform of different phases should be a square wave with the same duty cycle. However, due to the instability of the laser emission power or the demodulated signal, the duty cycles of different sampling signals will be inconsistent, and the inconsistency of the duty cycle will directly affect the inconsistency of the four phase sampling signals. In addition, the 2-Tap or multi-Tap pixel structure cannot ensure that the signal output gains of multiple integration nodes are equal, which will further worsen the inconsistency of the four-phase sampling signals. This inconsistency will cause spatial errors that cannot be eliminated. There is currently no solution to this spatial error. The embodiment of the present application proposes a charge quantity code value correction method for this problem, which can effectively suppress the spatial error caused by the inconsistency of the duty cycle and the output gain of the multi-integral node signal. For the convenience of explanation, the charge quantity code value error caused by the inconsistency of the four-phase signal is referred to as the Q value error in the embodiment of the present application.

[0088] In this embodiment, the Figure 2 The method shown corrects the Q value error. Figure 2 This is a schematic diagram of the Q value correction process. Figure 2 As shown, the following steps are included:

[0089] S201: Calibrate a receiving end detector without a lens installed, and illuminate the receiving end detector with uniform light of constant power.

[0090] Specifically, the integrating sphere is an optical device coated with a high-reflectivity material inside, which can ensure that the light is evenly distributed after multiple reflections in the sphere. When a light source (such as an LED or laser) shines on the entrance of the integrating sphere, the light will undergo multiple diffuse reflections in the sphere and eventually be evenly emitted from the exit or other openings of the integrating sphere. Fix the LiDAR receiver detector chip on the test platform to ensure that the chip surface is clean and in a horizontal position. Place the integrating sphere above the LiDAR chip to ensure that the exit of the integrating sphere is tightly fitted to the photosensitive surface of the LiDAR chip or maintain an appropriate distance. Start the light source in the integrating sphere and adjust the intensity and wavelength of the light source to meet the working requirements of the LiDAR chip. Use the adjusting device of the integrating sphere to ensure that the light emitted from the exit of the integrating sphere is evenly and stably irradiated on the photosensitive surface of the LiDAR chip.

[0091] S202: Obtaining charge quantity code values ​​of the receiving end detector at different modulation phases under a fixed integration time.

[0092] Specifically, timing control is the key to ensure that the entire calibration process proceeds in an orderly manner. Through timing control, the integration process of the lidar chip can be triggered in sequence, and the output of the four-phase sampling signal can be read at the end of each integration time period. Before the start of each integration period, it is necessary to ensure that the lidar chip is in a reset state in order to accurately record the number of photogenerated electrons in each integration period. By traversing different integration times, the response characteristics of the four-phase sampling signal at different integration times can be observed.

[0093] During the traversal process, it is necessary to ensure that the integration time setting range is wide enough to cover all lighting conditions that the lidar chip may encounter. At the same time, the integration time needs to be adjusted step by step to accurately observe the law of the four-phase sampling signal changing with the integration time.

[0094] At the end of each integration period, by reading the output signal of the lidar chip, the number of photogenerated electrons received by the four-phase sampling signal can be obtained as N0, N 90 、N 180 、N 270 .

[0095] When the integration time is too long or the light intensity is too high, the four-phase sampling signal may reach saturation, resulting in inaccurate data. To avoid signal saturation, it is necessary to monitor the output intensity of the four-phase sampling signal in real time during the calibration process and adjust the integration time or light intensity as needed to avoid saturation.

[0096] S203: completing calibration of the detector at the receiving end according to the charge quantity code values ​​under the different modulation phases.

[0097] Specifically, the actual incident light power and integration time are substituted into formula (1) to calculate the ideal photogenerated electron digital value, denoted as N ideal :

[0098]

[0099] Among them, P pixel_signal is the light power incident on the pixel, λ is the wavelength, c is the speed of light, h is Planck's constant, T int is the integration time.

[0100] In the scenario depicting the curves of each phase signal, the horizontal axis is set to represent the ideal number of photogenerated electrons expected under different integration time conditions, while the vertical axis records the number of photogenerated electrons actually received through the four-phase sampling technology. Under this setting, the slope of each curve directly reflects the size of the quantum efficiency (η), which quantifies the efficiency of converting photons into electrons. At the same time, the intercept of the vertical axis corresponds to the number of background noise electrons in the system (N noise ), which represents the number of electrons generated by the system due to various factors (such as dark current, thermal noise, etc.) in the absence of light.

[0101] Ideally, if the performance of the four-phase sampling system is exactly the same, then the signal curves corresponding to the four phases should have the same slope. However, in practical applications, due to the influence of various factors, such as the imbalance of the duty cycle of each phase, the difference in charge transfer efficiency, etc., the slope of the obtained curve may show certain fluctuations or inconsistencies. Figure 3 , Figure 3 Schematic diagram of the number of electrons collected by four-phase signals when the duty cycles are inconsistent.

[0102] In order to achieve Q value error correction and ensure the accurate coincidence of the four-phase photogenerated electron curves, the present embodiment adopts the following steps to correct the slope of the curve.

[0103] First, according to formula (2), the equivalent conversion efficiency of each phase (0°, 90°, 180°, 270°) is calculated, which are denoted as η0, η 90 , η 180 , η 270These equivalent conversion efficiencies reflect the differences in efficiency of each phase in converting photons into electrons.

