WO2022016341A1 - 一种信号处理方法及装置 - Google Patents

一种信号处理方法及装置 Download PDF

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Publication number
WO2022016341A1
WO2022016341A1 PCT/CN2020/103124 CN2020103124W WO2022016341A1 WO 2022016341 A1 WO2022016341 A1 WO 2022016341A1 CN 2020103124 W CN2020103124 W CN 2020103124W WO 2022016341 A1 WO2022016341 A1 WO 2022016341A1
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Prior art keywords
probability distribution
waveform
probability
peak point
signal strength
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PCT/CN2020/103124
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English (en)
French (fr)
Inventor
黄龙
石现领
秦博雅
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华为技术有限公司
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Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to PCT/CN2020/103124 priority Critical patent/WO2022016341A1/zh
Priority to CN202080004821.6A priority patent/CN112639515B/zh
Priority to JP2023504011A priority patent/JP7494379B2/ja
Priority to EP20945989.0A priority patent/EP4184212A4/en
Publication of WO2022016341A1 publication Critical patent/WO2022016341A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/483—Details of pulse systems
    • G01S7/486—Receivers
    • G01S7/4865—Time delay measurement, e.g. time-of-flight measurement, time of arrival measurement or determining the exact position of a peak
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/483—Details of pulse systems
    • G01S7/486—Receivers
    • G01S7/487—Extracting wanted echo signals, e.g. pulse detection
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/06—Systems determining position data of a target
    • G01S17/08—Systems determining position data of a target for measuring distance only
    • G01S17/10—Systems determining position data of a target for measuring distance only using transmission of interrupted, pulse-modulated waves
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/483—Details of pulse systems
    • G01S7/486—Receivers
    • G01S7/4865—Time delay measurement, e.g. time-of-flight measurement, time of arrival measurement or determining the exact position of a peak
    • G01S7/4866—Time delay measurement, e.g. time-of-flight measurement, time of arrival measurement or determining the exact position of a peak by fitting a model or function to the received signal

Definitions

  • the embodiments of the present application relate to the technical field of laser detection, and in particular, to a signal processing method and device.
  • lidar can transmit a laser pulse signal to the target object, and record the reception time of the peak point of the received pulse signal generated by the reflection of the target object, and the signal strength of the peak point, so as to detect the target object according to these information.
  • the surface reflectivity of the target object can also be determined according to the relationship between the signal intensity of the laser pulse signal sent by the lidar and the signal intensity of the peak point of the received pulse signal, and then the material and other information of the target object can be determined.
  • the peak point receiving time and the peak point signal strength of the received pulse signal it is usually necessary to sample the received pulse signal to obtain the receiving time and signal strength corresponding to each sampling point. Then, according to the multiple sampling points, the waveform of the received pulse signal is determined, and then the peak point receiving time and the peak point signal strength of the received pulse signal are determined.
  • FIG. 1 shows a schematic diagram of a fitted waveform of the received pulse signal.
  • the receiving time and signal strength corresponding to each sampling point are obtained.
  • each circle in Figure 1 represents one sampling.
  • the waveform of the received pulse signal can be fitted, as shown in (a) of FIG. 1 .
  • the peak reception time and peak signal strength of the received pulse signal can be determined, wherein the peak reception time is t, and the peak signal strength is P.
  • the laser radar may be due to the fact that the signal strength of the received pulse signal exceeds the dynamic range of the laser radar, or the nonlinear memory effect of the electronic components in the laser radar. As a result, the sampling parameters of the collected sampling points are distorted, which affects the accuracy of the detection results.
  • the waveform of the received pulse signal fitted according to the collected sampling points will be clipped, as shown in (b) in Figure 1. .
  • the signal strength corresponding to the sampling point in this area is the lidar.
  • the maximum signal strength of the dynamic range not the true signal strength of the received pulse signal. In this way, the waveform of the received pulse signal fitted according to these sampling points will be clipped.
  • Embodiments of the present application provide a signal processing method and device, which are used to solve the problem that the peak reception time and peak signal strength of the received pulse signal cannot be accurately obtained due to the distortion of the sampling parameters of the sampling point of the received pulse signal, which leads to the detection result. inaccurate question.
  • a signal processing method including: sampling a received pulse signal N times to obtain N sampling points.
  • the sampling parameters of each sampling point in the N sampling points include the receiving time and signal strength corresponding to the sampling point
  • the N sampling points include M rising edge sampling points and P clipping sampling points, N, M and P are integers greater than or equal to 1 respectively; determine the first probability distribution of the M rising edge sampling points distributed on each waveform in the preset waveform set; wherein, the preset waveform set includes at least one preset waveform; according to P Clipping the sampling point to determine the second probability distribution of the receiving time of the peak point of the received pulse signal and the third probability distribution of the signal strength of the peak point; determining the fourth probability distribution of the pulse width of the received pulse signal; according to the second probability distribution, the third probability distribution The probability distribution and the fourth probability distribution determine that each waveform in the preset waveform set is the fifth probability distribution of the received pulse signal; according to the first probability distribution and the fifth probability distribution, it is determined that the received pulse signal
  • the process of determining the waveform of the received pulse signal first determine the likelihood function (ie, the first probability distribution) of the waveform of the received pulse signal according to the sampled rising edge sampling points. Then, a priori distribution of the waveform of the received pulse signal (ie, the fifth probability distribution) is determined according to the prior information of the received pulse signal, wherein the prior information includes the probability distribution of various parameters affecting the received pulse signal waveform, specifically including : The probability distribution of the receiving time at the peak point of the received pulse signal (ie the second probability distribution), the probability distribution of the signal strength at the peak point (ie the third probability distribution) and the probability distribution of the pulse width of the received pulse signal (ie the fourth probability distribution) .
  • the posterior distribution (ie, sixth probability distribution) of the waveform of the received pulse signal can be calculated.
  • a waveform that may be the received pulse signal ie, the first preset waveform
  • the receiving time at the peak point of the received pulse signal and the signal strength at the peak point can be determined.
  • determining the second probability distribution of the reception time at the peak point of the received pulse signal and the third probability distribution of the signal strength of the peak point according to the P clipped sampling points includes: according to the P clipped sampling points The minimum value in the corresponding receiving time, the minimum value of the value range of the peak point receiving time is determined; according to the maximum value in the receiving time corresponding to the P clipping sampling points, the maximum value range of the peak point receiving time is determined. determine the second probability distribution according to the value range of the peak point receiving time; determine the minimum value of the value range of the peak point signal strength according to the signal strengths corresponding to the P clipped sampling points; The range of values to determine the third probability distribution.
  • the value range of the peak reception time and the value range of the signal strength of the peak point can be determined according to the peak clipping sampling points, and based on the determined value range, more accurate second probability distribution and first probability distribution can be determined. Three probability distributions.
  • determining the second probability distribution according to the value range of the peak point receiving time includes: determining that the peak point receiving time satisfies a uniform distribution within the value range of the peak point receiving time, the peak point receiving time The probability distribution of the reception time is obtained to obtain the second probability distribution. Based on the above design, the present application can simplify the calculation process and quickly obtain the second probability distribution.
  • determining the third probability distribution according to the value range of the signal strength at the peak point includes: determining that the signal strength at the peak point satisfies a uniform distribution within the value range of the signal strength at the peak point, The probability distribution of the signal strength, the third probability distribution is obtained. Based on the above design, the present application can simplify the calculation process and quickly obtain the third probability distribution.
  • determining the third probability distribution according to the value range of the signal strength of the peak point including: determining the probability distribution of the reflectivity of the object surface reflecting the received pulse signal is uniform distribution, the peak point The third probability distribution is obtained from the probability distribution of the signal strength within the value range of the signal strength at the peak point. Based on the above design, the third probability distribution can be obtained according to the probability distribution of the reflectivity of the object surface reflecting the received pulse signal, so as to obtain a more accurate third probability distribution.
  • receiving the fourth probability distribution of the pulse width of the pulse signal includes: determining the probability distribution of the pulse width under the condition that the pulse width satisfies a uniform distribution within the value range of the pulse width, and obtaining the fourth probability distributed. Based on the above design, the present application can simplify the calculation process and quickly obtain the fourth probability distribution.
  • determining the first probability distribution of the M rising edge sampling points distributed on each waveform in the preset waveform set includes: determining that each sampling point in the M rising edge sampling points is on the preset waveform The probability distribution distributed on each waveform in the set; the first probability distribution is determined according to the probability distribution of each sampling point in the M rising edge sampling points distributed on each waveform in the preset waveform set. Based on the above design, the first probability distribution may be determined by using the probability distribution of each of the M rising edge sampling points distributed on each waveform in the preset waveform set.
  • determining the probability distribution of each sampling point in the M rising edge sampling points on each waveform in the preset waveform set includes: probability distribution according to the intensity of noise when sampling the target sampling point , determining the probability distribution of the target sampling point distributed on each waveform in the preset waveform set; wherein, the target sampling point includes any one of the M rising edge sampling points.
  • the probability distribution of the target sampling point on each waveform in the preset waveform set satisfies the following formula 1:
  • p k represents the probability that the target sampling point k is distributed on the target waveform in the preset waveform set
  • y k represents the signal strength corresponding to the target sampling point k
  • s k represents the target waveform The signal strength of the target sampling point k is collected.
  • the Gaussian distribution is used to reflect the probability distribution of noise intensity during sampling
  • the above formula 1 is further proposed to calculate the probability distribution of sampling points distributed on each waveform in the preset waveform set. Through the above formula 1, the probability distribution of each sampling point distributed on each waveform in the preset waveform set can be quickly calculated.
