Lidar-based processing method and apparatus, and device and vehicle

Abstract

A LiDAR-based processing method and apparatus, and a device and a vehicle. The method comprises: in response to a trigger event, controlling a LiDAR to transmit a pulse signal to a target object and receive a returned pulse signal, and on the basis of the received pulse signal, generating first time-series data (101); using a preset filter to process the first time-series data (102); and on the basis of the processed first time-series data, determining the distance to the target object, and the echo intensity of the target object (103).

Description

A processing method, device, equipment, and vehicle based on lidar.

[0001] Cross-references to related applications

[0002] This application claims priority to Chinese Patent Application No. 202510090886.1, filed on January 20, 2025, entitled "A Processing Method, Apparatus, Device and Vehicle Based on LiDAR", the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of lidar technology, and in particular to a lidar-based processing method, apparatus, equipment, and vehicle. Background Technology

[0004] Currently, vehicle-mounted LiDAR has been widely used as a sensor in fields such as intelligent driving. Detection and ranging, as important functions of LiDAR, have also become important research directions. Low cost of LiDAR is an important consideration in engineering applications.

[0005] However, the methods used to improve the detection capabilities and ranging accuracy of lidar are computationally complex, involve complex systems for improving accuracy, and cannot simultaneously improve accuracy while distinguishing objects with different reflectivities at close range. Summary of the Invention

[0006] In view of the above problems, this application proposes a lidar-based processing method, apparatus, device, and vehicle to overcome or at least partially solve the above problems, including:

[0007] A processing method based on lidar, the method comprising:

[0008] In response to a triggering event, the lidar is controlled to emit pulse signals to the target object and receive the returned pulse signals, and first timing data is generated based on the received pulse signals;

[0009] The first time-series data is processed using a pre-set filter;

[0010] Based on the processed first time-series data, the distance to the target object and the echo intensity are determined.

[0011] In some embodiments, the first timing data includes multiple time intervals and the number of photodetectors triggered in each time interval. Generating the first timing data based on the received pulse signal includes:

[0012] Convert the received pulse signal into an electrical signal;

[0013] The number of photodetectors triggered in each time interval is determined based on the electrical signal, and the first time sequence data is generated based on the number of photodetectors triggered in each time interval.

[0014] In some embodiments, the first time-series data is histogram data, where the horizontal axis of the histogram data represents the time interval and the vertical axis of the histogram data represents the number of triggered photodetectors.

[0015] In some embodiments, a pre-set filter is used to process the first time-series data, including:

[0016] The first time-series data is processed using the filter coefficients of a pre-set filter.

[0017] The filter coefficients are determined in the following manner:

[0018] Acquire the second time-series data collected from the test object;

[0019] Based on the second time-series data, determine the reflected echo of the test object;

[0020] The filter coefficients are set based on the reflected echoes from highly reflective objects in the test object.

[0021] In some embodiments, the filter coefficients of the filter are set based on the reflected echo from a high-reflectivity object in the test object, including:

[0022] The reflected echoes from highly reflective objects in the test object are used as the filter coefficients of the filter.

[0023] In some embodiments, the reflected echo from a highly reflective object in the test object is used as the filter coefficient of the filter, including:

[0024] When the number of duration intervals in the reflected echo of a highly reflective object in the test object is less than the preset number, the reflected echo of the highly reflective object is used as the filter coefficient of the filter.

[0025] When the number of duration intervals in the reflected echo of a high-reflectivity object in the test object is greater than the preset number and the reflected echo of the high-reflectivity object is a rectangular wave, the reflected echo of the high-reflectivity object is used as the filter coefficient of the filter.

[0026] The number of duration intervals refers to the number of time intervals that last when the number of photodetectors triggered in the reflected echo of a highly reflective object reaches a preset number.

[0027] In some embodiments, the filter coefficients of the filter are set based on the reflected echo from a high-reflectivity object in the test object, including:

[0028] The rising and falling edges of the reflected echo from the high-reflectivity object in the test object are used as the rising and falling edges of the filter coefficients of the filter.

[0029] In some embodiments, the rising and falling edges of the reflected echo from a highly reflective object in the test object are used as the rising and falling edges of the filter coefficients of the filter, including:

[0030] When the number of duration intervals in the reflected echo of a high-reflectivity object in the test object is greater than the preset number and the reflected echo of the high-reflectivity object is a non-rectangular wave, the rising edge and falling edge of the reflected echo of the high-reflectivity object are used as the rising edge and falling edge of the filter coefficients of the filter.

