Lidar detection control method and device, and lidar

Abstract

The application relates to a detection control method and device of a laser radar and the laser radar, and the laser radar comprises a transmitter and a detector. The method comprises the following steps: before controlling the transmitter to emit detection light to a detection target, controlling the detector to receive an ambient light signal, and obtaining a pre-exposure histogram; wherein the ambient light signal is used for representing ambient interference in an environment where the laser radar is currently located; after controlling the transmitter to emit detection light to the detection target, controlling the detector to receive a detection signal, and obtaining a normal exposure histogram; and based on the pre-exposure histogram and the normal exposure histogram, obtaining a detection result of the detection target. By adopting the method, the detection accuracy of the detection target can be improved.

Description

Technical Field

[0001] This application relates to the field of lidar technology, and in particular to a lidar detection and control method, device, lidar, computer-readable storage medium, and computer program product. Background Technology

[0002] With the development of lidar technology, lidar is being used in more and more scenarios. The working principle of lidar is to emit light towards the target. Then, the received signal reflected back from the target is compared with the transmitted signal. By performing analysis and processing, parameters such as the target's distance, orientation, and altitude can be obtained.

[0003] However, when the lidar is in a scenario with environmental interference, the interference affects the lidar's detection performance, resulting in low accuracy in detecting targets. Summary of the Invention

[0004] Therefore, it is necessary to provide a detection and control method, device, lidar, computer-readable storage medium, and computer program product for lidar that can improve the detection accuracy of targets, in order to address the above-mentioned technical problems.

[0005] In a first aspect, this application provides a detection and control method for a lidar. The lidar includes a transmitter and a detector, and the method includes:

[0006] Before controlling the transmitter to emit detection light toward the target, the detector is controlled to receive ambient light signals to obtain a pre-exposure histogram; wherein, the ambient light signals are used to characterize the environmental interference in the current environment of the lidar.

[0007] After controlling the transmitter to emit detection light toward the target, the detector is controlled to receive the detection signal and obtain a normal exposure histogram;

[0008] The detection result of the target is obtained based on the pre-exposure histogram and the normal exposure histogram.

[0009] In one embodiment, the pre-exposure histogram includes the pre-exposure histogram of any frame, the normal exposure histogram includes the normal exposure histogram of any frame, each frame includes multiple subframes, there is a time interval between the multiple subframes, and normal exposure and pre-exposure alternate within each subframe, the cumulative duration of normal exposure and pre-exposure within each subframe is equal, the pre-exposure is used to characterize the detector receiving the ambient light signal, and the normal exposure is used to characterize the detector receiving the detection signal;

[0010] The step of obtaining the detection result of the target based on the pre-exposure histogram and the normal exposure histogram includes:

[0011] The detection result of the target in any given frame is obtained by accumulating the pre-exposure histogram and normal exposure histogram of all subframes within any given frame.

[0012] In one embodiment, obtaining the detection result of the target based on the pre-exposure histogram and the normal exposure histogram includes:

[0013] Obtain the difference histogram between the normal exposure histogram and the pre-exposure histogram;

[0014] If the target difference value in the difference histogram is less than 0, the target difference value is adjusted; wherein, the target difference value is used to characterize the difference between the light intensity in the normal exposure histogram and the light intensity in the pre-exposure histogram;

[0015] Based on the adjusted difference histogram, the detection result of the target is obtained.

[0016] In one embodiment, adjusting the target difference includes:

[0017] The target difference is adjusted to the light intensity corresponding to the target difference in the normal exposure histogram;

[0018] Alternatively, the target difference can be adjusted to a preset value.

[0019] In one embodiment, the detector includes pixels corresponding to different field of view angles, and the pre-exposure histogram includes the pre-exposure histogram of any frame; controlling the detector to receive ambient light signals includes:

[0020] Based on the pre-exposure histogram of a specific frame whose time interval with the current frame is less than a preset value, the actual fitting relationship between the frame and the noise baseline under different field of view angles is determined.

[0021] When the similarity between the actual fitting relationship and the theoretical fitting relationship is greater than a threshold, the ambient light signal is controlled to be received based on the pixel corresponding to the target field of view in any frame; wherein, the target field of view and the central field of view have a corresponding relationship.

[0022] In one embodiment, the detector includes pixels corresponding to different field of view angles, and controlling the detector to receive ambient light signals includes:

[0023] When preset conditions are met, the system controls the reception of ambient light signals in any frame based on the representative pixels corresponding to the full field of view.

[0024] In one embodiment, the preset conditions include:

[0025] The continuous cumulative frame rate of non-full-field pre-exposure reaches the preset frame rate.

[0026] And / or,

[0027] The noise reference under the target field of view in the pre-exposure histogram of the previous frame is greater than the reference threshold; wherein, the target field of view corresponds to the center field of view.

[0028] In one embodiment, the detector includes pixels corresponding to different field of view angles; controlling the detector to receive detection signals includes:

[0029] Control all pixels corresponding to the full field of view to receive detection signals.

[0030] Secondly, this application also provides a detection and control device for lidar. The device includes:

[0031] The first control module is used to control the detector to receive ambient light signals and obtain a pre-exposure histogram before controlling the transmitter to emit detection light towards the detection target; wherein, the ambient light signals are used to characterize the environmental interference in the current environment of the lidar.

[0032] The second control module is used to control the detector to receive the detection signal and obtain a normal exposure histogram after controlling the transmitter to emit detection light toward the detection target.

[0033] The processing module is used to obtain the detection result of the target based on the pre-exposure histogram and the normal exposure histogram.

[0034] Thirdly, this application also provides a lidar. The lidar includes: a transmitter, a detector, and a controller communicatively connected to the transmitter and the detector;

[0035] The transmitter is used to emit detection light toward the detection target;

[0036] The detector is used to receive ambient light signals or detection signals; wherein the ambient light signals are used to characterize the environmental interference in the current environment of the lidar.