  • determining that the received pulse signal is the sixth probability distribution of each waveform in the preset waveform set includes: according to the first probability distribution and the fifth probability distribution , construct a Markov chain with the preset waveform set as the state space, and obtain the sample sequence of the Markov chain ⁇ z 1 ,z 2 ,...,z m ,z m+1 ,...,z m+ n-1 ,z m+n ⁇ ; wherein, each sample in the sample sequence is used to represent a waveform; the sample sequence ⁇ z 1 ,z 2 ,...,z m ,z m+1 ,..., z m + n-1, m + n ⁇ after the sample z n items ⁇ z m + 1, ..., z m + n-1, z m + n ⁇ Characterization of the probability distribution for the sixth; according Six probability distributions, determining the first preset waveform from the preset waveform set, including
  • a Markov chain with a preset waveform set as the state space including: using the Metropolis-Hastings algorithm to construct an acceptance distribution ⁇ (z,z ') is a Markov chain that satisfies the following formula two:
  • z is a sample in the sample sequence of the Markov chain
  • z' is the sample after z in the sample sequence of the Markov chain
  • z') is the corresponding sample of z' in the first probability distribution
  • z) is the probability corresponding to z in the first probability distribution
  • p(z') is the probability corresponding to z' in the fifth probability distribution
  • p(z) is the probability corresponding to z in the fifth probability distribution
  • Probabilities, q(z',z) and q(z,z') are the proposed distributions for Markov chains.
  • the present application provides a signal processing apparatus, which can implement the functions in the first aspect or possible designs of the first aspect. These functions can be implemented by hardware or by executing corresponding software by hardware.
  • the hardware or software includes one or more modules corresponding to the above functions.
  • the signal processing apparatus may include: a sampling unit for sampling the received pulse signal N times to obtain N sampling points, and the sampling parameters of each sampling point in the N sampling points include the receiving time and the corresponding sampling point.
  • the N sampling points include M rising edge sampling points and P clipping sampling points, N, M and P are integers greater than or equal to 1 respectively;
  • the first probability determination unit is used to determine the M rising edge sampling points a first probability distribution of points distributed on each waveform in the preset waveform set; wherein, the preset waveform set includes at least one preset waveform; a second probability determination unit, configured to determine the received pulse according to the P clipped sampling points a second probability distribution of the reception time at the peak point of the signal and a third probability distribution of the signal strength at the peak point; the second probability determination unit, which is further configured to determine the fourth probability distribution of the pulse width of the received pulse signal; the third probability determination unit, for determining each waveform in the preset waveform set as the fifth probability distribution of the received pulse signal according to the second probability distribution, the third probability distribution and the fourth probability distribution; a fourth probability determining unit for determining according to the first probability distribution and a fifth probability distribution, for determining that the received pulse signal is a sixth probability distribution of each waveform in
  • a signal processing apparatus comprising one or more processors coupled with one or more memories; the one or more memories store computer instructions; when a When one or more processors execute the computer instructions, the signal processing apparatus is caused to execute the signal processing method provided in the first aspect.
  • a chip which includes a processing circuit and an interface; the processing circuit is used to call and run a computer program stored in the storage medium from a storage medium to execute the signal processing method provided in the first aspect.
  • a laser radar including the signal processing device provided in the second or third aspect, or the chip provided in the fourth aspect.
  • a computer-readable storage medium where instructions are stored in the computer-readable storage medium, and when the instructions are executed, the signal processing method in the first aspect or possible designs of the first aspect is executed.
  • a computer program product containing instructions which, when run on a computer, enable the computer to perform the signal processing method in the first aspect or possible designs of the first aspect.
  • FIG. 1 is one of schematic diagrams of waveforms of a fitted received pulse signal provided by an embodiment of the present application
  • FIG. 2 is a schematic structural diagram of a laser radar according to an embodiment of the present application.
  • FIG. 3 is a second schematic diagram of a fitted received pulse signal waveform according to an embodiment of the present application.
  • FIG. 4 is a third schematic diagram of a fitted received pulse signal waveform provided by an embodiment of the application.
  • FIG. 5 is one of the schematic flowcharts of a signal processing method provided by an embodiment of the present application.
  • FIG. 6 is the second schematic flowchart of a signal processing method provided by an embodiment of the present application.
  • FIG. 7 is a schematic diagram of a sampling point obtained by sampling a received pulse signal according to an embodiment of the present application.
  • Fig. 8 is the waveform schematic diagram of utilizing the prior art to fit the received pulse signal
  • FIG. 9 is a schematic diagram of a waveform of fitting a received pulse signal by using the signal processing method provided by an embodiment of the present application.
  • FIG. 10 is one of the schematic structural diagrams of a signal processing apparatus provided by an embodiment of the present application.
  • FIG. 11 is a second schematic structural diagram of a signal processing apparatus provided by an embodiment of the present application.
  • Lidar is a radar system that emits laser beams to detect the position, velocity and other characteristic quantities of target objects. Its working principle is to transmit a laser pulse signal to the target object, and then record the peak point reception time and peak point signal strength of the signal reflected back from the target object (hereinafter referred to as the received pulse signal) by the lidar. Then, according to the receiving time of the peak point of the received pulse signal, the signal strength of the peak point and the information of the transmitted laser pulse signal, the relevant information of the target object can be obtained. For example, the distance from the target object to the lidar, the reflectivity of the target object surface and other parameters.
  • FIG. 2 it is a schematic structural diagram of a lidar.
  • a waveform generator 101 is used to control a transmitter 102 to transmit a laser pulse signal of a preset waveform.
  • the waveform generator 101 and the transmitter 102 also send the signal parameters (such as transmission time, signal strength, etc.) of the emitted laser pulse signal to the signal processing module 108 .
  • the deflection mirror (fine steering) 103 is used to control the direction of the laser pulse signal, so that the laser pulse signal passes through the transmitting lens 104 and is directed towards the target object to be detected.
  • the laser radar 10 receives the received pulse signal reflected by the target object through the receiver lens 105, and uses the deflection mirror 106 to adjust the direction of the received pulse signal so that the detection module 107 receives the received pulse signal.
  • the detection module 107 obtains a plurality of sampling points by detecting and sampling the received pulse signal, wherein the sampling parameters of each sampling point may include the receiving time and signal strength corresponding to the sampling point, and so on.
  • the detection module 107 sends the sampling parameters of each sampling point to the signal processing module 108 .
  • the signal processing module 108 determines the relevant information of the target object according to the sampling points from the detection module 107 and the signal parameters from the waveform generator 101 and the transmitter 102 .
  • the signal processing module 108 fits the waveform of the received pulse signal according to the above-mentioned sampling points, so as to determine the peak point reception time and the peak point signal strength of the received pulse signal. Then, according to the receiving time and signal strength of the peak point of the received pulse signal, as well as the signal parameters from the waveform generator 101 and the transmitter 102, relevant information such as the distance from the target object to the lidar is calculated.
  • the receiving time corresponding to the sampling point may refer to the receiving time of the received pulse signal sampled at the sampling point
  • the signal strength corresponding to the sampling point may refer to the signal strength sampled at the sampling point. The signal strength of the received pulse signal.
  • each functional module in the lidar 10 may be implemented by hardware, software or a combination of software and hardware.
  • the transmitter 102 may be a laser diode (laser diode)
  • the detection module 107 may include an avalanche photodiode (Avalanche Photon Diode, APD), an analog to digital converter (analog to digital converter, ADC) and a detector (detector).
  • the laser pulse signal intensity emitted by the laser radar is high, the surface reflectivity of the target object is high, or the distance between the target object and the laser radar is short, It is possible to make the strength of the received pulse signal higher.
  • the signal strength of the received pulse signal exceeds the dynamic range of the lidar, for example, in the lidar 10 shown in FIG. 2, when the strength of the received pulse signal exceeds the normal working range of the detection unit 107, the detection unit 107 will not be able to sample a sample larger than the normal range. The signal strength of the working range, and then the waveform of the received pulse signal fitted according to the sampling point will appear clipping phenomenon.
  • the dynamic range of the laser radar in the embodiments of the present application can be understood as the linear working range of the functional unit (eg, the detection unit 107 in FIG. 2 ) in the laser radar for detecting the received pulse signal.
  • the signal strength corresponding to the sampling point can reflect the signal strength of the current received pulse signal, that is, as the signal strength of the received pulse signal increases, the corresponding The signal strength also increases accordingly.
  • the signal strength of the received pulse signal exceeds the maximum signal strength of the linear working range, the signal strength collected by the lidar at the sampling point will be saturated, that is, the signal strength corresponding to the collected sampling point will no longer follow the received pulse. increases as the signal strength increases, but maintains the maximum signal strength of the linear operating range.
  • the sampling parameters can be collected through n sampling points of the rising edge before the top clipping phenomenon occurs. sampling parameters. Then, waveform fitting is performed according to the n sampling points to fit the waveform of the received pulse signal. For example, the waveform of the received pulse signal can be fitted by using the least squares method. Then, according to the received pulse signal obtained by fitting, the signal strength of the peak point of the received pulse signal and the reception time of the peak point are determined, and the detection result is obtained.
  • the error of the fitted waveform is relatively large.
  • the waveform of the received pulse signal fitted by the least squares method can be shown as the dashed waveform in (b) of FIG. 3 . It can be seen that there is a large error between the fitted waveform and the actual waveform of the received pulse signal. Therefore, this method cannot obtain accurate detection results.
  • the received pulse signal first, and then set a sliding window for acquiring the signal strength collected by the sampling points in the sliding window.
  • the signal strength in the sliding window is continuously greater than the preset threshold, it is determined that the pulse signal is received in the sliding window.
  • find the waveform centroid in the found received pulse signal, and the receiving time of the waveform centroid is taken as the peak point receiving time of the received pulse signal.
