Calibration method and device applied to laser radar, laser radar and carrying tool

Abstract

The invention provides a calibration method and device applied to a laser radar, the laser radar, a carrying tool and a storage medium. The calibration method comprises the following steps: receiving first echo data from a first detector set and second echo data from a second detector set; the laser receiving circuit of the laser radar comprises a first detector group. The first detector group comprises a first detector set and a second detector set. Determining first calibration data for the first detector group; and performing first calibration on a first detection result of the first echo data and a second detection result of the second echo data based on the first calibration data. According to the scheme, the detection performance of the laser radar can be improved under the condition that the cost is saved.

Description

Technical Field

[0001] This disclosure relates to the field of optical detection technology, and in particular to calibration methods and apparatus for lidar, lidar, vehicles, and storage media. Background Technology

[0002] LiDAR (Light Detection and Ranging) uses laser light as a medium for object detection. It is widely used in fields such as autonomous driving, drones, robot recognition, geographic mapping, and environmental monitoring. However, LiDAR still faces the challenge of high cost in its applications.

[0003] Improving the detection performance of lidar while saving costs is of great importance. Summary of the Invention

[0004] This disclosure provides a calibration method and apparatus for lidar, lidar, vehicle, and storage medium, which can improve the detection performance of lidar while saving costs.

[0005] In a first aspect, a calibration method for a lidar is provided. The calibration method includes: receiving first echo data from a first detector set and second echo data from a second detector set, wherein the lidar's laser receiving circuit includes a first detector group, which includes a first detector set and a second detector set; determining first calibration data for the first detector group; and performing a first calibration on a first detection result of the first echo data and a second detection result of the second echo data based on the first calibration data.

[0006] The aforementioned first calibration data can be used to calibrate the detection results of multiple detector sets located in the same detector group. In this way, multiple detector sets within the same detector group can share the same calibration data. Thus, calibration improves the accuracy of the detection results; reusing calibration data reduces data storage requirements and the space occupied by the calibration data in the lidar's storage, thereby reducing circuit area overhead. This calibration method helps meet the lidar's detection performance requirements while saving costs.

[0007] Optionally, the above calibration method further includes: determining second calibration data for the first detector set; determining third calibration data for the second detector set; performing a second calibration on the first detection result based on the second calibration data; and performing a second calibration on the second detection result based on the third calibration data.

[0008] In this way, multiple detector sets in the same detector group can share calibration data, and multiple detector sets in the same detector group can also share calibration data. The number of calibrations is increased through multi-level calibration, which helps to improve the accuracy of the detection results.

[0009] Optionally, the above calibration method may further include: performing a first calibration on the first detection result or the second detection result, and then performing a second calibration on the first detection result or the second detection result; or performing a second calibration on the first detection result or the second detection result, and then performing a first calibration on the first detection result or the second detection result; or fusing the first calibration data and the second calibration data / third calibration data, and performing the first calibration and the second calibration simultaneously.

[0010] Optionally, the first calibration is used for the first level calibration of the first detection result and the second detection result, and the second calibration is used for the second level calibration of the first detection result and the second detection result. The second level calibration is used to correct the result of the first level calibration and further improve the accuracy.

[0011] Optionally, the first detector set includes a first detector, the second detector set includes a second detector, and the first and second detectors are in operation within the same time window.

[0012] Optionally, the first detector includes multiple detectors, and the output signals of the multiple detectors are used to form point cloud data of a point in the point cloud of the lidar.

[0013] Optionally, the second detector includes multiple detectors, and the output signals of the multiple detectors in the second detector are used to form point cloud data of a point in the point cloud of the lidar.

[0014] Optionally, based on the first calibration data, a first calibration is performed on the first detection result of the first echo data and the second detection result of the second echo data, including: determining a first characteristic parameter of the lidar echo based on the first echo data; determining a first calibration value based on a first mapping relationship between the first characteristic parameter and the first calibration value, wherein the first calibration data includes the first mapping relationship; performing a first calibration on the first detection result based on the first calibration value; determining a second characteristic parameter of the lidar echo based on the second echo data; determining a second calibration value based on a second mapping relationship between the second characteristic parameter and the second calibration value, wherein the first calibration data includes the second mapping relationship; and performing a first calibration on the second detection result based on the second calibration value.

[0015] Optionally, the first detection result includes a first distance, and the second detection result includes a second distance; the first calibration data includes distance calibration data, which is used to calibrate the first distance and the second distance; the distance calibration data includes a third mapping relationship between the echo pulse width and the distance calibration value, or a fourth mapping relationship between the echo pulse width and the echo time calibration value.

[0016] Optionally, the first detection result includes a first reflectivity, and the second detection result includes a second reflectivity; the first calibration data includes reflectivity calibration data, which includes at least one of a fifth mapping relationship or a sixth mapping relationship. The fifth mapping relationship includes a mapping relationship between at least one of the echo peak value or echo area and the received power calibration value, and the sixth mapping relationship includes a mapping relationship between the laser intensity of the lidar and the transmitted power calibration value. The reflectivity calibration data is used to calibrate the first reflectivity and the second reflectivity.

[0017] Optionally, the above calibration method further includes: determining fourth calibration data for the laser receiving circuit; and performing a third calibration on the first and second detection results based on the fourth calibration data. All detectors in the same laser receiving circuit can share the fourth calibration data for the third calibration. The scope of application of the fourth calibration data can include detector arrays. Thus, further reuse of calibration data can reduce the storage space occupied by calibration data, thereby reducing costs.

[0018] Optionally, the fourth calibration data above may include one or more of the fifth or sixth mapping relationships above.

[0019] Optionally, the above calibration method also includes: performing ambient light calibration on the first echo data or the second echo data. Echo data can be used to determine the detection results; improving the accuracy of the echo data through ambient light calibration can improve the accuracy of the detection results.

[0020] In a second aspect, a calibration apparatus for a lidar is provided. The lidar's laser receiving circuit includes multiple detector groups. The calibration apparatus includes an interface circuit and a processing circuit. The interface circuit is configured to receive echo data from the multiple detector groups, and the processing circuit is configured to perform the calibration method described in the first aspect or any one of the first aspects.

[0021] Thirdly, a lidar is provided, including the calibration device described in the second aspect above.

[0022] Fourthly, a vehicle is provided, including the lidar described in the third aspect above.

[0023] Fifthly, a computer program product is provided, including instructions, wherein when the instructions are executed by a processor, the calibration method described in the first aspect or any of the first aspects is executed.

[0024] In a sixth aspect, a non-transitory computer-readable storage medium is provided, wherein instructions are stored therein, which, when executed by a processor, cause the processor to perform the calibration method described in the first aspect or any one of the first aspects. Attached Figure Description

[0025] The accompanying drawings used in this disclosure are briefly described below.

[0026] Figure 1 An example structural diagram of a lidar consistent with some embodiments of this disclosure is shown.

[0027] Figure 2 An example diagram of a detector array consistent with some embodiments of this disclosure is shown.

[0028] Figure 3 An example diagram of the arrangement of several one-dimensional detector arrays consistent with some embodiments of this disclosure is shown.