[0037] The controller is used to control the transmitter and the detector to perform the steps of the method described in the first aspect or any one of the first aspects.

[0038] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0039] Before controlling the transmitter to emit detection light toward the target, the detector is controlled to receive ambient light signals to obtain a pre-exposure histogram; wherein, the ambient light signals are used to characterize the environmental interference in the current environment of the lidar.

[0040] After controlling the transmitter to emit detection light toward the target, the detector is controlled to receive the detection signal and obtain a normal exposure histogram;

[0041] The detection result of the target is obtained based on the pre-exposure histogram and the normal exposure histogram.

[0042] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0043] Before controlling the transmitter to emit detection light toward the target, the detector is controlled to receive ambient light signals to obtain a pre-exposure histogram; wherein, the ambient light signals are used to characterize the environmental interference in the current environment of the lidar.

[0044] After controlling the transmitter to emit detection light toward the target, the detector is controlled to receive the detection signal and obtain a normal exposure histogram;

[0045] The detection result of the target is obtained based on the pre-exposure histogram and the normal exposure histogram.

[0046] The aforementioned lidar detection control method, device, lidar, computer-readable storage medium, and computer program product, before controlling the transmitter to emit detection light towards the target, can obtain a pre-exposure histogram by controlling the detector to receive ambient light signals. Based on the pre-exposure histogram, environmental interference in the lidar's current environment can be identified. Furthermore, after controlling the transmitter to emit detection light towards the target, a normal exposure histogram is obtained by controlling the detector to receive detection signals. By considering environmental interference in the lidar's current environment, the detection accuracy can be improved by using both the pre-exposure and normal exposure histograms to detect targets in environmental interference. Attached Figure Description

[0047] Figure 1 This is a block diagram of the lidar structure in one embodiment;

[0048] Figure 2 This is a flowchart illustrating the detection and control method of a lidar in one embodiment;

[0049] Figure 3This is a schematic diagram illustrating the principle of lidar exposure in one embodiment;

[0050] Figure 4 This is a schematic diagram of a process for obtaining the detection result of a target based on a pre-exposure histogram and a normal exposure histogram in one embodiment.

[0051] Figure 5 This is a schematic diagram of the process of controlling the detector to receive ambient light signals in one embodiment;

[0052] Figure 6 This is a schematic diagram of pixels in a detector in one embodiment;

[0053] Figure 7 This is a flowchart illustrating the detection and control method of a lidar in another embodiment;

[0054] Figure 8 This is a structural block diagram of the detection and control device for a lidar in one embodiment. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0056] Currently, LiDAR products consist of a transmitter and a detector. The transmitter emits a signal towards the target, and the detector detects the signal reflected by the target. Thus, LiDAR can obtain parameters such as the target's distance, azimuth, and altitude using the emitted and reflected signals (collectively referred to as the detection signals). The detector contains pixels, and each pixel contains a single-photon avalanche diode (SPAD). To increase angular resolution within a smaller size, each pixel needs to contain fewer SPADs, but this affects the signal-to-noise ratio of each pixel, especially in environments with interference, such as strong sunlight outdoors or low-reflectivity scenarios, which can impact the LiDAR's ranging performance. Increasing the number of SPADs per pixel leads to a decrease in angular resolution or an increase in the size of the photosensitive element (sensor).

[0057] In view of this, without changing the physical dimensions of the current lidar product or affecting its angular resolution, this application provides a lidar detection and control method, which can be applied to applications such as... Figure 1 In the environment shown. Figure 1In this system, the lidar 100 includes a transmitter 102, a detector 104, and a controller 106 communicatively connected to the transmitter 102 and the detector 104. The transmitter 102 is used to emit detection light toward the target, and the detector 104 is used to receive detection signals or ambient light signals.

[0058] Specifically, before the controller 106 controls the transmitter 102 to emit detection light towards the target, it controls the detector 104 to receive the ambient light signal and obtain a pre-exposure histogram. After the controller 106 controls the transmitter 102 to emit detection light towards the target, it controls the detector 104 to receive the detection signal and obtain a normal exposure histogram. Then, based on the pre-exposure histogram and the normal exposure histogram, the controller 106 can obtain the detection result of the target.

[0059] In one embodiment, such as Figure 2 As shown, a detection and control method for lidar is provided, which is applied to... Figure 1 Taking controller 106 as an example, the explanation includes the following steps:

[0060] S202, before controlling the transmitter to emit detection light toward the detection target, controls the detector to receive the ambient light signal and obtain a pre-exposure histogram.

[0061] In this embodiment, the detector includes multiple pixels (the pixels can be SPADs). Before the transmitter emits detection light towards the target, the detector will not detect the reflected signal. At this time, activation can detect ambient light and obtain the ambient light signal corresponding to the ambient light. The ambient light signal is used to characterize the ambient noise level in the current environment of the lidar. Furthermore, based on the ambient light signal, the controller can obtain a pre-exposure histogram corresponding to the ambient light signal. The horizontal axis of the pre-exposure histogram refers to the counting time, which refers to the time when the detector receives the ambient light signal, and the vertical axis refers to the signal intensity of the ambient light signal.

[0062] S204: After controlling the transmitter to emit detection light toward the target, the detector is controlled to receive the detection signal and obtain a normal exposure histogram.

[0063] In this embodiment, the detector includes multiple pixels. After the transmitter emits a detection light towards the detection target, the detector can detect the reflected light of the detection light based on the multiple pixels, thereby obtaining a detection signal that includes ambient light and reflected light. Then, based on the detection signal, the controller can obtain a normal exposure histogram corresponding to the detection signal.