  • the signal strength collected in the sliding window (indicated by the dotted line box in the figure) is continuously maintained at the maximum signal strength P, and then it is determined that the pulse signal is received in the sliding window, and then the midpoint of the sliding window is used as the receiving signal.
  • the peak point of the pulse signal is also possible to sample the received pulse signal first, and then set a sliding window for acquiring the signal strength collected by the sampling points in the sliding window.
  • this method has requirements on the width of the sliding window. As shown in Figure 4, when the width of the sliding window is small, the peak receiving time of the received pulse signal determined according to the midpoint of the sliding window is Xc, while the actual peak value The point receiving time is Xc', and there is an error. In addition, this method also has the problem that only the reception time of the peak point can be estimated, but the signal strength of the peak point cannot be determined.
  • an embodiment of the present application provides a signal processing method.
  • a priori information of the received pulse signal is introduced, wherein the prior information includes: the peak point receiving time of the received pulse signal The probability distribution of the received pulse signal, the probability distribution of the signal strength at the peak point, and the probability distribution of the pulse width of the received pulse signal, and then use these prior information to limit the waveform of the received pulse signal, and then determine a more accurate waveform of the received pulse signal. Get more accurate peak signal strength and peak reception time.
  • the signal processing methods provided in the embodiments of the present application can be applied to lidar or other devices that need to determine the peak reception time and peak signal strength of received pulse signals, so that the above devices can determine more accurate received pulse signals.
  • the lidar as an example, the method will be introduced below. As shown in Figure 5, the method includes the following S201-S207:
  • the laser radar samples the received pulse signal N times to obtain N sampling points.
  • the laser pulse signal After transmitting a laser pulse signal to a target object, the laser pulse signal encounters the reflection of the target object to generate a received pulse signal. Then the received pulse signal is sent to the detection module 107 through the receiver lens 105 and the deflection mirror 106 . Then the detection module 107 can sample the received pulse signal to obtain sampling points after receiving the received pulse signal.
  • the sampling parameters of each sampling point in the N sampling points include the receiving time and signal strength corresponding to the sampling point.
  • the N sampling points include three sampling points a, b and c.
  • the sampling parameters of sampling point a include the receiving time and signal strength corresponding to sampling point a
  • the sampling parameters of sampling point b include the receiving time and signal strength corresponding to sampling point b
  • the signal strength and the sampling parameters of the sampling point c include the reception time and signal strength corresponding to the sampling point c.
  • N sampling points include M rising edge sampling points and P clipping sampling points.
  • N, M and P are positive integers greater than or equal to 1, respectively.
  • the signal strength corresponding to the sampling point may be a parameter reflecting the strength of the optical signal such as the optical power of the received pulse signal at the sampling point, or may be the optical signal at the sampling point in response to the received pulse signal The voltage or current value produced by the intensity. This application may not limit the actual physical quantity used for the signal strength.
  • the sampling point of the rising edge refers to the sampling point of the rising edge of the received pulse signal.
  • the clipping sampling point refers to the sampling point in the part where the clipping phenomenon occurs.
  • four clipping sampling points e, f, g and h are included.
  • the lidar determines a first probability distribution of the M rising edge sampling points distributed on each waveform in the preset waveform set.
  • the preset waveform set includes at least one preset waveform.
  • the sampling parameters of the sampling point on the rising edge can be used to determine each wave in the preset waveform set.
  • the probability distribution of the waveform of the received pulse signal that is, the first probability distribution of the M rising edge sampling points distributed on each waveform in the preset waveform set.
  • the received pulse signal is usually a Gaussian pulse
  • the current signal strength s and the current time x of the received pulse signal satisfy the following formula (1):
  • the waveform parameters A, t, and ⁇ take different values, the corresponding waveforms are different.
  • a waveform satisfying the above formula (1) is a waveform that may be a received pulse signal. Therefore, a preset waveform set can be constructed by using the waveforms satisfying the above formula (1), that is, the preset waveform set includes at least one preset waveform satisfying the above formula (1).
  • the waveforms in the preset waveform set may also be determined in other ways. That is, those skilled in the art can select an appropriate preset waveform set according to actual needs.
  • the present application may not limit which waveforms are included in the preset waveform set.
  • S202 of the present application may specifically include the following S2021-S2022:
  • the lidar determines the probability distribution of each sampling point in the M rising edge sampling points distributed on each waveform in the preset waveform set.
  • the M rising edge sampling points include a total of five sampling points, namely: sampling point 1, sampling point 2, sampling point 3, sampling point 4, and sampling point 5.
  • the sampling parameters of the five sampling points respectively include the receiving time and signal strength corresponding to the sampling points.
  • the preset waveform set includes waveforms satisfying the above formula (1). Then, for each sampling point, the probability that the sampling point is distributed on each waveform in the preset waveform set can be calculated according to the receiving time and signal strength of the sampling point.
  • the above S2021 may include: according to the probability distribution of the intensity of noise when sampling the target sampling point, determining that the target sampling point is in the preset waveform set The probability distribution distributed over each waveform in .
  • the target sampling point may be any sampling point among the M rising edge sampling points.
  • the signal strength collected at the target sampling point is y
  • the noise strength when sampling the target sampling point is w
  • the signal strength of the waveform in the preset waveform set e.g, the target waveform
  • the received pulse signal is the target waveform
  • it needs to satisfy w y-s.
  • the signal strength collected at the target sampling point is 5 (the physical unit of the signal strength can be determined according to the actual situation, it can be optical power, voltage or current, etc.), the signal strength of the target waveform at the target sampling point is 4, and the signal strength of the target waveform at the target sampling point is 4. If the probability that the intensity of the noise is 1 when the target sampling point is sampled is 20%, it can be determined that the probability that the target sampling point is distributed on the target waveform is 20%.
  • the probability distribution of the intensity of noise generally conforms to a Gaussian distribution with a mean of 0 and a variance of N 0 , where N 0 is the noise power, that is, the probability distribution of the intensity of noise p (w ) satisfies the following formula (3):
  • the target when determining the probability distribution of each sampling point in the M rising edge sampling points distributed on each waveform in the preset waveform set, the target can be determined according to the following formula (4)
  • the probability distribution of the sampling points distributed on each waveform in the preset waveform set that is, the probability distribution of the target sampling point distributed on each waveform in the preset waveform set satisfies the following formula (4):
  • p k represents the probability that the target sampling point k is distributed on the target waveform in the preset waveform set
  • y k represents the signal strength corresponding to the target sampling point k
  • s k represents the target waveform
  • the signal strength of the target sampling point k is collected.
  • the value of N 0 can be set according to actual needs.
  • the lidar determines the first probability distribution according to the probability distribution of each sampling point in the M rising edge sampling points distributed on each waveform in the preset waveform set.
  • each sampling point in the M rising edge sampling points may be distributed in the preset waveform set A multiplication operation is performed on the probability distributions distributed on each waveform of , and then the first probability distribution is determined.
  • the preset waveform set includes at least one preset waveform that satisfies the above formula (1), then It can be determined that the first probability distribution satisfies the following formula (5):
  • ⁇ ) represents the probability that M rising edge sampling points are distributed on the target waveform whose waveform parameters A, t, and ⁇ are ⁇
  • y k represents the signal strength corresponding to the target sampling point k
  • s k ( ⁇ ) Represents the signal strength of the target waveform whose waveform parameters A, t, and ⁇ are ⁇ when the target sampling point k is collected.
  • the lidar determines, according to the P clipped sampling points, a second probability distribution of the receiving time at the peak point of the received pulse signal and a third probability distribution of the signal strength of the peak point.
  • the receiving time of the peak point of the received pulse signal is within the time range corresponding to the clipping part, and the signal strength of the peak point of the received pulse signal is larger than the signal intensity sampled in the clipping part.
  • the peak point receiving time of the received pulse signal is between t1-t2
  • the peak point signal strength of the received pulse signal is greater than the signal strength P.
  • the peak receiving time of the received pulse signal and the value range of the peak signal strength can be determined, and then the difference between the peak receiving time and the peak signal strength can be determined.
  • Probability distributions ie, the second probability distribution and the third probability distribution).
  • the above-mentioned determination of the second probability distribution according to the P clipped sampling points may include:
  • the lidar determines the value range of the receiving time of the peak point according to the minimum value and the maximum value among the receiving times corresponding to the P clipped sampling points.
  • the minimum value of the value range of the peak point receiving time may be determined according to the minimum value among the receiving times corresponding to the P clipping sampling points.
  • the maximum value of the value range of the peak point receiving time may be determined according to the maximum value among the receiving times corresponding to the P clipping sampling points.
  • the reception times corresponding to sampling point 1 and sampling point 2 are the minimum and maximum values of the reception times corresponding to the cropped sampling points, respectively. Then, according to the receiving times corresponding to the sampling point 1 and the sampling point 2, the minimum value and the maximum value of the value range of the peak point receiving time can be determined.
  • the lidar determines the second probability distribution according to the value range of the peak point receiving time.
  • the probability distribution (ie the second probability distribution) of the peak point receiving time within the value range can be determined according to prior information such as the characteristics of the lidar itself.
  • the probability distribution of the reception time of the peak point within the value range is a uniform distribution.
  • the second probability distribution is obtained by determining the probability distribution of the peak point receiving time when the peak point receiving time satisfies a uniform distribution within the value range of the peak point receiving time.
  • the second probability distribution can be reflected as the probability distribution p (t) of the waveform parameter t, expressed as:
  • t 1 represents the minimum value of the value range of the peak point reception time
  • t 2 represents the maximum value of the value range of the peak point reception time
  • the second probability distribution of the receiving time at the peak point can also be used. For example, by performing multiple tests on the lidar, the peak receiving time of the received pulse signal obtained by each test can be counted, and then The second probability distribution of the reception time at the peak point is determined according to the statistical result, which may not be limited in this application.