[0104]

[0105] Next, the mode of these equivalent conversion efficiencies at different integration times, that is, the value with the highest frequency, is counted as the standard equivalent conversion efficiency η of the entire system. This value represents the most likely conversion efficiency of the system under different conditions and is used as a benchmark in the subsequent calibration process.

[0106] Then, the ratio of the equivalent conversion efficiency of each phase to the standard equivalent conversion efficiency is calculated to obtain four correction coefficients k0, k 90 , k 180 , k 270 , which correspond to the correction coefficients of 0°, 90°, 180°, and 270° phases. These correction coefficients reflect the conversion efficiency deviation of each phase relative to the system standard.

[0107] At the same time, the background electron number of each phase is converted into the background quantization code value, which is recorded as b0, b 90 , b 180 , b 270 These background quantization code values ​​represent the digital code values ​​corresponding to the number of electrons generated by system noise in each phase under no light conditions.

[0108] Finally, we use the following formula (3) to correct the digital code values ​​of the four phases:

[0109] D calibre =D actual k n -b n (3)

[0110] Among them, D calibre is the digital code value after Q value correction, D actual is the digital code value before correction, k n is the equivalent conversion efficiency correction coefficient (corresponding to k0, k 90 , k 180 , k 270 ), b n is the background noise voltage code value (corresponding to b0, b 90 , b 180 , b 270 ).

[0111] Through this correction process, the conversion efficiency differences and background noise effects between the phases can be effectively eliminated, so that the photogenerated electron curves of the four phases can accurately overlap after correction, thereby improving the measurement accuracy and stability of the system.

[0112] Furthermore, in order to analyze the relationship between the integration time and the output code value of the demodulated signal with different phases for the same pixel, the corresponding curve was drawn and marked as y=f(x). Subsequently, the first-order curve fitting technique was used, with the goal of finding a fitting function z=Ax+B that can minimize the linear deviation between z and y. The above fitting process was performed for each pixel of the entire chip, and the respective fitting coefficients were recorded.

[0113] S102, calibrate the laser radar module, make the digital output result of each pixel in the receiving end detector close to zero under the condition of no light, make the output of any two pixels in the receiving end detector consistent under the condition of the same incident light intensity, remove bad pixel pixels, import the lens distortion file to correct the lens distortion, move the position of the diffuser plate from the lens to the pre-obtained focus position to ensure that the diffuser plate is parallel to the optical platform and then output the focus distance of the laser radar module lens, move the test card in the first direction and the second direction respectively so that the rays of the test card in the third direction just pass through the center position of the laser radar module lens in the first direction and the second direction respectively, and then move the lens in the third direction to make the obtained image clear, adjust the position of the receiving end detector so that the image is in the center position of the field of view, and adjust the inclination of the lens so that the image clarity at the four positions is consistent.

[0114] In this embodiment, in order to optimize the imaging clarity of the laser radar module, it is crucial to ensure that the detector chip and the optical axis of the optical component are optimally aligned. Traditional passive calibration methods, such as Zhang's calibration method, are usually performed after the camera module (including the lens) is assembled. This means that the errors that may be introduced during the lens assembly process cannot be adjusted during the calibration process, and can only rely on subsequent internal and external parameter calibration to compensate for these errors.

[0115] In order to reduce the impact of assembly errors on the imaging quality of the LiDAR system from the source, this embodiment proposes a solution using active lens calibration (AA) technology. Active lens calibration technology can adjust the lens position in real time during the lens installation process to achieve optimal alignment with the optical axis of the detector chip. This method not only improves the calibration accuracy, but also can directly correct the errors generated during the assembly process, thereby significantly improving the imaging clarity and overall performance of the LiDAR system.

[0116] Specifically, AA technology aims to accurately determine the relative positions of parts during the assembly process. In the complex process of lens packaging, multiple parts such as detector chips, lens holders, PCBs (printed circuit boards), lenses, circuit boards, etc. need to be assembled accurately multiple times. As the number of assembly steps increases, the stacking tolerances between parts will gradually accumulate, resulting in increased tolerances.

[0117] This tolerance accumulation can lead to a range of issues, such as the position of the image captured by the lens may be offset from the center of the frame, or the sharpness of the four corners of the captured area may vary significantly. These issues not only affect the visual quality of the image, but may also have a negative impact on the resolution and accuracy of the image.

[0118] In the Flash LiDAR system, the application of AA technology is also crucial. LiDAR generates 3D point cloud data by emitting laser beams and receiving reflected light signals. When there are deviations between the lens and the detector chip in six degrees of freedom (i.e., three translation directions and three rotation angles), these deviations will directly affect the imaging quality of the LiDAR and the accuracy of the 3D point cloud.

