A method and device for adjusting and controlling laser radar detection parameters

Abstract

The application provides a laser radar detection parameter adjustment control method and device, wherein the method comprises the following steps: setting an initial detection parameter and a learning frame exposure time; emitting a learning frame detection light to a target according to the initial detection parameter and receiving corresponding reflected light, wherein the learning frame detection light is used for detecting a current environment condition; obtaining learning frame histogram data according to the received reflected light when the learning frame exposure time ends; analyzing the learning frame histogram data, and adaptively adjusting the initial detection parameter according to an analysis result to obtain optimal detection parameters matched with the current environment condition. The current environment condition is detected through the leading learning frame detection light, and then the detection parameters are dynamically adjusted, so that the laser radar can adaptively adjust the working parameters according to the environment condition, improve the matching degree between the laser radar and the detection environment, and achieve a better balance between performance and power consumption.

Description

Technical Field

[0001] This invention relates to the field of distance detection technology, and in particular to a method and apparatus for adjusting and controlling lidar detection parameters. Background Technology

[0002] LiDAR calculates the distance to an object by measuring the time it takes for a light beam to travel through space. Due to its advantages such as high accuracy and large measurement range, it is widely used in consumer electronics, autonomous driving, remote sensing, AR / VR and other fields.

[0003] In current lidar measurement systems based on the Direct Time-of-Flight (dTOF) method, there are typically a transmitter and a receiver. In typical lidar ranging, once the maximum detection distance is set, the duration and intensity of the laser emission, as well as the receiver settings of the detector, are determined. At the same time, in order to adapt to various working scenarios and maximize the accuracy and signal-to-noise ratio of distance detection, the laser emission power is usually set to the maximum power, and the sensitivity and bandwidth of the detector are also set to the optimal or maximum state.

[0004] The side effect of this is that the power consumption of the transmitter and receiver is too high in many working scenarios, or some of the power consumption is wasted, making it difficult to adapt to the parameter configuration requirements of different scenarios, and making it impossible to achieve a balance between detector performance and power consumption. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this invention is to provide a method and device for adjusting and controlling the detection parameters of a lidar, so as to realize adaptive adjustment of the detection parameters according to the environmental conditions, improve the matching degree between the operating parameters of the lidar and the environment, and achieve a better balance between performance and power consumption.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] The first aspect of this invention provides a method for adjusting and controlling lidar detection parameters, comprising the following steps:

[0008] Set initial detection parameters and learning frame exposure time, emit learning frame detection light toward the target with the initial detection parameters and receive the corresponding reflected light, the learning frame detection light is used to detect the current environmental conditions;

[0009] At the end of the exposure time of the learning frame, the learning frame histogram data is obtained based on the received reflected light;

[0010] The histogram data of the learning frames is analyzed, and the initial detection parameters are adaptively adjusted based on the analysis results to obtain the optimal detection parameters that match the current environmental conditions.

[0011] In one embodiment, the step of analyzing the learned frame histogram data and adaptively adjusting the initial detection parameters based on the analysis results to obtain optimal detection parameters that match the current environmental conditions includes:

[0012] The histogram data of the learning frames is analyzed to obtain the current environmental parameters, which include ambient light value, target distance, target reflectivity, and signal-to-noise ratio.

[0013] The initial detection parameters are adaptively adjusted based on the environmental parameters to obtain the optimal detection parameters that match the environmental parameters.

[0014] In one embodiment, analyzing the learned frame histogram data to obtain current environmental parameters includes:

[0015] Ambient light values ​​are obtained without emitting the probe light from the learning frame;

[0016] When the learning frame probe light is emitted, the learning frame histogram data collected by the emitted learning frame probe light is analyzed to obtain the current environmental parameters, including target distance, target reflectivity and signal-to-noise ratio.

[0017] In one embodiment, the step of adaptively adjusting the initial detection parameters based on the environmental parameters to obtain optimal detection parameters that match the environmental parameters specifically includes:

[0018] Based on at least one of the ambient light value, target distance, target reflectivity, and signal-to-noise ratio, the transmission parameters and / or reception parameters in the initial detection parameters are dynamically adjusted to obtain the corresponding optimal detection parameters.

[0019] The emission parameters include laser emission power and normal frame exposure time, and the reception parameters include receiver operating voltage, operating frequency, and data bandwidth.

