Processing method, device and equipment based on laser radar and vehicle

Abstract

The embodiment of the invention provides a processing method, device and equipment based on a laser radar, and a vehicle, and the method comprises the steps: controlling the laser radar to transmit a pulse signal to a target object through responding to a triggering event, receiving a returned pulse signal, generating first time sequence data according to the received pulse signal, and carrying out the first time sequence data through a preset filter, and processing the first time sequence data, and determining the distance and echo intensity of the target object according to the processed first time sequence data. According to the embodiment of the invention, the method achieves the optimization of the filter, improves the detection capability and range finding precision of the laser radar under the condition that the cost of a radar system is not increased, is low in complexity, and can give consideration to the discrimination of objects with different reflectance at a short distance while improving the precision.

Description

Technical Field

[0001] The present invention relates to the field of laser radar technology, and in particular to a laser radar-based processing method, device, equipment and vehicle. Background Art

[0002] At present, automotive laser radar has been widely used as a sensor in fields such as intelligent driving. Detection and ranging, as important functions of laser radar, have also become important research directions. The low cost of laser radar is an important consideration in engineering applications. Therefore, how to obtain higher detection capabilities and ranging accuracy without increasing the cost of the radar system is of great significance in the design and application of radar.

[0003] However, existing technologies for improving the detection capability and ranging accuracy of lidar have high computational complexity, complex systems for improving accuracy, and cannot simultaneously improve accuracy while distinguishing between objects with different reflectivity at close range. Summary of the invention

[0004] In view of the above problems, a laser radar-based processing method, device, equipment and vehicle are proposed to overcome the above problems or at least partially solve the above problems, including:

[0005] A laser radar-based processing method, the method comprising:

[0006] In response to a trigger event, control the laser radar to transmit a pulse signal to the target object and receive a returned pulse signal, and generate first time series data according to the received pulse signal;

[0007] Using a preset filter to process the first time series data;

[0008] The distance and echo intensity of the target object are determined according to the processed first time series data.

[0009] Optionally, the first time series data includes a plurality of time intervals and the number of light detectors triggered in each time interval, and the generating of the first time series data according to the received pulse signal includes:

[0010] Convert the received pulse signal into an electrical signal;

[0011] The number of light detectors triggered in each time interval is determined according to the electrical signal, and the first time series data is generated according to the number of light detectors triggered in each time interval.

[0012] Optionally, the first time series data is histogram data, the horizontal axis data of the histogram data is a time interval, and the vertical axis data of the histogram data is the number of triggered light detectors.

[0013] Optionally, the using a preset filter to process the first time series data includes:

[0014] Processing the first time series data using a preset filter coefficient;

[0015] The filter coefficients are determined in the following manner:

[0016] Acquiring second time series data collected from the test object;

[0017] determining a reflected echo of the test object according to the second time series data;

[0018] The filter coefficient of the filter is set according to the reflected echo of the high reflectivity object in the test object.

[0019] Optionally, setting a filter coefficient of a filter according to a reflected echo of an object with high reflectivity in the test object comprises:

[0020] The reflected echo of the object with high reflectivity in the test object is used as the filter coefficient of the filter.

[0021] Optionally, the using the reflected echo of the high reflectivity object in the test object as the filter coefficient of the filter includes:

[0022] When the number of duration intervals in the reflected echo of the high-reflectivity object in the test object is less than a preset number, using the reflected echo of the high-reflectivity object as the filter coefficient of the filter;

[0023] When the number of duration intervals in the reflected echo of the 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, using the reflected echo of the high-reflectivity object as a filter coefficient of the filter;

[0024] The number of duration intervals is the number of time intervals that last when the number of light detectors triggered by the reflected echo of the high-reflectivity object reaches a preset number.

[0025] Optionally, setting a filter coefficient of a filter according to a reflected echo of an object with high reflectivity in the test object comprises:

[0026] The rising edge and the falling edge of the reflected echo of the high reflectivity object in the test object are used as the rising edge and the falling edge of the filter coefficient of the filter.

[0027] Optionally, the taking the rising edge and the falling edge of the reflected echo of the high-reflectivity object in the test object as the rising edge and the falling edge of the filter coefficient of the filter includes:

[0028] When the number of duration intervals in the reflected echo of the 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 the falling edge of the reflected echo of the high-reflectivity object are used as the rising edge and the falling edge of the filter coefficient of the filter;

[0029] The number of duration intervals is the number of time intervals that last when the number of light detectors triggered by the reflected echo of the high-reflectivity object reaches a preset number.