[0029] Figure 4 A structural example diagram of a calibration device consistent with some embodiments of this disclosure is shown.

[0030] Figure 5 A flowchart illustrating a calibration method consistent with some embodiments of this disclosure is shown.

[0031] Figure 6 An example diagram is shown that illustrates a mapping relationship between detection distance and distance coefficient, consistent with some embodiments of this disclosure.

[0032] Figure 7 An example diagram of a calibration curve consistent with some embodiments of this disclosure is shown.

[0033] Figure 8 A flowchart illustrating another calibration method consistent with some embodiments of this disclosure is shown.

[0034] Figure 9 An example diagram of a fifth or sixth mapping relationship consistent with some embodiments of this disclosure is shown.

[0035] Figure 10 An example diagram of an ambient light calibration curve consistent with some embodiments of this disclosure is shown. Detailed Implementation

[0036] LiDAR emits laser light during object detection. When the laser encounters an object, it is reflected by the object's surface, forming an echo. LiDAR receives this echo and converts it into an electrical signal. By processing this electrical signal, LiDAR can obtain information about the object, such as one or more of the following: distance, reflectivity, position, velocity, or three-dimensional structure.

[0037] LiDAR has found applications in numerous fields, including intelligent driving (e.g., autonomous or assisted driving), drones, robot recognition, geographic mapping, and environmental monitoring. In these applications, LiDAR can be mounted on vehicles, ships, aircraft (e.g., flying vehicles or drones), robots (e.g., industrial or domestic robots), or surveying equipment. LiDAR provides sensing data to these vehicles, enabling them to perform one or more functions such as analysis, decision-making, or control. For example, in intelligent driving scenarios, LiDAR is mounted on vehicles. As the vehicle moves, the LiDAR can detect the surrounding environment, acquire sensing data, and provide it to the vehicle so that it can make decisions or control based on this data.

[0038] LiDAR can include mechanical LiDAR, semi-solid-state LiDAR, or solid-state LiDAR. For example, solid-state LiDAR can include optical phase array (OPA) LiDAR or flash LiDAR.

[0039] Figure 1 A structural example diagram of a lidar consistent with some embodiments of this disclosure is shown. Please refer to... Figure 1 The lidar 100 includes a laser emitting circuit 110, a laser receiving circuit 120, an optical component 130, a control circuit 140, and a data processing circuit 150. During the detection process of the lidar 100, the laser emitting circuit 110 emits a laser beam. The laser beam is emitted through the optical component 130 and, upon encountering an object 10, is reflected by the surface of the object 10. At least a portion of the reflected light (which can be called an echo) is reflected back to the lidar 100. After passing through the optical component 130, the echo is received by the laser receiving circuit 120 and converted into an electrical signal. After processing by at least one processing circuit, information about the object 10 can be obtained.

[0040] The laser emitting circuit 110 may include a laser and a driving circuit (also known as an excitation source). The driving circuit drives the laser to emit laser light under the control of the control circuit 140. For example, the laser may include a semiconductor laser, a fiber laser, or other types of lasers. For example, a semiconductor laser may include an emitting circuit, a vertical-cavity surface-emitting laser (VCSEL), an edge-emitting laser (EEL), a distributed feedback laser (DFB), or similar devices. These are merely examples, and this disclosure does not limit the type of laser.

[0041] The laser receiving circuit 120 may include a detector and preprocessing circuitry. The detector uses the photoelectric effect to convert the echo into an electrical signal. For example, the detector may include a single-photon avalanche diode (SPAD) or a similar device. The above are merely examples, and this disclosure does not limit the type of detector.

[0042] Optical assembly 130 may include a emitting optical element and a receiving optical element. The emitting optical element is disposed on the emission path of the laser (hereinafter referred to as the emission optical path). The emitting optical element is used to shape the laser emitted by the laser and adjust the laser's exit path. The receiving optical element is disposed on the receiving path of the laser (hereinafter referred to as the receiving optical path). The receiving optical element is used to collect the echo reflected back from the object and converge the echo onto the photosensitive surface of the detector. For example, the emitting optical element may include one or more optical elements such as a mirror, lens, beam splitter, homogenizer, or beam splitter. For example, the receiving optical element may include one or more optical elements such as a mirror, lens, beam splitter, or filter. The emitting optical element and the receiving optical element may be independent of each other, partially reused, or fully reused. For example, the emitting optical element and the receiving optical element may use completely different components. Another example is that the emitting optical element and the receiving optical element share some components, or the emitting optical element and the receiving optical element use the exact same components.

[0043] For example, the processing of electrical signals may include one or more of the following operations: preprocessing the electrical signal to obtain echo data (or response data), analyzing the echo data to extract echo information, acquiring point cloud data based on the echo information, and assembling the point cloud data. For example, at least one processing circuit may include a preprocessing circuit and a data processing circuit 150. For example, preprocessing may include one or more of amplification, filtering, and digitization. The preprocessing circuit may include one or more of amplification circuits, filtering circuits, and digitization circuits. For example, an amplification circuit may include an amplifier, which can amplify the electrical signal converted by the detector, thereby improving the signal-to-noise ratio. A filtering circuit may include a filter, which can filter out noise or interference. A digitization circuit may include one or more of an analog-to-digital converter (ADC) or a time-to-digital converter (TDC). The preprocessing circuit can be used to preprocess the electrical signal to obtain echo data. For example, the preprocessing circuit may include an ADC, which can convert the analog electrical signal into a digital signal by periodically sampling the detector output signal to obtain echo data. For example, the preprocessing circuit may include a time-distribution monitoring (TDC) circuit. The TDC can measure the arrival time of the echo by sampling the time of the detector output signal to obtain echo data. For instance, the detector output signal may include a current signal, which can be converted into a voltage signal and compared with a reference voltage to generate an over-threshold signal provided to the TDC. Based on the received over-threshold signal, the TDC measures the over-threshold time of the signal, performing time sampling to obtain echo data. For example, the echo data may include data reflecting one or more echo characteristics, such as the arrival time or intensity of the echo. The arrival time includes the time it takes for the detector to receive the echo; for example, the arrival time may include one or more of the following: the leading edge time of the echo pulse, or the center (or amplitude) time of the echo pulse.

[0044] In some embodiments, the data processing circuit 150 can analyze the echo data to obtain echo information. The echo information may include one or more of the echo's characteristic parameters or detection results. The echo's characteristic parameters may include one or more parameters such as echo peak value, echo pulse width, echo slope, or echo area. The detection results may include one or more of the object's distance, reflectivity, position, or velocity. For example, the data processing circuit 150 can perform waveform analysis on the echo data to obtain one or more characteristic parameters. Alternatively, the data processing circuit 150 can determine the time of flight based on the echo data (e.g., the echo's arrival time), and use the time of flight to determine the object's distance. Or, the data processing circuit 150 can determine the time of flight based on the echo's arrival time, use the time of flight to determine the object's distance, and determine the object's position based on the distance. The content of the echo information may differ depending on the processing operation performed by the data processing circuit 150. The processing of the echo data can be implemented by a single data processing circuit or by multiple data processing circuits in stages. In some embodiments, the data processing circuit 150 may also determine the generation of point cloud data or the packaging of point cloud data based on echo information.