[0020] In one embodiment, dynamically adjusting the transmission and / or reception parameters in the initial detection parameters based on at least one of the ambient light value, target distance, target reflectivity, and signal-to-noise ratio to obtain the corresponding optimal detection parameters specifically includes:

[0021] Based on the application scenario, construct the transmission parameter model and the reception parameter model in advance, and set the indicators of interest;

[0022] Based on the received environmental parameters, a first set of parameters that best matches the indicators of interest is selected from the transmission parameter model, and a second set of parameters that best matches the indicators of interest is selected from the reception parameter model. The first set of parameters and the second set of parameters are then used as the optimal detection parameters.

[0023] In one embodiment, constructing the transmission parameter model and the reception parameter model specifically includes: constructing the transmission parameter model and the reception parameter model through self-learning of the lidar by constructing functional relationships.

[0024] In one embodiment, the exposure time of the learning frame is less than or much less than the exposure time of the normal frame.

[0025] In one embodiment, after analyzing the learned frame histogram data and adaptively adjusting the initial detection parameters based on the analysis results to obtain optimal detection parameters that match the current environmental conditions, the method further includes:

[0026] The learning frame probe light is emitted once every preset time interval, and the current optimal detection parameters are adaptively readjusted to match the latest environmental conditions.

[0027] A second aspect of the present invention provides a lidar detection parameter adjustment and control device, comprising:

[0028] The transmitting module is used to transmit learning frame probe light to the target, and the learning frame probe light is used to detect the current environmental conditions.

[0029] The receiving module is used to receive the reflected light from the target and acquire the learning frame histogram data;

[0030] The laser control module is used to control the emission module to emit the learning frame probe light with initial detection parameters;

[0031] The main control and adaptive module is used to analyze the histogram data of the learning frame, adaptively adjust the initial detection parameters according to the analysis results, and output the optimal detection parameters that match the current environmental conditions.

[0032] In one embodiment, the main control and adaptive module includes:

[0033] The distance calculation unit is used to perform distance calculation and analysis on the histogram data of the learning frame to obtain the current environmental parameters;

[0034] An adaptive adjustment unit is used to adaptively adjust the initial detection parameters according to the environmental parameters to obtain the optimal detection parameters that match the environmental parameters;

[0035] The main controller is used to output the optimal detection parameters to the laser control module and / or receiving module to control the working state of the transmitting module and / or receiving module.

[0036] The beneficial effects of this invention are as follows: It provides a method and device for adjusting and controlling the detection parameters of a lidar, which detects the current environmental conditions by using a learning frame detection light as a lead, and then dynamically adjusts the detection parameters so that the lidar can adaptively adjust its operating parameters according to the environmental conditions, improve its matching degree with the detection environment, and achieve a better balance between performance and power consumption. Attached Figure Description

[0037] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings:

[0038] Figure 1 This is a flowchart of the lidar detection parameter adjustment and control method in an embodiment of the present invention;

[0039] Figure 2 This is a comparative diagram of the data frame structure before and after adding a learning frame in an embodiment of the present invention;

[0040] Figure 3 This is a structural diagram of the lidar detection parameter adjustment and control device in an embodiment of the present invention;

[0041] Figure 4 This is a flowchart of a distance detection method in an embodiment of the present invention. Detailed Implementation

[0042] To make the technical problems, technical solutions, and beneficial effects of the embodiments of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0043] It should be noted that when a component is referred to as "fixed to" or "set on" another component, it can be directly on or indirectly on that other component. When a component is referred to as "connected to" another component, it can be directly connected to or indirectly connected to that other component. Furthermore, a connection can be for both fixing and circuit connection purposes.

[0044] It should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the present invention.

[0045] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying 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. In the description of embodiments of the present invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0046] The lidar detection parameter adjustment and control method provided in this invention is applied to a lidar measurement system based on the time-of-flight (TOF) method. This lidar measurement system includes at least a controller, a transmitter, and a receiver. The controller is connected to both the transmitter and the receiver. The transmitter emits a detection beam towards a target object, and at least a portion of the detection beam is reflected by the target object to form reflected light. The receiver includes a pixel array composed of multiple pixels, used to receive the reflected light from the target object. The controller synchronously controls the emission and reception of light, performs histogram statistics on the photons received by the receiver using time bins, and then calculates the time of flight of the photons using the histogram to determine the distance to the target object.

[0047] Specifically, the transmitter includes a driver and a light source, which can be a light-emitting diode (LED), a laser diode (LD), an edge-emitting laser (EEL), a vertical-cavity surface-emitting laser (VCSEL), a picosecond laser, etc. Under the drive and control of the driver, the light source emits a detection beam, which can be visible light, infrared light, ultraviolet light, etc. At least a portion of the detection beam is emitted toward the target object, and the reflected light generated by the reflection of at least a portion of the detection beam by the target object is received by the receiver.