[0119] Therefore, in the manufacturing process of Flash LiDAR, it is crucial to use AA technology to accurately align the lens and detector chip. By accurately adjusting the relative position between them, the deviation can be minimized, thereby improving the imaging quality of the LiDAR and the accuracy of the 3D point cloud. Figure 4 , Figure 4 Figure 1 is a schematic diagram showing the positional relationship between the theoretical lens, lens mount, and detector chip. Figure 4 As shown in the ideal optical path concept, the lens and the detector chip should be in a completely parallel state, the optical axis center of the lens and the optical axis center of the detector chip must overlap accurately, and the optical axis center must maintain a perfect perpendicular relationship with the detector surface. However, in the actual manufacturing, production and assembly process, due to the existence of various error factors, such as machining accuracy limitations, assembly process deviations, etc., it becomes extremely difficult to achieve this ideal state. These errors may cause slight misalignment between the lens and the detector chip, the optical axis center cannot be accurately aligned, and even the verticality of the optical axis and the detector will be affected to a certain extent. The combined effect of these factors makes it difficult for the camera module finally produced to reach the theoretically perfect state. For details, please refer to Figure 5-Figure 6 . Figure 5 This is a schematic diagram of the optical axis deviation caused by lens assembly. Figure 5As shown in the figure, the optical axis deviation phenomenon occurs in the lens assembly process. During the stacking and assembly process of the lenses, due to various factors (such as manufacturing accuracy, assembly process, etc.), the optical axis of the lens is offset, resulting in the optical center of the lens not being strictly located on the central axis of the lens. This optical axis deviation will have a negative impact on the imaging quality of the lens. Ideally, the optical center of the lens should be precisely located on the central axis of the lens to ensure that the light can be accurately focused and form a clear image. However, when the optical axis is offset, the light will not be able to focus correctly, resulting in problems such as blurred and distorted images.

[0120] Figure 6 This is a schematic diagram of the lens and detector chip assembly deviation. Figure 6 As shown in the figure, due to the existence of installation tolerance during the detector chip assembly process, the center position of the detector chip is displaced relative to the optical center of the lens, and the chip may also have a certain inclination. This displacement and inclination have a direct impact on the performance of the detector. Ideally, the center of the detector chip should be precisely aligned with the optical center of the lens to ensure that the received light signal can be converted into an effective electrical signal to the maximum extent. However, when displacement and inclination occur, part of the light signal may deviate from the sensitive area of ​​the detector chip, resulting in signal loss and reduced imaging quality.

[0121] Active centering technology can effectively compensate for the tolerances generated during the front-end assembly process in five degrees of freedom. These degrees of freedom include X-axis and Y-axis offsets, as well as Tilt offset correction, to ensure that the center axis of the lens is precisely overlapped with the center axis of the detector chip.

[0122] This assembly process is completed when the camera module is lit and in working condition. First, the center point and four corners of the detector chip are adjusted through active centering technology to ensure that they all achieve the best clarity. Once the adjustment is completed, UV glue is used to fix the position of the lens to ensure its stability and durability.

[0123] The position of each module after active centering technology processing, such as Figure 7 As shown, Figure 7 Schematic diagram of the position of the lens and detector chip after the active centering process.

[0124] The following is a detailed introduction to the laser radar module calibration process provided in the embodiment of the present application.

[0125] In view of the lack of specially customized automated platform equipment, this embodiment adopts the manual active alignment (Manual Active Alignment, referred to as manual AA) method in the laser radar lens calibration process. The manual AA platform integrates multiple key components to jointly support this precise calibration process. These components mainly include: Infrared light source: used to provide stable infrared light irradiation to simulate the working environment of the laser radar.

[0126] Light diffuser: ensures uniform light distribution and reduces the impact of uneven light on calibration results. Transmissive ISO12233 resolution test card: used as a standard reference in the calibration process to evaluate the resolution performance of the lens. Three-axis translation stage: allows fine adjustment of the lens in three directions: X (first direction), Y (second direction), and Z (third direction) to achieve precise alignment. θ-axis rotation stage: provides freedom for the lens to rotate around the optical axis to correct angle deviation. Lens holder fixture and hardware board moving stage: firmly clamps the lens to ensure its stability during the calibration process, and is used to adjust the position of the detector chip or related components to achieve optimal alignment with the lens. Computer: acts as the control center, runs the calibration software, receives and processes data from the test card. Data transmission cable: connects the computer and various hardware components to ensure real-time transmission and processing of data. Optical vibration isolation table: ensures that the entire platform is in a horizontal state to reduce errors caused by tilt and vibration.

[0127] The manual AA platform layout used in this embodiment is as follows Figure 8 As shown, Figure 8 This is a schematic diagram of the manual AA platform. Figure 8 The platform shown provides the necessary accuracy and flexibility for LiDAR lens calibration by integrating the above components.

[0128] The complete active alignment is divided into two stages. The first is the grayscale image correction stage. The main goal of this step is to eliminate the non-ideal factors that may exist on the grayscale image and ensure that they do not interfere with the accurate judgment of the focus clarity. Through the correction work, it can ensure that the focus process can proceed smoothly, laying the foundation for the subsequent steps.

[0129] Active calibration technology relies on image clarity to evaluate whether the positional relationship between the lens and the detector chip is accurate. In order to ensure the accuracy of calibration, the consistency of the LiDAR output image must be compensated. The core of this compensation process is to collect and process the background noise to eliminate the offset between pixels, so that the digital output result of each pixel is close to zero under no light conditions.

[0130] The specific steps are as follows: First, in a dark environment, collect the output digital code values ​​of all pixels. Since the offset is usually more obvious between pixel columns, each column of data is centered, that is, the mean of the pixel output of each column is calculated and subtracted from the output data of each pixel in the column. This step effectively reduces the inconsistency between columns and improves the accuracy of image data. The calibrated image has significantly improved in uniformity and consistency, which provides support for the subsequent accurate judgment of image clarity.