[0045] Data processing circuitry 150 may include one or more processors. For example, the processor may include one or more of the following: application-specific integrated circuit (ASIC), programmable logic device (PLD) circuitry, such as a field-programmable gate array (FPGA), microcontroller unit (MCU), digital signal processor (DSP), or central processing unit (CPU). This disclosure does not limit the number or type of processors included in the processing circuitry (e.g., preprocessing circuitry or data processing circuitry). Different processing circuits may include the same or different types of processors.

[0046] The data processing circuit 150 and the laser receiving circuit 120 can be fully or partially integrated together, or they can be set up independently. The control circuit 140 can be set up independently; or the control circuit 140 can be integrated with one or more data processing circuits, for example, integrated into a main control chip. In some embodiments, when multiple processing circuits are integrated, they can be implemented in the form of a system on chip (SOC).

[0047] In some embodiments, the laser receiving circuit 120 may include multiple detectors (e.g., a detector array). The laser receiving circuit 120 may also include a gating circuit. The gating circuit can select all or some of the detectors under the control of the control circuit 140. The multiple detectors may be arranged in a one-dimensional array or a two-dimensional array to form a one-dimensional or two-dimensional detector array.

[0048] Figure 2 An example diagram of a detector array consistent with some embodiments of this disclosure is shown. Please refer to... Figure 2 In this diagram, each square represents a detector, C represents a row, n represents the number of rows, R represents a column, and m represents the number of columns. n and m are positive integers. Detectors can be activated in various ways. For example, they can be activated by column (or row). Alternatively, they can be activated by multiple columns (or rows). Furthermore, two or more detectors in the same column (or row) can be activated simultaneously. Finally, two or more detectors in different columns (or rows) can be activated simultaneously. Figure 2 Taking n=15 and m=10 as an example, the detector array includes 15×10 detectors. Figure 2 Only one exemplary detector array arrangement is shown; other different arrangements are possible to meet the constraints of detector layout area or the requirements of transmit / receive alignment. For example, a lidar may include a one-dimensional detector array. Alternatively, a lidar may include multiple one-dimensional detector arrays. Figure 3 An example diagram showing the arrangement of several one-dimensional detector arrays consistent with some embodiments of this disclosure is provided. Please refer to... Figure 3 In this diagram, a circle represents a detector. Different one-dimensional detector arrays can be staggered in at least one direction (e.g., at least one of two mutually perpendicular directions on a circuit board). For example, one-dimensional detector arrays in different rows (or columns) can be staggered from each other, for example, Figure 3 (a) Detector arrays 310 and 320. For example, one-dimensional detector arrays in different rows (or columns) can be aligned, e.g., Figure 3 (b) Detector arrays 330, 340, and 350. Different one-dimensional detector arrays can be rotated at different angles, for example, Figure 3 (c) Detector arrays 360 and 370. For example, a lidar may include a single two-dimensional detector array. Alternatively, a lidar may include multiple two-dimensional detector arrays. Different two-dimensional detector arrays may be staggered in at least one direction (e.g., at least one of two mutually perpendicular directions on a circuit board), or different two-dimensional detector arrays may be rotated at different angles. The arrangement of multiple two-dimensional detector arrays is similar to the arrangement of a one-dimensional detector array, as can be found in [reference]. Figure 3 Related descriptions.

[0049] During the detection process, the echo data from a lidar system may be affected by environmental factors, differences in object reflectivity, and the lidar's own hardware characteristics. The detection results obtained based on the echo data may differ from the actual object information, affecting the accuracy of the detection results and thus the lidar's detection performance. In some embodiments, the detection results from the echo data can be calibrated to improve the accuracy of the detection results. Figure 4 A structural example diagram of a calibration device consistent with some embodiments of this disclosure is shown. Please refer to... Figure 4 The calibration device 400 includes an interface circuit 410 and a processing circuit 420. The interface circuit 410 can receive echo data from a detector array. The processing circuit 420 can calibrate the detection results of the echo data (e.g., the detection results of the detector array). For example, the processing circuit 420 can calibrate the detection results based on calibration data. The calibration data can be stored in the processing circuit (e.g., processing circuit 420) or the storage circuit of the lidar. In some embodiments, the processing circuit 420 may include one or more of a data processing circuit or a preprocessing circuit. For example, with... Figure 1 One or more of the data processing circuits or preprocessing circuits in the corresponding embodiments.

[0050] by Figure 2 Taking detector R5C6 as an example, the lidar (e.g., lidar 100) can generate corresponding echo data based on the echo received by detector R5C6. The lidar can then obtain the detection result of detector R5C6 based on this echo data. The lidar stores calibration data corresponding to detector R5C6. The processing circuit 420 can calibrate the detection result of detector R5C6 based on this calibration data. The lidar can set different calibration data for different detectors in the detector array. As the number of detectors increases, the amount of calibration data also increases. This may increase the lidar's storage overhead, which occupies a larger circuit area and increases the lidar's hardware cost.

[0051] Based on this, this disclosure provides a calibration method and apparatus for lidar, as well as a lidar solution, which can reduce the storage overhead of lidar. It meets the requirements of lidar for detection performance and storage capacity while saving costs. The following description is in conjunction with the accompanying drawings.

[0052] Figure 5 A flowchart illustrating a calibration method consistent with some embodiments of this disclosure is shown. This calibration method is used for lidar. For example, this calibration method can be performed by the processing circuit 420 described above. Please refer to... Figure 5 The calibration method includes at least the following steps:

[0053] S510: Receives first echo data from the first detector set and second echo data from the second detector set. The laser receiving circuit of the lidar includes a first detector group, which includes a first detector set and a second detector set.

[0054] S520: Determine the first calibration data for the first detector group;

[0055] S530: Based on the first calibration data, perform a first calibration on the first detection result of the first echo data and the second detection result of the second echo data.

[0056] In some embodiments, multiple detector sets within the same detector group can share the same calibration data. For example, first calibration data can be used to calibrate the detection results of multiple detector sets located within the same detector group. This reduces the amount of calibration data required for storage. This calibration method is advantageous for meeting the detection performance requirements of lidar while saving costs.