[0048] The receiver includes a pixel array and receiving optical elements, which can be one or more combinations of lenses, microlens arrays, mirrors, etc. The receiving optical elements receive reflected light and guide it to the pixel array. The pixel array includes multiple pixels that collect photons. In one embodiment, the pixel array consists of multiple single-photon avalanche photodiodes (SPADs). The SPADs can respond to the incident single photon and output a photon signal indicating the arrival time of the received photon at each SPAD. Of course, in other embodiments, photoelectric conversion devices such as avalanche photodiodes, photomultiplier tubes, silicon photomultiplier tubes, etc., can also be used.

[0049] Currently, in lidar measurement systems, the transmission and reception parameters are typically set based on the maximum detection distance, and these parameters are not changed during the distance detection process. This leads to wasted power consumption in many working scenarios. Therefore, the following describes how to solve this problem by applying a detection parameter adjustment control method to this lidar measurement system, so as to achieve flexible adjustment of detection parameters, better match and adaptively adjust detection parameters according to environmental conditions, improve the matching degree between lidar operating parameters and the environment, and achieve a better balance between performance and power consumption.

[0050] like Figure 1 As shown, Figure 1 This is a flowchart of a lidar detection parameter adjustment and control method in one embodiment of the present invention. The method specifically includes the following steps:

[0051] S101. Set initial detection parameters and learning frame exposure time, emit learning frame detection light to the target with the initial detection parameters and receive the corresponding reflected light, the learning frame detection light is used to detect the current environmental conditions.

[0052] During distance detection, the current environmental conditions are detected by a lead learning frame probe light. The exposure time of the learning frame is first set to adjust the length of the time window for receiving photons, and a set of initial detection parameters for the lidar are set, including emission parameters and reception parameters. The driver drives the light source to emit the learning frame probe light toward the target with the currently set emission parameters. The learning frame probe light can be visible light, infrared light, ultraviolet light, etc. The reflected light after the learning frame probe light is reflected by the target is received by the receiver with the currently set reception parameters to obtain the reflected light containing environmental information.

[0053] S102. At the end of the exposure time of the learning frame, the learning frame histogram data is obtained based on the received reflected light.

[0054] After receiving the reflected light through the pixel array, the receiver converts the time information into a quantized multi-bit digital signal, namely TDC photon trigger data, through a TDC (Time-to-Digital Converter). The TDC is a device that converts time into digital signals. It is a circuit structure that can accurately measure the time interval between the start pulse signal and the stop pulse signal. The converted TDC photon trigger data can record the flight time of each received light signal, that is, the time interval between the transmitted pulse and the received pulse. The TDC converts and calculates the photon signal to confirm the time bin into which the photon falls. Then, the value of the time bin is incremented by 1. Different time bins correspond to different addresses in the storage space.

[0055] Therefore, as the exposure of the learning frame continues, the TDC photon trigger data will be accumulated in the storage address corresponding to each time box. When the exposure time of the learning frame ends, the count value of each storage address corresponding to the reflected light can be obtained as the learning frame histogram data, which serves as an accurate basis for analyzing environmental conditions and adjusting parameters.

[0056] S103. Analyze the histogram data of the learning frame, and adaptively adjust the initial detection parameters according to the analysis results to obtain the optimal detection parameters that match the current environmental conditions.

[0057] Based on the histogram data of the learning frames obtained statistically under the initial detection parameters, environmental condition analysis is performed, such as the brightness of the environment, the distance of the target, and the reflectivity. This enables the scene perception process before formal distance detection. The initial detection parameters are dynamically adjusted according to the analysis results, so that the lidar emits and receives detection light with the optimal detection parameters that match the current environmental conditions. In this embodiment, the detection light of the lead learning frame is used to adaptively learn the scene environment and dynamically adjust the emission and reception parameters to the optimal state. This makes the overall performance of the lidar more compatible with the environment, avoids the power consumption waste caused by fixed parameter configuration, and improves the environmental adaptability and flexibility of the lidar.

[0058] In one embodiment, step S103 includes:

[0059] The histogram data of the learning frames is analyzed to obtain the current environmental parameters, which include ambient light value, target distance, target reflectivity, and signal-to-noise ratio.

[0060] The initial detection parameters are adaptively adjusted based on the environmental parameters to obtain the optimal detection parameters that match the environmental parameters.

[0061] In this embodiment, during environmental analysis and parameter adjustment, a corresponding learning frame histogram can be drawn based on the learning frame histogram data. The background noise, the position of the highest peak, etc. of the learning frame histogram can be further analyzed to calculate the current ambient light value, target distance, and signal-to-noise ratio. Furthermore, the target reflectivity can be calculated by integrating the received reflected light using photocurrent, thereby obtaining the current environmental parameters. Based on the analyzed environmental parameters, the initial detection parameters are adaptively adjusted to ensure that the detection parameters of the lidar can match the current parameters when performing formal distance detection, thereby reducing system power consumption and avoiding power waste.