[0030] Optionally, it also includes:

[0031] The number of time intervals during which the value in the filter coefficient reaches a preset value is set to be greater than the number of duration intervals.

[0032] Optionally, it also includes:

[0033] Each coefficient of the filter coefficients is optimized.

[0034] Optionally, the optimizing each coefficient in the filter coefficients includes:

[0035] Summing each coefficient in the filter coefficients to obtain a sum value;

[0036] Each of the filter coefficients is divided by the summed value.

[0037] Optionally, the optimizing each coefficient in the filter coefficients includes:

[0038] Each coefficient of the filter coefficients is normalized.

[0039] Optionally, the optimizing each coefficient in the filter coefficients includes:

[0040] Each of the filter coefficients is multiplied by the expected echo strength.

[0041] Optionally, the second time series data includes a plurality of time intervals and the number of light detectors triggered in each time interval, and the acquiring of the second time series data collected from the test object includes:

[0042] The laser radar is controlled to transmit a pulse signal to the test object at a specified distance and receive a returned pulse signal, and second time series data is generated according to the received pulse signal.

[0043] Optionally, the second time series data is histogram data, the abscissa data of the histogram data is a time interval, and the ordinate data of the histogram data is the number of triggered light detectors.

[0044] A processing device based on laser radar, the device is used for:

[0045] In response to a trigger event, control the laser radar to transmit a pulse signal to the target object and receive a returned pulse signal, and generate first time series data according to the received pulse signal;

[0046] Using a preset filter to process the first time series data;

[0047] The distance and echo intensity of the target object are determined according to the processed first time series data.

[0048] An electronic device comprises a processor, a memory and a computer program stored in the memory and capable of running on the processor, wherein the computer program implements the method described above when executed by the processor.

[0049] A vehicle, comprising the device as described above, and / or the electronic device as described above.

[0050] The embodiments of the present invention have the following advantages:

[0051] In an embodiment of the present invention, by responding to a trigger event, the laser radar is controlled to transmit a pulse signal to the target object and receive a returned pulse signal, a first time series data is generated according to the received pulse signal, the first time series data is processed using a pre-set filter, and the distance and echo intensity of the target object are determined according to the processed first time series data. This achieves the improvement of the detection capability and ranging accuracy of the laser radar without increasing the cost of the radar system by optimizing the filter, has low complexity, and can improve accuracy while distinguishing objects with different reflectivity at close range. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solution of the present invention, the accompanying drawings required for use in the description of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0053] Figure 1 is a flowchart of a laser radar-based processing method provided by some embodiments of the present invention;

[0054] Figure 2a is a flowchart of another laser radar-based processing method provided by some embodiments of the present invention;

[0055] Figure 2b is a flowchart of another laser radar-based processing method provided by some embodiments of the present invention;

[0056] Figure 3 It is a step flow chart of another laser radar-based processing method provided in some embodiments of the present invention. DETAILED DESCRIPTION

[0057] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] In the embodiment of the present invention, 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 intensity distinction function of objects with different reflectivity at close range without the need for a known transmission signal model and without changing the sampling frequency, and having the advantage of low complexity due to the easy implementation of the algorithm.

[0059] On the one hand, the ranging accuracy of the laser radar is related to the sampling frequency of the radar. For example, when the sampling frequency is 1Ghz, one time interval represents a nominal distance accuracy of 30cm, or 15cm when the round-trip time is considered. The FIR filter designed based on the reflected echo signal in the embodiment of the present invention can obtain higher accuracy without increasing the sampling frequency. The convolution operation refers to the counts of the previous and next time intervals when calculating the counts of the current time interval, which will statistically reduce the count fluctuations in the same time interval. At the same time, when the maximum echo count lasts for multiple time intervals, these indifferent counts can be distinguished.

[0060] After reducing the count fluctuations in the same time interval of the rising and falling edges, the interpolation calculation can obtain more accurate half-width starting and ending points. When the echo maximum value lasts for multiple time intervals, due to the characteristics of matched filtering, the only maximum value of the echo convolution with the designed filter is the peak position (when the echo maximum value has only one time interval, the only maximum value of the convolution is also the peak position). Therefore, after convolution with the filter, a more accurate pulse position can be obtained.

