A data processing method of a laser radar, an electronic device, and a storage medium

Abstract

The application provides a data processing method of a laser radar, an electronic device and a storage medium. The method is applied to the technical field of laser radars. The laser radar comprises a transmitting unit and a receiving unit. One transmitting unit corresponds to N receiving units, and N is a natural number greater than 1. The method comprises the following steps: selecting echo signals of M receiving units, wherein M is less than or equal to N; and outputting detection information corresponding to a target object according to the echo signals of the M receiving units. The method is beneficial to reducing the process complexity of the laser radar and improving the detection accuracy and flexibility of the laser radar.

Description

Technical Field

[0001] This application relates to the field of lidar, and more specifically, to a lidar data processing method, electronic device, and storage medium. Background Technology

[0002] LiDAR is an active remote sensing device that uses photoelectric technology for detection. It combines photoelectric detection technology with laser technology and is an advanced detection method that uses laser as the detection light source.

[0003] In related technologies, the alignment design of LiDAR transceivers is often limited by equipment size, power consumption, and cost control requirements. The industry typically employs a line-source emission scheme to improve the alignment accuracy of the transmitting and receiving units, thereby indirectly optimizing the number of channel lines. However, current transceiver alignment designs place extremely high demands on the precision of the back-end packaging process, increasing process complexity. They also suffer from limited dynamic range and a lack of flexibility in signal acquisition, easily leading to decreased accuracy of detection results and failing to meet the detection needs of high-dynamic scenarios. Summary of the Invention

[0004] This application provides a data processing method, electronic device, and storage medium for lidar, which helps to reduce the manufacturing complexity of lidar and improve its detection accuracy and flexibility.

[0005] In a first aspect, a data processing method for a lidar is provided. The lidar includes a transmitting unit and a receiving unit, with one transmitting unit corresponding to N receiving units, where N is a natural number greater than 1. The method includes: selecting echo signals from M receiving units, where M ≤ N; and outputting detection information corresponding to a target object based on the echo signals from the M receiving units.

[0006] The aforementioned technical solution redefines the transceiver relationship of LiDAR, assigning a single transmitting unit to N receiving units. Depending on the real-time detection scenario, some receiving units can be selectively activated to output echo signals. This non-fixed alignment mode of "one transmitting unit corresponding to N receiving units" reduces the precision requirements for transceiver unit packaging and alignment, effectively controlling backend process costs and complexity. Dynamically selecting the operating state of the receiving units allows for real-time adjustment of the receiving link's coverage and signal acquisition accuracy, significantly improving detection flexibility. The flexible configuration of multiple receiving units enables the system to acquire richer echo signals, supporting accurate calculations by the data processing module and thus improving the accuracy of the detection results.

[0007] In conjunction with the first aspect, in some possible implementations, selecting the echo signals of the M receiving units includes: determining the number M of the receiving units to be selected based on the detection scenario of the lidar; determining the position information of the M receiving units to be selected based on a pre-calibrated spot offset; and selecting the echo signals of the M receiving units based on the number M of the receiving units to be selected and the position information.

[0008] In combination with the first aspect and the above implementation methods, in some possible implementation methods, determining the number M of the receiving units to be selected based on the detection scenario of the lidar includes: when the detection scenario of the lidar is a near-field detection scenario, determining that the number M of the receiving units to be selected satisfies the following condition: 1≤M<N.

[0009] The above technical solution, in near-field detection scenarios, selects some receiving units from N receiving units instead of all receiving units, thereby effectively suppressing background noise and improving the signal-to-noise ratio and accuracy of near-field measurements.

[0010] In combination with the first aspect and the above implementation, in some possible implementations, determining the number M of the receiving units to be selected based on the detection scenario of the lidar includes: when the detection scenario of the lidar is a far-field detection scenario, determining that the number M of the receiving units to be selected satisfies the following condition: 2≤M≤N.

[0011] In the far-field detection scenario, the above technical solution selects at least two echo signals from N receiving units, which facilitates the subsequent fusion or superposition of echo signals from multiple receiving units to improve the overall signal strength, increase the dynamic range of ranging, and enhance the detection probability and ranging capability.

[0012] In combination with the first aspect and the above implementation, in some possible implementations, selecting the echo signals of the M receiving units includes: determining the echo intensity of each of the echo signals received by the N receiving units; and selecting the echo signals of the M receiving units based on the echo intensity of each of the echo signals received by the N receiving units.

[0013] In combination with the first aspect and the above implementation, in some possible implementations, the step of outputting detection information of the target object based on the echo signals of the M receiving units includes: when M>1, fusing the echo signals of the M receiving units to obtain a fused signal; and outputting the detection information corresponding to the target object based on the fused signal.