[0062] In one embodiment, the learning frame histogram data is analyzed to obtain current environmental parameters, including:

[0063] Ambient light values ​​are obtained without emitting the probe light from the learning frame;

[0064] When the learning frame probe light is emitted, the learning frame histogram data collected by the emitted learning frame probe light is analyzed to obtain the current environmental parameters, including target distance, target reflectivity and signal-to-noise ratio.

[0065] Since the ambient light value obtained when emitting the learning frame probe light may be affected by the laser itself, which may lead to inaccurate ambient light value, this embodiment obtains a more accurate ambient light value without emitting the learning frame probe light, which is also obtained through histogram. However, when the learning frame probe light is emitted, histogram plotting and analysis of the learning frame histogram data are performed to calculate the target distance, target reflectivity and signal-to-noise ratio, which further improves the accuracy of environmental parameter acquisition.

[0066] It is understood that the steps in this embodiment can have different execution orders. That is, the ambient light value can be obtained before or after the learning frame probe light is emitted. For example, taking the learning frame exposure time as 200us as an example, the ambient light value can be obtained directly without emitting the learning frame probe light in the first 50us, and the learning frame probe light can be emitted in the last 150us to obtain the learning frame histogram data. Conversely, the learning frame probe light can be emitted in the first 150us to obtain the learning frame histogram data, and the ambient light value can be obtained directly without emitting the learning frame probe light in the last 50us. Both methods can achieve the goal of obtaining accurate ambient light values ​​without emitting lasers.

[0067] In one embodiment, the initial detection parameters are adaptively adjusted based on the environmental parameters to obtain optimal detection parameters that match the environmental parameters, specifically including:

[0068] Based on at least one of the ambient light value, target distance, target reflectivity, and signal-to-noise ratio, the transmission parameters and / or reception parameters in the initial detection parameters are dynamically adjusted to obtain the corresponding optimal detection parameters.

[0069] The emission parameters include laser emission power and normal frame exposure time, and the reception parameters include receiver operating voltage, operating frequency, and data bandwidth.

[0070] In this embodiment, when performing adaptive parameter adjustment, one or more environmental parameters can be combined for parameter adjustment. During adjustment, the emission parameters (including laser emission power and normal frame exposure time) can be adjusted separately, or the receiving parameters (including receiver operating voltage, operating frequency and data bandwidth) can be adjusted separately, or the emission parameters and receiving parameters can be adjusted simultaneously to achieve comprehensive optimization of the lidar operating parameters.

[0071] The normal frame exposure time is the exposure time of the normal detection light used for accurate ranging. The learning frame exposure time is less than or much less than the normal frame exposure time. "Much less" means that the learning frame exposure time is two or more orders of magnitude less than the normal frame exposure time. This ensures that the preceding learning frame detection light does not occupy too much distance detection time to complete environmental perception and improves the efficiency of lidar detection parameter adjustment.

[0072] For example, adjusting the initial detection parameters can include the following scenarios:

[0073] (1) Adjust the laser emission power dynamically according to the ambient light level. For example, reduce the laser emission power in pure indoor or low ambient light conditions to save power consumption, and increase the laser emission power in outdoor or strong ambient light conditions to improve the signal-to-noise ratio.

[0074] (2) The laser emission power is dynamically adjusted according to the distance to the target and the reflectivity of the target. For example, when the target is far away or the reflectivity of the target is low, the laser emission power is increased to improve the signal-to-noise ratio and improve the accuracy and confidence of the detection distance; when the target is close or the reflectivity of the target is strong, the laser emission power is reduced to save system power consumption.

[0075] (3) Based on the indoor and outdoor application environment and the distance to the target, dynamically adjust the voltage and performance parameters of the receiver (such as the bias voltage Vex, avalanche voltage Vbd, quenching voltage Vq of SPAD, etc.) to achieve a better balance between performance and power consumption.

[0076] (4) Adjust the receiver’s operating frequency and data bandwidth dynamically according to the ambient light level. For example, reduce the receiver’s operating frequency and data bandwidth in pure indoor or low ambient light conditions to save power consumption; increase the receiver’s operating frequency and data bandwidth in outdoor or strong ambient light conditions to achieve a better signal-to-noise ratio.

[0077] Of course, the adjustment of the initial detection parameters is not limited to the above situations. The parameters can be flexibly and adaptively adjusted according to actual needs. This embodiment does not limit this.