[0031] The number of duration intervals refers to the number of time intervals that last when the number of photodetectors triggered in the reflected echo of a highly reflective object reaches a preset number.

[0032] In some embodiments, it also includes:

[0033] Set the number of time intervals during which the values ​​of the filter coefficients reach a preset value to be greater than the number of duration intervals.

[0034] In some embodiments, it also includes:

[0035] Optimize each coefficient in the filter coefficients.

[0036] In some embodiments, optimization of each coefficient in the filter coefficients includes:

[0037] Sum the coefficients in the filter coefficients to obtain the sum value;

[0038] Divide each coefficient in the filter coefficients by the sum of the values.

[0039] In some embodiments, optimization of each coefficient in the filter coefficients includes:

[0040] Normalize each coefficient in the filter coefficients.

[0041] In some embodiments, optimization of each coefficient in the filter coefficients includes:

[0042] Multiply each coefficient in the filter coefficients by the desired echo intensity.

[0043] In some embodiments, the second time-series data includes multiple time intervals and the number of photodetectors triggered in each time interval. Acquiring the second time-series data collected on the test object includes:

[0044] The system controls the lidar to emit pulse signals at the test object at a specified distance and receives the returned pulse signals, and generates second timing data based on the received pulse signals.

[0045] In some embodiments, the second time-series data is histogram data, where the horizontal axis of the histogram data represents the time interval and the vertical axis of the histogram data represents the number of triggered photodetectors.

[0046] A lidar-based processing device, the device being used for:

[0047] In response to a triggering event, the lidar is controlled to emit pulse signals to the target object and receive the returned pulse signals, and first timing data is generated based on the received pulse signals;

[0048] The first time-series data is processed using a pre-set filter;

[0049] Based on the processed first time-series data, the distance to the target object and the echo intensity are determined.

[0050] An electronic device includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the method described above.

[0051] A vehicle comprising the above-described means and / or, the above-described electronic devices.

[0052] The embodiments of this application have the following advantages:

[0053] In this embodiment, by responding to a trigger event, the lidar is controlled to emit a pulse signal to the target object and receive the returned pulse signal. First time-series data is generated based on the received pulse signal. The first time-series data is processed using a pre-set filter. Based on the processed first time-series data, the distance to the target object and the echo intensity are determined. This achieves the improvement of the lidar's detection capability and ranging accuracy without increasing the cost of the lidar system through filter optimization. It has low complexity and can distinguish objects with different reflectivities at close range while improving accuracy. Attached Figure Description

[0054] To more clearly illustrate the technical solution of this application, the drawings used in the description of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0055] Figure 1 is a flowchart of a processing method based on lidar provided in some embodiments of this application;

[0056] Figure 2a is a flowchart of another processing method based on lidar provided in some embodiments of this application;

[0057] Figure 2b is a flowchart of another processing method based on lidar provided in some embodiments of this application;

[0058] Figure 3 is a flowchart of another processing method based on lidar provided in some embodiments of this application;

[0059] Figure 4 is a schematic diagram of an electronic device provided in some embodiments of this application. Detailed Implementation

[0060] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0061] In this embodiment, the convolution operation of the FIR filter (Finite Impulse Response) is used to complete the matched filtering function, thereby improving the ranging accuracy and realizing the function of distinguishing the intensity of objects with different reflectivities at close range without needing to know the transmitted signal model or change the sampling frequency. Moreover, it has the advantage of low complexity because the algorithm is easy to implement.

[0062] On the one hand, the ranging accuracy of lidar is related to its sampling frequency. For example, when the sampling frequency is 1 GHz, a time interval represents a nominal distance accuracy of 30 cm, or 15 cm when round-trip time is considered. However, the FIR filter designed based on reflected echo signals in this application embodiment achieves higher accuracy without increasing the sampling frequency. The convolution operation references the counts of preceding and following time intervals when calculating the count for the current time interval. This statistically reduces count fluctuations within the same time interval and distinguishes indistinguishable counts when the maximum echo count persists across multiple time intervals.

[0063] By reducing the count fluctuations within the same time interval during the rising and falling edges, interpolation can yield more accurate start and end points at half maximum width (FWHM). When the echo maximum value persists across multiple time intervals, due to the characteristics of matched filtering, the unique maximum value of the convolution between the echo and the designed filter is the peak position (and conversely, when the echo maximum value exists only within a single time interval, the unique maximum value is also the peak position). Therefore, convolution with the filter yields a more precise pulse position.

[0064] On the other hand, the inability to distinguish the echo intensity (or power) of objects with different reflectivities at close range can affect signal processing and point cloud algorithm processing. The filter design method proposed in this application maximizes the compatibility with the function of distinguishing the echo intensity of objects with different reflectivities at close range while maintaining the accuracy improvement function.