  • the above-mentioned determination of the third probability distribution according to the P clipped sampling points may include:
  • the lidar determines the value range of the signal strength of the peak point according to the signal strengths corresponding to the P clipped sampling points.
  • the signal strength of the clipping sampling point is generally near the signal strength P.
  • the minimum value of the signal strength at the peak point is greater than the clipping point.
  • the signal strength of the top sampling point so the minimum value of the value range of the peak point signal strength can be determined according to the signal strengths corresponding to the P clipped top sampling points. For example, the maximum signal strength among the signal strengths corresponding to the P clipping sampling points may be taken as the minimum value of the value range of the peak point signal strength.
  • the value range of the signal strength at the peak point can be further determined.
  • the signal intensity at the peak point of the laser pulse signal emitted by the lidar can be taken as the maximum value of the signal intensity at the peak point.
  • the maximum value and the minimum value of the signal strength at the peak point are known, and the value range of the signal strength at the peak point can be determined.
  • the lidar determines the third probability distribution according to the value range of the signal strength of the peak point.
  • a third probability distribution of the signal strength at the peak point within the value range can be determined according to prior information such as the characteristics of the lidar itself.
  • the probability distribution of the signal strength of the peak point within the value range may be considered as a uniform distribution.
  • the third probability distribution can be obtained by determining the probability distribution of the signal strength of the peak point when the signal strength of the peak point satisfies a uniform distribution within the value range of the peak point signal strength.
  • the third probability distribution can be reflected as the probability distribution p (A) of the waveform parameter A, expressed as:
  • a 2 represents the minimum value of the value range of the peak point signal strength
  • a 1 represents the maximum value of the value range of the peak point signal strength
  • the signal strength of the received pulse signal there is a correlation between the signal strength of the received pulse signal and the reflectivity of the object surface reflecting the received pulse signal. For example, the higher the reflectivity of the object surface, the stronger the signal strength of the received pulse signal is generally. .
  • the reflectivity of the surface of the object that reflects the received pulse signal can be regarded as a uniform distribution.
  • the third probability distribution can be obtained by determining the probability distribution of the signal intensity at the peak point within the value range of the signal intensity at the peak point when the probability distribution of the reflectivity of the object surface reflecting the received pulse signal is uniform.
  • the third probability distribution can also be determined in other ways. For example, by performing multiple tests on the lidar, the signal strength of the peak point of the received pulse signal obtained by each test can be counted, and then the signal strength of the peak point can be determined according to the statistical result.
  • the third probability distribution of which may not be limited in this application.
  • the lidar determines a fourth probability distribution of the pulse width of the received pulse signal.
  • the value range of the pulse width of the received pulse signal and the fourth probability distribution of the pulse width within the value range can be obtained by testing the laser pulse signal sent by the lidar under different usage scenarios.
  • the probability distribution of the pulse width within the value range can be considered as a uniform distribution.
  • the fourth probability distribution can be obtained by determining the probability distribution of the signal intensity at the peak point within the value range of the signal intensity at the peak point when the probability distribution of the reflectivity of the object surface reflecting the received pulse signal is uniform.
  • the fourth probability distribution can be reflected as the probability distribution p ( ⁇ ) of the waveform parameter ⁇ , expressed as:
  • ⁇ 1 represents the minimum value of the value range of the pulse width
  • ⁇ 2 represents the maximum value of the value range of the pulse width
  • the lidar determines, according to the second probability distribution, the third probability distribution, and the fourth probability distribution, that each waveform in the preset waveform set is the fifth probability distribution of the received pulse signal.
  • the probability that a waveform (such as the target waveform) in the preset waveform set is the received pulse signal can be expressed as the probability that the following three points are satisfied simultaneously:
  • the peak point receiving time of the target waveform is the peak point receiving time of the received pulse signal
  • the peak point signal strength of the target waveform is the peak point signal strength of the received pulse signal
  • the pulse width of the target waveform is the pulse width of the received pulse signal.
  • the laser radar determines, according to the first probability distribution and the fifth probability distribution, that the received pulse signal is the sixth probability distribution of each waveform in the preset waveform set.
  • the first probability distribution can be considered as the probability distribution of the waveform of the received pulse signal when M sampling points of the rising edge (that is, M sampling points distributed on the waveform of the received pulse signal) are given.
  • ⁇ ) that is, the first probability distribution is the likelihood function L ( ⁇
  • the fifth probability distribution can be considered as the prior distribution of the waveform of the received pulse signal, that is, p ( ⁇ ) .
  • y) that the received pulse signal is each waveform in the preset waveform set is calculated, that is, the posterior distribution of the waveform of the received pulse signal.
  • P (y) can be set according to actual needs or can be calculated by using a related algorithm to reduce P (y) .
  • a Markov Chain Monte Carlo (Markov Chain Monte Carlo, MCMC) algorithm may be used to determine the sixth probability distribution.
  • MCMC Markov Chain Monte Carlo
  • the first probability distribution and the fifth probability distribution construct a Markov chain with the preset waveform set as the state space, and obtain the sample sequence of the Markov chain ⁇ z 1 ,z 2 ,...,z m ,z m +1 ,...,z m+n-1 ,z m+n ⁇ .
  • each sample in the sample sequence of the Markov chain is used to characterize a waveform.
  • the probability of the sample value in the sample sequence of the Markov chain will gradually converge to the sixth probability distribution. Therefore, the sample sequence ⁇ z 1 ,z 2 ,...,z m ,z m +1, ..., after z m + n-1 z m + n ⁇ of n items samples ⁇ z m + 1, ..., z m + n-1, z m + n ⁇ for characterizing Sixth probability distribution.
  • the Metropolis-Hastings algorithm in the MCMC algorithm can be used to construct a Markov chain.
  • the acceptance distribution ⁇ (z, z') in the Metropolis-Hastings algorithm satisfies the following formula (6):
  • z is a sample in the sample sequence of the Markov chain
  • z' is the sample after z in the sample sequence of the Markov chain
  • each sample in the sample sequence of the Markov chain is used to represent a waveform
  • z') is the probability corresponding to the waveform z' in the first probability distribution
  • z) is the probability corresponding to the waveform z in the first probability distribution
  • p(z') is the fifth probability distribution
  • p(z) is the probability corresponding to the waveform z in the fifth probability distribution
  • q(z', z) and q(z, z') are the proposed distributions of the Markov chain.
  • the current signal strength s of the received pulse signal and the current time x satisfy formula (1):
  • the process of building a Markov chain using the Metropolis-Hastings algorithm will be described. The process may include the following steps 1-4:
  • Step 1 Randomly set an initial waveform, that is, the first item sample Z 1 of the Markov chain.
  • Step 2 Set the proposed distribution of the Metropolis-Hastings algorithm.
  • the suggested distribution may be set with reference to the related content in the prior art.
  • different proposal distributions have different convergence rates. This application may not limit which proposed distribution to adopt.
  • Step 4 A number u is randomly selected from the interval (0,1). If u ⁇ ( ⁇ 1 , ⁇ 2 ), determine the second sample Z 2 of the Markov chain as ⁇ 2 ; otherwise, repeat step 3 until the second sample Z 2 of the Markov chain is determined.
  • the samples of the Markov chain are determined in turn, and then the sample sequence of the Markov chain ⁇ z 1 ,z 2 ,...,z m ,z m+1 ,... .,z m+n-1 ,z m+n ⁇ .
  • S207 Determine the first preset waveform from the preset waveform set according to the sixth probability distribution.
  • the peak receiving time and the peak signal strength of the received pulse signal are determined according to the first preset waveform.
  • the received pulse signal is the sixth probability distribution of each waveform in the preset waveform set.
  • a waveform that may be the received pulse signal ie, the first preset waveform can be determined from the preset waveform set) waveform
  • the expectation of the sixth probability distribution can be calculated to obtain the first preset waveform, or the waveform with the highest probability in the sixth probability distribution can be selected as the first preset waveform.
  • the receiving time at the peak point of the received pulse signal and the signal strength at the peak point can be determined.
  • the sixth probability distribution when the sixth probability distribution is determined by using the MCMC algorithm, the sixth probability distribution, determining the first preset waveform from the preset waveform set, may include: calculating the samples of the Markov chain The expectation of the last n samples ⁇ z m+1 ,...,z m+n-1 , z m+n ⁇ in the sequence is to obtain the first preset waveform.
  • the process of determining the waveform of the received pulse signal in the process of determining the waveform of the received pulse signal, first determine the likelihood function (ie, the first probability distribution) of the waveform of the received pulse signal according to the sampled rising edge sampling points. Then, a priori distribution of the waveform of the received pulse signal (ie, the fifth probability distribution) is determined according to the prior information of the received pulse signal, wherein the prior information includes the probability distribution of various parameters affecting the received pulse signal waveform, specifically including : The probability distribution of the receiving time at the peak point of the received pulse signal (ie the second probability distribution), the probability distribution of the signal strength at the peak point (ie the third probability distribution) and the probability distribution of the pulse width of the received pulse signal (ie the fourth probability distribution) .
  • the posterior distribution (ie, sixth probability distribution) of the waveform of the received pulse signal can be calculated.
  • a waveform that may be the received pulse signal ie, the first preset waveform
  • the receiving time at the peak point of the received pulse signal and the signal strength at the peak point can be determined.
  • the beneficial effects of the signal processing method provided by this embodiment are described below in combination with the actual simulation results.