[0078] In one embodiment, the transmission and / or reception parameters in the initial detection parameters are dynamically adjusted based on at least one of the ambient light value, target distance, target reflectivity, and signal-to-noise ratio to obtain the corresponding optimal detection parameters, specifically including:

[0079] Based on the application scenario, construct the transmission parameter model and the reception parameter model in advance, and set the indicators of interest;

[0080] Based on the received environmental parameters, a first set of parameters that best matches the indicators of interest is selected from the transmission parameter model, and a second set of parameters that best matches the indicators of interest is selected from the reception parameter model. The first set of parameters and the second set of parameters are then used as the optimal detection parameters.

[0081] Since the values ​​of environmental parameters cannot be exhaustively listed, and the relationship between environmental parameters and transmission and reception parameters is not a simple one, this embodiment achieves more accurate detection parameter adjustment by using pre-constructed parameter models and set key performance indicators (such as signal-to-noise ratio, performance, and power consumption). First, transmission and reception parameter models are constructed according to different application scenarios, such as indoor, outdoor, and close-range detection scenarios. Specifically, functional relationships are constructed so that the lidar can self-learn and adjust its parameters under different environmental parameters to reach the corresponding constraints, thus completing the construction of the transmission and reception parameter models.

[0082] The constructed transmission and reception model parameters can adaptively output the optimal detection parameters for the current environment based on the received environmental parameters and the set indicators of interest. Specifically, the transmission parameter model outputs a first set of parameters that best matches the indicators of interest, and the reception parameter model outputs a second set of parameters that best matches the indicators of interest. The first and second sets of parameters are used as the optimal detection parameters that best match the current environmental conditions, thus achieving comprehensive and efficient adaptive adjustment of working parameters.

[0083] 1) For example, suppose the relevant environmental parameters obtained from the learning frame are as follows:

[0084] Ambient light value is 0 or close to 0; target distance is less than the distance threshold (e.g., 5m); target reflectivity is not lower than the reflectivity threshold (e.g., 50%); signal-to-noise ratio is higher than the first threshold (e.g., 30dB);

[0085] This indicates that the current detection environment has no ambient light or very weak ambient light, and the object being detected is close to the receiver with high reflectivity, resulting in a high signal-to-noise ratio. This allows for a reduction in laser power and exposure time, while also reducing receiver performance and bandwidth. Therefore, the optimal detection parameters can be output by the emission parameter model and the reception parameter model as follows:

[0086] Set the laser emission pulse width to laser_pulse_width (e.g., 1ns); set the laser emission peak power to laser_pulse_peak (e.g., 10W); set the laser repetition rate period to laser_freq (e.g., 25MHz); set the laser exposure time to laser_expo_time (e.g., 1ms); set the receiving sensor system operating frequency to sys_clk_freq (e.g., 100MHz); set the receiving sensor operating voltages Vbd (e.g., -20V), Vex (e.g., 2.5V), and Vq (e.g., 3.0V).

[0087] 2) Assume the relevant environmental parameters obtained from the learning frames are as follows:

[0088] The ambient light value is higher than the ambient noise threshold (e.g., 80); the target distance is greater than the distance threshold (e.g., 5m); the target reflectivity is lower than the reflectivity threshold (e.g., 50%); the signal-to-noise ratio is lower than the second threshold (e.g., 10dB);

[0089] This indicates that the current detection environment has strong ambient light, and the object being detected is far from the receiver with low reflectivity, resulting in a low signal-to-noise ratio. Therefore, the laser power and exposure time can be increased, while simultaneously improving receiver performance and bandwidth. Thus, the optimal detection parameters can be output from the emission and reception parameter models as follows:

[0090] Set the laser emission pulse width to laser_pulse_width (e.g., 2ns); set the laser emission peak power to laser_pulse_peak (e.g., 45W); set the laser repetition rate period to laser_freq (e.g., 20MHz, the lower the frequency, the farther it can be measured); set the laser exposure time to laser_expo_time (e.g., 4ms); set the receiving sensor system operating frequency to sys_clk_freq (e.g., 200MHz); set the receiving sensor operating voltages Vbd (e.g., -22V), Vex (e.g., 2.8V), and Vq (e.g., 3.3V).

[0091] In one embodiment, after step S103, the method further includes:

[0092] The learning frame probe light is emitted once every preset time interval, and the current optimal detection parameters are adaptively readjusted to match the latest environmental conditions.