[0065] The distinction between the intensities of objects with different reflectivities at close range is mainly achieved by designing the number of time intervals for the duration of the filter's maximum value. When the duration of the filter's maximum value is greater than the duration of the maximum value of a high-reflectivity object, since the duration of the maximum value of a high-reflectivity object is longer than that of an ordinary object, objects with different maximum value durations can be directly distinguished by intensity through convolution.

[0066] In the embodiments of this application, the designed FIR filter can directly achieve accuracy improvement and intensity differentiation without the need for additional algorithms, additional system assistance, and prior information of the signal model. Therefore, it has low computational complexity and is easy to implement, making it a radar system with higher practicality.

[0067] The embodiments of this application improve ranging accuracy while distinguishing the intensity of objects with different reflectivities at close range, and have low computational complexity and do not require prior information of the signal model, as detailed below:

[0068] (1) No signal model is required as prior information. The optimal matched filter (several matched filters designed according to the curves of different reflected signals are used to filter and identify the optimal matched filter) requires the model of the transmitted signal as prior information to design the filter. However, the embodiments of this application do not need to obtain the model of the transmitted signal. The filter configuration can be completed using only the reflected signal.

[0069] (2) It has lower computational complexity. Compared with the method of calculating the target distance by multiple echo time differences, and the method of identifying and fitting filters for each signal curve and the method of complex algorithm calculation, the embodiments of this application do not need to search for filter coefficients for each signal curve, nor do they need to repeat or perform complex calculations. Therefore, it can achieve the function while having lower computational complexity.

[0070] (3) It simultaneously improves accuracy and distinguishes the intensity of objects with different reflectivity at close range. Compared to methods that only improve signal accuracy but cannot distinguish echo intensity, the filter designed based on the reflected signal in this application embodiment can more directly and realistically achieve the matched filtering function, thereby improving accuracy. In addition, by designing the filter based on the difference in the maximum duration of highly reflective and non-highly reflective objects, the resulting filter can improve accuracy while also distinguishing the intensity of objects with different reflectivity at close range.

[0071] The present application will be further described below with reference to the accompanying drawings:

[0072] Referring to Figure 1, a flowchart of a processing method based on lidar provided in some embodiments of this application is shown, which may specifically include the following steps:

[0073] Step 101: In response to the triggering event, control the lidar to emit a pulse signal to the target object and receive the returned pulse signal, and generate the first timing data based on the received pulse signal.

[0074] As an example, the triggering event can be an event that uses LiDAR, such as when LiDAR can be mounted on a vehicle and is needed to activate the vehicle's autonomous driving or assisted driving functions.

[0075] In some embodiments of this application, the first time-series data includes multiple time intervals and the number of photodetectors triggered in each time interval. In some examples, the first time-series data can be histogram data, where the horizontal axis of the histogram data can be the time interval and the vertical axis of the histogram data can be the number of photodetectors triggered.

[0076] In some embodiments of this application, generating first timing data based on a received pulse signal includes:

[0077] The received pulse signal is converted into an electrical signal; the number of photodetectors triggered in each time interval is determined based on the electrical signal, and the first time sequence data is generated based on the number of photodetectors triggered in each time interval.

[0078] The number of triggered photodetectors can characterize the number of photons received.

[0079] Step 102: Process the first time-series data using a pre-set filter.

[0080] As an example, the filter can be an FIR filter, which is the most basic component in a digital signal processing system. It can guarantee arbitrary amplitude-frequency characteristics while having strictly linear phase-frequency characteristics, and its unit sample response is of finite length.

[0081] In some embodiments of this application, a pre-set filter is used to process the first time-series data, including:

[0082] The first time-series data is processed using the filter coefficients of a pre-set filter.

[0083] Step 103: Determine the distance and echo intensity of the target object based on the processed first time series data.

[0084] After processing the first time-series data through a pre-set filter, the time interval of the horizontal axis of the processed first time-series data (i.e., histogram data) remains unchanged, while the vertical axis data shows a change in the number of triggered photodetectors. By using the processed first time-series data, the distance to the target object and the echo intensity can be determined, thereby improving the accuracy of distance detection and the intensity of echo differentiation.

[0085] As shown in Figure 2a, a laser emitter of the radar emits a pulse to the target object. The SPAD (Single Photon Avalanche Diode) receives the pulse reflected back from the target object and converts it into an electrical signal. The SPAD determines the number of photodetectors triggered in each time interval, thereby generating a histogram. The original histogram is convolved with a configured FIR filter to output the calculated histogram. Then, the target distance and echo intensity are obtained from the histogram using a distance estimation algorithm.