[0064] In the normal exposure histogram, the horizontal axis represents the counting time, which is the time it takes for the detector to receive the detection signal, and the vertical axis represents the intensity of the detection signal. It should be understood that when the detection light encounters the target, the target will reflect the detection light back to the lidar, allowing the detector to detect the reflected light.

[0065] In some embodiments, the detector includes pixels corresponding to different field of view angles. Specifically, the controller can control all pixels corresponding to the full field of view angle to receive the detection signal, that is, the detection signal can be received based on all pixels corresponding to the full field of view angle.

[0066] S206, based on the pre-exposure histogram and the normal exposure histogram, obtains the detection results of the target.

[0067] In this embodiment, since the ambient light signal is used to characterize environmental interference in the current environment of the lidar, the external environment can be identified through the pre-exposure histogram. Therefore, based on the pre-exposure histogram, noise floor information can be provided for the normal exposure histogram. Consequently, when obtaining the detection results of the target based on the pre-exposure histogram and the normal exposure histogram, the detection accuracy can be improved.

[0068] In this embodiment, the detection results include, but are not limited to, the position and speed of the detected target. The detection results can be obtained based on the difference histogram between the pre-exposure histogram and the normal exposure histogram. The horizontal axis of the difference histogram represents the counting time, which is the time it takes for the detector to receive the detection signal. The vertical axis represents the signal intensity, which refers to the light intensity of the target signal. The target signal is the signal obtained by subtracting the detection signal from the ambient light signal. The time it takes for the detector to receive the detection signal is also the time it takes for the detector to receive the ambient light signal.

[0069] Specifically, the counting time corresponding to the maximum light intensity in the difference histogram is determined as the target counting time. Based on the emission time of the probe light emitted by the transmitter, the target counting time, and the propagation speed of the probe light, the position of the target is obtained.

[0070] In summary, based on Figure 2The method shown allows for the acquisition of a pre-exposure histogram by controlling the detector to receive ambient light signals before the transmitter emits probe light towards the target. This pre-exposure histogram enables the identification of environmental interference in the current environment of the lidar. Although normal detection signals include ambient light information, the presence of other interferences, such as crosstalk, can lead to a low signal-to-noise ratio, making it impossible to distinguish how the noise signal was generated. Conversely, by determining and eliminating ambient light noise levels in advance, the detection signal and other types of interference can be identified more clearly. Furthermore, after the transmitter emits probe light towards the target, the detector receives the probe signal to obtain a normal exposure histogram. By considering environmental interference in the current environment of the lidar, the detection accuracy can be improved by using both the pre-exposure and normal exposure histograms to detect targets in environmental interference.

[0071] In one embodiment, such as Figure 3 The diagram illustrates a flowchart for obtaining target detection results based on pre-exposure histograms and normal exposure histograms. This method is then applied to… Figure 1 Taking control 106 as an example, the steps include:

[0072] S302, obtains the difference histogram between the normal exposure histogram and the pre-exposure histogram.

[0073] In this embodiment, a difference histogram can be obtained by subtracting the normal exposure histogram and the pre-exposure histogram. In this histogram, the horizontal axis represents the counting time, and the vertical axis represents the signal intensity. In the normal exposure histogram, the counting time refers to the time it takes for the detector to receive the detection signal, and the signal intensity refers to the intensity of the detection signal. Similarly, in the pre-exposure histogram, the counting time refers to the time it takes for the detector to receive the ambient light signal, and the signal intensity refers to the intensity of the ambient light signal.

[0074] Specifically, the light intensity in the normal exposure histogram and the light intensity in the pre-exposure histogram can be subtracted within multiple counting time periods to obtain the light intensity difference within multiple counting time periods. Based on the light intensity difference within multiple counting time periods, a difference histogram can be obtained.

[0075] It should be understood that the pre-exposure histogram can identify environmental interference in the current environment of the LiDAR. Therefore, by subtracting the normal exposure histogram from the pre-exposure histogram, the environmental interference in the normal exposure histogram can be removed. In other words, the difference histogram represents the histogram after the environmental interference has been removed.

[0076] S304, if the target difference in the difference histogram is less than 0, adjust the target difference.

[0077] In this embodiment, the target difference is used to characterize the difference between the light intensity in the normal exposure histogram and the light intensity in the pre-exposure histogram. When the target difference is less than 0, it indicates that the light intensity in the probe signal histogram is less than the light intensity in the ambient light signal histogram. This is due to the fluctuation of the environment and the fact that the pre-exposure and normal exposure occur at different times. The light intensity of the ambient light signal detected in the ambient light signal histogram may be greater than the light intensity of the ambient light signal detected in the probe signal histogram. Therefore, when subtracting the probe signal histogram from the ambient light signal histogram, the target difference may be less than 0. Therefore, to avoid detection errors, the ambient noise in the probe signal histogram when the target difference is less than 0 can be adjusted; that is, the target difference is adjusted when the target difference in the difference histogram is less than 0.

[0078] In some embodiments, the target difference can be adjusted to a preset value, which includes 0 or other values. In this embodiment, the preset value is 0.

[0079] S306. Based on the adjusted difference histogram, the detection results of the target are obtained.

[0080] The method for obtaining the detection results of the target based on the adjusted difference histogram can be described in accordance with the content of S206, and will not be repeated here.

[0081] In summary, based on Figure 3 The method shown can obtain the detection result of the target based on the difference histogram between the normal exposure histogram and the pre-exposure histogram. Thus, by removing environmental interference in the normal exposure histogram, the detection accuracy of the target can be improved.

[0082] It should be understood that lidar can detect targets in real time. That is, lidar will continuously emit multiple frames of detection light to detect targets in real time. Therefore, lidar can achieve real-time detection of targets based on the detection results of each frame.