[0131] Conversion gain correction is to ensure that within the field of view, when two pixels receive incident light of the same intensity, the corresponding pixels on the detector chip can output consistent results. To achieve this goal, conversion gain correction is required to eliminate the output inconsistency caused by the slope difference between pixels.

[0132] The specific operation steps are as follows: First, collect the response curves of all pixels in the range of no light and saturated light intensity. These response curves reflect the output characteristics of each pixel under different light intensities. Then, normalize the response curve of each pixel so that the output code value of each pixel can cover the same range under the same light intensity. The purpose of this step is to ensure that the output results of all pixels remain consistent under the same light intensity conditions.

[0133] After this step is completed, a conversion gain correction file will be generated. This file records the normalized correction parameters of each pixel and can be used in subsequent image processing to ensure accurate judgment of image clarity.

[0134] Before focusing begins, it is a crucial step to remove bad pixels on the detector chip. Due to factors such as the production process, the conversion gain of individual pixels may be problematic. If these bad pixels appear near the center of the field of view, they will have a significant impact on the center judgment of the detector chip.

[0135] In order to effectively remove these bad pixels, the following specific steps are taken: First, the output code values ​​of all pixels are collected in a dark environment, and the standard deviation σ and mean μ of these code values ​​are calculated. Next, the absolute value x of the difference between the output code value of each pixel and the mean μ is calculated. If x is greater than a preset threshold, which can be a multiple of σ, such as 3σ, 4σ, etc., the pixel is judged as a bad pixel and removed from subsequent processing.

[0136] After completing a round of bad pixel removal, repeat the above steps again to perform a new round of screening on the remaining pixels until the x value of all pixels is less than the preset threshold. This process ensures that only stable and normal pixels are used for subsequent image processing and focusing.

[0137] Once the bad pixel removal step is completed, a removal correction file will be generated. This file records all the bad pixel information that has been removed and can be used in subsequent image processing and system calibration to ensure the performance and accuracy of the detector chip.

[0138] During the design and processing of the lens, barrel distortion or pincushion distortion is often unavoidable. These two distortions correspond to the "-" and "+" signs of the distortion parameters in the lens specifications. The larger the absolute value of the distortion parameter, the more significant the distortion phenomenon. Therefore, in order to obtain accurate images and focusing effects, it is particularly important to correct the lens distortion. Usually, lens manufacturers will provide detailed lens distortion parameters at the factory so that users can perform subsequent correction work. The existence of distortion will seriously affect the accurate judgment of the field of view angle and center position during the focusing process, thus bringing great difficulties to the focusing operation. To solve this problem, you can directly import the lens distortion correction file. This file contains the distortion correction parameters and algorithms for a specific lens, which can effectively eliminate or reduce the distortion phenomenon.

[0139] The above embodiments are all intended to ensure the uniformity and consistency of the detector array, which is a prerequisite for smooth focusing. Specifically, by correcting the grayscale image, eliminating the offset between pixels, performing conversion gain correction, and removing bad pixel pixels, the stability and accuracy of the detector array can be significantly improved.

[0140] At the same time, the correction of lens distortion is also crucial. The existence of distortion will interfere with the accurate judgment of the field angle and center position during the focusing process, thereby affecting the accuracy and reliability of focusing. Therefore, by importing and applying the lens distortion correction file, we can eliminate or reduce the distortion phenomenon and provide more accurate image information for focusing work.

[0141] Next comes the focal length determination and optical axis alignment stage. In this stage, the focal length of the lens is determined based on the corrected grayscale image, and the optical axis of the lens and the detector chip are precisely adjusted to achieve the best alignment. This step is the key to achieving the best position match between the lens and the detector chip, and is crucial to improving the imaging quality and performance of the entire optical system.

[0142] In order to achieve focus, the depth of field of the lens must be calculated first. This is a key step in determining the object distance at which the focus is completed to ensure that the LiDAR system can present a clear image within the set range. Depth of field, in short, refers to the distance between the closest point and the farthest point in the scene that can produce a relatively clear image. The length of the depth of field directly affects the range of scenes that can be presented clearly: the longer the depth of field, the wider the range of clear presentation.

[0143] When the focal length and aperture remain constant, the depth of field is closely related to the distance from the subject to the lens. When the subject is closer to the lens, the depth of field is relatively small; conversely, when the subject is farther from the lens, the depth of field is relatively large. The reason for this phenomenon is that the size of the image is directly affected by the object distance. When the subject is closer to the lens, the image will increase accordingly, causing the circle of confusion to become thicker, so that the smaller the object distance, the shallower the depth of field. As the distance between the subject and the lens increases, the circle of confusion gradually decreases, so the depth of field also gradually increases accordingly.

[0144] The depth of field of the lens can be expressed as:

[0145] The depth of field behind the lens can be expressed as:

[0146] The depth of field DOF of a lens can be expressed as:

[0147]

[0148] Where L is the shooting distance, δ is the diameter of the allowable circle of confusion, F is the lens aperture value, and f is the focal length of the lens.