[0086] In some embodiments of this application, the filter coefficients are determined in the following manner:

[0087] Acquire the second time-series data collected from the test object; determine the reflected echo of the test object based on the second time-series data; set the filter coefficients of the filter based on the reflected echo of the high reflectivity object in the test object.

[0088] The test objects can include high-reflectivity objects and low-reflectivity objects. For example, traffic signs are high-reflectivity objects with a reflectivity of 90%-100%, while black cars are low-reflectivity objects with a reflectivity of 10%.

[0089] In some embodiments of this application, the second time-series data may include multiple time intervals and the number of photodetectors triggered in each time interval. In some examples, the second time-series data may be histogram data, where the horizontal axis of the histogram data may be the time interval and the vertical axis of the histogram data may be the number of photodetectors triggered.

[0090] In some embodiments of this application, acquiring second time-series data collected on the test object includes:

[0091] The system controls the lidar to emit pulse signals at the test object at a specified distance and receives the returned pulse signals, and generates second timing data based on the received pulse signals.

[0092] As an example, the specified distance can be 6m or 2m, allowing you to choose an extreme close-range situation.

[0093] For setting the filter coefficients, at least two cases exist: 1. Using the reflected echo from a highly reflective object in the test object as the filter coefficients; 2. Using the rising and falling edges of the reflected echo from a highly reflective object in the test object as the rising and falling edges of the filter coefficients. The following provides a detailed explanation of these two cases:

[0094] 1. Use the reflected echo from highly reflective objects in the test object as the filter coefficients of the filter:

[0095] In some embodiments of this application, the filter coefficients of the filter are set based on the reflected echo from a high-reflectivity object in the test object, including:

[0096] The reflected echoes from highly reflective objects in the test object are used as the filter coefficients of the filter.

[0097] In some embodiments of this application, the reflected echo from a highly reflective object in the test object is used as the filter coefficient of the filter, including:

[0098] When the number of duration intervals in the reflected echo of a highly reflective object in the test object is less than the preset number, the reflected echo of the highly reflective object is used as the filter coefficient of the filter.

[0099] When the number of duration intervals in the reflected echo of a high-reflectivity object in the test object is greater than the preset number and the reflected echo of the high-reflectivity object is a rectangular wave, the reflected echo of the high-reflectivity object is used as the filter coefficient of the filter.

[0100] The number of duration intervals refers to the number of time intervals that last when the number of photodetectors triggered in the reflected echo of a highly reflective object reaches a preset number.

[0101] 2. The rising and falling edges of the reflected echo from the highly reflective object in the test object are used as the rising and falling edges of the filter coefficients:

[0102] In some embodiments of this application, the filter coefficients of the filter are set based on the reflected echo from a high-reflectivity object in the test object, including:

[0103] The rising and falling edges of the reflected echo from the high-reflectivity object in the test object are used as the rising and falling edges of the filter coefficients of the filter.

[0104] In some embodiments of this application, the rising and falling edges of the reflected echo from a highly reflective object in the test object are used as the rising and falling edges of the filter coefficients of the filter, including:

[0105] When the number of duration intervals in the reflected echo of a high-reflectivity object in the test object is greater than the preset number and the reflected echo of the high-reflectivity object is a non-rectangular wave, the rising edge and falling edge of the reflected echo of the high-reflectivity object are used as the rising edge and falling edge of the filter coefficients of the filter.

[0106] The number of duration intervals refers to the number of time intervals that last when the number of photodetectors triggered in the reflected echo of a highly reflective object reaches a preset number.

[0107] In practical applications, the number of duration intervals in the reflected echoes of high-reflectivity objects in the test object is obtained, and then it is determined whether the number of duration intervals is greater than a preset number, such as 1.

[0108] When the number of duration intervals is less than or equal to the preset number, the reflected echoes from highly reflective objects can be directly used as filter coefficients for the filter.

[0109] If the number of duration intervals exceeds the preset number, it can be further determined whether the reflected echo of a high-reflectivity object is a rectangular wave, and differentiated processing can be performed based on the detection of rectangular waves, as follows:

[0110] When the reflected echo from a highly reflective object is a rectangular wave, the reflected echo from the highly reflective object can be directly used as the filter coefficients. In some examples, it can be further determined whether the reflected echo from a non-highly reflective object at the same distance is a rectangular wave. If the reflected echo from a non-highly reflective object at the same distance is not a rectangular wave, the reflected echo from the highly reflective object can be directly used as the filter coefficients. If the reflected echo from a non-highly reflective object at the same distance is a rectangular wave, it indicates that the current situation is indistinguishable and the intensity cannot be distinguished through waveform calculation, but the reflected echo from the highly reflective object can still be used as the filter coefficients.