[0061] On the other hand, the phenomenon that the echo intensity (or power) of objects with different reflectivity at close range cannot be distinguished will affect signal processing and point cloud algorithm processing. The filter design method proposed in the present invention is compatible with the function of distinguishing the echo intensity of objects with different reflectivity at close range to the greatest extent while maintaining the accuracy improvement function.

[0062] The intensity of objects with different reflectivity at close range is mainly distinguished by designing the number of time intervals during which the filter maximum value lasts. When the duration of the filter maximum value is greater than the duration of the maximum value of the high-reflectivity object, since the maximum value of the high-reflectivity object lasts longer than that of ordinary objects, objects with different maximum value durations can be directly distinguished in terms of intensity through convolution.

[0063] In the embodiment of the present invention, the designed FIR filter can directly achieve accuracy improvement and intensity differentiation in terms of function, without the need for additional algorithms, additional system assistance and prior information of the signal model. Therefore, it has lower computational complexity and is easy to implement, and is a radar system with higher practicality.

[0064] Through the embodiments of the present invention, the distance measurement accuracy can be improved while distinguishing the intensity of objects with different reflectivity at close range, and the computational complexity is low and no prior information of the signal model is required. The details are as follows:

[0065] (1) The signal model is not required as a priori information. The best matched filter (filtering is performed by designing several matched filters according to the curves of different reflected signals to identify the best matched filter) requires the model of the transmitted signal as a priori information to design the filter. However, the embodiment of the present invention does not need to obtain the model of the transmitted signal and only needs to use the reflected signal to complete the filter configuration.

[0066] (2) It has lower computational complexity. Compared with the method of calculating the target distance by using multiple echo time differences, and the method of identifying a fitting filter for each signal curve and requiring complex algorithm operations, the embodiment of the present invention does not need to search for filter coefficients for each signal curve, nor does it require repeated or complex operations. Therefore, it can achieve functions while having lower computational complexity.

[0067] (3) It has the functions of improving accuracy and distinguishing the intensity of objects with different reflectivity at close range. Compared with the method of only improving the signal accuracy but failing to distinguish the echo intensity, the filter designed according to the reflected signal in the embodiment of the present invention realizes the matched filtering function more directly and truly, thereby achieving the purpose of improving accuracy. In addition, the filter is designed according to the difference in the maximum duration of high-reflective objects and non-high-reflective objects. The obtained filter improves the accuracy and has the function of distinguishing the intensity of objects with different reflectivity at close range.

[0068] The present invention will be further described below in conjunction with the accompanying drawings:

[0069] Reference Figure 1 , shows a flowchart of a laser radar-based processing method provided by some embodiments of the present invention, which may specifically include the following steps:

[0070] Step 101, in response to a trigger event, control the laser radar to transmit a pulse signal to a target object and receive a returned pulse signal, and generate first time series data according to the received pulse signal.

[0071] As an example, the triggering event may be an event of using a lidar, such as a lidar that can be mounted on a vehicle and that is required to enable automatic driving or assisted driving of the vehicle.

[0072] In some embodiments of the present invention, the first timing data includes multiple time intervals and the number of light detectors triggered in each time interval. In some examples, the first timing data may be histogram data, the horizontal axis data of the histogram data may be the time interval, and the vertical axis data of the histogram data may be the number of light detectors triggered.

[0073] In some embodiments of the present invention, generating first time series data according to the received pulse signal includes:

[0074] The received pulse signal is converted into an electrical signal; the number of light detectors triggered in each time interval is determined according to the electrical signal, and the first time series data is generated according to the number of light detectors triggered in each time interval.

[0075] The number of triggered photodetectors can represent the number of received photons.

[0076] Step 102: Use a preset filter to process the first time series data.

[0077] As an example, the filter may be a FIR filter, which is the most basic element in a digital signal processing system. It can have a strict linear phase-frequency characteristic while ensuring an arbitrary amplitude-frequency characteristic, and its unit sampling response is of finite length.

[0078] In some embodiments of the present invention, the using a preset filter to process the first time series data includes:

[0079] The first time series data is processed using a preset filter coefficient.

[0080] Step 103, determining the distance and echo intensity of the target object according to the processed first time series data.

[0081] After the first time series data is processed by a preset filter, the time interval of the horizontal axis of the processed first time series data (i.e., the histogram data) remains unchanged, and the vertical axis data is the number of triggered light detectors that changes. By using the processed first time series data, the distance and echo intensity of the target object are determined, thereby improving the detection accuracy of the distance and the echo distinction intensity.