[0149] According to the lens imaging theory, the image is ultimately formed by multiple points. Even if the image formed by each point is a little "blurry", the final image can still be clearly seen, so the actual allowable "blurry" point size is called the allowable confusion circle. The calculation formula for the allowable confusion circle diameter δ is:

[0150] δ=d / 1730 (7)

[0151] Where d is the diagonal length of the detector chip.

[0152] In short, the depth of field of the lens is directly determined by the position of the focus. When the focus position is adjusted, the depth of field of the lens will change accordingly. Specifically, by setting a specific focus distance, the foreground depth of field and the background depth of field can be calculated separately. The range of these two together constitutes the area of ​​clear imaging, which must be greater than or equal to the ranging range of the lidar.

[0153] After determining the appropriate focus distance, the next step is to adjust the relative position of the diffuser and the lens to achieve the focus position. During this process, the parallelism of the diffuser needs to be tested to ensure that it remains parallel to the optical platform. This step is crucial because it directly affects the quality and accuracy of imaging.

[0154] After completing the above adjustments, the distance between the diffuser and the detector chip can be further adjusted using the ISO12233 test card to optimize the imaging effect. Finally, the focusing distance parameters of the module lens will be output.

[0155] In the focusing process, optical axis alignment is an important step. First, you need to use the Z-direction ray of the level to accurately mark the center position of the test card on the XYZ axis. Next, by adjusting the X-axis of the XYZ three-axis translation stage, ensure that the Z-direction ray can accurately pass through the X-axis center of the lens and fix the X-axis at this position.

[0156] Then, use the Z-direction ray of the level again to mark the center position of the test card on the Y-axis. Adjust the Y-axis of the XYZ three-axis translation stage so that the Z-direction ray can accurately pass through the Y-axis center of the lens, and fix the Y-axis at this position.

[0157] After the above steps, the center of the lens and the test card are aligned, and the optical axis alignment is completed. Fig. 9 , Fig. 9 Schematic diagram of the ideal optical axis and test card position.

[0158] After completing the above steps, first move the lens along the Z axis until the image is basically clear. If the image observed at this time is not in the center of the field of view, and the image cannot be adjusted to the center no matter how the lens is tilted left, right, up, or down along the Z axis, this usually means that the center of the lens mount is not aligned with the center of the detector chip.

[0159] In this case, the positional relationship between the lens mount and the detector chip needs to be readjusted. Specifically, if the center of the test card is always observed to be located to the left of the image, the detector chip needs to be adjusted to the left because the chip output data is opposite in the left and right directions; if the center of the test card is to the right, the chip needs to be adjusted to the right. Similarly, if the center of the test card is always located to the upper part of the image, the detector chip needs to be adjusted downward because the chip output data in the upper and lower directions is correct; if the center of the test card is to the lower part, the chip needs to be adjusted upward.

[0160] During the adjustment process, it is necessary to constantly observe whether the image has moved to the center of the field of view. If the image center cannot be aligned with the center of the screen without moving the XYZ three-axis translation stage (for example, considering that the chip resolution is 320×240, the center pixel should be located at the 120th pixel in the row direction and the 160th pixel in the column direction), the current focusing material is considered unsuitable and a new material needs to be replaced and the focusing process repeated until the image center is aligned with the center of the screen.

[0161] Next, make sure the image is clear at four locations (top, bottom, left, and right) by adjusting the rotation angle. If the left side of the image is clear, tilt the lens to the right; if the right side of the image is clear, tilt it to the left. Similarly, if the top side of the image is clear, tilt the lens to the bottom; if the bottom side of the image is clear, tilt it to the top.

[0162] After completing the above adjustments, the position alignment between the lens mount and the center of the detector chip is achieved, that is, the optical axis alignment is completed. At this time, it is necessary to fix the position relationship between the lens mount and the detector chip, and record the position and rotation angle θ of the XYZ three-axis translation stage. Finally, glue is applied to fix the lens to ensure the stability and durability of the focusing result.

[0163] S103, using Fourier series to fit the error between the measured distance and the actual distance, and correcting the measured distance according to the function obtained by fitting.

[0164] Specifically, it is known from the above embodiments that non-ideal modulation waveforms will introduce nonlinear errors into the final distance measurement results, and such errors are named as waggling errors. On the other hand, fixed phase pattern noise (FPPN) is a phase offset unique to each pixel, which originates from the specific position of the pixel in the array, and is therefore also called pixel depth non-uniformity. FPPN is mainly affected by modulation frequency and operating temperature, and exists as a fixed deviation, which is easy to correct through calibration.

[0165] In order to calibrate Waggling error and FPPN, a lookup table method is often used. In specific implementation, the LiDAR system needs to be firmly mounted on the guide rail, and the reflectivity plate is placed within the LiDAR's field of view. Then, by setting the moving step of the guide rail, a series of measurements are performed to construct a lookup table, thereby achieving accurate calibration of the two errors.

[0166] Specifically, after all actual distances are measured, a comparison curve between the actual measured distance and the ideal distance can be drawn, and an error curve can be generated based on the error value. Next, by recording the error values ​​of all sampling points, a lookup table is constructed, and the calibrated data is calculated using formula (8):

[0167] D calibre =D measure +D offset (8)

[0168] It should be noted that the correction accuracy of the lookup table usually increases with the increase in the number of sampling points, but this also increases the consumption of storage space accordingly. Therefore, in practical applications, it is necessary to find a balance between storage depth and system accuracy.