[0111] When the reflected echo of a high-reflectivity object is a non-rectangular wave, the rising and falling edges of the reflected echo of the high-reflectivity object in the test object can be used as the rising and falling edges of the filter coefficients. Furthermore, the number of time intervals during which the values ​​of the filter coefficients reach the preset values ​​can be set to be greater than the number of duration intervals, and the steps of optimizing each coefficient in the filter coefficients can be performed.

[0112] In some embodiments of this application, the method further includes setting the number of time intervals during which the values ​​of the filter coefficients reach a preset value to be greater than the number of duration intervals.

[0113] In practical applications, the duration of the maximum value of the filter coefficients (i.e., the number of time intervals during which the value reaches a preset value) is designed to be M+1, where M+1 is greater than the maximum duration M of highly reflective objects (i.e., the number of time intervals in the reflected echo of highly reflective objects in the test object). In this case, the length of the filter coefficients is the echo width plus one. By setting the number of time intervals during which the filter coefficients reach a preset value to be greater than the number of duration intervals, the reflected echoes of highly reflective and low-reflective objects can be distinguished in intensity after filter convolution, improving the accuracy of close-range differentiation.

[0114] In some embodiments of this application, the method further includes optimizing each coefficient in the filter coefficients.

[0115] In some embodiments of this application, the optimization of each coefficient in the filter coefficients includes: summing each coefficient in the filter coefficients to obtain a sum value; and dividing each coefficient in the filter coefficients by the sum value.

[0116] In practical applications, by summing the designed filter coefficients and denoting the sum as SumFIR, and then dividing the filter coefficients by SumFIR, this step converts the maximum value of the echo intensity obtained after convolution (the original echo and the result of convolving the filter) into 1.

[0117] In this embodiment, by summing the filter coefficients and dividing each filter coefficient by the summation value, the filter coefficients can be limited to the maximum value range, which facilitates subsequent data processing.

[0118] In some embodiments of this application, the optimization of each coefficient in the filter coefficients includes: normalizing each coefficient in the filter coefficients.

[0119] In practical applications, the designed filter coefficients can be divided by their maximum values. This step converts the maximum value of the filter to 1, and the other filter coefficients are proportionally converted to values ​​between 0 and 1, thereby normalizing each coefficient in the filter coefficients.

[0120] In this embodiment, by normalizing each coefficient in the filter coefficients, the filter coefficients with different dimensions are unified to the same dimension, so that the output amplitude of different filter coefficients is consistent, which facilitates subsequent comparison and analysis, and can maintain the stability of the filter, prevent numerical problems caused by coefficients that are too large or too small, and enhance the adaptability and compatibility of the filter.

[0121] In some embodiments of this application, the optimization of each coefficient in the filter coefficients includes multiplying each coefficient in the filter coefficients by the desired echo intensity.

[0122] In practical applications, by multiplying the filter coefficients by the expected maximum value of the echo intensity after convolution, this step transforms the maximum value of the echo intensity after filter convolution into the expected value, and transforms the echo intensity range into 0 to the maximum value of the echo intensity after convolution mapped.

[0123] In this embodiment, the filter coefficients are correlated with the desired echo intensity by multiplying each coefficient in the filter coefficients by the desired echo intensity, thereby improving the accuracy of the set filter coefficients.

[0124] As shown in Figure 2b, the specific details are as follows:

[0125] Step 201: Collect a large amount of histogram data of the object at the selected distance, calculate the average to obtain the average histogram, and obtain the reflected echo of the object at the selected distance.

[0126] Step 202: Determine the number of time intervals in which the maximum reflected echo of the selected high-reflectivity object lasts, denoted as M.

[0127] Step 203: Determine if M is greater than 1. If yes, execute S205; otherwise, execute S204.

[0128] Step 204: Since the echo must have a maximum value, M is a positive integer. M is not greater than 1, which means M equals 1. At this time, there is only one maximum echo value, and the reflected echo of this highly reflective object can be used as the filter coefficient.

[0129] Step 205: Determine whether the reflected echo from the high-reflectivity object is a rectangular wave. If yes, proceed to step S206; otherwise, proceed to step S209.

[0130] Step 206: Determine whether the reflected echo from a non-high reflective object at the same distance is a rectangular wave. If yes, proceed to step S207; otherwise, proceed to step S208.