[0014] In combination with the first aspect and the above implementation, in some possible implementations, the position of the transmitting unit corresponds to the center position of the N receiving units.

[0015] In the above technical solution, the position of the transmitting unit corresponds to the center position of N receiving units. This allows the detection light emitted by the transmitting unit to uniformly cover the N receiving units, ensuring that the echo signal reflected from the same target can be received by the N receiving units with approximately equal probability and intensity. This lays a good foundation for back-end signal processing and effectively improves the uniformity and reliability of detection.

[0016] In combination with the first aspect and the above implementation, in some possible implementations, the receiving array and transmitting array of the lidar at least partially include the correspondence in the first aspect or any possible implementation of the first aspect, wherein the correspondence refers to one transmitting unit corresponding to N receiving units.

[0017] In the above technical solution, at least part of the detection area formed by the transmitting and receiving arrays of the lidar adopts the one-to-many pairing relationship of "1 transmitting unit corresponds to N receiving units", while the remaining area can adopt the traditional one-to-one pairing relationship of "1 transmitting unit corresponds to 1 receiving unit", forming a differentiated layout, which is conducive to balancing detection performance and cost.

[0018] In a second aspect, an electronic device is provided, comprising: a memory for storing executable program code; and a processor for calling and running the executable program code from the memory, causing the electronic device to perform the method of the first aspect or any possible implementation thereof.

[0019] Thirdly, a computer program product is provided, comprising: computer program code, which, when run on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof.

[0020] Fourthly, a computer-readable storage medium is provided that stores computer program code, which, when executed on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof. Attached Figure Description

[0021] Figure 1 This is a schematic diagram illustrating the transmit / receive correspondence of a lidar according to an embodiment of this application;

[0022] Figure 2 This is a schematic diagram of another LiDAR transmit / receive correspondence provided in an embodiment of this application;

[0023] Figure 3 This is a schematic flowchart illustrating a data processing method for a lidar provided in an embodiment of this application;

[0024] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0025] The technical solutions in this application will be clearly and thoroughly described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in the text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more than two.

[0026] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0027] LiDAR (Light Detection and Ranging) is an active remote sensing device that uses photoelectric technology for detection. It combines photoelectric detection with laser technology, representing an advanced detection method that uses laser as the detection light source. LiDAR mainly consists of a transmitting module, a scanning control module, a receiving module, and a data processing module. It transmits a detection signal to the target using the transmitting module, then receives and processes the echo signal to obtain information such as the target's distance, reflectivity, velocity, and size. LiDAR equipment is characterized by high precision, strong anti-interference capabilities, high sensitivity, and is less affected by darkness. It is currently widely used in fields such as autonomous driving, vehicle-to-everything (V2X) communication, logistics vehicles, robotics, and intelligent public transportation.

[0028] Currently, LiDAR scanning methods are mainly divided into: 1) Mechanical rotation type: a motor drives the optical engine and hardware to rotate together; 2) Semi-solid type: only a few scanning devices rotate, while transceiver devices are fixed; 3) Solid-state LiDAR: all devices are fixed, and there are no scanning devices. Currently, mechanical rotation type can achieve a 360° circumferential scanning field of view (FOV), while semi-solid and solid-state types can only achieve a scanning field of view of about 120°, with a smaller coverage area.

[0029] In online scanning LiDAR, the mainstream receiving devices currently include avalanche photodiodes (APDs), single-photon imaging modules (SPIMs), and single-photon avalanche diodes (SPADs). SPAD devices are typically densely stacked, allowing for pixel binning to increase the number of transceiver channels. In the alignment design of online scanning LiDAR, due to limitations in equipment size, power consumption, and cost control, the industry typically employs a line-source emission scheme to improve the alignment accuracy between the transmitting and receiving units, thereby indirectly optimizing the number of channel lines.

[0030] However, the transmission and reception alignment of lidar in related technologies generally adopts a "one-to-one fixed correspondence" design mode, that is, one transmitting unit corresponds to one receiving unit, forming a unique signal transmission link. This design mode has the following technical problems:

[0031] First, the fixed alignment relationship places extremely high demands on the precision of the back-end packaging process, requiring strict matching between the transmitting and receiving optical axes, which directly increases the complexity of the process.

[0032] Second, the single-link signal reception mode limits the dynamic range of detection. When faced with scenarios such as sudden changes in target distance or multiple targets overlapping in complex environments, it is impossible to adjust the coverage of the receiving link according to actual detection needs.