[0169] By observing the principle of error generation and the actual error curve, it can be found that the error curve presents periodic changes and its shape is similar to a sine wave. In order to more effectively describe this error, this embodiment uses the Fourier series fitting method to fit the error curve. The specific formula is shown in (9):

[0170]

[0171] In this formula, the constant term A0 represents the correction parameter of the FPPN error, and a n , b n and ω are the correction parameters for the Waggling error. Once the order n of the fit is determined, it is only necessary to solve A0, a n , b n The error curve can be completely drawn by using the unknowns ω and ω. This method significantly reduces the storage requirements of the correction data while ensuring accuracy.

[0172] In addition, when using the guide rail to collect data at different distances, there is a challenge, that is, the energy of the echo signal at a long distance is weak, which may lead to an increase in the precision error. According to the analysis of the system's ranging accuracy, it is known that the weakening of the echo energy will aggravate the precision error. Therefore, when correcting the swing error, it is necessary to eliminate the interference of the precision error at different ranging distances. Although this error can be reduced by collecting a large amount of data at the same distance and averaging it, this will reduce the efficiency of the calibration. In order to solve this problem, this embodiment proposes a phase delay method, which simulates the change in distance by adjusting the phase change of the transmitted wave and the echo, thereby achieving the decoupling of the precision error and the accuracy error. This method not only ensures the accuracy of the calibration, but also improves the efficiency of the calibration. See Figure 2 for details. Fig.10 and Fig.11 , Fig.10 This is the schematic diagram of the swing error test system. Fig.11 This is a schematic diagram of the phase delay method data acquisition board.

[0173] like Fig.10 As shown, at the beginning of the test, the distance between the module to be tested and the reflectivity plate is first accurately fixed at a relatively close position (for example, 1 meter) using an electric control rail, and the distance is accurately calibrated using a single-point rangefinder. After determining the fixed test distance, it is necessary to select a suitable modulation frequency f (first frequency). Next, by configuring the FPGA (field programmable gate array) on the phase acquisition board, the phase shift of the transmitted modulation waveform can be achieved, and its phase shift accuracy is t delay This step is crucial because it allows us to accurately measure and obtain the total 1 / f1*t at the demodulation frequency f1. delay data points.

[0174] After completing the data collection, two curves can be drawn based on the data: one is the ideal distance measurement curve, and the other is the actual distance measurement curve. Fig.12 As shown, Fig.12The diagram is a comparison curve between the theoretical distance and the measured distance. The error curve can be drawn by subtracting the measured distance from the theoretical distance, such as Fig.13 As shown, Fig.13 is a schematic diagram of the error curve. In this embodiment, the residual curve is fitted using the Fourier series. By observing the fitting graph, it can be found that when the Fourier series reaches 7, the fitting effect is already quite ideal. After the swing error is corrected using the 7-order Fourier series fitting curve, the residual curve is redrawn, as shown in the following figure. Fig.14 shown. Fig.14 Schematic diagram of the residual curve after Waggling+FPPN elimination.

[0175] After the linearity and error calibration of the first demodulation frequency f1 is completed, multiple sets of second demodulation frequencies f2 that meet the conditions are selected according to the unambiguous distance formula (15) of dual-frequency ranging. The formula is as follows:

[0176]

[0177] Among them, f1 and f2 represent the two modulation frequencies in dual-frequency ranging, f E is the equivalent modulation frequency, D E is the equivalent fuzzy distance, and gcd represents the greatest common divisor of f1 and f2.

[0178] For each f2 that meets the conditions, the above calibration process is repeated, and the residual curve is redrawn after the swing error is eliminated. We record the peak-to-peak value of each residual curve, which is denoted as E 1PP ,E 2PP ,…,E nPP Finally, from these candidate f2 frequencies, select the peak-to-peak value E pp The smallest one is used as the final dual-frequency ranging frequency to ensure the accuracy and stability of ranging.

[0179] S104, performing a second-order linear fit on the measured distance and temperature data, and performing temperature correction on the measured distance according to a curve obtained by the fitting.

[0180] Specifically, the ambient temperature has a direct impact on the laser emission power, which in turn indirectly affects the measured distance of the i-ToF technology. This phenomenon is called thermal drift or temperature drift. Fortunately, the characteristics of temperature drift are linear, affecting all pixels the same, but will vary with the modulation frequency. In order to compensate for the drift caused by temperature in the system, it is first necessary to fully characterize the temperature characteristics of the system and implement precise correction measures for the ranging error accordingly.

[0181] In order to quantify the drift of distance measurement with temperature changes, i-ToF LiDAR systems are usually placed in a temperature chamber for testing. However, the internal space of the temperature chamber is limited and the walls are mostly made of metal. Such an environment is very likely to induce multipath interference problems. Therefore, low-reflectivity baffles are often installed around the temperature chamber to solve this problem. These baffles can cover the entire path from the camera lens to the target object, effectively suppressing multipath propagation. The test environment is set up as follows Fig.15 As shown, Fig.15 This is a schematic diagram of the temperature calibration test scenario. Since the impact of temperature drift on each pixel is the same, it is only necessary to collect pixel data in the center area of ​​the image to meet the test requirements.