[0083] In one embodiment, the pre-exposure histogram includes the pre-exposure histogram of any frame, the normal exposure histogram includes the normal exposure histogram of any frame, any frame includes multiple subframes, there is a time interval between the multiple subframes, and normal exposure and pre-exposure alternate within each subframe, the cumulative duration of normal exposure and pre-exposure within each subframe is equal, the pre-exposure is used to characterize the detector receiving the ambient light signal, and the normal exposure is used to characterize the detector receiving the detection signal.

[0084] The time interval refers to the time interval between adjacent subframes within any given frame. Each subframe forms a row or column of data, and multiple subframe data are stitched together to form a complete frame. The cumulative pre-exposure time within each subframe refers to the time the detector receives the ambient light signal within each subframe, and the cumulative normal exposure time within each subframe refers to the cumulative time the detector receives the detection signal within each subframe.

[0085] It should be understood that when the cumulative duration of normal exposure and pre-exposure within each subframe is equal, the cumulative duration of normal exposure and pre-exposure within a single frame is also equal. This ensures a balance in the cumulative number of histograms calculated by the LiDAR during pre-exposure and normal exposure, thus accurately measuring the ambient light level. Furthermore, because normal exposure and pre-exposure alternate with a very short interval, abrupt changes in ambient light can be avoided, resulting in more uniform and reliable measurement of ambient light information.

[0086] It should be noted that within each subframe, the transmitter emits probe light multiple times, and within each subframe, pre-exposure and normal exposure alternate, thereby obtaining continuously changing ambient light information. For example... Figure 4 As shown, a schematic diagram of the principle of lidar exposure is provided. Figure 4 The laser in the image is the transmitter. It can be seen that one frame consists of multiple subframes. Within each subframe, the transmitter emits four probe beams (i.e., the laser emits four beams). Before each probe beam emission, the lidar detector performs a pre-exposure; after each probe beam emission, the lidar detector performs a normal exposure. Therefore, when four probe beams are emitted within a subframe, the lidar performs eight exposures: four pre-exposures and four normal exposures.

[0087] Specifically, the detection result of the target is obtained based on the pre-exposure histogram and the normal exposure histogram. This includes obtaining the detection result of the target in any frame by accumulating the pre-exposure histogram and the normal exposure histogram of all subframes within any frame. In other words, each subframe within any frame will obtain a pre-exposure histogram and a normal exposure histogram. By statistically analyzing the pre-exposure histogram and the normal exposure histogram corresponding to all subframes within any frame, the detection result of the target in any frame can be obtained based on the final statistical pre-exposure histogram and the final statistical normal exposure histogram.

[0088] In some embodiments, the detection result of the target in any frame is obtained based on the cumulative pre-exposure histogram and normal exposure histogram of all subframes within any frame, including: obtaining a difference histogram between the cumulative normal exposure histogram and the cumulative pre-exposure histogram of any frame; adjusting the target difference if the target difference in the difference histogram is less than 0; wherein the target difference is used to characterize the difference between the light intensity in the cumulative normal exposure histogram and the light intensity in the cumulative pre-exposure histogram of any frame; and obtaining the detection result of the target in any frame based on the adjusted difference histogram.

[0089] Combination Figure 4 It should be understood that the pre-exposure histogram for each subframe is also obtained by statistically analyzing multiple pre-exposure histograms within each subframe. The number of pre-exposure histograms within each subframe is related to the number of probe beams emitted by the transmitter within that subframe. Similarly, the normal exposure histogram for each subframe is also obtained by statistically analyzing multiple normal exposure histograms within each subframe. The number of normal exposure histograms within each subframe is related to the number of probe beams emitted by the transmitter within that subframe, and the number of normal exposure histograms within each subframe is the same as the number of pre-exposure histograms within each subframe.

[0090] In one embodiment, the detector includes pixels corresponding to different field-of-view angles, and the pre-exposure histogram includes the pre-exposure histogram of any frame, such as... Figure 5 The diagram illustrates a flowchart for controlling a detector to receive ambient light signals, and how this method can be applied to... Figure 1 Taking controller 106 as an example, the following steps are included:

[0091] S502 determines the actual fitting relationship between the frame and the noise reference at different field of view angles based on the pre-exposure histogram of a specific frame whose time interval with the current frame is less than a preset value.

[0092] In this embodiment, combined with Figure 2 This allows for the acquisition of a pre-exposure histogram for a specific frame. In some embodiments, a specific frame is a frame whose time interval from the current frame is less than a preset value, and within that specific frame, pixels corresponding to different field-of-view angles are all pre-exposed (i.e., full-field-of-view pre-exposure). For example, the horizontal field of view is divided into several equal parts, each part corresponding to a representative pixel. The pre-exposure data of the representative pixel can detect the ambient light level at the corresponding field of view angle. Because the time interval is less than the preset value, the ambient light level of the specific frame and the current frame does not change significantly, making it more referential. The representative pixel can be the pixel corresponding to the center position of each field of view angle, or it can be all pixels corresponding to that field of view angle.

[0093] Specifically, ambient light signals received by pixels corresponding to different field-of-view angles are extracted from the pre-exposure histogram of a specific frame to obtain the light intensity at different field-of-view angles; the light intensity at different field-of-view angles is then fitted to obtain the actual fitting relationship for the specific frame. The light intensity corresponding to different field-of-view angles is used to characterize the noise baseline at those angles. In some embodiments, the fitting relationship can be represented by an actual fitting curve. The noise baseline is obtained based on statistical information from the ambient light histogram, such as the average value over a period of time.

[0094] S504, when the similarity between the actual fitting relationship and the theoretical fitting relationship is greater than a threshold, controls the pixel corresponding to the target field of view to receive the ambient light signal.