[0033] Third, fixed correspondences lack the flexibility of signal acquisition, and the accuracy of detection results is easily reduced due to missed or invalid acquisition of echo signals, making it difficult to meet the detection needs of high dynamic scenarios.

[0034] It is evident that the aforementioned "one-to-one fixed correspondence" design pattern places extremely high demands on the precision of the back-end packaging process, increasing process complexity. It also suffers from limited dynamic range and a lack of flexibility in signal acquisition, easily leading to decreased accuracy and failing to meet the detection requirements of high-dynamic scenarios. Therefore, reducing the process complexity of lidar and improving its detection accuracy and flexibility have become urgent technical challenges.

[0035] To at least address the aforementioned technical problems, embodiments of this application provide a data processing method for lidar, which helps reduce the manufacturing complexity of lidar and improves its detection accuracy and flexibility. The execution entity of this lidar data processing method can be the data processing system within the lidar, or an electronic device communicatively connected to the lidar. This electronic device can be a mobile terminal such as a smartphone, tablet, or wearable device, or it can be a computer, cloud server, radar-assisted computer, or other equipment used in various application scenarios.

[0036] Specifically, in this embodiment, the transmit-receive correspondence of the lidar is redefined (also known as the transmit-receive alignment relationship), so that a single transmitting unit corresponds to N receiving units. Depending on the real-time detection scenario, some receiving units can be selectively activated to output echo signals. This non-fixed alignment mode of "one transmitting unit corresponding to N receiving units (hereinafter referred to as one-to-many)" reduces the precision requirements for the packaging and alignment of the transmitting and receiving units, effectively controlling the cost and complexity of the back-end processes. By dynamically selecting the operating state of the receiving units, the coverage and signal acquisition accuracy of the receiving link can be adjusted in real time, significantly improving detection flexibility. The flexible gating configuration of multiple receiving units enables the system to acquire richer echo signals, providing support for accurate calculations by the data processing module, thereby improving the accuracy of the detection results.

[0037] Figure 1 This is a schematic diagram of the transmit and receive correspondence of a lidar according to an embodiment of this application.

[0038] For example, such as Figure 1 As shown, the lidar includes a transmitting unit and a receiving unit, with one transmitting unit corresponding to two receiving units. For example, transmitting unit 101 corresponds to receiving units 201 and 202, transmitting unit 102 corresponds to receiving units 203 and 204, transmitting unit 103 corresponds to receiving units 205 and 206, and transmitting unit 104 corresponds to receiving units 207 and 208. The receiving units can be the aforementioned SPADs.

[0039] In practical implementation, a single VCSEL transmitter block can include one transmitter unit or integrate multiple transmitter units. For VCSEL transmitter blocks integrating multiple transmitter units, all transmitter units within the block can share a single drive circuit for common driving, eliminating the need for a separate drive circuit for each transmitter unit. This integrated design of multiple transmitter units significantly improves the overall integration of the LiDAR, aligning with the current trend of miniaturization and chip-based LiDAR development. Furthermore, because the transmitter units within the same VCSEL transmitter block exhibit high consistency in packaging technology and device parameters, signal deviation during multi-pixel signal merging (binning) can be effectively reduced, improving detection consistency among transmitter units and thus optimizing signal processing accuracy.

[0040] like Figure 1 As shown, a VCSEL transmitter block can consist of only transmitter unit 101, or it can integrate transmitter units 101 and 102, transmitter units 101, 102, and 103, or transmitter units 101, 102, 103, and 104. However, this embodiment does not specifically limit the number of transmitter units integrated in a single VCSEL transmitter block.

[0041] For example, in this embodiment, the spatial layout and optical phase surface design of the LiDAR transceiver unit are optimized collaboratively. The transmitting phase surface is the optical reference plane where the transmitting unit is located (i.e., the equivalent optical plane of the laser emission end of the transmitting unit). The receiving phase surface is the equivalent optical reference plane of the array composed of N receiving units (i.e., the set of planes containing the photosensitive areas of the N receiving units). The area of ​​the transmitting phase surface is smaller than that of the receiving phase surface. Only one transmitting unit is integrated within a single transmitting phase surface, while N receiving units corresponding to the transmitting unit are integrated within a single receiving phase surface.

[0042] For example, the position of the transmitting unit corresponds to the center position of the N receiving units, which allows the probe light emitted by the transmitting unit to uniformly cover the N receiving units.

[0043] In this example, in a one-to-many transmit-receive alignment architecture, the physical layout of the transmitting unit is optimized so that it corresponds to the optical center of the receiving area formed by the corresponding N receiving units. That is, the physical center of a single transmitting unit is precisely aligned with the geometric center of the array formed by the corresponding N receiving units, and the optical axis of the transmitting unit coincides with the geometric center of the array formed by the N receiving units.