[0057] Please continue to refer to this. Figure 2 A detector array may include detector sets. A detector set may include at least one detector. In some embodiments, multiple detectors of the same detector set may be located in the same row or column. For example, detector set 210 includes detectors R4C3, R5C3, and R6C3. In some embodiments, multiple detectors of the same detector set may be located in different rows or columns, either wholly or partially. For example, detector set 220 includes detectors R3C10, R3C11, R3C12, and R4C10; and detector set 230 includes detectors R6C13 and R5C14. In some embodiments, the same column or row of a detector array may include multiple detector sets. In some embodiments, the output signals (e.g., electrical signals) of multiple detectors in the same detector set can be used to form point cloud data of a point in the point cloud of a lidar. For example, a first detector set includes a first detector, a first detector includes multiple detectors, and a first detector includes multiple detectors. Figure 2As shown, detector set 230 includes detectors R6C13 and R5C14. A first detector set can be detector set 230, and the first detector may include detectors R6C13 and R5C14. The output signals of detectors R6C13 and R5C14 can be used to form point cloud data of a point in the point cloud of a lidar. In some embodiments, the output signals of multiple detector sets within the same detector group can be used to form point cloud data of two different points in the point cloud of a lidar. For example, a first detector set includes a first detector, a second detector set includes a second detector, and the first and second detectors include multiple detectors. The output signals of the multiple detectors in the first detector are used to form point cloud data of a first point in the point cloud of the lidar, and the output signals of the multiple detectors in the second detector are used to form point cloud data of a second point in the point cloud of the lidar. In some embodiments, a detector includes multiple photosensitive areas, and different photosensitive areas can be connected to different pads. A gating circuit can activate the detector by gating the photosensitive areas through the pads. The photosensitive area may include one or more photosensitive devices (e.g., SPADs). For example, a detector set may include at least one photosensitive area.

[0058] Similarly, a detector array can include a group of detectors. A group of detectors can include at least one set of detectors. For example, a group of detectors can include at least one set of detectors in the same column or row. As another example, a group of detectors can include multiple sets of detectors at distances satisfying a preset distance. For instance, the distance between detector sets can include the distance between reference points of different detector sets, where the reference point can be any point on the detector set. For example, such as... Figure 2 As shown, detector group 260 includes detector set 240 and detector set 250. Detector set 240 includes detectors R8C11, R8C12, R8C13, R9C11, R9C12, and R9C13. Detector set 250 includes detectors R8C10, R9C10, R10C10, R10C11, R10C12, and R10C13. In some embodiments, multiple detector sets within the same detector group are operational within the same time window. For example, detector set 240 and detector set 250 are operational within the same time window. In some embodiments, multiple detectors within the same detector group are operational within the same time window. For example, a first detector set includes a first detector, a second detector set includes a second detector, and the first and second detectors are operational within the same time window. Figure 2As shown, detector R8C11 of detector set 240 and detector R8C10 of detector set 250 are in the same working state within the same time window. The working state can include a response optical signal state or an output electrical signal state. The response optical signal state means that the detector is activated by the gating circuit; the output electrical signal state means that the detector can convert the optical signal into an electrical signal and output it after being activated.

[0059] The calibration method described above will be explained below using detector group 260 as an example. For ease of distinction, detector set 240 can be referred to as the first detector set, detector set 250 as the second detector set, and detector group 260 as the first detector group. Each detector in the detector array can generate echo data from the echo received. For ease of distinction, the echo data generated based on the echo received by the first detector set can be referred to as the first echo data. The echo data generated based on the echo received by the second detector set can be referred to as the second echo data. The detection result obtained based on the first echo data can be referred to as the first detection result; the detection result obtained based on the second echo data can be referred to as the second detection result. The relevant descriptions of the echo data and detection results can be found in the foregoing embodiments.

[0060] The detection results may deviate from the true values ​​(e.g., the detection distance may differ from the actual distance to the object). Based on calibration data, the detection results of the echo data can be calibrated to compensate for these errors, thereby improving the accuracy of the detection results and enhancing the detection performance of the lidar. In some embodiments, calibration data for the detector group can be determined based on the index information of the detector group. The index information indicates the correlation between the detector group and the calibration data. For example, first calibration data for the first detector group can be determined based on the index information of the first detector group. The index information may include one or more types of information, such as position information or channel information. The position information indicates the relative position of the detector group within the detector array. Position information may include, for example, the position coordinates of a reference position on the detector group in a reference coordinate system. The calibration data for the detector group can be determined by indexing the position coordinates. The reference position can be the position of any point on the detector group. For example, the reference position may be the position of the upper left detector of the first detector group, and the position information may be the position coordinates of the upper left detector of the first detector group. In some embodiments, the reference coordinate system may be a world coordinate system or a lidar coordinate system, etc. Channel information indicates the independent path through which the lidar receives the echo. The independent path may include a path where one detector receives the echo, or a path where multiple detectors receive the echo. Channel information, such as channel identification (ID), may be included. For example, channel information may include the channel ID of a first detector group. In some embodiments, index information may be pre-stored in the lidar's data processing circuitry or storage circuitry, and the processing circuitry 420 may retrieve the index information through the data processing circuitry or storage circuitry.

[0061] In some embodiments, for multiple detector sets within the same detector group, their detection results can be calibrated using the same calibration data. For example, the first detection result of the first echo data and the second detection result of the second echo data can share calibration data (e.g., the first calibration data) for calibration (for ease of distinction, it can be referred to as the first calibration). In this way, calibration data can be reused, reducing data storage requirements. Figure 2As shown, detector group 260 includes detector set 240 and detector set 250. Detector set 240 and detector set 250 can share calibration data. Detector group 260 includes 12 detectors. If the calibration data sharing method is not used, each detector corresponds to different calibration data, and the lidar would need to store 12 sets of calibration data to meet calibration requirements. However, if the calibration data sharing method is used, these 12 detectors correspond to the same calibration data, and the lidar only needs to store one set of calibration data to meet the calibration requirements of all 12 detectors. While meeting calibration requirements, this reduces the storage space occupied by calibration data in the lidar, thereby reducing circuit area overhead and saving costs. In some embodiments, multiple detector sets within the same detector group can share calibration data, either wholly or partially. For example, when the number of detector sets in the same detector group is greater than or equal to 3, all or part of the detector sets in that detector group can share calibration data.

[0062] The calibration process based on calibration data is explained below.

[0063] In some embodiments, calibration data may include calibration values. Calibration values ​​can be determined at the factory through multiple tests before the LiDAR leaves the factory. In some embodiments, calibration values ​​can be positive or negative.

[0064] For example, calibration data may include calibration values ​​of the detection results. These calibration values ​​can be directly superimposed on the detection results to compensate for (or correct) them, resulting in calibrated detection results. For instance, a first detection result may include a detection distance, such as a first distance. First calibration data includes distance calibration data used to calibrate the first distance. The distance calibration data may include calibration values ​​of the first distance. These calibration values ​​can be superimposed on the first distance to compensate for it, resulting in a calibrated first distance. Similarly, a first detection result may include reflectivity. First calibration data may include reflectivity calibration data used to calibrate reflectivity. Reflectivity calibration data may include reflectivity calibration values. These calibration values ​​can be superimposed on the reflectivity to compensate for it, resulting in a calibrated reflectivity. In some embodiments, distance calibration data may be used to calibrate both a first and a second detection result. A second detection result may include a detection distance, such as a second distance. For example, a first detection result may include a first distance, a second detection result may include a second distance, and distance calibration data may be used to calibrate both the first and second distances, with the first and second distances sharing the same calibration data. For example, the first detection result includes the first reflectance, the second detection result includes the second reflectance, and the reflectance calibration data is used to calibrate the first reflectance and the second reflectance. The first reflectance and the second reflectance share the calibration data.