[0131] Step 207: If the reflected echoes of both high-reflection and low-reflection objects are rectangular waves, they are considered physically indistinguishable and cannot achieve the purpose of distinguishing intensity using waveform calculations. However, the reflected echoes of high-reflection objects can still be used as filter coefficients to improve accuracy.

[0132] Step 208: The reflected echo of a highly reflective object is a rectangular wave, while the reflected echo of a non-highly reflective object is not a rectangular wave. Using the reflected echo of this highly reflective object as the filter coefficient can improve accuracy and distinguish the intensity of objects with different reflectivities at close range.

[0133] Step 209: When the reflected echo from a highly reflective object is not a rectangular wave, it indicates that the highly reflective object has not reached full saturation at the current distance. Therefore, the low-reflective object is also not saturated. The maximum duration of the low-reflective object's value will be shorter than that of the highly reflective object, thus distinguishing between the two. In this case, the rising and falling edges of the reflected echo are used as the rising and falling edges of the filter.

[0134] Step 210: Design the duration of the maximum value of the filter coefficients to be M+1, where the duration of the maximum value of M+1 is greater than the duration of the maximum value of the highly reflective object, M. At this point, the length of the filter coefficients is the echo width plus 1. This allows the reflected echoes from highly reflective and low-reflective objects to be distinguished in intensity after the filter convolution.

[0135] Step 211: Sum the coefficients of the designed filter and denote the sum as SumFIR.

[0136] Step 212: Divide the designed filter coefficients by their maximum value. This step converts the maximum value of the filter to 1, and the other filter coefficients are converted to numbers between 0 and 1 proportionally.

[0137] Step 213: Divide the filter coefficients by SumFIR. This step converts the maximum value of the echo intensity obtained after convolution (the original echo and the echo obtained by convolving the filter) to 1.

[0138] Step 214: Multiply the filter coefficients by the expected maximum value of the echo intensity after convolution. This step transforms the maximum value of the echo intensity after filter convolution into the expected value, and transforms the echo intensity range into 0 to the mapped maximum value of the echo intensity after convolution.

[0139] In this embodiment, by responding to a trigger event, the lidar is controlled to emit a pulse signal to the target object and receive the returned pulse signal. First time-series data is generated based on the received pulse signal. The first time-series data is processed using a pre-set filter. Based on the processed first time-series data, the distance to the target object and the echo intensity are determined. This achieves the improvement of the lidar's detection capability and ranging accuracy without increasing the cost of the lidar system through filter optimization. It has low complexity and can distinguish objects with different reflectivities at close range while improving accuracy.

[0140] Referring to FIG3, a flowchart of another LiDAR-based processing method provided in some embodiments of this application is shown, which may specifically include the following steps:

[0141] Step 301: Obtain the second time-series data collected from the test object.

[0142] Step 302: Determine the reflected echo of the test object based on the second time series data.

[0143] Step 303: Set the filter coefficients of the filter based on the reflected echoes from high-reflectivity objects in the test object.

[0144] Step 304: In response to the triggering event, control the lidar to emit a pulse signal to the target object and receive the returned pulse signal, and generate the first timing data based on the received pulse signal.

[0145] Step 305: The first time-series data is processed using a pre-set filter.

[0146] Step 306: Determine the distance to the target object and the echo intensity based on the processed first time series data.

[0147] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of this application are not limited to the described order of actions, because according to the embodiments of this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all examples, and the actions involved are not necessarily required for the embodiments of this application.

[0148] Some embodiments of this application also provide a LiDAR-based processing device, which is used for:

[0149] In response to a triggering event, the lidar is controlled to emit pulse signals to the target object and receive the returned pulse signals, and first timing data is generated based on the received pulse signals;

[0150] The first time-series data is processed using a pre-set filter;

[0151] Based on the processed first time-series data, the distance to the target object and the echo intensity are determined.

[0152] In some embodiments, the first timing data includes multiple time intervals and the number of photodetectors triggered in each time interval. Generating the first timing data based on the received pulse signal includes:

[0153] Convert the received pulse signal into an electrical signal;

[0154] The number of photodetectors triggered in each time interval is determined based on the electrical signal, and the first time sequence data is generated based on the number of photodetectors triggered in each time interval.

[0155] In some embodiments, the first time-series data is histogram data, where the horizontal axis of the histogram data represents the time interval and the vertical axis of the histogram data represents the number of triggered photodetectors.

[0156] In some embodiments, a pre-set filter is used to process the first time-series data, including:

[0157] The first time-series data is processed using the filter coefficients of a pre-set filter.