[0082] like Figure 2a , the radar's laser transmitter emits pulses to the target object, SPAD (Single Photon Avalanche Diode) receives the pulses reflected from the target object and converts them into electrical signals, SPAD determines the number of photodetectors triggered in each time interval, and then generates a histogram. The original histogram and the configured FIR filter are convolved to output the calculated histogram, and then the target distance and echo intensity are obtained from the histogram by using the distance estimation algorithm.

[0083] In some embodiments of the present invention, the filter coefficients are determined in the following manner:

[0084] Acquire second time series data collected from the test object; determine the reflected echo of the test object according to the second time series data; and set the filter coefficient of the filter according to the reflected echo of the high reflectivity object in the test object.

[0085] The test objects may include high-reflectivity objects and low-reflectivity objects, such as traffic signs are high-reflectivity objects with a reflectivity of 90%-100%, and black cars are low-reflectivity objects with a reflectivity of 10%.

[0086] In some embodiments of the present invention, the second timing data may include multiple time intervals and the number of light detectors triggered in each time interval. In some examples, the second timing data may be histogram data, the horizontal axis data of the histogram data may be the time interval, and the vertical axis data of the histogram data may be the number of light detectors triggered.

[0087] In some embodiments of the present invention, the step of acquiring the second time series data collected from the test object includes:

[0088] The laser radar is controlled to transmit a pulse signal to the test object at a specified distance and receive a returned pulse signal, and second time series data is generated according to the received pulse signal.

[0089] As an example, the specified distance may be 6m or 2m, and an extreme close distance situation may be selected.

[0090] There are at least two situations for setting the filter coefficient of the filter: 1. Using the reflected echo of the high reflectivity object in the test object as the filter coefficient of the filter; 2. Using the rising edge and falling edge of the reflected echo of the high reflectivity object in the test object as the rising edge and falling edge of the filter coefficient of the filter. The following are specific descriptions of these two situations:

[0091] 1. Use the reflected echo of the high reflectivity object in the test object as the filter coefficient of the filter:

[0092] In some embodiments of the present invention, setting the filter coefficient of the filter according to the reflected echo of the high reflectivity object in the test object includes:

[0093] The reflected echo of the object with high reflectivity in the test object is used as the filter coefficient of the filter.

[0094] In some embodiments of the present invention, the step of using the reflected echo of the high reflectivity object in the test object as the filter coefficient of the filter includes:

[0095] When the number of duration intervals in the reflected echo of the high-reflectivity object in the test object is less than a preset number, using the reflected echo of the high-reflectivity object as the filter coefficient of the filter;

[0096] When the number of duration intervals in the reflected echo of the 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, using the reflected echo of the high-reflectivity object as a filter coefficient of the filter;

[0097] The number of duration intervals is the number of time intervals that last when the number of light detectors triggered by the reflected echo of the high-reflectivity object reaches a preset number.

[0098] 2. The rising edge and falling edge of the reflected echo of the high reflectivity object in the test object are used as the rising edge and falling edge of the filter coefficient of the filter:

[0099] In some embodiments of the present invention, setting the filter coefficient of the filter according to the reflected echo of the high reflectivity object in the test object includes:

[0100] The rising edge and the falling edge of the reflected echo of the high reflectivity object in the test object are used as the rising edge and the falling edge of the filter coefficient of the filter.

[0101] In some embodiments of the present invention, the method of using the rising edge and the falling edge of the reflected echo of the high reflectivity object in the test object as the rising edge and the falling edge of the filter coefficient of the filter includes:

[0102] When the number of duration intervals in the reflected echo of the 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 the falling edge of the reflected echo of the high-reflectivity object are used as the rising edge and the falling edge of the filter coefficient of the filter;

[0103] The number of duration intervals is the number of time intervals that last when the number of light detectors triggered by the reflected echo of the high-reflectivity object reaches a preset number.

[0104] In practical applications, the number of duration intervals in the reflected echo of the high-reflectivity object 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 the preset number is 1.

[0105] When the number of duration intervals is less than or equal to a preset number, the reflected echo of the high reflectivity object can be directly used as the filter coefficient of the filter.