[0044] like Figure 1As shown, taking N=2 as an example, the position of the transmitting unit 101 corresponds to the center of the receiving units 201 and 202, that is, the transmitting unit 101 is set on the symmetrical center line of the receiving units 201 and 202. This layout design allows the light spot formed by the detection beam emitted by the transmitting unit 101 after reflection by the target object to cover the effective photosensitive area of ​​the two receiving units with high symmetry. From the optical path perspective, this correspondence helps ensure that the echo signal reflected by the same target object can be received by the receiving units 201 and 202 with approximately equal probability and intensity, thus laying a good foundation for the subsequent signal processing and effectively improving the uniformity and reliability of the detection.

[0045] It should be noted that, Figure 1 The example provided uses N equal to 2 as an illustration. In actual implementation, N can be greater than 2, and this embodiment does not impose any specific limitations on this. Figure 1 This is a schematic diagram illustrating horizontal alignment between the transmitting and receiving units. In actual implementations, there are also... Figure 2 The vertical alignment method shown.

[0046] Figure 2 This is a schematic diagram of another LiDAR transmit / receive correspondence provided in an embodiment of this application.

[0047] For example, such as Figure 2 As shown, the transmitting and receiving units are vertically aligned, with one transmitting unit corresponding to two receiving units. For example, transmitting unit 101 corresponds to receiving unit 201 and receiving unit 202.

[0048] For example, the receiving and transmitting arrays of a lidar system at least partially include the one-to-many correspondence described above, where one transmitting unit corresponds to N receiving units. In other words, within the detection area formed by the lidar's transmitting and receiving arrays, at least a portion adopts the aforementioned one-to-many pairing relationship of "one transmitting unit to N receiving units," while the remaining area can retain the traditional one-to-one pairing relationship of "one transmitting unit to one receiving unit," forming a differentiated layout that helps balance detection performance and cost.

[0049] Optionally, the regions with the aforementioned one-to-many alignment relationships and the regions with the aforementioned one-to-one alignment relationships can be differentiated according to the different positions of the detection areas in the optical field of view. For example, the central detection area adopts the aforementioned one-to-many alignment relationship layout, while the edge detection areas adopt the aforementioned one-to-one alignment relationship layout.

[0050] The central detection area of ​​a lidar refers to the core field of view corresponding to the main detection direction of the lidar. It usually needs to meet the requirements of high resolution, large dynamic range and long-distance detection. Therefore, the above one-to-many alignment relationship can be arranged in the central detection area to achieve accurate capture of detailed features through dynamic gating of receiving units.

[0051] The edge detection area of ​​a lidar refers to the field of view located outside the central detection area and close to the boundary of the total field of view. The resolution and dynamic range requirements of the edge detection area are lower than those of the central detection area. Therefore, the basic detection requirements can be met by using the above one-to-one alignment in the edge detection area, while reducing the overall device cost and signal processing load of the detection array.

[0052] Through the above-described regional configuration scheme, the lidar in this application embodiment achieves the best balance between system resources and detection performance, that is, high-precision detection is achieved in the critical central detection area, while effective detection is ensured in the resource-constrained edge detection area, thereby optimizing the performance and cost of lidar as a whole.

[0053] Figure 3 This is a schematic flowchart of a data processing method for a lidar provided in an embodiment of this application.

[0054] For example, such as Figure 3 As shown, the data processing method of this lidar includes the following steps S301 to S302:

[0055] S301: Select echo signals from M receiving units, where M≤N.

[0056] As described above, in this embodiment, one transmitting unit corresponds to N receiving units. Therefore, the echo signals of M receiving units can be selected from the echo signals of N receiving units to achieve selection of at least some of the receiving units.

[0057] In this embodiment, the echo signals of M receiving units can be adaptively selected from N receiving units for output according to actual detection requirements, where M is greater than or equal to 1 and less than or equal to N.

[0058] For example, the above-mentioned implementation of S301 includes the following S3011 to S3013:

[0059] S3011: Determine the number M of receiver units to be selected based on the detection scenario of the lidar.

[0060] The detection performance requirements of lidar vary dynamically with scene parameters such as target distance and ambient light intensity. The number of gated receiving units M needs to match the characteristics of the detection scene. Different detection scenes have different requirements for signal-to-noise ratio, dynamic range, and resolution. Therefore, different numbers of receiving units need to be adapted. By gating the receiving units as needed, the receiving link is adapted to the performance requirements of different detection scenes.