[0095] In this embodiment, the light signals received by pixels at different field of view angles will be attenuated to varying degrees compared to the central field of view angle. Therefore, the light attenuation relationship at different field of view angles can be obtained through simulation based on window panes, lenses, different light intensities, and scenes. This relationship can be pre-calibrated to form a theoretical fitting relationship, reflecting the degree of attenuation of ambient light at different field of view angles relative to the target field of view angle under different radar structures, light intensities, and other conditions. The target field of view angle can be the central field of view.

[0096] In some embodiments, the similarity between the actual fitted curve and the theoretical fitted curve is calculated. When the similarity is greater than a threshold, the theoretical fitting relationship is considered to be correctly calibrated, and the theoretical fitting result can be directly applied to the detection of the current frame. That is, under the conditions of the current frame, the attenuation law of different field angles relative to the target field angle still holds. The target field angle is the central field of view, which is a field of view with 0 degrees as the center and a range of -n to n degrees. In the current frame, it is only necessary to control the representative pixel corresponding to the target field angle to receive the ambient light signal, and then calculate the ambient light level under other field angles based on the ambient light level corresponding to the target field angle, instead of starting the pre-exposure of pixels under multiple field angles as in a specific frame.

[0097] like Figure 6 As shown, a schematic diagram of pixels in a detector is provided, wherein the detector includes multiple pixels corresponding to the field of view. When the similarity between the actual fitting relationship and the theoretical fitting relationship is greater than a threshold, the representative pixel 602 corresponding to the target field of view is controlled to receive the ambient light signal.

[0098] In summary, based on Figure 5 As shown in the method, the way the detector receives ambient light signals in the current frame is related to the pre-exposure histogram of the specific frame. By using the environmental interference in the current environment of the lidar in the specific frame, the way the detector receives ambient light signals in the current frame can be adaptively adjusted, thereby improving the accuracy of real-time detection of the target.

[0099] based on Figure 5 As shown, the implementation of receiving ambient light signals in any frame is related to the pre-exposure histogram of that specific frame. In some embodiments, the controller can also determine whether preset conditions are met, and control the detector to receive ambient light signals based on the determination result. Specifically, when the preset conditions are met, the controller controls the reception of ambient light signals in any frame based on representative pixels corresponding to the entire field of view (full field of view pre-exposure). The representative pixels can be all pixels corresponding to each field of view angle, or only a portion of the pixels corresponding to each field of view angle. Thus, based on the received ambient light signals, the pre-exposure histogram of that frame can be obtained.

[0100] The preset conditions are used to determine whether to enable the detector's full-field-of-view pre-exposure function. When the preset conditions are met, the detector's full-field-of-view pre-exposure function is enabled, meaning that ambient light signals are received based on representative pixels corresponding to all field-of-view angles in the detector. When the preset conditions are not met, the detector's full-field-of-view pre-exposure function is not enabled.

[0101] In some embodiments, the preset conditions may include the number of consecutive cumulative frames of non-full field-of-view pre-exposure reaching a preset number, and / or the noise reference change at the target field of view in the pre-exposure histogram of the previous frame being greater than a reference threshold.

[0102] Based on the foregoing, it should be understood that full-field-of-view pre-exposure can comprehensively detect ambient light levels across all field-of-view angles, while non-full-field-of-view pre-exposure only exposes pixels within the target field-of-view angle. For ambient light levels in other field-of-view angles, the derivation of a fitting relationship is required. Although non-full-field-of-view pre-exposure is simpler, it is significantly affected by the accuracy of the calibration relationship. Therefore, it is necessary to use full-field-of-view pre-exposure at intervals. These intervals can be identified by the cumulative number of consecutive frames of non-full-field-of-view pre-exposure. The cumulative number of consecutive frames of non-full-field-of-view pre-exposure refers to the number of consecutive frames that the pre-set LiDAR has performed. For example, if the cumulative number of consecutive frames of non-full-field-of-view pre-exposure is 10, then the 11th frame requires full-field-of-view pre-exposure to reduce the accumulation of errors.

[0103] Additionally, if the change in noise reference corresponding to the center field of view of the previous frame is greater than the reference threshold, it indicates that a sudden change in ambient light may have occurred. In other words, the noise reference change of the previous frame is higher than that of the two frames before it, and the full field of view pre-exposure function can be enabled. Here, the noise reference under the target field of view refers to the light intensity of the ambient light signal received by the representative pixel corresponding to the target field of view, which can be the center field of view.

[0104] In conjunction with the above, in one embodiment, such as Figure 7 As shown, a detection and control method for lidar is provided, which is applied to... Figure 1 Taking controller 106 as an example, the following steps are included:

[0105] S702, before controlling the transmitter to emit probe light toward the target, determines the actual fitting relationship between the actual and theoretical fitting relationships at different field of view angles based on the pre-exposure histogram of a specific frame with a time interval of less than a preset value; when the similarity between the actual and theoretical fitting relationships is greater than a threshold, controls the pixel corresponding to the target field of view to receive the ambient light signal and obtain the pre-exposure histogram.

[0106] S704, before controlling the transmitter to emit probe light toward the target, when preset conditions are met, controls the receiver to receive ambient light signals based on representative pixels corresponding to the full field of view in any frame to obtain a pre-exposure histogram.

[0107] The preset conditions include the number of consecutive cumulative frames of non-full field-of-view pre-exposure reaching a preset number, and / or the noise reference under the target field-of-view angle in the pre-exposure histogram of the previous frame being greater than the reference threshold; wherein the target field-of-view angle corresponds to the center field of view.

[0108] The controller can use the S702 or S704 method to control the detector to receive ambient light signals before controlling the transmitter to emit detection light to the detection target.

[0109] S706, after controlling the transmitter to emit probe light toward the target, controls the receiver to receive probe signals based on all pixels corresponding to the full field of view in any frame, and obtains a normal exposure histogram.