[0158] The filter coefficients are determined in the following manner:

[0159] Acquire the second time-series data collected from the test object;

[0160] Based on the second time-series data, determine the reflected echo of the test object;

[0161] The filter coefficients are set based on the reflected echoes from highly reflective objects in the test object.

[0162] In some embodiments, the filter coefficients of the filter are set based on the reflected echo from a high-reflectivity object in the test object, including:

[0163] The reflected echoes from highly reflective objects in the test object are used as the filter coefficients of the filter.

[0164] In some embodiments, the reflected echo from a highly reflective object in the test object is used as the filter coefficient of the filter, including:

[0165] When the number of duration intervals in the reflected echo of a highly reflective object in the test object is less than the preset number, the reflected echo of the highly reflective object is used as the filter coefficient of the filter.

[0166] When the number of duration intervals in the reflected echo of a high-reflectivity object in the test object is greater than the preset number and the reflected echo of the high-reflectivity object is a rectangular wave, the reflected echo of the high-reflectivity object is used as the filter coefficient of the filter.

[0167] The number of duration intervals refers to the number of time intervals that last when the number of photodetectors triggered in the reflected echo of a highly reflective object reaches a preset number.

[0168] In some embodiments, the filter coefficients of the filter are set based on the reflected echo from a high-reflectivity object in the test object, including:

[0169] The rising and falling edges of the reflected echo from the high-reflectivity object in the test object are used as the rising and falling edges of the filter coefficients of the filter.

[0170] In some embodiments, the rising and falling edges of the reflected echo from a highly reflective object in the test object are used as the rising and falling edges of the filter coefficients of the filter, including:

[0171] When the number of duration intervals in the reflected echo of a high-reflectivity object in the test object is greater than the preset number and the reflected echo of the high-reflectivity object is a non-rectangular wave, the rising edge and falling edge of the reflected echo of the high-reflectivity object are used as the rising edge and falling edge of the filter coefficients of the filter.

[0172] The number of duration intervals refers to the number of time intervals that last when the number of photodetectors triggered in the reflected echo of a highly reflective object reaches a preset number.

[0173] In some embodiments, it also includes:

[0174] Set the number of time intervals during which the values ​​of the filter coefficients reach a preset value to be greater than the number of duration intervals.

[0175] In some embodiments, it also includes:

[0176] Optimize each coefficient in the filter coefficients.

[0177] In some embodiments, optimization of each coefficient in the filter coefficients includes:

[0178] Sum the coefficients in the filter coefficients to obtain the sum value;

[0179] Divide each coefficient in the filter coefficients by the sum of the values.

[0180] In some embodiments, optimization of each coefficient in the filter coefficients includes:

[0181] Normalize each coefficient in the filter coefficients.

[0182] In some embodiments, optimization of each coefficient in the filter coefficients includes:

[0183] Multiply each coefficient in the filter coefficients by the desired echo intensity.

[0184] In some embodiments, the second time-series data includes multiple time intervals and the number of photodetectors triggered in each time interval. Acquiring the second time-series data collected on the test object includes:

[0185] The system controls the lidar to emit pulse signals at the test object at a specified distance and receives the returned pulse signals, and generates second timing data based on the received pulse signals.

[0186] In some embodiments, the second time-series data is histogram data, where the horizontal axis of the histogram data represents the time interval and the vertical axis of the histogram data represents the number of triggered photodetectors.

[0187] Some embodiments of this application also provide an electronic device, as shown in FIG4. FIG4 is a schematic diagram of an electronic device provided in some embodiments of this application. The electronic device includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, it implements the method described above.

[0188] Some embodiments of this application also provide a vehicle that includes the above-described devices and / or, the above-described electronic devices.

[0189] Some embodiments of this application also provide a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, it implements the method described above.

[0190] Some embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the method described above.

[0191] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0192] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0193] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0194] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0195] This application describes embodiments with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

[0196] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0197] These computer program instructions may also be loaded onto a computer or other programmable data processing terminal equipment to cause a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable terminal equipment, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0198] Although some embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make further changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including some embodiments as well as all changes and modifications falling within the scope of the embodiments of this application.

[0199] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes the aforementioned element.

[0200] The above provides a detailed description of a laser radar-based processing method, apparatus, device, and vehicle. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A processing method based on lidar, wherein, The method includes: In response to a triggering event, the lidar is controlled to emit pulse signals to the target object and receive the returned pulse signals, and first timing data is generated based on the received pulse signals; The first time-series data is processed using a pre-set filter; Based on the processed first time-series data, the distance to the target object and the echo intensity are determined.