[0106] When the number of duration intervals is greater than the preset number, it is possible to further determine whether the reflected echo of the high reflectivity object is a rectangular wave, and perform differentiated processing according to the detection of the rectangular wave, as follows:

[0107] When the reflected echo of the high-reflectivity object is a rectangular wave, the reflected echo of the high-reflectivity object can be directly used as the filter coefficient of the filter. In some examples, it can be further determined whether the reflected echo of the non-high-reflectivity object at the same distance is a rectangular wave. When the reflected echo of the non-high-reflectivity object at the same distance is a non-rectangular wave, the reflected echo of the high-reflectivity object can be directly used as the filter coefficient of the filter. When the reflected echo of the non-high-reflectivity object at the same distance is a rectangular wave, it indicates that the current situation is indistinguishable and the intensity cannot be distinguished by waveform calculation, but the reflected echo of the high-reflectivity object can also be used as the filter coefficient of the filter.

[0108] When the reflected echo of the high-reflectivity object is a non-rectangular wave, the rising edge and the falling edge of the reflected echo of the high-reflectivity object in the test object can be used as the rising edge and the falling edge of the filter coefficient of the filter, and the number of time intervals when the value in the filter coefficient reaches a preset value can be further set to be greater than the number of duration intervals, and the steps of optimizing each coefficient in the filter coefficient can be performed.

[0109] In some embodiments of the present invention, the further step includes: setting the number of time intervals for which the value in the filter coefficient reaches a preset value to be greater than the number of duration intervals.

[0110] In practical applications, the duration of the maximum value of the filter coefficient (i.e., the number of time intervals that last when the value reaches the preset value) is designed to be M+1, and M+1 is greater than the maximum duration M of the high-reflectivity object (i.e., the number of duration intervals in the reflected echo of the high-reflectivity object in the test object), and the filter coefficient length is the echo width plus 1. By setting the number of time intervals that last when the value in the filter coefficient reaches the preset value to be greater than the number of duration intervals, the reflected echoes of high-reflectivity objects and low-reflectivity objects can be distinguished in echo intensity after filter convolution, thereby improving the accuracy of close-range distinction.

[0111] In some embodiments of the present invention, the method further includes: optimizing each coefficient of the filter coefficients.

[0112] In some embodiments of the present invention, the optimizing 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.

[0113] In practical applications, the designed filter coefficients are summed, the sum is recorded as SumFIR, and the filter coefficient is divided by SumFIR. This step converts the maximum value of the echo intensity obtained after convolution (the original echo and the convolution of the filter) into 1.

[0114] In the embodiment of the present invention, by summing the filter coefficients and dividing each filter coefficient by the sum, each filter coefficient can be limited within a maximum value range, which facilitates subsequent data processing.

[0115] In some embodiments of the present invention, the optimizing each coefficient in the filter coefficients includes: normalizing each coefficient in the filter coefficients.

[0116] In practical applications, the designed filter coefficient can be divided by its maximum value. This step converts the maximum value of the filter into 1, and the other filter coefficients are converted into values ​​between 0 and 1 in the same proportion, thereby realizing the normalization of each coefficient in the filter coefficient.

[0117] In an embodiment of the present invention, by normalizing each coefficient in the filter coefficients, and then unifying the filter coefficients of different dimensions into the same dimension, the output amplitudes of different filter coefficients are made consistent, which is convenient for subsequent comparison and analysis, and can maintain the stability of the filter, prevent numerical problems caused by excessively large or small coefficients, and enhance the adaptability and compatibility of the filter.

[0118] In some embodiments of the present invention, the optimizing each coefficient in the filter coefficients includes: multiplying each coefficient in the filter coefficients by the expected echo intensity.

[0119] In practical applications, this step converts the maximum echo intensity after filter convolution into the expected value by multiplying the filter coefficient by the expected maximum echo intensity after convolution, and converts the echo intensity range into 0 to the maximum echo intensity after mapping.

[0120] In the embodiment of the present invention, the filter coefficients are linked to the expected echo strength by multiplying each coefficient in the filter coefficients by the expected echo strength, thereby improving the accuracy of the set filter coefficients.

[0121] like Figure 2b , specifically as follows:

[0122] Step 201: A large amount of histogram data is collected from an object at a selected distance, and an average histogram is obtained to obtain a reflected echo of the object at the selected distance.

[0123] Step 202: Determine the number of time intervals during which the maximum value of the reflected echo of the high-reflectivity object at the selected distance lasts, denoted as M.

[0124] Step 203: Determine whether M is greater than 1, if so, execute S205, if not, execute S204.