[0110] Each frame includes multiple subframes, with time intervals between them. Normal exposure and pre-exposure alternate within each subframe, and the cumulative duration of normal exposure and pre-exposure within each subframe is equal. Pre-exposure is used to characterize the detector receiving ambient light signals, while normal exposure is used to characterize the detector receiving detection signals.

[0111] S708 obtains the detection result of the target in any frame based on the cumulative sum of the pre-exposure histogram and normal exposure histogram of all subframes within any frame.

[0112] Specifically, a difference histogram is obtained between the cumulative normal exposure histogram and the cumulative pre-exposure histogram of any frame; if the target difference in the difference histogram is less than 0, the target difference is adjusted; wherein, the target difference is used to characterize the difference between the light intensity in the cumulative normal exposure histogram and the light intensity in the cumulative pre-exposure histogram of any frame; based on the adjusted difference histogram, the detection result of the target in any frame is obtained.

[0113] The specific content of S702-S708 can be found in the aforementioned description and will not be repeated here.

[0114] Based on the above, it should be understood that the method provided in this application, without changing the physical size of the current LiDAR product or affecting its angular resolution, obtains the current ambient noise through temporal pre-exposure (i.e., performs pre-exposure), and then performs normal exposure, obtaining histograms for the two exposures, namely the pre-exposure histogram and the normal exposure histogram. The final histogram (i.e., the difference histogram) can be obtained by subtracting the normal exposure histogram from the pre-exposure histogram. Simultaneously, since ambient light noise exhibits a similar form across all pixels, and the window and lens transmittance differ for pixels corresponding to different field of view angles, this application can estimate the pre-exposure histogram data for different field of view angles using theoretical attenuation. Furthermore, by controlling the LiDAR to alternately perform pre-exposure and normal exposure, this application is suitable for scenarios with rapidly changing ambient light. Moreover, this application can identify the external environment through the pre-exposure histogram and provide background noise information for the normal exposure histogram, which can help subtract environmental interference within the normal histogram, outputting the final histogram, improving the signal-to-noise ratio, and optimizing low signal-to-noise ratio point cloud scenarios in strong outdoor sunlight. Furthermore, this application uses the pre-histogram features of the real-time detection center's field of view to determine environmental changes based on feature changes, thereby reducing the number of pre-exposures and the area covered, which can reduce a large amount of data transmission and processing.

[0115] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0116] Based on the same inventive concept, this application also provides a laser radar detection and control device for implementing the laser radar detection and control method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of one or more laser radar detection and control device embodiments provided below can be found in the limitations of the laser radar detection and control method described above, and will not be repeated here.

[0117] In one embodiment, such as Figure 8 As shown, a detection and control device for a lidar is provided, comprising: a first control module 802, a second control module 804, and a processing module 806, wherein:

[0118] The first control module 802 is used to control the detector to receive ambient light signals and obtain a pre-exposure histogram before the transmitter emits detection light to the detection target; wherein, the ambient light signals are used to characterize environmental interference.

[0119] The second control module 804 is used to control the detector to receive the detection signal and obtain a normal exposure histogram after the transmitter emits detection light toward the detection target.

[0120] The processing module 806 is used to obtain the detection results of the target based on the pre-exposure histogram and the normal exposure histogram.

[0121] In one embodiment, the pre-exposure histogram includes the pre-exposure histogram of any frame, the normal exposure histogram includes the normal exposure histogram of any frame, any frame includes multiple subframes, there is a time interval between the multiple subframes, and normal exposure and pre-exposure alternate within each subframe, the cumulative duration of normal exposure and pre-exposure within each subframe is equal, pre-exposure is used to characterize the detector receiving ambient light signals, and normal exposure is used to characterize the detector receiving detection signals; the processing module 806 is further configured to: obtain the detection result of the target in any frame based on the cumulative sum of the pre-exposure histograms and normal exposure histograms of all subframes within any frame.

[0122] In one embodiment, the processing module 806 is further configured to: obtain a difference histogram between the normal exposure histogram and the pre-exposure histogram; adjust the target difference when the target difference in the difference histogram is less than 0; wherein the target difference is used to characterize the difference between the light intensity in the normal exposure histogram and the light intensity in the pre-exposure histogram; and obtain the detection result of the target based on the adjusted difference histogram.

[0123] In one embodiment, the processing module 806 is further configured to: adjust the target difference to the light intensity corresponding to the target difference in the normal exposure histogram; or, adjust the target difference to a preset value.

[0124] In one embodiment, the detector includes pixels corresponding to different field of view angles, and the pre-exposure histogram includes the pre-exposure histogram of any frame; the first control module 802 is further configured to: determine the actual fitting relationship between the actual fitting relationship and the noise reference under different field of view angles based on the pre-exposure histogram of a specific frame with a time interval of less than a preset value; when the similarity between the actual fitting relationship and the theoretical fitting relationship is greater than a threshold, control the reception of ambient light signals based on pixels corresponding to the target field of view angle in any frame; wherein the target field of view angle and the central field of view have a corresponding relationship.

[0125] In one embodiment, the detector includes pixels corresponding to different field of view angles, and the first control module 802 is further configured to: when a preset condition is met, control the reception of ambient light signals based on representative pixels corresponding to the full field of view angle in any frame.

[0126] In one embodiment, the preset conditions include: the number of consecutive cumulative frames of non-full field-of-view pre-exposure reaches a preset number of frames, and / or, the noise reference under the target field-of-view angle in the pre-exposure histogram of the previous frame is greater than a reference threshold; wherein, the target field-of-view angle and the center field of view have a specific correspondence.