[0182] After completing the construction of the test environment, the ambient temperature can be adjusted in the target working area, and the distance information of the target object can be recorded simultaneously. For example, the ambient temperature of the system under test can be controlled within the range of -40°C to 85°C. In this process, considering the important impact of temperature stabilization time on test reliability, it is necessary to find a balance between test efficiency and cost. If the temperature stabilization time is too short, it may lead to inaccurate temperature measurement, which in turn affects the accuracy of the calibration results; if the time is too long, it will increase the total time required for calibration and increase the test cost.

[0183] In order to ensure the accuracy of the test and improve the efficiency, this embodiment selects 20°C as the preset temperature step for temperature adjustment, and the stabilization time of each temperature group is set to 20 minutes. After the temperature reaches a stable state, more than 30 sets of data are collected at the current temperature. By averaging these data, the impact of measurement errors on the collected data can be further reduced, thereby improving the reliability of the data. The final test data has been sorted and is shown in Table (1):

[0184] Table-1 Test data at different temperatures

[0185]

[0186] Use the measured data to draw a curve of temperature and measured distance, such as Fig.16 As shown, Fig.16 Schematic diagram of the measured distance curve before and after temperature correction.

[0187] A second-order linear fit is performed on the data, and its expression is:

[0188] D Temperature_offset =a+bT+cT 2 (0-1)

[0189] Among them, a, b, c are temperature correction coefficients, T is temperature, and after solving a, b, c by the least square method, the error curve before and after temperature correction can be drawn as follows: Fig.17 As shown, Fig.17 The diagram is a diagram of the curve of the measured distance affected by temperature. It can be seen from the data that when the temperature is within the range of -40℃ to 85℃, after temperature correction, the accuracy deviation caused by temperature drift is corrected to within 4mm.

[0190] In summary, compared with the prior art, this embodiment has the following advantages:

[0191] 1. Improved ranging accuracy: By fitting the residual curve using Fourier series, the present invention can accurately identify and compensate for the swing error, thereby significantly improving the ranging accuracy.

[0192] 2. Optimized dual-frequency ranging frequency selection: Based on the unambiguous distance formula of dual-frequency ranging, the present invention scientifically selects multiple groups of qualified second demodulation frequencies f2, and selects the optimal dual-frequency ranging frequency by comparing the peak-to-peak value of the residual curve. This method not only simplifies the frequency selection process, but also ensures the accuracy and stability of dual-frequency ranging.

[0193] 3. Enhanced system adaptability: The method proposed in this embodiment is not only applicable to specific i-ToF laser radar systems, but can also be widely used in other similar ranging systems. By adjusting the parameters in the calibration process, it can flexibly adapt to the needs of different systems, thereby improving the versatility and practicality of the method.

[0194] 4. Reduced test costs: During the test process, this embodiment effectively reduces the test costs by optimizing the temperature stabilization time and the number of data acquisitions. At the same time, the accuracy and reliability of the test results are ensured through precise temperature control and data acquisition processing.

[0195] In summary, this embodiment proposes an efficient, accurate and universal i-ToF lidar system dual-frequency ranging error calibration method, which can significantly improve ranging accuracy, optimize frequency selection, enhance system adaptability, and reduce testing costs.

[0196] Those skilled in the art should understand that the embodiments of the present specification may be provided as methods, systems or computer program products. Therefore, those skilled in the art may imagine that the functional modules / units or controllers and related method steps described in the above embodiments may be implemented in software, hardware or a combination of software / hardware.

[0197] Unless explicitly stated, the actions or steps of the methods, programs, and embodiments of the present invention do not have to be performed in a specific order and can still achieve the desired results. In some implementations, multitasking and parallel processing are also possible or may be advantageous.

[0198] Multiple embodiments of the present invention have been described, but for the sake of brevity, the description of each embodiment is not exhaustive, and the same or similar features or parts between the various embodiments may be omitted. In this article, "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" are intended to be applicable to at least one embodiment or example according to the present invention, but not all embodiments. The above terms do not necessarily mean to refer to the same embodiment or example. In the absence of contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples.

[0199] The exemplary systems and methods of the present invention have been specifically shown and described with reference to the above embodiments, which are merely examples of the best modes for implementing the present systems and methods. It will be appreciated by those skilled in the art that various changes may be made to the embodiments of the systems and methods described herein when implementing the present systems and / or methods without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims

1. A calibration method for a time-of-flight ranging laser radar, characterized in that: include: Calibrate a receiving-end detector without a lens installed, illuminate the receiving-end detector with uniform light of constant power, obtain charge quantity code values ​​of the receiving-end detector at different modulation phases under a fixed integration time, and complete the calibration of the receiving-end detector according to the charge quantity code values ​​at different modulation phases; Calibrate the laser radar module, make the digital output result of each pixel in the receiving end detector close to zero under the condition of no light, make the output of any two pixels in the receiving end detector consistent under the condition of the same incident light intensity, remove bad pixel pixels, import the lens distortion file to correct the lens distortion, move the position of the light diffuser from the lens to the pre-obtained focus position to ensure that the light diffuser is parallel to the optical platform and then output the focus distance of the laser radar module lens, move the test card in the first direction and the second direction respectively so that the rays of the test card in the third direction just pass through the center position of the laser radar module lens in the first direction and the second direction respectively, and then move the lens in the third direction to make the obtained image clear, adjust the position of the receiving end detector so that the image is in the center of the field of view, and adjust the inclination of the lens so that the image clarity at the four positions is consistent; The error between the measured distance and the actual distance is fitted using the Fourier series, and the measured distance is corrected according to the function obtained by fitting; A second-order linear fit is performed on the measured distance and temperature data, and the measured distance is temperature corrected according to a curve obtained by the fitting.