[0065] For example, calibration data may include the calibration value of a first influencing parameter. The first influencing parameter can be used to determine the detection result. This calibration value can be superimposed on the first influencing parameter to compensate for it, resulting in a calibrated first influencing parameter, thereby indirectly calibrating the detection result. The first influencing parameter may include one or more parameters such as a distance influencing parameter or a reflectivity influencing parameter. In some embodiments, the distance influencing parameter may include the echo time. In this case, the distance calibration data may include the calibration value of the echo time, such as the calibration value of the echo arrival time. The echo time can be used to determine the flight time, and the detection distance can be determined based on the flight time. The detection distance can be determined based on the calibrated echo time, indirectly calibrating the detection distance. Different objects have different reflectivities. Objects with high reflectivity have higher echo intensity, and the detector is more likely to receive the echo from a high-reflectivity object. When the distance between the lidar and the object is constant, the object's reflectivity affects the characteristic parameters of the echo. The echo time can be used to determine the flight time, thereby determining the detection distance. The influence of these characteristic parameters can lead to errors between the detected distance and the true distance value. By compensating for the echo time, the influence of object reflectivity (or echo intensity) can be reduced, enabling calibration of the detection range. In some embodiments, the reflectivity influence parameter may include one or more parameters such as received power, transmitted power, or range coefficient. The reflectivity of an object can be determined based on one or more of the lidar's received power information, transmitted power information, or range coefficient. For example, the reflectivity ref can be determined using the following formula:

[0066]

[0067] Where g(dist) represents the distance coefficient, P r P represents the received power. t represents the transmit power, and dist represents the detection range. According to formula (1), the reflectivity calibration data can include the received power P. r and transmit power P t The calibration data includes one or more of the following calibration values. Taking received power as an example, superimposing the received power calibration value onto the received power can compensate for the received power, which can then be used to determine the reflectivity, thereby indirectly calibrating the reflectivity. For example, the above reflectivity calibration data may also include one or more calibration values ​​from received power characterization data and transmitted power characterization data. For instance, the reflectivity (ref) can be determined using the following formula:

[0068]

[0069] Where K represents the distance constant and D represents the preset distance. The distance constant K is related to the preset distance D, and both K and D can be determined at the factory through multiple tests. Received power characterization data can include log2(P) r Transmit power characterization data can include log2(P) t According to formula (2), the reflectivity calibration data may include the received power P. r Transmit power P t Received power characterization data log2(P) r ), transmit power characterization data log2(P t One or more calibration values ​​in )

[0070] The distance coefficients mentioned above can be used to indicate the degree of attenuation during laser reflection. When the detection distance is greater than the preset distance, the distance coefficient is inversely proportional to the square of the detection distance; when the detection distance is less than or equal to the preset distance, there is a direct mapping relationship between the detection distance and the distance coefficient. Figure 6 An example diagram is shown that illustrates a mapping relationship between detection distance and distance coefficient, consistent with some embodiments of this disclosure. Figure 6 In the diagram, the horizontal axis x1 represents the detection distance, and the vertical axis y1 represents the distance coefficient. When x1 < D (preset distance), the data points are discretely distributed; when x1 ≥ D, y1 is inversely proportional to the square of x1. The distance coefficient can be used to determine reflectivity, and the distance coefficient will vary with different detection distances. By determining an accurate distance coefficient, the accuracy of reflectivity determination can be improved.

[0071] In some embodiments, calibration data may include a mapping relationship between characteristic parameters of the echo and calibration values. Based on this mapping relationship, a first calibration can be performed on a first detection result: based on the first echo data, a first characteristic parameter of the lidar echo is determined; based on the first mapping relationship between the first characteristic parameter and the first calibration value, a first calibration value is determined; based on the first calibration value, the first detection result is calibrated. Similarly, a first calibration can be performed on a second detection result based on the mapping relationship: based on the second echo data, a second characteristic parameter of the lidar echo is determined; based on the first mapping relationship between the second characteristic parameter and the second calibration value, a second calibration value is determined; based on the second calibration value, the second detection result is calibrated. The descriptions of determining characteristic parameters based on echo data and calibrating detection results based on calibration values ​​can be found in the foregoing embodiments. The mapping relationship can be represented by one or more of the following: calibration tables, calibration functions, or calibration curves. For example, the first calibration data may include a calibration curve, which may reflect multiple mapping relationships, such as the first and second mapping relationships described above.

[0072] In some embodiments, the characteristic parameters of the lidar echo may include the characteristic parameters of the echo from a single detector, or the characteristic parameters of the accumulated echo obtained by summing the echoes from multiple detectors. For example, the first characteristic parameter may include the characteristic parameters of the echo from a first detector. Alternatively, the first characteristic parameter may include the characteristic parameters of the accumulated echoes from a first detector set or a second detector set. Or, the first characteristic parameter may include the characteristic parameters of the accumulated echoes from a first detector group. The second characteristic parameter is similar to the first characteristic parameter and will not be described in detail here. Optionally, when the characteristic parameters of the lidar echo include the characteristic parameters of the accumulated echo, the first mapping relationship and the second mapping relationship are the same, and the first calibration value and the second calibration value are the same. In this way, the first detection result and the second detection result share calibration data, further reducing the storage overhead of the lidar.

[0073] The process of determining the first calibration value based on the first feature parameter and the first mapping relationship is described below. The process of determining the second calibration value based on the second feature parameter and the second mapping relationship is similar to the process of determining the first calibration value, and will not be described again.

[0074] In some embodiments, the first mapping relationship described above may include a direct mapping relationship between the first feature parameter and the first calibration value. For example, different values ​​of the first feature parameter may correspond to different first calibration values, and the first calibration value can be directly determined through the first feature parameter. The first calibration value may include one or more of the following:

[0075] In the first scenario, the first calibration value may include the calibration value of the detection result. For example, the first detection result includes a first distance, the first calibration data includes distance calibration data, and the first calibration value may include a distance calibration value used to calibrate the first distance. In this case, the distance calibration data may include a direct mapping relationship between a first characteristic parameter and the distance calibration value, and the distance calibration value can be directly determined through the first characteristic parameter. The first characteristic parameter may include one or more characteristic parameters such as echo pulse width, echo slope (e.g., the slope of the echo leading edge), echo area, or echo peak value. For a description of the characteristic parameters, please refer to the content of the foregoing embodiments. For example, the distance calibration data may include a direct mapping relationship between the echo pulse width and the distance calibration value, and the distance calibration value can be directly determined through the echo pulse width. Alternatively, the distance calibration data may include a direct mapping relationship between the slope of the echo leading edge and the distance calibration value, or a direct mapping relationship between the echo area and the distance calibration value, or a direct mapping relationship between the echo peak value and the distance calibration value. For example, the first detection result includes a first reflectance, the first calibration data may include reflectance calibration data, and the first calibration value may include a reflectance calibration value used to calibrate the first reflectance. In this case, the reflectance calibration data may include a direct mapping relationship between a first characteristic parameter and the reflectance calibration value, and the reflectance calibration value can be directly determined through the first characteristic parameter.