[0125] Step 204: Since the echo must have a maximum value, M is a positive integer, and M is not greater than 1, that is, M is equal to 1. At this time, there is only one echo maximum value, and the reflected echo of this highly reflective object can be selected as the filter coefficient.

[0126] Step 205: Determine whether the reflected echo wave of the highly reflective object is a rectangular wave. If so, execute S206; if not, execute S209.

[0127] Step 206: Determine whether the reflected echo from the non-highly reflective object at the same distance is a rectangular wave. If so, execute S207; if not, execute S208.

[0128] Step 207: If the reflected echoes of the high-reflective and low-reflective objects are both rectangular waves, they are considered physically indistinguishable and cannot be used to distinguish the intensity using waveform calculations. However, the reflected echoes of the high-reflective objects can still be used as filter coefficients to improve accuracy.

[0129] Step 208: The reflected echo of the high-reflective object is a rectangular wave, but the reflected echo of the non-high-reflective object is not a rectangular wave. Selecting the reflected echo of this high-reflective object as the filter coefficient can achieve accuracy improvement and intensity distinction of objects with different reflectivity at close range.

[0130] Step 209: When the reflected echo of the high-reflective object is not a rectangular wave, it means that the high-reflective object has not reached full saturation at the current distance, and the low-reflective object is also not saturated. The maximum duration of the low-reflective object will be shorter than that of the high-reflective object, so the high-reflective object and the low-reflective object can be distinguished. At this time, the rising edge and falling edge of the reflected echo are used as the rising edge and falling edge of the filter.

[0131] Step 210: The duration of the maximum value of the filter coefficient is designed to be M+1, and the maximum duration of M+1 is greater than the maximum duration M of the high-reflective object. At this time, the length of the filter coefficient is the echo width plus 1. This allows the reflected echoes of the high-reflective object and the low-reflective object to distinguish the echo intensity after the filter convolution.

[0132] Step 211: Sum the designed filter coefficients and record the sum as SumFIR.

[0133] Step 212: Divide the designed filter coefficient by its maximum value. This step converts the maximum value of the filter into 1, and the other filter coefficients are converted into numbers between 0 and 1 in the same proportion.

[0134] Step 213: Divide the filter coefficient by SumFIR. This step converts the maximum value of the echo intensity obtained after convolution (the original echo and the echo obtained by convolution of the filter) into 1.

[0135] Step 214: multiply the filter coefficient by the expected maximum echo intensity after convolution. This step converts the maximum echo intensity after filter convolution into the expected value and converts the echo intensity range from 0 to the maximum echo intensity after convolution mapped.

[0136] In an embodiment of the present invention, by responding to a trigger event, the laser radar is controlled to transmit a pulse signal to the target object and receive a returned pulse signal, a first time series data is generated according to the received pulse signal, the first time series data is processed using a pre-set filter, and the distance and echo intensity of the target object are determined according to the processed first time series data. This achieves the improvement of the detection capability and ranging accuracy of the laser radar without increasing the cost of the radar system by optimizing the filter, has low complexity, and can improve accuracy while distinguishing objects with different reflectivity at close range.

[0137] Reference Figure 3 , shows a flowchart of another laser radar-based processing method provided by some embodiments of the present invention, which may specifically include the following steps:

[0138] Step 301: Acquire second time series data collected from a test object.

[0139] Step 302: Determine the reflected echo of the test object according to the second time series data.

[0140] Step 303: setting a filter coefficient of a filter according to the reflected echo of the object with high reflectivity in the test object.

[0141] Step 304, in response to a trigger event, control the laser radar to transmit a pulse signal to the target object and receive a returned pulse signal, and generate first time series data according to the received pulse signal.

[0142] Step 305: Use a preset filter to process the first time series data.

[0143] Step 306, determining the distance and echo intensity of the target object according to the processed first time series data.

[0144] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0145] Some embodiments of the present invention also provide a laser radar-based processing device, the device being used for:

[0146] In response to a trigger event, control the laser radar to transmit a pulse signal to the target object and receive a returned pulse signal, and generate first time series data according to the received pulse signal;

[0147] Using a preset filter to process the first time series data;

[0148] The distance and echo intensity of the target object are determined according to the processed first time series data.

[0149] Optionally, the first time series data includes a plurality of time intervals and the number of light detectors triggered in each time interval, and the generating of the first time series data according to the received pulse signal includes:

[0150] Convert the received pulse signal into an electrical signal;

[0151] The number of light detectors triggered in each time interval is determined according to the electrical signal, and the first time series data is generated according to the number of light detectors triggered in each time interval.