2. The calibration method of the time-of-flight ranging laser radar according to claim 1, characterized in that: The calibration of the receiving-end detector is completed according to the charge quantity code values ​​under the different modulation phases, including: obtaining a charge quantity code value curve of the same pixel under the different modulation phases within the fixed integration time; fitting the charge quantity code value curve through a first-order curve function so that the linear deviation between the first-order curve function and the charge quantity code value curve is minimized; traversing all pixels of the receiving-end detector to obtain fitting curve coefficients of all pixels.

3. The calibration method of the time-of-flight ranging laser radar according to claim 2, characterized in that: The fitting curve coefficients include an equivalent conversion efficiency correction coefficient and a background noise voltage code value, wherein the equivalent conversion efficiency correction coefficient is a ratio of the mode of the equivalent conversion efficiency at different modulation phases at different integration times to the equivalent conversion efficiency at different modulation phases; The equivalent conversion efficiency is the ratio of the actual charge quantity code obtained by irradiating the receiving end detector without the lens with uniform light through the integrating sphere under different modulation phases to the ideal photogenerated electron digital value; The background noise voltage code value is the vertical axis intercept of the charge quantity code value curve.

4. The calibration method of the time-of-flight ranging laser radar according to claim 3, characterized in that: The formula for the ideal photogenerated electron digital value is as follows: Among them, P pixel_signal is the light power incident on the pixel, λ is the wavelength, c is the speed of light, h is Planck's constant, T int is the integration time.

5. The calibration method of the time-of-flight ranging laser radar according to claim 1, characterized in that: The step of removing bad pixel pixels includes: collecting charge quantity code values ​​output by all pixels of the receiving end detector in a dark environment, calculating the standard deviation and mean of the charge quantity code values, calculating the absolute value of the difference between the charge quantity code values ​​of all pixels and the mean, and judging whether the absolute value is greater than a preset threshold, wherein the preset threshold is a multiple of the standard deviation; If so, the pixel is determined to be a bad pixel and is removed.

6. The calibration method of the time-of-flight ranging laser radar according to claim 1, characterized in that: The test card is moved in the first direction and the second direction respectively so that the rays of the test card in the third direction just pass through the center position of the laser radar module lens in the first direction and the second direction respectively, and then the lens is moved in the third direction so that the obtained image is clear, and the position of the detector at the receiving end is adjusted so that the image is in the center position of the field of view, including: marking the axis center positions of the test card in the first direction, the second direction and the third direction through the rays of the third direction of the level, moving the axis of the first direction of the three-axis displacement stage so that the rays of the third direction just pass through the center position of the axis of the first direction of the lens, and fixing the position of the axis of the first direction of the three-axis displacement stage; Mark the center position of the second axis of the test card through the third direction ray of the level, move the second axis of the three-axis translation stage so that the third direction ray just passes through the center position of the second axis of the lens, and fix the position of the second axis of the three-axis translation stage.

7. The calibration method of the time-of-flight ranging laser radar according to claim 1, characterized in that: Adjusting the position of the receiving end detector so that the image is located at the center of the field of view includes: when the image is not located at the center of the field of view, moving the receiving end detector in the opposite direction of the image deviating from the center of the field of view.

8. The calibration method of the time-of-flight ranging laser radar according to claim 1, characterized in that: Adjusting the inclination of the lens so that the image clarity at four position points is consistent includes: adjusting the rotation angle of the lens in the opposite direction of the image clarity direction.

9. The calibration method of the time-of-flight ranging laser radar according to claim 1, characterized in that: The error between the measured distance and the actual distance is fitted using the Fourier series, and the measured distance is corrected according to the function obtained by fitting, including: setting the laser radar module to be measured and the reflectivity plate at a fixed distance, and calibrating the fixed distance; Obtain two curves of ideal distance measurement and actual distance measurement at a first demodulation frequency, obtain an error curve between the ideal distance measurement and the actual distance measurement, and use Fourier series to fit the error curve at the first frequency; According to the unambiguous distance formula of dual-frequency ranging, a second demodulation frequency that meets the conditions is selected, and two curves of ideal ranging and actual ranging are obtained at the second demodulation frequency, and an error curve between the ideal ranging and actual ranging is obtained. The error curve at the second frequency is fitted using Fourier series, and the second frequency corresponding to the minimum value of the peak value of the error curve after the error is eliminated is obtained as the second frequency of dual-frequency ranging.

10. The calibration method of the time-of-flight ranging laser radar according to claim 1, characterized in that: A second-order linear fit is performed on the measured distance and temperature data, and the measured distance is temperature corrected according to the curve obtained by fitting, including: placing the laser radar module in an incubator with low-reflectivity baffles on all sides; adjusting the temperature of the incubator according to a preset temperature step to obtain a curve of the measured distance and temperature, and performing a second-order linear fit on the curve of the measured distance and temperature.

Images