[0093] In this embodiment, as Figure 2 As shown, the implementation of the learning frame probe light periodically in the time dimension is illustrated using a frame rate of 30fps (30 exposures per second, with each exposure generating 1 frame of data). Without the learning frame probe light, the transmission / exposure and reception configurations used to generate each frame of data are identical, including exposure time, laser intensity, and receiver sensitivity. These configurations, once determined, cannot be modified, thus failing to adapt to the current detected environment. Consequently, the overall power consumption and reception performance are inevitably suboptimal. In this embodiment, a learning frame is added before the original normal frame at preset intervals. Figure 2 The diagram shows that a learning frame is added every second. That is, a learning frame probe light is emitted before the normal frame to detect the current environmental conditions. Then, the optimal detection parameters set in the previous cycle are adaptively adjusted, so that the normal probe light of the next 30 frames is emitted and received with the latest set working parameters. This allows the lidar to work with parameters that match the environment in real time in each cycle. It can flexibly adapt to environmental changes or target changes during the distance detection process, and further improve the lidar's adaptive adjustment capability.

[0094] Specifically, the histogram data of the learning frame obtained after the exposure time of the learning frame is not used as the data output of the normal frame detection light, that is, it does not participate in the construction of the histogram of the precise distance of the target in the subsequent detection. Instead, the 30 frames of data after adaptive learning are used as the output data for accurate ranging. The additional learning frames will not affect the frame rate of the entire system.

[0095] It should be noted that there is no necessary order between the above steps. Those skilled in the art will understand from the description of the embodiments of the present invention that the above steps may have different execution orders in different embodiments, that is, they may be executed in parallel or in turn, etc.

[0096] The present invention also provides a lidar detection parameter adjustment and control device, such as... Figure 3 As shown, Figure 3This is a structural diagram of a lidar detection parameter adjustment and control device according to an embodiment of the present invention. It includes a transmitting module 301, a receiving module 302, a laser control module 303, and a main control and adaptive module 304. The receiving module 302 and the laser control module 303 are both connected to the main control and adaptive module 304, and the laser control module 303 is also connected to the transmitting module 301. The transmitting module 301 is used to transmit learning frame detection light to the target, including a driver and a light source. The light source can be a light-emitting diode (LED), a laser diode (LD), an edge-emitting laser (EEL), a vertical-cavity surface-emitting laser (VCSEL), a picosecond laser, etc. The learning frame detection light is used to detect the current environmental conditions. The receiving module 302 is used to receive the reflected light from the target and acquire learning frame histogram data. It includes at least a photosensitive element for distance imaging and its related computation and processing circuitry. The photosensitive element can be a SPAD array, an avalanche photodiode, a photomultiplier tube, a silicon photomultiplier tube, etc. The processing circuitry can include a TDC or a TDC array, an ADC (Analog-to-Digital Converter), etc. Converter (analog-to-digital converter) or ADC array, histogram circuit, etc.; Laser control module 303 is used to control the transmitting module 301 to transmit the learning frame detection light with initial detection parameters; Main control and adaptive module 304 is used to analyze the histogram data of the learning frame, adaptively adjust the initial detection parameters according to the analysis results, and output the optimal detection parameters that match the current environmental conditions. The receiving module 302, laser control module 303, and main control and adaptive module 304 can be independent chips or systems, or they can be integrated on a single chip, or the receiving module 302 and laser control module 303 can be integrated on a single chip or system, and the main control and adaptive module 304 can be on a single chip or system. Since the above method embodiments have described the adjustment process of the lidar detection parameters in detail, please refer to the corresponding method embodiments above for details, and will not be repeated here.

[0097] In one embodiment, the main control and adaptive module 304 includes a distance calculation unit 341, an adaptive adjustment unit 342, and a main controller 343, wherein the distance calculation unit 341, the adaptive adjustment unit 342, and the main controller 343 are connected sequentially, and both the distance calculation unit 341 and the main controller 343 are connected to the receiving module 302. The distance calculation unit 341 is used to perform distance calculation and analysis on the learning frame histogram data to obtain the current environmental parameters. The adaptive adjustment unit 342 is used to adaptively adjust the initial detection parameters according to the environmental parameters to obtain the optimal detection parameters that match the environmental parameters. The main controller 343 is used to output the optimal detection parameters to the laser control module 303 and / or the receiving module 302 to control the working state of the transmitting module 301 and / or the receiving module 302. Since the adaptive parameter adjustment has been described in detail in the above method embodiment, please refer to the corresponding method embodiment above for details, and it will not be repeated here.

[0098] The following combination Figure 4 This paper introduces the distance detection process using a lidar detection parameter adjustment and control method:

[0099] S401, Set the laser emission and reception conditions for the learning frame;

[0100] S402, Learning Frame Exposure and Histogram Statistics;

[0101] S403, Learn frame histogram processing;

[0102] S404. Determine whether the target distance is less than the minimum range. If yes, proceed to step S405; otherwise, proceed to step S406.