  • the sampling points shown as circles in the figure
  • the fitted waveform of the received pulse signal the waveform obtained by connecting the sampling points in sequence in the figure. It can be seen that the received pulse signal fitted in the figure has a top clipping phenomenon in the part outlined by the dashed circle. Therefore, the received pulse signal fitted according to FIG. 7 cannot accurately determine the peak signal strength and peak reception time of the received pulse signal.
  • the first method is to fit the waveform of the received pulse signal according to a plurality of rising edge sampling points using the least squares method, and determine the peak reception time and peak signal strength of the received pulse signal according to the fitted waveform.
  • the waveform of the received pulse signal is determined, and the peak reception time and the peak signal strength of the received pulse signal are determined according to the fitted waveform.
  • the sampling points of the rising edge portion of the received pulse signal used by the two methods are the same, which are the four sampling points a, b, c and d in FIG. 7 .
  • FIG. 8 shows the waveform of the received pulse signal fitted by using the signal processing method (ie, the second method) provided in this embodiment. It can be seen that the fitting performance of the signal processing method provided in this embodiment is good.
  • Table 1 is the statistical result of the ToF calculated by using the simulation results after 100 times of Monte Carlo simulations using the above-mentioned two methods respectively
  • Table 2 is after 100 times of Monte Carlo simulations using the above-mentioned two methods respectively.
  • FIG. 10 it is a schematic diagram of the composition of a signal processing apparatus provided by an embodiment of the present application.
  • the signal processing apparatus 30 may be a part of the laser radar in the above method embodiments, and when the signal processing apparatus 30 is running, the laser radar may be made to execute the signal processing methods provided in the above embodiments.
  • the signal processing device 30 may specifically be the signal processing module 108 in the lidar shown in FIG. 2 .
  • the signal processing device 30 may also be a chip or a system-on-chip in a lidar.
  • the signal processing apparatus 30 can also be applied to other devices that need to determine the peak point receiving time and the peak point signal strength of the received pulse signal, so that the above device can determine a more accurate received pulse signal.
  • the signal processing apparatus 30 may include: a sampling unit 301, configured to sample the received pulse signal N times to obtain N sampling points, each of the N sampling points
  • the sampling parameters of the sampling points include the receiving time and signal strength corresponding to the sampling points
  • the N sampling points include M rising edge sampling points and P clipping sampling points
  • N, M, and P are integers greater than or equal to 1, respectively.
  • the first probability determination unit 302 is configured to determine a first probability distribution of the M rising edge sampling points distributed on each waveform in the preset waveform set; wherein the preset waveform set includes at least one preset waveform.
  • the second probability determining unit 303 is configured to determine, according to the P clipped sampling points, a second probability distribution of the peak reception time of the received pulse signal and a third probability distribution of the signal strength of the peak point.
  • the second probability determination unit 303 is further configured to determine a fourth probability distribution of the pulse width of the received pulse signal.
  • the third probability determining unit 304 is configured to determine, according to the second probability distribution, the third probability distribution and the fourth probability distribution, that each waveform in the preset waveform set is the fifth probability distribution of the received pulse signal.
  • the fourth probability determination unit 305 is configured to determine, according to the first probability distribution and the fifth probability distribution, that the received pulse signal is a sixth probability distribution of each waveform in the preset waveform set.
  • the waveform determining unit 306 is configured to determine the first preset waveform from the preset waveform set according to the sixth probability distribution.
  • the parameter determination unit 307 is configured to determine, according to the first preset waveform, the peak point receiving time and the peak point signal strength of the received pulse signal.
  • the second probability determination unit 303 is specifically configured to: determine the minimum value of the value range of the peak point reception time according to the minimum value of the reception times corresponding to the P clipped sampling points; The maximum value among the reception times corresponding to the P clipped sampling points is determined to determine the maximum value of the value range of the reception time of the peak point.
  • the second probability distribution is determined according to the value range of the peak point receiving time. According to the signal strengths corresponding to the P clipped sampling points, the minimum value of the value range of the signal strengths of the peak points is determined.
  • the third probability distribution is determined according to the value range of the signal strength of the peak point.
  • determining the second probability distribution according to the value range of the peak point receiving time includes: determining that the peak point receiving time satisfies a uniform distribution within the value range of the peak point receiving time, the peak point receiving time The probability distribution of the reception time is obtained to obtain the second probability distribution.
  • determining the third probability distribution according to the value range of the signal strength at the peak point includes: determining that the signal strength at the peak point satisfies a uniform distribution within the value range of the signal strength at the peak point. The probability distribution of the signal strength, the third probability distribution is obtained.
  • determining the third probability distribution according to the value range of the signal strength of the peak point including: determining the probability distribution of the reflectivity of the object surface reflecting the received pulse signal is a uniform distribution, the peak point The third probability distribution is obtained from the probability distribution of the signal strength within the value range of the signal strength at the peak point.
  • the second probability determination unit 303 is specifically configured to determine the probability distribution of the pulse width under the condition that the pulse width satisfies a uniform distribution within the value range of the pulse width, to obtain a fourth probability distribution.
  • the first probability determining unit 302 is specifically configured to: determine the probability distribution of each sampling point in the M rising edge sampling points distributed on each waveform in the preset waveform set.
  • the first probability distribution is determined according to the probability distribution of each of the M rising edge sampling points distributed on each waveform in the preset waveform set.
  • determining the probability distribution of each sampling point in the M rising edge sampling points on each waveform in the preset waveform set includes: probability distribution according to the intensity of noise when sampling the target sampling point , determining the probability distribution of the target sampling point distributed on each waveform in the preset waveform set; wherein, the target sampling point includes any one of the M rising edge sampling points.
  • the probability distribution of the target sampling point on each waveform in the preset waveform set satisfies the following formula 1:
  • p k represents the probability that the target sampling point k is distributed on the target waveform in the preset waveform set
  • y k represents the signal strength corresponding to the target sampling point k
  • s k represents the target waveform The signal strength of the target sampling point k is collected.
  • the fourth probability determination unit 305 is specifically configured to: construct a Markov chain with the preset waveform set as the state space according to the first probability distribution and the fifth probability distribution, and obtain the Markov chain
  • the waveform determining unit 306 is specifically configured to calculate the expectation of the next n samples ⁇ z m+1 , . . . , z m+n-1 , z m+n ⁇
  • a Markov chain with a preset waveform set as the state space is constructed, including:
  • z is a sample in the sample sequence of the Markov chain
  • z' is the sample after z in the sample sequence of the Markov chain
  • z') is the corresponding sample of z' in the first probability distribution
  • z) is the probability corresponding to z in the first probability distribution
  • p(z') is the probability corresponding to z' in the fifth probability distribution
  • p(z) is the probability corresponding to z in the fifth probability distribution
  • Probabilities, q(z',z) and q(z,z') are the proposed distributions for Markov chains.
  • FIG. 11 is a schematic diagram showing the composition of another data transmission apparatus.
  • the data transmission apparatus 40 includes: one or more processors 401 and one or more memories 402 .
  • One or more processors 401 are coupled to one or more memories 402 for storing computer-executable instructions.
  • the data transmission device 40 is caused to perform S201-S207 as shown in FIG. 5 and other operations that the lidar needs to perform.
  • the embodiment of the present application further provides a computer-readable storage medium, where an instruction is stored in the computer-readable storage medium, and when the instruction is executed, the method provided by the embodiment of the present application is executed.
  • Embodiments of the present application also provide a computer program product including instructions. When it runs on a computer, the computer can execute the methods provided by the embodiments of the present application.
  • an embodiment of the present application further provides a chip.
  • the chip includes a processor.
  • the processor executes the computer program instructions
  • the chip can execute the method provided by the embodiments of the present application.
  • the instruction can come from memory inside the chip or from memory outside the chip.
  • the chip also includes an input and output circuit as a communication interface.
  • the functions or actions or operations or steps in the above embodiments may be implemented in whole or in part by software, hardware, firmware or any combination thereof.
  • a software program When implemented using a software program, it may be implemented in whole or in part in the form of a computer program product.
  • the computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, all or part of the processes or functions described in the embodiments of the present application are generated.
  • the computer may be a general purpose computer, special purpose computer, computer network, or other programmable device.
  • the computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be downloaded from a website site, computer, server, or data center Transmission to another website site, computer, server, or data center by wire (eg, coaxial cable, optical fiber, digital subscriber line, DSL) or wireless (eg, infrared, wireless, microwave, etc.).
  • the computer-readable storage medium can be any available medium that can be accessed by a computer, or data storage devices including one or more servers, data centers, etc. that can be integrated with the medium.
  • the usable media may be magnetic media (eg, floppy disks, hard disks, magnetic tapes), optical media (eg, DVDs), or semiconductor media (eg, solid state disks (SSDs)), and the like.