[0076] In the second scenario, the first calibration value may include the calibration value of one or more of the following parameters: distance-influencing parameters or reflectance-influencing parameters. For example, the first detection result includes a first distance, the first calibration data includes distance calibration data, and the first calibration value may be a distance-influencing parameter calibration value. In this case, the distance calibration data may include a direct mapping relationship between the first characteristic parameter and the distance-influencing parameter calibration value, allowing the distance-influencing parameter calibration value to be directly determined through the first characteristic parameter. For instance, the distance calibration data may include a direct mapping relationship between the echo pulse width and echo time calibration values, allowing the echo time calibration value to be directly determined through the echo pulse width. Similarly, the first detection result includes a first reflectance, the first calibration data may include reflectance calibration data, and the first calibration value may be a reflectance-influencing parameter calibration value. In this case, the reflectance calibration data may include a direct mapping relationship between the first characteristic parameter and the reflectance-influencing parameter calibration value, allowing the reflectance-influencing parameter calibration value to be directly determined through the first characteristic parameter. In this context, reflectivity calibration data may include one or more of the following mapping relationships: For example, a direct mapping relationship between at least one of the echo peak value or echo area and the received power calibration value (for ease of distinction, this can be referred to as the fifth mapping relationship), through which the received power calibration value can be directly determined; another example is a direct mapping relationship between the laser intensity of the lidar and the transmitted power calibration value (for ease of distinction, this can be referred to as the sixth mapping relationship), through which the received power calibration value can be directly determined; yet another example is a direct mapping relationship between at least one of the echo peak value or echo area and the received power characterization data calibration value (for ease of distinction, this can be referred to as the seventh mapping relationship), through which the received power characterization data calibration value can be directly determined; yet another example is a direct mapping relationship between the laser intensity of the lidar and the transmitted power characterization data calibration value (for ease of distinction, this can be referred to as the eighth mapping relationship), through which the transmitted power characterization data calibration value can be directly determined; the relevant descriptions of distance influence parameters and reflectivity influence parameters can be found in the foregoing embodiments.

[0077] In the case of a direct mapping relationship, for a calibration curve, the first calibration value lies on the calibration curve; for a calibration table, the first characteristic parameter can be directly indexed to determine the first calibration value; for a calibration function, the first characteristic parameter can be used as an independent variable, and the first calibration value can include the function value of the calibration function.

[0078] In some embodiments, the first mapping relationship may include an indirect mapping relationship between a first characteristic parameter and a first calibration value. For example, the first detection result includes a first distance, the first calibration data includes distance calibration data, and the first calibration value may be a distance influence parameter calibration value. The distance calibration data may include an indirect mapping relationship between the first characteristic parameter and the distance influence parameter calibration value, and the distance influence parameter calibration value can be indirectly determined through the first characteristic parameter. For example, the distance calibration data may include an indirect mapping relationship between echo pulse width and echo time calibration values, and the echo time calibration value can be indirectly determined through the echo pulse width. For ease of distinction, the third mapping relationship may include a direct or indirect mapping relationship between the echo pulse width and the distance calibration value; the fourth mapping relationship may include a direct or indirect mapping relationship between the echo pulse width and the echo time calibration value.

[0079] The above indirect mapping relationship will be explained below with reference to the calibration curve. Figure 7 An example diagram of a calibration curve consistent with some embodiments of this disclosure is shown. Assume there are four objects with different reflectivities, denoted as object 1, object 2, object 3, and object 4. The echo intensities of these four objects may differ. Under first emission conditions (e.g., the same laser intensity, wavelength, emission power, etc.), the lidar detects objects 1, 2, 3, and 4 located at preset positions, respectively, and obtains the corresponding echo data. Analyzing the echo data determines the echo times f0, f1, f2, and f3 of the echo pulses corresponding to objects 1-4, as well as the echo pulse widths w0, w1, w2, and w3. Objects 1-4 represent different echo intensities, the echo pulse widths corresponding to different objects represent the echo pulse widths under different echo intensities, and the echo times corresponding to different objects represent the echo times under different echo intensities. Plotting w as the x-axis and f as the y-axis yields... Figure 7 The curve in the figure. The above indirect mapping relationship can be used to indicate the correspondence between the first characteristic parameter and the distance influence parameter under different echo intensities. Figure 7 In this context, f_cali represents the reference value for the echo time. This reference value refers to the echo time received by the lidar when detecting an object at a preset position, excluding the influence of echo intensity. wt represents the echo pulse width, and ft represents the echo time. The first characteristic parameter can include the echo pulse width wt and the echo time ft. Based on the echo pulse width wt, the echo time ft, and the calibration curve, the echo time calibration value can be determined: such as... Figure 7As shown, the coordinates of point a are (wt, ft). If point a lies on the curve, the difference between f_cali and ft represents the echo time calibration value, as shown for points b (w1, f2) or c (w2, f1). For example, for point b, its echo time calibration value is δf1, and f2 + δf1 represents the calibrated echo time. For the case where point a is not on the calibration curve, assuming the adjacent pulse widths of wt are w1 and w2, ft falls between f1 and f2. δf1 represents the difference between f_cali and f2, and δf2 represents the difference between f_cali and f1. Based on the x-coordinate of point a, point d can be determined on the curve. The difference between f_cali and the y-coordinate of point d represents the echo time calibration value δft, and the calibrated echo time ft_cali = ft + δft. Thus, the echo time under different echo intensities can be compensated by the echo time calibration value δft under the corresponding pulse width, thereby eliminating the influence of the object's reflectivity on the detection distance and achieving calibration of the detection distance. In some embodiments, the echo time calibration value δft can be determined using interpolation. For example, linear interpolation can be used, and the echo time calibration value δft can be determined by the following formula:

[0080] δft=δf1×(w2-wt) / (w2-w1)+δf2×(wt-w1) / (w2-w1) (3)

[0081] Alternatively, other types of interpolation methods can be used to determine the echo time calibration value δft, such as Lagrange interpolation or Newton interpolation.

[0082] Furthermore, different emission conditions (e.g., different laser intensities) may affect the detection results, thus influencing the trend of the calibration curve. For example, different emission conditions can produce different calibration curves. In some embodiments, the calibration curve can be determined based on the current emission conditions of the lidar. For example, ce_gate represents the currently used laser intensity, and it is assumed that the two light intensities adjacent to ce_gate, ce_gate0 and ce_gate1, correspond to calibration curves L0 and L1, respectively. Based on L0 and L1, a similar calibration curve can be determined. Figure 7 The interpolation method used in this study determines the calibration values ​​δf3 and δf4 corresponding to the two calibration curves. Based on these two calibration values ​​δf3 and δf4, and according to the currently used laser intensity ce_gate, the calibration value δft' corresponding to the currently used laser intensity is further obtained using an interpolation method (e.g., linear interpolation). In this way, by using multiple interpolations, the influence of different emission conditions on the detection results is reduced, and the calibration effect is improved.