[0103] S405, prompting the user to stop exposure;

[0104] S406. Determine if there are stains on the lens. If so, proceed to step S405; otherwise, proceed to step S407.

[0105] S407, Parameter adaptive adjustment;

[0106] S408, Set normal frame laser transmission and reception conditions;

[0107] S409, Normal Exposure in Histogram Statistics;

[0108] S410, Normal Frame Histogram Processing.

[0109] Before performing precise ranging, an additional learning frame is added to detect the current environmental conditions. Exposure is performed using the set laser emission and reception conditions of the learning frame until the exposure ends. Histogram statistics are then performed to obtain the learning frame histogram. By processing the learning frame histogram, environmental parameters including ambient light value, target distance, target reflectivity, and signal-to-noise ratio are obtained as input data for adaptive parameter adjustment.

[0110] Before the parameters are adaptively adjusted, it is also determined whether the currently detected target distance is less than the minimum range. If it is less than the minimum range, it means that the LiDAR cannot accurately detect the target at close range. For example, if the system's minimum range is 30cm, but the object is 10cm away, an exposure stop prompt will be output, prompting the user to move away from the target object appropriately to ensure the accuracy of the distance measurement. At the same time, it is further determined whether there are obvious stains on the lens. For example, it can be judged by features such as lens flare. If there are stains, an exposure stop prompt will also be output, and the user will be further prompted to wipe or clean the lens to avoid the lens from affecting the distance measurement error.

[0111] When performing adaptive parameter adjustment, environmental parameters are used as input data through pre-established parameter models or lookup tables, and the corresponding optimal detection parameters are adaptively adjusted and output. These parameters include emission parameters such as laser emission power and normal frame exposure time, as well as reception parameters such as receiver operating voltage, operating frequency, and data bandwidth.

[0112] Based on the optimal detection parameters output, the emission and reception conditions of the normal frame laser are set, and the exposure and histogram statistics of the normal frame are performed to obtain the corresponding normal frame histogram. By finding the peak and calculating the distance in the normal frame histogram, the accurate target distance under the optimal detection parameters can be obtained, so that the lidar can adaptively adjust its working parameters according to the environmental conditions to achieve a better balance between performance and power consumption.

[0113] In summary, this invention provides a method and apparatus for adjusting and controlling the detection parameters of a lidar. The method includes: setting initial detection parameters and a learning frame exposure time; emitting a learning frame detection light towards a target using the initial detection parameters and receiving the corresponding reflected light, wherein the learning frame detection light is used to detect the current environmental conditions; at the end of the learning frame exposure time, acquiring learning frame histogram data based on the received reflected light; analyzing the learning frame histogram data; and adaptively adjusting the initial detection parameters based on the analysis results to obtain optimal detection parameters that match the current environmental conditions. By detecting the current environmental conditions using a leading learning frame detection light and then dynamically adjusting the detection parameters, the lidar can adaptively adjust its operating parameters according to the environmental conditions, improving its matching degree with the detection environment and achieving a better balance between performance and power consumption.

[0114] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, several equivalent substitutions or obvious modifications can be made without departing from the concept of the present invention, and all such modifications, achieving the same performance or purpose, should be considered within the scope of protection of the present invention.

Claims

1. A method for adjusting and controlling lidar detection parameters, characterized in that, Includes the following steps: Set initial detection parameters and learning frame exposure time, emit learning frame detection light toward the target with the initial detection parameters and receive the corresponding reflected light. The learning frame detection light is used to detect the current environmental conditions. The initial detection parameters include emission parameters and reception parameters. At the end of the exposure time of the learning frame, the learning frame histogram data is obtained based on the received reflected light; The histogram data of the learning frames is analyzed, and the initial detection parameters are adaptively adjusted based on the analysis results to obtain the optimal detection parameters that match the current environmental conditions. The step of analyzing the histogram data of the learned frames and adaptively adjusting the initial detection parameters based on the analysis results to obtain optimal detection parameters that match the current environmental conditions includes: The histogram data of the learning frames is analyzed to obtain the current environmental parameters, which include ambient light value, target distance, target reflectivity, and signal-to-noise ratio. The initial detection parameters are adaptively adjusted based on the environmental parameters to bring the transmission and reception parameters to an optimal state, thereby obtaining the optimal detection parameters that match the environmental parameters. The step of adaptively adjusting the initial detection parameters based on the environmental parameters to obtain optimal detection parameters that match the environmental parameters specifically includes: Based on at least one of the ambient light value, target distance, target reflectivity, and signal-to-noise ratio, the emission parameters and / or receiving parameters in the initial detection parameters are dynamically adjusted to obtain the corresponding optimal detection parameters; wherein, the emission parameters include laser emission power and normal frame exposure time, and the receiving parameters include the receiver's operating voltage, operating frequency, and data bandwidth; The step of dynamically adjusting the transmission and / or reception parameters in the initial detection parameters based on at least one of the ambient light value, target distance, target reflectivity, and signal-to-noise ratio to obtain the corresponding optimal detection parameters specifically includes: Based on the application scenario, the transmission parameter model and the reception parameter model are constructed in advance, and the indicators of interest are set. Specifically, by constructing functional relationships, the lidar can perform self-learning and parameter adjustment under different environmental parameters to reach the corresponding constraints, thus completing the construction of the transmission parameter model and the reception parameter model. Based on the received environmental parameters, a first set of parameters that best matches the indicators of interest is selected from the transmission parameter model, and a second set of parameters that best matches the indicators of interest is selected from the reception parameter model. The first set of parameters and the second set of parameters are then used as the optimal detection parameters.