[0061] In some embodiments, when the detection scene of the lidar is a near-field detection scene, it is determined that the number M of receiving units to be gated satisfies the following condition: 1 ≤ M < N.

[0062] In other embodiments, when the detection scene of the lidar is a far-field detection scene, it is determined that the number M of receiving units to be gated satisfies the following condition: 2 ≤ M ≤ N.

[0063] The near-field detection scene refers to the working scene when the lidar detects a nearby target. The far-field detection scene refers to the working scene when the lidar detects a distant target. The boundary threshold between the near-field detection scene and the far-field detection scene is not a fixed value but is determined by the optical parameters of the lidar (including but not limited to laser divergence angle, receiving field angle, transmit power, etc.). Exemplarily, a boundary distance threshold can be preset. When the estimated or measured distance of the detection target is less than this boundary distance threshold, it is determined that the current is in the near-field detection scene. When the estimated or measured distance of the detection target is greater than or equal to this boundary distance threshold, it is determined that the current is in the far-field detection scene.

[0064] In the near-field detection scene, the distance between the target object and the lidar is relatively close. At this time, after the detection light emitted by the transmitting unit is reflected by the target object, the spot energy on the receiving phase surface is concentrated and the signal intensity of the echo signal is high. If all N receiving units are enabled, it is easy to reduce the signal-to-noise ratio due to the oversaturation of the echo signal and the introduction of too much ambient background noise (background noise). Therefore, in this scene, it is preferably determined that M satisfies: 1 ≤ M < N, that is, some receiving units will be selected from the N receiving units, rather than all receiving units, thereby effectively suppressing the background noise and improving the signal-to-noise ratio and accuracy of near-field measurement. For example, the receiving units in the area where the spot energy is most concentrated can be selected, which can minimize the background noise while ensuring signal integrity. Optionally, in the near-field detection scene, the echo signal of 1 receiving unit can be selected from the N receiving units.

[0065] In far-field detection scenarios, the distance between the target object and the lidar is relatively large. In such cases, the echo signal experiences significant energy attenuation after long-distance transmission and is easily affected by atmospheric scattering, leading to a decrease in the signal-to-noise ratio. Therefore, it is determined that M satisfies 2≤M≤N, meaning that at least two echo signals from N receiving units are selected. This facilitates subsequent fusion or superposition of echo signals from multiple receiving units to improve the overall signal strength, increase the dynamic range of ranging, and enhance detection probability and ranging capability.

[0066] S3012: Determine the position information of the M receiving units to be selected based on the pre-calibrated spot offset.

[0067] This step aims to ensure that the selected M receiving units accurately cover the actual landing point of the light spot on the receiving unit, thereby maximizing signal collection efficiency. Combined with the light spot offset, the selected M receiving units are made to overlap as much as possible with the energy concentration area of ​​the actual echo light spot, avoiding signal omissions or invalid acquisitions due to light spot offset.

[0068] The spot offset can be understood as the deviation between the actual imaging position of the spot formed on the receiving unit by the probe light emitted by the transmitting unit after reflection from the target object and the optical axis of the receiving optical system (hereinafter referred to as the receiving optical axis). This deviation includes the offset distance and direction, such as how much it is offset to the left or to the right. The spot offset can also be understood as the offset distance and direction of the geometric center of the spot formed on the receiving unit by the probe light emitted by the transmitting unit after reflection from the target object and relative to the geometric center of the array composed of N receiving units.

[0069] The occurrence of beam offset is mainly due to the following two factors: near-field effect and degraded lidar performance.

[0070] Near-field effect-induced spot shift refers to the unexpected geometric shift in the imaging position of the light spot on the receiving array due to the parallax effect caused by the baseline distance between the transmitting and receiving optical paths in off-axis optical systems during close-range detection. Degradation of lidar performance-induced spot shift refers to the unintended, random spot shift resulting from changes in the alignment between the transmitting and receiving units caused by factors such as device aging, mechanical vibration, installation stress, or manufacturing errors.

[0071] The spot offset can be pre-calibrated. The following describes the optional calibration methods:

[0072] For example, during the assembly and adjustment of a lidar, the position of the probe light emitted by the transmitting unit on the receiving phase surface is already determined. The receiving phase surface integrates N receiving units corresponding to the transmitting unit. By selecting receiving units at different positions, the region where the receiving unit coincides with the light spot position is determined, and the offset of this region from the geometric center of the receiving array is calculated. This offset is used as the light spot offset.