[0152] Optionally, the first time series data is histogram data, the horizontal axis data of the histogram data is a time interval, and the vertical axis data of the histogram data is the number of triggered light detectors.

[0153] Optionally, the using a preset filter to process the first time series data includes:

[0154] Processing the first time series data using a preset filter coefficient;

[0155] The filter coefficients are determined in the following manner:

[0156] Acquiring second time series data collected from the test object;

[0157] determining a reflected echo of the test object according to the second time series data;

[0158] The filter coefficient of the filter is set according to the reflected echo of the high reflectivity object in the test object.

[0159] Optionally, setting a filter coefficient of a filter according to a reflected echo of an object with high reflectivity in the test object comprises:

[0160] The reflected echo of the object with high reflectivity in the test object is used as the filter coefficient of the filter.

[0161] Optionally, the using the reflected echo of the high reflectivity object in the test object as the filter coefficient of the filter includes:

[0162] When the number of duration intervals in the reflected echo of the high-reflectivity object in the test object is less than a preset number, using the reflected echo of the high-reflectivity object as the filter coefficient of the filter;

[0163] When the number of duration intervals in the reflected echo of the 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, using the reflected echo of the high-reflectivity object as a filter coefficient of the filter;

[0164] The number of duration intervals is the number of time intervals that last when the number of light detectors triggered by the reflected echo of the high-reflectivity object reaches a preset number.

[0165] Optionally, setting a filter coefficient of a filter according to a reflected echo of an object with high reflectivity in the test object comprises:

[0166] The rising edge and the falling edge of the reflected echo of the high reflectivity object in the test object are used as the rising edge and the falling edge of the filter coefficient of the filter.

[0167] Optionally, the taking the rising edge and the falling edge of the reflected echo of the high-reflectivity object in the test object as the rising edge and the falling edge of the filter coefficient of the filter includes:

[0168] When the number of duration intervals in the reflected echo of the 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 the falling edge of the reflected echo of the high-reflectivity object are used as the rising edge and the falling edge of the filter coefficient of the filter;

[0169] The number of duration intervals is the number of time intervals that last when the number of light detectors triggered by the reflected echo of the high-reflectivity object reaches a preset number.

[0170] Optionally, it also includes:

[0171] The number of time intervals during which the value in the filter coefficient reaches a preset value is set to be greater than the number of duration intervals.

[0172] Optionally, it also includes:

[0173] Each coefficient of the filter coefficients is optimized.

[0174] Optionally, the optimizing each coefficient in the filter coefficients includes:

[0175] Summing each coefficient in the filter coefficients to obtain a sum value;

[0176] Each of the filter coefficients is divided by the summed value.

[0177] Optionally, the optimizing each coefficient in the filter coefficients includes:

[0178] Each coefficient of the filter coefficients is normalized.

[0179] Optionally, the optimizing each coefficient in the filter coefficients includes:

[0180] Each of the filter coefficients is multiplied by the expected echo strength.

[0181] Optionally, the second time series data includes a plurality of time intervals and the number of light detectors triggered in each time interval, and the acquiring of the second time series data collected from the test object includes:

[0182] The laser radar is controlled to transmit a pulse signal to the test object at a specified distance and receive a returned pulse signal, and second time series data is generated according to the received pulse signal.

[0183] Optionally, the second time series data is histogram data, the abscissa data of the histogram data is a time interval, and the ordinate data of the histogram data is the number of triggered light detectors.

[0184] Some embodiments of the present invention further provide an electronic device, comprising a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the above method is implemented when the computer program is executed by the processor.

[0185] Some embodiments of the present invention further provide a vehicle, comprising the apparatus as described above, and / or the electronic device as described above.

[0186] Some embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented.

[0187] Some embodiments of the present invention further provide a computer program product, including a computer program, which implements the above method when executed by a processor.

[0188] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0189] 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, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0190] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0191] Those skilled in the art will appreciate that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product 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 codes.

[0192] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0193] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0194] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0195] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0196] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the above elements.

[0197] The above is a detailed introduction to a laser radar-based processing method, device, equipment and vehicle. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A laser radar-based processing method, characterized in that: The method comprises: In response to a trigger event, control the laser radar to transmit a pulse signal to the target object and receive a returned pulse signal, and generate first time series data according to the received pulse signal; Using a preset filter to process the first time series data; The distance and echo intensity of the target object are determined according to the processed first time series data.