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Abstract

本申请实施例提供一种信号处理方法及装置，涉及激光探测技术领域，可应用于自动驾驶或辅助驾驶。本申请实施例能够提高接收脉冲信号的峰值点信号强度和峰值点接收时间的准确性。该方法包括：激光雷达确定M个上升沿采样点在预设波形集合中的各波形上分布的第一概率分布；确定预设波形集合中的各波形为接收脉冲信号的第五概率分布；根据第一概率分布和第五概率分布，确定接收脉冲信号为预设波形集合中的各波形的第六概率分布；根据第六概率分布，从预设波形集合中确定第一预设波形；根据第一预设波形确定接收脉冲信号的峰值点接收时间和峰值点信号强度。

Description

一种信号处理方法及装置 技术领域
本申请实施例涉及激光探测技术领域，尤其涉及一种信号处理方法及装置。
背景技术
目前，激光雷达可以通过向目标对象发射激光脉冲信号，并记录激光雷达接收目标对象反射生成的接收脉冲信号的峰值点接收时间、峰值点信号强度等信息，以根据这些信息对该目标对象进行探测。例如，可以根据激光雷达发射激光脉冲信号的发射时间T1和接收脉冲信号的峰值点接收时间T2，计算激光的飞行时间(time of flight，ToF)为τ＝T2-T1。进而根据飞行时间τ以及光速，可以计算出目标对象到激光雷达的距离。再例如，还可以根据激光雷达所发出的激光脉冲信号的信号强度和接收脉冲信号的峰值点信号强度的关系，判断目标对象的表面反射率，进而判断目标对象的材质等信息。
为了确定接收脉冲信号的峰值点接收时间和峰值点信号强度，通常需要通过对接收脉冲信号进行采样，得到各采样点对应的接收时间和信号强度。然后根据多个采样点，确定接收脉冲信号的波形，进而确定接收脉冲信号的峰值点接收时间和峰值点信号强度。
例如，图1中的(a)所示为一种拟合出的接收脉冲信号的波形示意图。通过对接收脉冲信号进行采样，得到各采样点对应的接收时间和信号强度。其中，图1中每个圆圈表示一次采样。然后，根据各采样点对应的接收时间和信号强度，便可以拟合出接收脉冲信号的波形，如，图1中的(a)所示。根据拟合出的接收脉冲信号，可以确定出接收脉冲信号的峰值点接收时间和峰值点信号强度，其中峰值点接收时间为t，峰值点信号强度为P。
但在实际应用中，激光雷达在采样接收脉冲信号的过程中，可能会由于接收脉冲信号的信号强度超出激光雷达的动态范围(dynamic range)，或激光雷达中电子元件的非线性记忆效应等原因导致采集到的采样点的采样参数失真，影响探测结果的准确性。
例如，当接收脉冲信号的信号强度超出激光雷达的动态范围时，根据所采集到的采样点拟合出的接收脉冲信号的波形就会出现削顶现象，如图1中的(b)所示。结合图1中的(b)，假设在时刻t1和时刻t2之间的区域内接收脉冲信号的信号强度超出激光雷达的动态范围，则在这一区域内的采样点对应的信号强度为激光雷达动态范围的最大信号强度，而非接收脉冲信号的真实信号强度。这样，根据这些采样点拟合出的接收脉冲信号的波形就会出现削顶现象。
因此，如何才能避免由采样参数失真导致探测结果不准确的这种情况，这是保证激光雷达正常工作的关键之一。
发明内容
本申请实施例提供一种信号处理方法及装置，用于解决由于接收脉冲信号的采样 点的采样参数失真而导致无法准确获取接收脉冲信号的峰值点接收时间和峰值点信号强度，进而导致探测结果不准确的问题。
第一方面，提供一种信号处理方法，包括：对接收脉冲信号进行N次采样，得到N个采样点。其中，N个采样点中的每个采样点的采样参数包括采样点对应的接收时间和信号强度，N个采样点包括M个上升沿采样点以及P个削顶采样点，N、M和P分别为大于或等于1的整数；确定M个上升沿采样点在预设波形集合中的各波形上分布的第一概率分布；其中，预设波形集合中包括至少一个预设波形；根据P个削顶采样点确定接收脉冲信号的峰值点接收时间的第二概率分布和峰值点信号强度的第三概率分布；确定接收脉冲信号的脉冲宽度的第四概率分布；根据第二概率分布、第三概率分布以及第四概率分布确定预设波形集合中的各波形为接收脉冲信号的第五概率分布；根据第一概率分布和第五概率分布，确定接收脉冲信号为预设波形集合中的各波形的第六概率分布；根据第六概率分布，从预设波形集合中确定第一预设波形；根据第一预设波形确定接收脉冲信号的峰值点接收时间和峰值点信号强度。
本实施例所提供上述技术方案，在确定接收脉冲信号的波形的过程中，首先根据采样到的上升沿采样点确定出关于接收脉冲信号的波形的似然函数(即第一概率分布)。然后，根据接收脉冲信号的先验信息，确定出接收脉冲信号的波形的先验分布(即第五概率分布)，其中先验信息包括影响接收脉冲信号波形的各种参数的概率分布，具体包括：接收脉冲信号的峰值点接收时间的概率分布(即第二概率分布)、峰值点信号强度的概率分布(即第三概率分布)以及接收脉冲信号脉冲宽度的概率分布(即第四概率分布)。进而，可以计算出接收脉冲信号的波形的后验分布(即第六概率分布)。然后，根据第六概率分布，可以从预设波形集合中确定出可能是接收脉冲信号的波形(即第一预设波形)。从而根据第一预设波形，即可以确定出接收脉冲信号的峰值点接收时间和峰值点信号强度。通过上述方法，可以更加准确的确定出峰值点信号强度和峰值点接收时间。
在一种可能的设计中，根据P个削顶采样点确定接收脉冲信号的峰值点接收时间的第二概率分布和峰值点信号强度的第三概率分布，包括：根据P个削顶采样点所对应的接收时间中的最小值，确定峰值点接收时间的取值范围的最小值；根据P个削顶采样点所对应的接收时间中的最大值，确定峰值点接收时间的取值范围的最大值；根据峰值点接收时间的取值范围，确定第二概率分布；根据P个削顶采样点对应的信号强度，确定峰值点信号强度的取值范围的最小值；根据峰值点信号强度的取值范围，确定第三概率分布。基于上述设计，可以根据削顶采样点确定出峰值点接收时间的取值范围以及峰值点信号强度的取值范围，进而基于确定出的取值范围可以确定出更加准确的第二概率分布和第三概率分布。
在一种可能的设计中，根据峰值点接收时间的取值范围，确定第二概率分布，包括：确定峰值点接收时间在峰值点接收时间的取值范围内满足均匀分布的情况下，峰值点接收时间的概率分布，得到第二概率分布。基于上述设计，本申请可以简化计算过程，快速得到第二概率分布。
在一种可能的设计中，根据峰值点信号强度的取值范围，确定第三概率分布，包括：确定峰值点信号强度在峰值点信号强度的取值范围内满足均匀分布的情况下，峰 值点信号强度的概率分布，得到第三概率分布。基于上述设计，本申请可以简化计算过程，快速得到第三概率分布。
在一种可能的设计中，根据峰值点信号强度的取值范围，确定第三概率分布，包括：确定在反射接收脉冲信号的对象表面的反射率的概率分布为均匀分布的情况下，峰值点信号强度在峰值点信号强度的取值范围内的概率分布，得到第三概率分布。基于上述设计，可以通过根据反射接收脉冲信号的对象表面的反射率的概率分布得到第三概率分布，以得到更加准确的第三概率分布。
在一种可能的设计中，接收脉冲信号的脉冲宽度的第四概率分布，包括：确定脉冲宽度在脉冲宽度的取值范围内满足均匀分布的情况下，脉冲宽度的概率分布，得到第四概率分布。基于上述设计，本申请可以简化计算过程，快速得到第四概率分布。
在一种可能的设计中，确定M个上升沿采样点在预设波形集合中的各波形上分布的第一概率分布，包括：确定M个上升沿采样点中每个采样点在预设波形集合中的各波形上分布的概率分布；根据M个上升沿采样点中每个采样点在预设波形集合中的各波形上分布的概率分布，确定第一概率分布。基于上述设计，可以利用M个上升沿采样点中每个采样点在预设波形集合中的各波形上分布的概率分布，确定出第一概率分布。
在一种可能的设计中，确定M个上升沿采样点中每个采样点在预设波形集合中的各波形上分布的概率分布，包括：根据在采样目标采样点时噪声的强度的概率分布，确定目标采样点在预设波形集合中的各波形上分布的概率分布；其中，目标采样点包括M个上升沿采样点中任一个。基于上述设计，通过利用噪声对采样结果的影响，来确定M个采样点中每个采样点在预设波形集合中的各波形上分布的概率分布，进而可以确定出更加准确的概率分布结果。
在一种可能的设计中，目标采样点在预设波形集合中的各波形上分布的概率分布，满足以下公式一：
Figure PCTCN2020103124-appb-000001
其中，p k表示目标采样点k在预设波形集合中目标波形上分布的概率，y k表示目标采样点k对应的信号强度，s k表示目标波形在采集目标采样点k时的信号强度。在上述设计中，通过利用高斯分布来反映采样时的噪声强度的概率分布，进而提出利用上述公式一来计算采样点在预设波形集合中的各波形上分布的概率分布。通过上述公式一，可以快速计算出各采样点在预设波形集合中的各波形上分布的概率分布。
在一种可能的设计中，根据第一概率分布和第五概率分布，确定接收脉冲信号为预设波形集合中的各波形的第六概率分布，包括：根据第一概率分布以及第五概率分布，构建以预设波形集合为状态空间的马尔可夫链，得到马尔可夫链的样本序列{z 1,z 2,...,z m,z m+1,...,z m+n-1,z m+n}；其中，样本序列中各样本分别用于表征一种波形；样本序列{z 1,z 2,...,z m,z m+1,...,z m+n-1,z m+n}中的后n项样本{z m+1,...,z m+n-1,z m+n}用于表征第六概率分布；根据第六概率分布，从预设波形集合中确定第一预设波形，包括：计算后n项样本{z m+1,...,z m+n-1,z m+n}的期望，得到第一预设波形。在上述设计中，通过构建马尔可夫链，可以方便快捷的确定出第六概率分布，进而得到第一预设波形。