2. The lidar detection parameter adjustment and control method according to claim 1, characterized in that, The step of analyzing the learned frame histogram data to obtain the current environmental parameters includes: Ambient light values ​​are obtained without emitting the probe light from the learning frame; When the learning frame probe light is emitted, the learning frame histogram data collected by the emitted learning frame probe light is analyzed to obtain the current environmental parameters, including target distance, target reflectivity and signal-to-noise ratio.

3. The lidar detection parameter adjustment and control method according to claim 1, characterized in that, The exposure time of the learning frame is less than or much less than the exposure time of the normal frame.

4. The lidar detection parameter adjustment and control method according to claim 1, characterized in that, After analyzing the histogram data of the learned frames and adaptively adjusting the initial detection parameters based on the analysis results to obtain the optimal detection parameters that match the current environmental conditions, the method further includes: The learning frame probe light is emitted once every preset time interval to adaptively readjust the current optimal probe parameters to match the latest environmental conditions.

5. A lidar detection parameter adjustment and control device, characterized in that, include: A transmitting module is used to transmit a learning frame probe light to a target with initial detection parameters. The learning frame probe light is used to detect the current environmental conditions. The initial detection parameters include transmission parameters and reception parameters. The receiving module is used to receive the reflected light from the target and acquire the learning frame histogram data. The laser control module is used to control the emission module to emit the learning frame probe light with initial detection parameters; The main control and adaptive module is used to analyze the histogram data of the learning frame, adaptively adjust the initial detection parameters according to the analysis results, and output the optimal detection parameters that match the current environmental conditions. The main control and adaptive module includes: The distance calculation unit is used to perform distance calculation and analysis on the histogram data of the learning frame to obtain the current environmental parameters, including ambient light value, target distance, target reflectivity and signal-to-noise ratio; An adaptive adjustment unit is used to adaptively adjust the initial detection parameters according to the environmental parameters, adjust the transmission parameters and reception parameters to the optimal state, and obtain the optimal detection parameters that match the environmental parameters. The main controller is used to output the optimal detection parameters to the laser control module and / or receiving module to control the working state of the transmitting module and / or receiving module; The step of adaptively adjusting the initial detection parameters based on the environmental parameters to obtain optimal detection parameters that match the environmental parameters specifically includes: Based on at least one of the ambient light value, target distance, target reflectivity, and signal-to-noise ratio, the emission parameters and / or receiving parameters in the initial detection parameters are dynamically adjusted to obtain the corresponding optimal detection parameters; wherein, the emission parameters include laser emission power and normal frame exposure time, and the receiving parameters include the receiver's operating voltage, operating frequency, and data bandwidth; The step of dynamically adjusting the transmission and / or reception parameters in the initial detection parameters based on at least one of the ambient light value, target distance, target reflectivity, and signal-to-noise ratio to obtain the corresponding optimal detection parameters specifically includes: Based on the application scenario, the transmission parameter model and the reception parameter model are constructed in advance, and the indicators of interest are set. Specifically, by constructing functional relationships, the lidar can perform self-learning and parameter adjustment under different environmental parameters to reach the corresponding constraints, thus completing the construction of the transmission parameter model and the reception parameter model. Based on the received environmental parameters, a first set of parameters that best matches the indicators of interest is selected from the transmission parameter model, and a second set of parameters that best matches the indicators of interest is selected from the reception parameter model. The first set of parameters and the second set of parameters are then used as the optimal detection parameters.

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