2. The method according to claim 1, wherein, The first time-series data includes multiple time intervals and the number of photodetectors triggered in each time interval. Generating the first time-series data based on the received pulse signals includes: Convert the received pulse signal into an electrical signal; The number of photodetectors triggered in each time interval is determined based on the electrical signal, and first time-series data is generated based on the number of photodetectors triggered in each time interval.

3. The method according to claim 2, wherein, The first time-series data is histogram data, where the horizontal axis of the histogram data represents the time interval, and the vertical axis of the histogram data represents the number of triggered photodetectors.

4. The method according to any one of claims 1 to 3, wherein, The process of processing the first time-series data using a pre-set filter includes: The first time-series data is processed using the filter coefficients of a pre-set filter. The filter coefficients are determined in the following manner: Acquire the second time-series data collected from the test object; The reflected echo of the test object is determined based on the second time series data; The filter coefficients are set based on the reflected echoes from high-reflectivity objects in the test object.

5. The method according to claim 4, wherein, The step of setting the filter coefficients based on the reflected echo from the high-reflectivity object in the test object includes: The reflected echoes from highly reflective objects in the test object are used as the filter coefficients of the filter.

6. The method according to claim 5, wherein, The step of using the reflected echo from the high-reflectivity object in the test object as the filter coefficients includes: When the number of duration intervals in the reflected echo of a high-reflectivity object in the test object is less than a preset number, the reflected echo of the high-reflectivity object is used as the filter coefficient of the filter. When the number of duration intervals in the reflected echo of a high-reflectivity object in the test object is greater than a preset number and the reflected echo of the high-reflectivity object is a rectangular wave, the reflected echo of the high-reflectivity object is used as the filter coefficient of the filter. The number of duration intervals refers to the number of time intervals that last when the number of photodetectors triggered in the reflected echo of the highly reflective object reaches a preset number.

7. The method according to claim 4, wherein, The step of setting the filter coefficients based on the reflected echo from the high-reflectivity object in the test object includes: The rising and falling edges of the reflected echo from the high-reflectivity object in the test object are used as the rising and falling edges of the filter coefficients of the filter.

8. The method according to claim 7, wherein, The step of using the rising and falling edges of the reflected echo from the high-reflectivity object in the test object as the rising and falling edges of the filter coefficients includes: When the number of duration intervals in the reflected echo of a high-reflectivity object in the test object is greater than a preset number and the reflected echo of the high-reflectivity object is a non-rectangular wave, the rising edge and falling edge of the reflected echo of the high-reflectivity object are used as the rising edge and falling edge of the filter coefficients of the filter. The number of duration intervals refers to the number of time intervals that last when the number of photodetectors triggered in the reflected echo of the highly reflective object reaches a preset number.

9. The method according to claim 8, wherein, Also includes: The number of time intervals during which the values ​​of the filter coefficients reach a preset value is set to be greater than the number of duration intervals.

10. The method according to any one of claims 4 to 9, wherein, Also includes: The coefficients in the filter coefficients are optimized.

11. The method according to claim 10, wherein, The optimization of each coefficient in the filter coefficients includes: The summation of each coefficient in the filter coefficients is obtained; Divide each coefficient in the filter coefficients by the summation value.

12. The method according to claim 10, wherein, The optimization of each coefficient in the filter coefficients includes: Normalize each coefficient in the filter coefficients.

13. The method according to claim 10, wherein, The optimization of each coefficient in the filter coefficients includes: Multiply each coefficient in the filter coefficients by the desired echo intensity.

14. The method according to any one of claims 4 to 13, wherein, The second time-series data includes multiple time intervals and the number of photodetectors triggered in each time interval. Acquiring the second time-series data collected from the test object includes: The system controls the lidar to emit pulse signals at the test object at a specified distance and receives the returned pulse signals, and generates second timing data based on the received pulse signals.

15. The method according to claim 14, wherein, The second time-series data is histogram data, where the horizontal axis of the histogram data represents the time interval, and the vertical axis of the histogram data represents the number of triggered photodetectors.

16. A processing device based on lidar, wherein, The device is used for: In response to a triggering event, the lidar is controlled to emit pulse signals to the target object and receive the returned pulse signals, and first timing data is generated based on the received pulse signals; The first time-series data is processed using a pre-set filter; Based on the processed first time-series data, the distance to the target object and the echo intensity are determined.

17. An electronic device, wherein, It includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the method as described in any one of claims 1 to 15.

18. A vehicle, wherein, The vehicle includes the device as described in claim 16, and / or the electronic device as described in claim 17.

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