在一种可能的设计中，根据第一概率分布以及第五概率分布，构建以预设波形集合为状态空间的马尔可夫链，包括：利用Metropolis-Hastings算法，构建接受分布α(z,z')满足以下公式二的马尔可夫链：
Figure PCTCN2020103124-appb-000002
其中，z为马尔可夫链的样本序列中的一项样本，z'为马尔可夫链的样本序列中z后一项样本，p(y|z')为第一概率分布中z'对应的概率，p(y|z)为第一概率分布中z对应的概率，p(z')为第五概率分布中z'对应的概率，p(z)为第五概率分布中z对应的概率，q(z',z)和q(z,z')为马尔可夫链的建议分布。
第二方面，本申请提供一种信号处理装置，该信号处理装置可以实现上述第一方面或第一方面中可能的设计中的功能。这些功能可以通过硬件实现，也可以通过硬件执行相应的软件实现。硬件或软件包括一个或多个上述功能相应的模块。如：该信号处理装置可以包括：采样单元，用于对接收脉冲信号进行N次采样，得到N个采样点，N个采样点中的每个采样点的采样参数包括采样点对应的接收时间和信号强度，N个采样点包括M个上升沿采样点以及P个削顶采样点，N、M和P分别为大于或等于1的整数；第一概率确定单元，用于确定M个上升沿采样点在预设波形集合中的各波形上分布的第一概率分布；其中，预设波形集合中包括至少一个预设波形；第二概率确定单元，用于根据P个削顶采样点确定接收脉冲信号的峰值点接收时间的第二概率分布和峰值点信号强度的第三概率分布；第二概率确定单元，还用于确定接收脉冲信号的脉冲宽度的第四概率分布；第三概率确定单元，用于根据第二概率分布、第三概率分布以及第四概率分布确定预设波形集合中的各波形为接收脉冲信号的第五概率分布；第四概率确定单元，用于根据第一概率分布和第五概率分布，确定接收脉冲信号为预设波形集合中的各波形的第六概率分布；波形确定单元，用于根据第六概率分布，从预设波形集合中确定第一预设波形；参数确定单元，用于根据第一预设波形确定接收脉冲信号的峰值点接收时间和峰值点信号强度。当然，该信号处理装置还可以包括更多或更少的单元，用于实现其他的功能。
第三方面，提供一种信号处理装置，该信号处理装置包括一个或多个处理器，该一个或多个处理器和一个或多个存储器耦合；一个或多个存储器存储有计算机指令；当一个或多个处理器执行计算机指令时，使得信号处理装置执行如上述第一方面所提供的信号处理方法。
第四方面，提供一种芯片，芯片包括处理电路和接口；处理电路用于从存储介质中调用并运行存储介质中存储的计算机程序，以执行如上述第一方面所提供的信号处理方法。
第五方面，提供一种激光雷达，包括上述第二或第三方面所提供的信号处理装置，或者包括上述第四方面提供的芯片。
第六方面，提供一种计算机可读存储介质，该计算机可读存储介质中存储有指令，当该指令运行时，执行上述第一方面或者第一方面中可能的设计中的信号处理方法。
第七方面，提供一种包含指令的计算机程序产品，当其在计算机上运行时，使得计算机可以执行上述第一方面或者第一方面中可能的设计中的信号处理方法。
其中，第二方面至第七方面中任一种设计方式所带来的技术效果可以参见上述第一方面中的不同设计方式所带来的技术效果，在此不再赘述。
附图说明
图1为本申请实施例提供的一种拟合出的接收脉冲信号的波形示意图之一；
图2为本申请实施例提供的一种激光雷达的结构示意图；
图3为本申请实施例提供的一种拟合出的接收脉冲信号的波形示意图之二；
图4为本申请实施例提供的一种拟合出的接收脉冲信号的波形示意图之三；
图5为本申请实施例提供的一种信号处理方法的流程示意图之一；
图6为本申请实施例提供的一种信号处理方法的流程示意图之二；
图7为本申请实施例提供的一种对接收脉冲信号进行采样得到的采样点的示意图；
图8为利用现有技术拟合接收脉冲信号的波形示意图；
图9为利用本申请实施例所提供的信号处理方法拟合接收脉冲信号的波形示意图；
图10为本申请实施例所提供的一种信号处理装置的结构示意图之一；
图11为本申请实施例所提供的一种信号处理装置的结构示意图之二。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行描述。为了便于清楚描述本申请实施例的技术方案，在本申请的实施例中，采用了“第一”、“第二”等字样对功能和作用基本相同的相同项或相似项进行区分。本领域技术人员可以理解“第一”、“第二”等字样并不对数量和执行次序进行限定，并且“第一”、“第二”等字样也并不限定一定不同。同时，在本申请实施例中，“示例性的”或者“例如”等词用于表示作例子、例证或说明。本申请实施例中被描述为“示例性的”或者“例如”的任何实施例或设计方案不应被解释为比其它实施例或设计方案更优选或更具优势。确切而言，使用“示例性的”或者“例如”等词旨在以具体方式呈现相关概念，便于理解。
首先，对本申请实施例所涉及的相关技术进行介绍：
激光雷达是以发射激光束探测目标对象的位置、速度等特征量的雷达系统。其工作原理是向目标对象发射激光脉冲信号，然后记录激光雷达接收到从目标对象反射回来的信号(下文称为接收脉冲信号)的峰值点接收时间、峰值点信号强度。然后根据接收脉冲信号的峰值点接收时间、峰值点信号强度以及发送的激光脉冲信号的信息，便可以获取目标对象的相关信息。例如，目标对象到激光雷达的距离、目标对象表面反射率等参数。
如图2所示，为一种激光雷达的结构示意图。其中，在激光雷达10中，波形发生器(waveform generator)101用于控制发射机(transmitter)102发射预设波形的激光脉冲信号。另外，波形发生器101和发射机102还将发射的激光脉冲信号的信号参数(如发射时间、信号强度等)发送至信号处理模块108。偏转镜(fine steering)103用于控制激光脉冲信号的方向，以使激光脉冲信号透过发射端透镜104，射向待检测 的目标对象。然后，激光雷达10通过接收端透镜105接收目标对象反射的接收脉冲信号，并利用偏转镜106调整接收脉冲信号的方向以使探测模块107接收到该接收脉冲信号。然后探测模块107通过对接收脉冲信号进行检测、采样得到多个采样点，其中各采样点的采样参数可以包括采样点对应的接收时间和信号强度等等。之后探测模块107将各采样点的采样参数发送至信号处理模块108。信号处理模块108根据来自探测模块107的采样点和来自波形发生器101、发射机102的信号参数，确定目标对象的相关信息。例如，信号处理模块108根据上述采样点，拟合出接收脉冲信号的波形，以确定接收脉冲信号的峰值点接收时间和峰值点信号强度。然后根据接收脉冲信号的峰值点接收时间和峰值点信号强度，以及来自波形发生器101、发射机102的信号参数，计算目标对象到激光雷达的距离等相关信息。
需要说明的是，在本实施例中，采样点对应的接收时间可以是指在该采样点采样到的接收脉冲信号的接收时间，采样点对应的信号强度可以是指在该采样点采样到的接收脉冲信号的信号强度。
上述图2所示激光雷达10仅为了便于读者理解本申请技术方案，示例性的给出了激光雷达的原理结构。容易理解的是，其中激光雷达10中各功能模块可以由硬件、软件或软硬件结合的方式来实现。例如，其中发射机102可以为激光二极管(laser diode)，探测模块107可以包括雪崩光电二极管(Avalanche Photon Diode，APD)、模拟数字转换器(analog to digital converter，ADC)以及检测器(detector)。
目前，激光雷达在采样接收脉冲信号的过程中，若存在激光雷达发射的激光脉冲信号强度较大、目标对象的表面反射率较高，或者目标对象与激光雷达之间距离较近这些情况时，就可能使接收脉冲信号的强度较高。当接收脉冲信号的信号强度超出激光雷达的动态范围时，例如在图2所示激光雷达10中当接收脉冲信号的强度超出探测单元107的正常工作范围时，探测单元107将无法采样到大于正常工作范围的信号强度，进而根据采样点拟合出的接收脉冲信号的波形会出现削顶现象。
其中，需要说明的是，本申请实施例中所称激光雷达的动态范围，可以理解为激光雷达中用于检测接收脉冲信号的功能单元(例如图2中探测单元107)的线性工作范围。当接收脉冲信号的信号强度没有超出线性工作范围时，采样点对应的信号强度可以反映当前接收脉冲信号的信号强度，即随着接收脉冲信号的信号强度的变大，所采集的采样点对应的信号强度也相应变大。当接收脉冲信号的信号强度超出线性工作范围的最大信号强度时，激光雷达在采样点采集到的信号强度就会发生饱和，即此时采集到的采样点对应的信号强度不再随着接收脉冲信号强度的增大而增大，而是会保持线性工作范围的最大信号强度。
另外，由于激光雷达中电子元件的非线性记忆效应，如图1中的(c)所示，可以看出在接收脉冲信号的下降沿部分的采样点处，采集到的信号强度要大于实际接收脉冲信号的信号强度，进而拟合出的接收脉冲信号的波形出现拖尾现象；另外在下降沿部分的采样点处，采集到的信号强度还会出现大幅度波动，进而拟合出的接收脉冲信号的波形出现振铃现象。