[0127] In one embodiment, the detector includes pixels corresponding to different field of view angles; the second control module 804 is further configured to: control all pixels corresponding to the full field of view angle to receive the detection signal.

[0128] The various modules in the aforementioned lidar detection and control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the lidar's processor in hardware form or independent of it, or stored in the lidar's memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0129] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0130] Before the transmitter emits probe light toward the target, the detector receives ambient light signals to obtain a pre-exposure histogram. The ambient light signals characterize the environmental interference in the current environment of the lidar. After the transmitter emits probe light toward the target, the detector receives probe signals to obtain a normal exposure histogram. Based on the pre-exposure histogram and the normal exposure histogram, the detection result of the target is obtained.

[0131] In one embodiment, the pre-exposure histogram includes the pre-exposure histogram of any frame, the normal exposure histogram includes the normal exposure histogram of any frame, any frame includes multiple subframes, there is a time interval between the multiple subframes, and normal exposure and pre-exposure alternate within each subframe, the cumulative duration of normal exposure and pre-exposure within each subframe is equal, pre-exposure is used to characterize the detector receiving ambient light signals, and normal exposure is used to characterize the detector receiving detection signals; when the computer program is executed by the processor, it also implements the following steps: based on the cumulative sum of the pre-exposure histograms and normal exposure histograms of all subframes within any frame, the detection result of the target in any frame is obtained.

[0132] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining a difference histogram between the normal exposure histogram and the pre-exposure histogram; adjusting the target difference when the target difference in the difference histogram is less than 0; wherein the target difference is used to characterize the difference between the light intensity in the normal exposure histogram and the light intensity in the pre-exposure histogram; and obtaining the detection result of the target based on the adjusted difference histogram.

[0133] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: adjusting the target difference to the light intensity corresponding to the target difference in the normal exposure histogram; or, adjusting the target difference to a preset value.

[0134] In one embodiment, the detector includes pixels corresponding to different field of view angles, and the pre-exposure histogram includes the pre-exposure histogram of any frame; when the computer program is executed by the processor, it further implements the following steps: determining the actual fitting relationship between the actual fitting relationship and the noise reference under different field of view angles based on the pre-exposure histogram of a specific frame with a time interval of less than a preset value; when the similarity between the actual fitting relationship and the theoretical fitting relationship is greater than a threshold, controlling the reception of ambient light signals based on pixels corresponding to the target field of view angle in any frame; wherein the target field of view angle and the central field of view have a corresponding relationship.

[0135] In one embodiment, the detector includes pixels corresponding to different field of view angles, and the computer program, when executed by the processor, further implements the following steps: when preset conditions are met, controlling the reception of ambient light signals based on representative pixels corresponding to the full field of view angle in any frame.

[0136] In one embodiment, when the computer program is executed by the processor, it further implements the following steps: preset conditions, including: the number of consecutive cumulative frames of non-full field of view pre-exposure reaches a preset number of frames, and / or, the noise reference under the target field of view angle in the pre-exposure histogram of the previous frame is greater than a reference threshold; wherein, the target field of view angle and the center field of view have a specific correspondence.

[0137] In one embodiment, the detector includes pixels corresponding to different field of view angles; when the computer program is executed by the processor, it further performs the following steps: controlling all pixels corresponding to the full field of view angle to receive the detection signal.

[0138] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0139] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0140] Before the transmitter emits probe light toward the target, the detector receives ambient light signals to obtain a pre-exposure histogram. The ambient light signals characterize the environmental interference in the current environment of the lidar. After the transmitter emits probe light toward the target, the detector receives probe signals to obtain a normal exposure histogram. Based on the pre-exposure histogram and the normal exposure histogram, the detection result of the target is obtained.

[0141] In one embodiment, the pre-exposure histogram includes the pre-exposure histogram of any frame, the normal exposure histogram includes the normal exposure histogram of any frame, any frame includes multiple subframes, there is a time interval between the multiple subframes, and normal exposure and pre-exposure alternate within each subframe, the cumulative duration of normal exposure and pre-exposure within each subframe is equal, pre-exposure is used to characterize the detector receiving ambient light signals, and normal exposure is used to characterize the detector receiving detection signals; when the computer program is executed by the processor, it also implements the following steps: based on the cumulative sum of the pre-exposure histograms and normal exposure histograms of all subframes within any frame, the detection result of the target in any frame is obtained.

[0142] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining a difference histogram between the normal exposure histogram and the pre-exposure histogram; adjusting the target difference when the target difference in the difference histogram is less than 0; wherein the target difference is used to characterize the difference between the light intensity in the normal exposure histogram and the light intensity in the pre-exposure histogram; and obtaining the detection result of the target based on the adjusted difference histogram.

[0143] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: adjusting the target difference to the light intensity corresponding to the target difference in the normal exposure histogram; or, adjusting the target difference to a preset value.

[0144] In one embodiment, the detector includes pixels corresponding to different field of view angles, and the pre-exposure histogram includes the pre-exposure histogram of any frame; when the computer program is executed by the processor, it further implements the following steps: determining the actual fitting relationship between the actual fitting relationship and the noise reference under different field of view angles based on the pre-exposure histogram of a specific frame with a time interval of less than a preset value; when the similarity between the actual fitting relationship and the theoretical fitting relationship is greater than a threshold, controlling the reception of ambient light signals based on pixels corresponding to the target field of view angle in any frame; wherein the target field of view angle and the central field of view have a corresponding relationship.

[0145] In one embodiment, the detector includes pixels corresponding to different field of view angles, and the computer program, when executed by the processor, further implements the following steps: when preset conditions are met, controlling the reception of ambient light signals based on representative pixels corresponding to the full field of view angle in any frame.