[0073] For example, in the overall testing of a lidar system, a target plate can be placed at a specific calibration distance. This specific calibration distance can be determined based on the lidar's transmit / receive arrangement and transmit / receive interval. The reflectivity of the target plate is not limited, but a low-reflectivity target plate is generally preferred. The gating window of the receiving array is controlled to slide among N receiving units to sequentially select each receiving unit. The receiving area corresponding to the N receiving units contains the optimal receiving area after the transmitting unit emits the probe light. During the scanning process, the transmitting unit emits the probe light, and the signal strength of the echo signal received by the receiving unit at each gating position is recorded. The center position of the gating window corresponding to the maximum signal strength of the echo signal is the actual center position x of the light spot on the receiving array. The deviation of this actual center position x from the theoretical center position of the receiving optical axis is the required calibrated light spot offset.

[0074] For example, the method for determining the position information of M receiving units based on the spot offset can be as follows:

[0075] Using the center of the light spot after offset as a reference, and combining the value of M and the arrangement of the receiving units (linear array or area array), the range of continuous receiving units is determined. The offset center of the light spot is also the actual center position x of the light spot on the receiving array. Here, the offset center of the light spot is relative to the theoretical center position of the receiving optical axis. Under ideal design and alignment, this theoretical center position coincides with the geometric center of the array composed of N receiving units.

[0076] For example, if it's a linear array and M is odd, select M consecutive receiving units with the offset spot center as the midpoint. If M is even, select M consecutive receiving units with the offset spot center as the line of symmetry. If it's an area array, select a rectangular region composed of M receiving units with the offset spot center as the geometric center. This method determines the specific location index or address information of the M receiving units to be selected. For example, when N receiving units are linearly arranged and M=3, select the receiving unit corresponding to the offset spot center and its two adjacent receiving units to the left and right, forming three consecutive receiving units.

[0077] The spot offset determines the positions of the M receiving units to be selected, so that the final selected M receiving units are as close as possible to the areas covered by the spot. In other words, the M receiving units are in continuous positions, and the center position of the M receiving units can be determined based on the spot offset. Based on the center position, the position information of the M receiving units can be determined.

[0078] S3013: Select the echo signals of M receiving units based on the number M receiving units and the above location information.

[0079] For example, the scanning control module generates a gating control signal based on the M value determined by S3011 and the position information output by S3012, and sends the gating control signal to the unit gating circuit of the receiving module. The target receiving units, i.e., the selected M receiving units, are activated by switching between high and low levels. The activated M receiving units will capture the echo signal, while the inactive receiving units can remain in a turned-off state and not generate signal output to reduce power consumption.

[0080] In other embodiments, the above-mentioned selection of echo signals from M receiving units includes: determining the echo intensity of each of the echo signals received by N receiving units; and selecting the echo signals from M receiving units based on the echo intensity of each of the echo signals received by N receiving units.

[0081] In this embodiment, by evaluating the quality of the echo signals from N receiving units, the receiving unit with the highest signal-to-noise ratio is preferentially selected for output. Specifically, after the transmitting unit emits a probe light, all N receiving units corresponding to that transmitting unit receive the echo signal corresponding to the probe light, acquiring and recording the signal strength of the echo signal from each of the N receiving units. From the N receiving units, M receiving units whose echo signal strength falls within a pre-defined intensity threshold range are selected.

[0082] Understandably, an ideal, undisturbed echo signal should have a signal strength within a expected range. A weak signal may stem from the receiver unit not effectively covering the light spot, decreased device sensitivity, or obstruction; an excessively strong signal, or even saturation, can lead to ranging distortion and introduce nonlinear errors. Therefore, by setting a reasonable intensity threshold range, M receiver units operating at their optimal state can be selected.

[0083] The aforementioned intensity threshold range is not a fixed range; it is related to the target distance to ensure that the intensity threshold range at different distances meets the signal recognition requirements. Different target distances can correspond to their own intensity threshold ranges, which can be calibrated as follows:

[0084] At multiple known calibration distances (e.g., 5 meters, 50 meters, 100 meters, 150 meters), a standard reflectivity target plate is used as the target. The detection signal is emitted through the transmitting unit, and the signal strength (hereinafter referred to as echo strength) of the echo signal received by all N corresponding receiving units is recorded.

[0085] For each calibration distance, the ideal echo intensity range is determined based on the signal strength of the echo signals collected by N receiving units. Specifically, by analyzing the energy distribution pattern of the light spot corresponding to different echo intensities on the receiving array, the range of echo intensity corresponding to the ideal light spot that best matches the expected optical model is determined as the ideal echo intensity range for that calibration distance. The ideal echo intensity range is also known as the intensity threshold range. By statistically analyzing data from multiple calibration distances, a mapping relationship characterizing the distance and the intensity threshold range is constructed.