[0083] For example, the first detection result includes a first distance, the first calibration data includes distance calibration data, and the first calibration value may be a distance calibration value. The distance calibration data may include an indirect mapping relationship between a first characteristic parameter and the distance calibration value, through which the distance calibration value can be indirectly determined. For instance, the distance calibration data may include an indirect mapping relationship between the echo pulse width and the distance calibration value, through which the distance calibration value can be indirectly determined. In this case, Figure 7 The vertical axis can also be the detection distance. The process of determining the distance calibration value is similar to the process of determining the echo time calibration value through the calibration curve, as described above. Figure 7 The relevant description. In some embodiments, distance calibration data may include an indirect mapping between echo slope and distance calibration value, or an indirect mapping between echo area and distance calibration value, or an indirect mapping between echo peak value and distance calibration value. For example, Figure 7 The horizontal axis can also represent other characteristic parameters, such as the peak value, area, or slope of the echo pulse.

[0084] In some embodiments, multi-level calibration can be performed to further improve the calibration effect and enhance the accuracy of the detection results. Figure 8 A flowchart illustrating another calibration method consistent with some embodiments of this disclosure is shown. Please refer to... Figure 8 The above calibration methods also include:

[0085] S540: Determine the second calibration data for the first detector set;

[0086] S550: Determine the third calibration data for the second detector set;

[0087] S560: Perform a second calibration on the first detection result based on the second calibration data;

[0088] S570: Perform a second calibration on the second detection result based on the third calibration data.

[0089] Similar to the determination of the first calibration data, the second or third calibration data can also be determined using index information. For example, the index information may include the position coordinates of any point on the first or second detector set in a reference coordinate system. Alternatively, it may include the channel ID corresponding to the first or second detector set. The content of determining the second or third calibration data based on the index information can be referred to the description in the foregoing embodiments.

[0090] Please continue to refer to this. Figure 2Detector sets 240 and 250 of detector group 260 can share the first calibration data for the first calibration. Multiple detector sets within the same detector group can share calibration data to reduce the storage space occupied by calibration data. Furthermore, multiple detectors within the same detector set can also share calibration data for calibration (for ease of distinction, this can be referred to as the second calibration). For example, multiple detectors in the first detector set can share the second calibration data for the second calibration. Multiple detectors in the second detector set can share the third calibration data for the second calibration. Figure 2 As shown, detectors R8C11, R8C12, R8C13, R9C11, R9C12, and R9C13 of detector set 240 can share the second calibration data. Detectors R8C10, R9C10, R10C10, R10C11, R10C12, and R10C13 of detector set 250 can share the third calibration data. The second calibration process is similar to the first calibration process described above, and can be referred to the relevant content in the foregoing embodiments.

[0091] In some embodiments, calibration can be divided into different levels based on the applicability of the calibration data. For example, the detector range of the first-level calibration may overlap with that of the second-level calibration, and the detector range of the first-level calibration may be greater than or equal to that of the second-level calibration. For instance, the detector range of the first-level calibration may include a group of detectors, and the detector range of the second-level calibration may include a set of detectors, such as... Figure 2 As shown, the first-level calibration can be used to calibrate the detection results of detector group 260, and the second-level calibration can be used to calibrate the detection results of detector set 250. In this case, detector set 250 undergoes two calibrations. For example, the first-level and second-level calibrations can be used to calibrate the detection results of detector group 260. In this case, detector group 260 undergoes two calibrations. Thus, increasing the number of calibrations through multi-level calibration is beneficial for improving the accuracy of the detection results. In some embodiments, the scope of application of the first calibration data includes the first detector group, the scope of application of the second calibration data includes the first detector set, and the scope of application of the third calibration data includes the second detector set. In this case, the first calibration can be used for the first-level calibration of the first and second detection results, and the second calibration can be used for the second-level calibration of the first and second detection results.

[0092] In some embodiments, the first calibration and the second calibration can be used to calibrate the same detection result. For example, both the first calibration and the second calibration can be used to calibrate the detection distance or reflectivity. Alternatively, the first calibration and the second calibration can be used to calibrate different detection results. For example, the first calibration can be used to calibrate the detection distance, and the second calibration can be used to calibrate the reflectivity, etc. In some embodiments, the first calibration can be performed first, followed by the second calibration; or the second calibration can be performed first, followed by the first calibration; or the first calibration data and the second calibration data can be fused, and the first calibration and the second calibration can be performed simultaneously; or the first calibration data and the third calibration data can be fused, and the first calibration and the second calibration can be performed simultaneously. The types of detection results, the order of the first calibration and the second calibration, and the order of the first-level calibration and the second-level calibration can be arbitrarily combined. For example, the first calibration and the second calibration are used to calibrate the same detection results (e.g., both the first calibration and the second calibration are used to calibrate the detection distance), and the first calibration is a first-level calibration and the second calibration is a second-level calibration. Thus, the second-level calibration can be used to correct the calibration results of the first-level calibration, further improving accuracy.

[0093] In some embodiments, the calibration method further includes: determining fourth calibration data for the laser receiving circuit; and performing a third calibration on the first detection result and the second detection result based on the fourth calibration data. Multiple detectors in the same laser receiving circuit can share the fourth calibration data for the third calibration. The scope of application of the fourth calibration data may include detector arrays, to... Figure 2 For example, the fourth calibration data can be used for... Figure 2 The 15×10 detectors in the detector array are calibrated. At this time, each detector in the array shares a single set of calibration data. This further reuse of calibration data reduces the storage space required for calibration data, thereby reducing costs; and it also meets the calibration requirements of the lidar. Similarly, the fourth calibration data can also be obtained through index information, as described in the foregoing embodiments. The type of the third calibration can be the same as or different from the type of the first or second calibration. The order of the third calibration can be before or after the first or second calibration.

[0094] For example, the third calibration can be used to calibrate reflectivity, and the fourth calibration data can include one or more of the fifth, sixth, seventh, or eighth mapping relationships mentioned above. The fifth or sixth mapping relationship can be a direct proportional relationship. Figure 9An example diagram of a fifth or sixth mapping relationship consistent with some embodiments of this disclosure is shown. Figure 9 In the diagram, the horizontal axis x2 is proportional to the vertical axis y2, where x2 can represent the echo peak value or echo area, and y2 can represent the received power calibration value; alternatively, x1 can represent the laser intensity of the lidar, and y2 can represent the transmitted power calibration value. For example, the fourth calibration data may include a mapping relationship between the second influencing parameter and the distance calibration value or reflectivity calibration value. The magnitude of the second influencing parameter may affect the detection results. The second influencing parameter may include one or more parameters such as temperature or photon detection efficiency (PDE). In this case, performing the third calibration based on the fourth calibration data can reduce the influence of the second influencing parameter on the third detection results.