[0146] In one embodiment, when the computer program is executed by the processor, it further implements the following steps: preset conditions, including: the number of consecutive cumulative frames of non-full field of view pre-exposure reaches a preset number of frames, and / or, the noise reference under the target field of view angle in the pre-exposure histogram of the previous frame is greater than a reference threshold; wherein, the target field of view angle and the center field of view have a specific correspondence.

[0147] In one embodiment, the detector includes pixels corresponding to different field of view angles; when the computer program is executed by the processor, it further performs the following steps: controlling all pixels corresponding to the full field of view angle to receive the detection signal.

[0148] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0149] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0150] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A detection and control method for a lidar, characterized in that, The lidar includes a transmitter and a detector, and the method includes: Before controlling the transmitter to emit detection light toward the target, the detector is controlled to receive ambient light signals to obtain a pre-exposure histogram; wherein, the ambient light signals are used to characterize the environmental interference in the current environment of the lidar. After controlling the transmitter to emit detection light toward the target, the detector is controlled to receive the detection signal and obtain a normal exposure histogram; Based on the pre-exposure histogram and the normal exposure histogram, the detection result of the target is obtained; The pre-exposure histogram includes the pre-exposure histogram of any frame, and the normal exposure histogram includes the normal exposure histogram of any frame. Each frame includes multiple subframes, and there is a time interval between the multiple subframes. Normal exposure and pre-exposure alternate within each subframe, and the cumulative duration of normal exposure and pre-exposure within each subframe is equal. The pre-exposure is used to characterize the detector receiving the ambient light signal, and the normal exposure is used to characterize the detector receiving the detection signal. The step of obtaining the detection result of the target based on the pre-exposure histogram and the normal exposure histogram includes: The detection result of the target in any given frame is obtained by accumulating the pre-exposure histogram and normal exposure histogram of all subframes within any given frame.

2. The method according to claim 1, characterized in that, The method further includes: Obtain the difference histogram between the normal exposure histogram and the pre-exposure histogram; If the target difference value in the difference histogram is less than 0, the target difference value is adjusted; wherein, the target difference value is used to characterize the difference between the light intensity in the normal exposure histogram and the light intensity in the pre-exposure histogram; Based on the adjusted difference histogram, the detection result of the target is obtained.

3. The method according to claim 2, characterized in that, The adjustment of the target difference includes: The target difference is adjusted to the light intensity corresponding to the target difference in the normal exposure histogram; Alternatively, the target difference can be adjusted to a preset value.

4. The method according to claim 1, characterized in that, The detector includes pixels corresponding to different field of view angles, and the pre-exposure histogram includes the pre-exposure histogram of any frame; controlling the detector to receive ambient light signals includes: Based on the pre-exposure histogram of a specific frame whose time interval with the current frame is less than a preset value, the actual fitting relationship between the frame and the noise baseline under different field of view angles is determined. When the similarity between the actual fitting relationship and the theoretical fitting relationship is greater than a threshold, the representative pixel corresponding to the target field of view is controlled to receive the ambient light signal; wherein, the target field of view and the central field of view have a corresponding relationship.

5. The method according to claim 1, characterized in that, The detector includes pixels corresponding to different field of view angles, and controlling the detector to receive ambient light signals includes: When preset conditions are met, the system controls the reception of ambient light signals in any frame based on the representative pixels corresponding to the full field of view.

6. The method according to claim 5, characterized in that, The preset conditions include: The continuous cumulative frame rate of non-full-field pre-exposure reaches the preset frame rate. And / or, The noise baseline change in the target field of view angle of the pre-exposure histogram of any frame is greater than the baseline threshold; wherein, the target field of view angle corresponds to the center field of view.

7. The method according to any one of claims 1-6, characterized in that, The detector includes pixels corresponding to different field of view angles; controlling the detector to receive detection signals includes: Control all pixels corresponding to the full field of view to receive detection signals.

8. A detection and control device for a lidar, characterized in that, The lidar includes a transmitter and a detector, and the device includes: The first control module is used to control the detector to receive ambient light signals and obtain a pre-exposure histogram before controlling the transmitter to emit detection light towards the detection target; wherein, the ambient light signals are used to characterize the environmental interference in the current environment of the lidar. The second control module is used to control the detector to receive the detection signal and obtain a normal exposure histogram after controlling the transmitter to emit detection light toward the detection target. The processing module is used to obtain the detection result of the target based on the pre-exposure histogram and the normal exposure histogram; The pre-exposure histogram includes the pre-exposure histogram of any frame, and the normal exposure histogram includes the normal exposure histogram of any frame. Each frame includes multiple subframes, and there are time intervals between the multiple subframes. Normal exposure and pre-exposure alternate within each subframe, and the cumulative duration of normal exposure and pre-exposure within each subframe is equal. The pre-exposure is used to characterize the detector receiving ambient light signals, and the normal exposure is used to characterize the detector receiving detection signals. The processing module is also used to obtain the detection result of the target in any frame based on the cumulative sum of the pre-exposure histograms and normal exposure histograms of all subframes within any frame.

9. The apparatus according to claim 8, characterized in that, The processing module is further configured to: Obtain the difference histogram between the normal exposure histogram and the pre-exposure histogram; If the target difference value in the difference histogram is less than 0, the target difference value is adjusted; wherein, the target difference value is used to characterize the difference between the light intensity in the normal exposure histogram and the light intensity in the pre-exposure histogram; Based on the adjusted difference histogram, the detection result of the target is obtained.

10. A lidar, characterized in that, The lidar includes: a transmitter, a detector, and a controller communicatively connected to the transmitter and the detector; The transmitter is used to emit detection light toward the detection target; The detector is used to receive ambient light signals or detection signals; wherein the ambient light signals are used to characterize the environmental interference in the current environment of the lidar. The controller is used to control the transmitter and the detector to perform the steps of the method according to any one of claims 1 to 7.

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