[0086] In actual detection, the distance to the target object is estimated using preliminary detection or data from the previous frame. Based on this distance, the mapping relationship between the distance and the intensity threshold range is looked up to obtain the corresponding intensity threshold range for that distance. The signal strength of the echo signals from N receiving units is compared with this intensity threshold range, and M receiving units whose signal strength falls within this intensity threshold range are selected.

[0087] S302: Based on the echo signals from the M receiving units, output the detection information corresponding to the target object.

[0088] This step aims to perform final processing on the echo signals from the M receiving units selected in the preceding steps to acquire and output the detection information of the target object. The specific implementation varies depending on the number of receiving units M selected, to adapt to the requirements of accuracy, signal-to-noise ratio, and data processing efficiency in different detection scenarios. The detection information corresponding to the target object includes the target object's distance information and / or reflectivity information.

[0089] When M=1, the echo signal from one receiving unit is transmitted to the data processing module, which processes the echo signal from that single receiving unit and outputs the detection information corresponding to the target object. For example... Figure 1As shown, when M=1, the echo signal from receiver 201 is selected from the two receivers corresponding to transmitter 101 and transmitted to the data processing module; the echo signal from receiver 202 is not output to the data processing module. Similarly, the echo signal from receiver 203 is selected from the two receivers corresponding to transmitter 102 and transmitted to the data processing module; the echo signal from receiver 204 is not transmitted to the data processing module. Likewise, the echo signal from receiver 205 is selected from the two receivers corresponding to transmitter 103 and transmitted to the data processing module; the echo signal from receiver 206 is not transmitted to the data processing module. Finally, the echo signal from receiver 207 is selected from the two receivers corresponding to transmitter 104 and transmitted to the data processing module; the echo signal from receiver 208 is not transmitted to the data processing module. The data processing module processes the echo signals from receiving unit 201, receiving unit 203, receiving unit 205, and receiving unit 207 (there may be other echo signals, which will not be discussed here) and outputs the detection information corresponding to the target object.

[0090] When M > 1, the echo signals from M receiving units are fused to obtain a fused signal; based on the fused signal, the detection information corresponding to the target object is output. In other words, the echo signals from multiple selected receiving units are fused to form a fused signal with a higher signal-to-noise ratio and stronger reliability, thereby improving the accuracy and stability of distance measurement.

[0091] For example, key parameters are extracted from the echo signals of M receiving units, mainly including: distance values ​​calculated based on the time-of-flight principle, and signal amplitudes characterized by peak voltage, energy integral, or amplitudes at specific feature points of the echo waveform. A preset amplitude threshold is set to distinguish between valid signals and noise. The signal amplitudes of each of the M receiving units are checked against this preset threshold. If the signal amplitude of a receiving unit is not greater than the preset threshold, its data is considered noise and does not participate in subsequent fusion, or is assigned a very low weight. Echo signals from receiving units with signal amplitudes greater than the preset threshold are retained for fusion to ensure the reliability of the fusion basis data. A weighting coefficient is assigned to each receiving unit participating in fusion. The weighting coefficient can be determined based on quality; for example, the larger the signal amplitude, the higher the assigned weighting coefficient. Alternatively, the weighting coefficient can be determined based on spatial location; for example, the closer the receiving unit is to the center of the light spot determined by the light spot offset, the higher its weighting coefficient. Based on the weighting coefficients of each receiving unit participating in fusion, the distance values ​​corresponding to the echo signals of the M receiving units are weighted and fused to obtain the distance value corresponding to the fused signal. Based on the weighting coefficients of each receiving unit participating in the fusion, the signal amplitudes corresponding to the echo signals of the M receiving units are weighted and fused to obtain the comprehensive amplitude of the fused signal, which is used for reflectivity estimation or signal quality assessment. Finally, the receiving module transmits the fused signal to the data processing module, which processes the fused signal and outputs the detection information corresponding to the target object.

[0092] The data processing module may receive multiple fused signals. For example... Figure 1 As shown, when M=2, in the two receiving units corresponding to transmitting unit 101, the echo signals from receiving unit 201 and receiving unit 202 are fused to obtain fused signal 1, which is then transmitted to the data processing module. In the two receiving units corresponding to transmitting unit 102, the echo signals from receiving unit 203 and receiving unit 204 are fused to obtain fused signal 2, which is then transmitted to the data processing module. In the two receiving units corresponding to transmitting unit 103, the echo signals from receiving unit 205 and receiving unit 206 are fused to obtain fused signal 3, which is then transmitted to the data processing module. In the two receiving units corresponding to transmitting unit 104, the echo signals from receiving unit 207 and receiving unit 208 are fused to obtain fused signal 4, which is then transmitted to the data processing module. The data processing module processes the received fused signals and outputs the detection information corresponding to the target object.