2. The method according to claim 1, characterized in that The first time series data includes a plurality of time intervals and the number of light detectors triggered in each time interval. The first time series data is generated according to the received pulse signal, including: Convert the received pulse signal into an electrical signal; The number of light detectors triggered in each time interval is determined according to the electrical signal, and the first time series data is generated according to the number of light detectors triggered in each time interval.

3. The method according to claim 2, characterized in that The first time series data is histogram data, the abscissa data of the histogram data is the time interval, and the ordinate data of the histogram data is the number of triggered light detectors.

4. The method according to any one of claims 1 to 3, characterized in that: The using a preset filter to process the first time series data includes: Processing the first time series data using a preset filter coefficient; The filter coefficients are determined in the following manner: Acquiring second time series data collected from the test object; determining a reflected echo of the test object according to the second time series data; The filter coefficient of the filter is set according to the reflected echo of the high reflectivity object in the test object.

5. The method according to claim 4, characterized in that The step of setting the filter coefficient of the filter according to the reflected echo of the high reflectivity object in the test object comprises: The reflected echo of the object with high reflectivity in the test object is used as the filter coefficient of the filter.

6. The method according to claim 5, characterized in that The method of using the reflected echo of the high reflectivity object in the test object as the filter coefficient of the filter comprises: When the number of duration intervals in the reflected echo of the high-reflectivity object in the test object is less than a preset number, using the reflected echo of the high-reflectivity object as the filter coefficient of the filter; When the number of duration intervals in the reflected echo of the 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, using the reflected echo of the high-reflectivity object as a filter coefficient of the filter; The number of duration intervals is the number of time intervals that last when the number of light detectors triggered by the reflected echo of the high-reflectivity object reaches a preset number.

7. The method according to claim 4, characterized in that The step of setting the filter coefficient of the filter according to the reflected echo of the high reflectivity object in the test object comprises: The rising edge and the falling edge of the reflected echo of the high reflectivity object in the test object are used as the rising edge and the falling edge of the filter coefficient of the filter.

8. The method according to claim 7, characterized in that The method of using the rising edge and the falling edge of the reflected echo of the high reflectivity object in the test object as the rising edge and the falling edge of the filter coefficient of the filter includes: When the number of duration intervals in the reflected echo of the 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 the falling edge of the reflected echo of the high-reflectivity object are used as the rising edge and the falling edge of the filter coefficient of the filter; The number of duration intervals is the number of time intervals that last when the number of light detectors triggered by the reflected echo of the high-reflectivity object reaches a preset number.

9. The method according to claim 8, characterized in that Also includes: The number of time intervals during which the value in the filter coefficient reaches a preset value is set to be greater than the number of duration intervals.

10. The method according to claim 9, characterized in that Also includes: Each coefficient of the filter coefficients is optimized.

11. The method according to claim 10, characterized in that The step of optimizing each coefficient in the filter coefficients comprises: Summing each coefficient in the filter coefficients to obtain a sum value; Each of the filter coefficients is divided by the summed value.

12. The method according to claim 10, characterized in that The step of optimizing each coefficient in the filter coefficients comprises: Each coefficient of the filter coefficients is normalized.

13. The method according to claim 10, characterized in that The step of optimizing each coefficient in the filter coefficients comprises: Each of the filter coefficients is multiplied by the expected echo strength.

14. The method according to claim 4, characterized in that The second time series data includes a plurality of time intervals and the number of light detectors triggered in each time interval. The acquiring of the second time series data collected from the test object includes: The laser radar is controlled to transmit a pulse signal to the test object at a specified distance and receive a returned pulse signal, and second time series data is generated according to the received pulse signal.

15. The method according to claim 14, characterized in that The second time series data is histogram data, the abscissa data of the histogram data is the time interval, and the ordinate data of the histogram data is the number of triggered light detectors.

16. A laser radar-based processing device, characterized in that: The device is used for: In response to a trigger event, control the laser radar to transmit a pulse signal to the target object and receive a returned pulse signal, and generate first time series data according to the received pulse signal; Using a preset filter to process the first time series data; The distance and echo intensity of the target object are determined according to the processed first time series data.

17. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program implements the method according to any one of claims 1 to 15 when executed by the processor.

18. A vehicle, characterized in that: The vehicle comprises the apparatus as claimed in claim 16 and / or the electronic device as claimed in claim 17.

Images