[0095] In some embodiments, the calibration method further includes: performing ambient light calibration on the first echo data or the second echo data. Figure 10 An example graph of an ambient light calibration curve consistent with some embodiments of this disclosure is shown. Please refer to... Figure 10 The horizontal axis *n* represents ambient light noise, and the vertical axis *p* represents characteristic parameters corresponding to different ambient light noise levels, such as echo peak value or echo area. Calibration curves L1, L2, and L3 show the trends of echo characteristic parameters with ambient light noise at different echo intensities. Taking the vertical axis *p* representing the echo peak value as an example... Figure 10 In the series n0-n3, ambient light noise increases sequentially, where n0 represents no ambient light noise. For example... Figure 10 As shown, the coordinates of point E are (nt, pt), where nt represents the current noise level and pt represents the echo peak value under the current noise level. Let the coordinates of point I be (n0, ptcali), where pt_cali represents the peak value after removing the influence of ambient light noise. The coordinates of point H are (n0, pt_1_0), and the coordinates of point J are (n0, pt_2_0). If nt falls within the interval n1-n2, then the coordinates of point F are (n1, pt_1), and the coordinates of point G are (n2, pt_2). pt_1 is located between p1_2 and p2_1, and pt_2 is located between p2_2 and p0_2, and pt_1 = pt_2 = pt. Figure 10 In this context, assuming a linear relationship between echo intensity and peak value within the peak range (vertical axis), and a linear relationship between peak value and ambient light noise for the same echo intensity within the noise range (horizontal axis), then the ratio of line segment JI to line segment IH is equal to the ratio of line segment GE to line segment EF. Using this ratio, the peak value pt_cali corresponding to n0 can be calculated.

[0096]

[0097] pt_cali represents the peak echo value after ambient light calibration. Ambient light calibration allows for the acquisition of echo data free from ambient light noise, improving the quality of the echo data and thus enhancing the accuracy of the detection results.

[0098] Furthermore, this disclosure also provides a computer-readable storage medium including instructions stored thereon, which, when invoked by a processor, allow any calibration method described in the embodiments of this disclosure to be executed. For example, the computer-readable storage medium may be non-transitory. For instance, the computer-readable storage medium may be a read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, random access memory (RAM) or other types of dynamic storage devices capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0099] This disclosure also provides a computer program product including instructions that, when invoked by a processor, execute any of the calibration methods described in the above embodiments.

[0100] In this disclosure, unless otherwise expressly specified and limited, ordinal numbers, such as "first," "second," etc., are used only to distinguish and describe related objects, and should not be construed as indicating or implying the relative importance or order between related objects. Furthermore, ordinal numbers do not represent the quantity of related objects. For example, "first detector" may include one detector or multiple detectors.

[0101] "Multiple" includes two or more, and other classifiers are similar.

[0102] The terms "or" and "and / or" in this disclosure are used to describe relationships between related objects, indicating a non-exclusive inclusion. For example, "A and / or B" and "A or B" can both include: "A alone," "B alone," or "A and B," where "A" and "B" can include a single object or multiple objects. Similarly, "A, B and / or C," "A, B or C," and "A, B and C" can both include: "A alone," "B alone," "C alone," "A and B," "A and C," "B and C," or "A, B and C," where "A," "B," and "C" can include a single object or multiple objects. Additionally, the " / " in this disclosure is used to indicate an "or" relationship between related objects. The meanings of "at least one of A or B" and "one or more of A and B" in this disclosure are the same as the meaning of "A or B" above. The meanings of "one or more of A, B, and C" and "at least one of A, B, or C" are the same as the meaning of "A, B, or C" above. The meaning of "one or more of A, B, and C" is the same as the meaning of "A, B, or C" above.

[0103] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not described in detail or in a particular embodiment can be referred to in the relevant descriptions of other embodiments. Furthermore, the above embodiments can be freely combined as needed.

Claims

1. A calibration method applied to a laser radar, comprising: receiving first echo data from a first set of detectors and second echo data from a second set of detectors, a laser receiving circuit of the laser radar comprising a first detector group, the first detector group comprising the first set of detectors and the second set of detectors; determining first calibration data for the first detector group; performing first calibration on first detection results of the first echo data and second detection results of the second echo data based on the first calibration data.

2. The calibration method of claim 1, wherein, Further comprising: determining second calibration data for the first set of detectors; determining third calibration data for the second set of detectors; performing second calibration on the first detection results based on the second calibration data; performing second calibration on the second detection results based on the third calibration data.

3. The method of calibration of claim 2, wherein, The first calibration is used for first-level calibration of the first detection results and the second detection results, the second calibration is used for second-level calibration of the first detection results and the second detection results, and the second-level calibration is used for correcting results of the first-level calibration.

4. The calibration method according to any one of claims 1 to 3, characterized in that, The first set of detectors comprises a first detector, and the second set of detectors comprises a second detector, the first detector and the second detector being in an active state within a same time window.

5. The method of calibration of claim 4, wherein, The first detector comprises a plurality of detectors, the plurality of detectors comprising the first detector, and output signals of the plurality of detectors being used to form point cloud data of a point in a point cloud of the laser radar.

6. The calibration method according to any one of claims 1 to 5, characterized in that, The performing first calibration on the first detection results of the first echo data and the second detection results of the second echo data based on the first calibration data comprises: determining first characteristic parameters of echoes of the laser radar based on the first echo data; determining first calibration values based on a first mapping relationship between the first characteristic parameters and the first calibration values, the first calibration data comprising the first mapping relationship; performing the first calibration on the first detection results based on the first calibration values; determining second characteristic parameters of echoes of the laser radar based on the second echo data; determining second calibration values based on a second mapping relationship between the second characteristic parameters and the second calibration values, the first calibration data comprising the second mapping relationship; performing the first calibration on the second detection results based on the second calibration values.

7. The method of calibration according to any of claims 1 to 6, characterized in that The first detection results comprise first distances, and the second detection results comprise second distances; The first calibration data comprises distance calibration data, the distance calibration data being used to calibrate the first distances and the second distances; The distance calibration data comprises a third mapping relationship between echo pulse widths and distance calibration values, or a fourth mapping relationship between the echo pulse widths and echo time calibration values.

8. The calibration method according to any one of claims 1 to 7, characterized in that, The first detection results comprise first reflectivities, and the second detection results comprise second reflectivities; The first calibration data includes reflectivity calibration data, the reflectivity calibration data includes at least one of a fifth mapping relationship or a sixth mapping relationship, the fifth mapping relationship includes a mapping relationship between at least one of a peak value of an echo or an echo area and a received power calibration value, and the sixth mapping relationship includes a mapping relationship between a laser intensity of the laser radar and a transmitted power calibration value, and the reflectivity calibration data is used to calibrate the first reflectivity and the second reflectivity.

9. The calibration method according to any one of claims 1 to 8, characterized in that, Further comprising: determining fourth calibration data for the laser receiving circuit; based on the fourth calibration data, performing third calibration on the first detection result and the second detection result.

10. The calibration method according to any one of claims 1 to 9, characterized in that, Further comprising: performing ambient light calibration on the first echo data or the second echo data.

11. A calibration device applied to a laser radar, for a laser radar, a laser receiving circuit of the laser radar including a plurality of detector groups, the calibration device including an interface circuit and a processing circuit, the interface circuit being configured to receive echo data from the plurality of detector groups, and the processing circuit being configured to perform the calibration method according to any one of claims 1-10.

12. A lidar, comprising: including the calibration device according to claim 11.

13. A vehicle characterized by, including the laser radar according to claim 12.

14. A non-transitory computer readable storage medium, comprising: The storage medium stores instructions, and the instructions, when executed by a processor, cause the processor to perform the method according to any one of claims 1-10.

Images