[0093] In summary, the embodiments of this application introduce a one-to-many transmit / receive alignment method and an adaptive signal gating and fusion mechanism, enabling the lidar to adaptively optimize its working mode according to different detection scenarios such as near-field and far-field. This effectively improves the signal-to-noise ratio of near-field detection and the sensitivity of far-field detection, significantly enhances ranging accuracy and dynamic range, and improves the lidar's robustness to optical offset and complex environments. Thus, the overall performance and reliability of lidar detection are comprehensively optimized.

[0094] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0095] For example, such as Figure 4 As shown, the electronic device 400 includes a memory 401 and a processor 402. The memory 401 stores executable program code 4011, and the processor 402 is used to call and execute the executable program code 4011 to perform a data processing method for a lidar.

[0096] Furthermore, this application also protects an apparatus that may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to perform a data processing method for lidar provided in this application.

[0097] This embodiment can divide the device into functional modules based on the above method example. For example, each module can correspond to a separate function, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0098] It should be understood that the device provided in this embodiment is used to execute the above-described data processing method for a lidar, and therefore can achieve the same effect as the above-described implementation method.

[0099] When using integrated units, the device may include a processing module and a storage module. When applied to an electronic device, the processing module can be used to control and manage the operation of the electronic device. The storage module can be used to support the execution of relevant program code by the electronic device.

[0100] The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits shown in conjunction with the disclosure of this application. The processor may also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc., and the storage module may be a memory.

[0101] In addition, the device provided in the embodiments of this application may specifically be a chip, component or module. The chip may include a connected processor and a memory. The memory is used to store instructions. When the processor calls and executes the instructions, the chip can execute a data processing method for a lidar provided in the above embodiments.

[0102] This embodiment also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the above-described related method steps to implement the data processing method for lidar provided in the above embodiment.

[0103] This embodiment also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned related steps to implement a data processing method for lidar provided in the above embodiment.

[0104] In this embodiment, the device, computer-readable storage medium, computer program product, or chip are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0105] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0106] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0107] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A data processing method for lidar, characterized in that, The lidar includes: a transmitting unit and a receiving unit, wherein one transmitting unit corresponds to N receiving units, and N is a natural number greater than 1; the method includes: When the detection scenario of the lidar is a near-field detection scenario, the number M of the receiver units to be selected is determined to satisfy the following condition: 1≤M<N; When the detection scenario of the lidar is a far-field detection scenario, the number M of the receiving units to be selected is determined to satisfy the following condition: 2≤M≤N; The position information of the M receiving units to be selected is determined based on the pre-calibrated spot offset. Based on the number M of the receiving units to be selected and the location information, select the echo signals of M receiving units, where M≤N; Based on the echo signals from the M receiving units, the detection information corresponding to the target object is output; The step of determining the position information of the M receiving units to be selected based on the pre-calibrated spot offset includes: Using the center of the light spot after offset based on the light spot offset amount as a reference, and combining the value of M and the arrangement of the receiving units, a continuous range of receiving units is determined. The arrangement is either a linear array or a surface array, and the center of the light spot after offset is the actual center position of the light spot on the receiving array. If the arrangement is a linear array and M is odd, then M consecutive receiving units with the offset spot center as the midpoint are selected; if M is even, then M consecutive receiving units with the offset spot center as the line of symmetry are selected. If the arrangement is a planar array, then a rectangular region composed of M receiving units with the offset spot center as the geometric center is selected.

2. The method according to claim 1, characterized in that, The step of outputting detection information of the target object based on the echo signals from the M receiving units includes: When M > 1, the echo signals from the M receiving units are fused to obtain a fused signal; Based on the fused signal, the detection information corresponding to the target object is output.

3. The method according to claim 1, characterized in that, The position of the transmitting unit corresponds to the center position of the N receiving units.

4. The method according to claim 1, characterized in that, The receiving array and transmitting array of the lidar at least partially include the correspondence as claimed in any one of claims 1 to 3, wherein the correspondence refers to one transmitting unit corresponding to N receiving units.

5. An electronic device, characterized in that, The electronic device includes: Memory, used to store executable program code; A processor for calling and running the executable program code from the memory, causing the electronic device to perform the method as described in any one of claims 1 to 4.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed, implements the method as described in any one of claims 1 to 4.

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