进一步的，当激光雷达在各采样点采集采样参数时，若同时存在削顶现象、拖尾现象以及振铃现象时，采集到的采样点的信号强度如图1中的(d)所示。可以看出， 此时除上升沿的部分采样点的信号强度能够反映接收脉冲的信号强度之外，其他采样点的信号强度都发生了失真。
另外，在连续两次发射激光脉冲信号的情况下，当两次激光脉冲信号的发射时间间隔较短时，在接收脉冲信号的下降沿进行采样时，还可能受到下一个接收脉冲信号的干扰。
可以看出，当激光雷达在各采样点采集采样参数时，若出现削顶现象、拖尾现象、振铃现象以及受到其他接收脉冲信号的干扰等情况，都可能导致在接收脉冲信号的后一部分进行采样时采样点的信号强度失真。而采样点采集的信号强度失真，就会进一步导致无法准确拟合出接收脉冲信号的波形，也就无法确定接收脉冲信号的峰值点信号强度以及峰值点接收时间。最终影响激光雷达的探测结果的准确性。因此，如何才能避免由采样参数失真导致探测结果不准确的这种情况，这是保证激光雷达正常工作的关键之一。
为了解决上述技术问题，可以通过在出现削顶现象之前的n个上升沿采样点采集采样参数，例如图3中的(a)所示在a、b、c、d和e五个采样点采集采样参数。然后根据这n个采样点进行波形拟合，拟合出接收脉冲信号的波形，例如可以利用最小二乘法拟合出接收脉冲信号的波形。然后根据拟合出的接收脉冲信号，确定接收脉冲信号的峰值点信号强度和峰值点接收时间，进而得到探测结果。但该方法中，由于只有上升沿能提供有效拟合点，因此拟合出的波形误差较大。例如，根据上述a、b、c、d和e五个采样点，利用最小二乘法拟合出的接收脉冲信号的波形可以为图3中的(b)中虚线波形所示。可以看出，其中拟合出的波形与接收脉冲信号实际波形之间存在较大误差。因此该方法无法得出准确的探测结果。
另外，还可以先对接收脉冲信号进行采样，然后设置一个滑窗，用于获取滑窗内采样点所采集到的的信号强度。当滑窗内的信号强度持续大于预设阈值时，则确定滑窗内是接收脉冲信号。然后，再在找到的接收脉冲信号中找到波形形心，波形形心的接收时间即作为接收脉冲信号的峰值点接收时间。如图4所示，在滑窗(图中虚线框所示)内采集到的信号强度持续保持在最大信号强度P，进而确定滑窗内是接收脉冲信号，然后将滑窗的中点作为接收脉冲信号的峰值点。可以看出，这种方法对滑窗的宽度有要求，如图4中当滑窗的宽度较小时，根据滑窗中点确定出的接收脉冲信号的峰值点接收时间是Xc，而实际的峰值点接收时间则是Xc’，存在误差。另外，这种方式还存在只能估计峰值点接收时间，无法确定该峰值点信号强度的问题。
针对上述问题，本申请实施例提供一种信号处理方法，在确定接收脉冲信号的波形的过程中，通过引入接收脉冲信号的先验信息，其中先验信息包括：接收脉冲信号的峰值点接收时间的概率分布、峰值点信号强度的概率分布以及接收脉冲信号脉冲宽度的概率分布，然后利用这些先验信息对接收脉冲信号的波形的限制，进而确定出更加准确的接收脉冲信号的波形，从而确定出更加准确的峰值点信号强度和峰值点接收时间。
本申请实施例提供的信号处理方法可以应用于激光雷达或其他需要确定接收脉冲信号的峰值点接收时间和峰值点信号强度的设备中，以使得上述设备确定出更加准确的接收脉冲信号。以下以激光雷达为例，对该方法进行介绍，如图5所示，该方法包 括以下S201-S207：
S201、激光雷达对接收脉冲信号进行N次采样，得到N个采样点。
例如图2所示激光雷达10中，在向目标对象发射激光脉冲信号后，激光脉冲信号遇到目标对象反射生成接收脉冲信号。然后接收脉冲信号通过接收端透镜105、偏转镜106至探测模块107。然后探测模107便可以在接收到接收脉冲信号后，对接收脉冲信号进行采样得到采样点。
其中，N个采样点中每个采样点的采样参数包括该采样点对应的接收时间和信号强度。例如N个采样点包括a、b和c三个采样点，其中采样点a的采样参数包括采样点a对应的接收时间和信号强度，采样点b的采样参数包括采样点b对应的接收时间和信号强度，以及采样点c的采样参数包括采样点c对应的接收时间和信号强度。
另外，N个采样点包括M个上升沿采样点以及P个削顶采样点。其中，N、M和P分别为大于或等于1的正整数。
其中，在实际实施过程中，采样点对应的信号强度，可以为在采样点处接收脉冲信号的光功率等反映光信号强度的参数，也可以为在采样点处响应于接收脉冲信号的光信号强度产生的电压值或电流值。对于信号强度所使用的实际物理量，本申请可以不做限制。
需要说明的是，本申请实施例中，上升沿采样点指在接收脉冲信号的上升沿的采样点。例如，图1中的(d)中，包括a、b、c和d四个上升沿采样点。削顶采样点指在出现削顶现象的部分的采样点。例如，图1中的(d)中，包括e、f、g和h四个削顶采样点。
S202、激光雷达确定M个上升沿采样点在预设波形集合中的各波形上分布的第一概率分布。
其中，预设波形集合中包括至少一个预设波形。
通过上文对激光雷达的介绍可知，激光雷达在接收脉冲信号的上升沿进行采样时失真的可能性较小，因此可以利用上升沿采样点的采样参数，确定出预设波形集合中的各波是接收脉冲信号的波形的概率分布，即M个上升沿采样点在预设波形集合中的各波形上分布的第一概率分布。
示例性的，考虑到接收脉冲信号通常为高斯脉冲，也就是说接收脉冲信号的当前信号强度s与当前时间x满足以下公式(1)：
Figure PCTCN2020103124-appb-000003
其中，当波形参数A、t、σ取不同值时对应的波形不同。下文中为了便于描述，用θ表示A、t、σ的集合，即θ＝(A,t,σ)。
因此，可以认为满足上述公式(1)的波形，即为可能是接收脉冲信号的波形。因此，可以利用满足上述公式(1)的波形构建预设波形集合，即预设波形集合中包括满足上述公式(1)的至少一个预设波形。
当然，可以理解的是，在本申请实施例所提供技术方案在实施过程中，也可以按照其他方式确定预设波形集合中的波形。也就是说，本领域技术人员可以根据实际需要选择合适的预设波形集合。对于预设波形集合中包括哪些波形，本申请可以不做限 制。
在一种实现方式中，考虑到可以根据M个事件分别发生的概率来确定M个事件同时发生的概率，例如将M个事件分别发生的概率求积即可得到M个事件同时发生的概率。因此也可以根据M个上升沿采样点中各采样点在预设波形集合中各波形上分布的概率分布，来确定M个上升沿采样点在预设波形集合中的各波形上分布的第一概率分布。因此，如图6所示，本申请S202具体可以包括以下S2021-S2022：
S2021、激光雷达确定M个上升沿采样点中每个采样点在预设波形集合中的各波形上分布的概率分布。
例如，M个上升沿采样点中共包括五个采样点，分别为：采样点1、采样点2、采样点3、采样点4、采样点5。五个采样点的采样参数分别包括该采样点对应的接收时间和信号强度。另外，假设预设波形集合中包括满足上述公式(1)的波形。然后，针对每个采样点，根据该采样点的接收时间和信号强度，便可以计算出该采样点在预设波形集合中的各波形上分布的概率。
在一种可能的设计中，考虑到在接收脉冲信号的上升沿部分对采样点处采样参数产生干扰的主要是噪声。也就是说在采样点处采集到的信号强度，实际上反映了接收脉冲信号的当前信号强度与当前噪声的强度之和。因此，在计算目标采样点在预设波形集合中的各波形上分布的概率时，上述S2021可以包括：根据在采样目标采样点时噪声的强度的概率分布，确定目标采样点在预设波形集合中的各波形上分布的概率分布。其中目标采样点可以为M个上升沿采样点中任一采样点。
例如，假设目标采样点所采集到的信号强度为y，在采样目标采样点时噪声的强度为w，预设波形集合中波形(如称为目标波形)在目标采样点的信号强度为s。那么，若接收脉冲信号为目标波形，则需要满足w＝y-s。另外，因为y已知，所以根据在采样目标采样点时噪声的强度w的概率分布，便可以计算出w＝y-s的概率，即就是目标采样点在目标波形上分布的概率。例如，假设目标采样点所采集到的信号强度为5(信号强度的物理单位可根据实际情况确定，可以是光功率、电压或电流等)，目标波形在目标采样点的信号强度为4，在采样目标采样点时噪声的强度为1的概率为20％，则可以确定目标采样点在目标波形上分布的概率为20％。
进一步的，在一种可能的设计中，考虑到噪声的强度的概率分布通常符合均值为0，方差为N 0的高斯分布，其中N 0为噪声功率，即噪声的强度的概率分布p (w)满足以下公式(3)：
Figure PCTCN2020103124-appb-000004
因此，本申请实施例所提供技术方案中，在确定M个上升沿采样点中每个采样点在预设波形集合中的各波形上分布的概率分布时，可以根据以下公式(4)确定目标采样点在预设波形集合中的各波形上分布的概率分布，也就是说目标采样点在预设波形集合中的各波形上分布的概率分布满足以下公式(4)：
Figure PCTCN2020103124-appb-000005
其中，p k表示目标采样点k在预设波形集合中目标波形上分布的概率，y k表示目标采样点k对应的信号强度，s k表示目标波形在采集目标采样点k时的信号强度。N 0的取值可根据实际需要进行设定。
S2022、激光雷达根据M个上升沿采样点中每个采样点在预设波形集合中的各波形上分布的概率分布，确定第一概率分布。
例如，在确定M个上升沿采样点中每个采样点在预设波形集合中的各波形上分布的概率分布之后，可以将M个上升沿采样点中每个采样点在预设波形集合中的各波形上分布的概率分布进行求积运算，进而确定出第一概率分布。
例如，当目标采样点在预设波形集合中的各波形上分布的概率分布满足上述公式(4)，预设波形集合中包括满足上述公式(1)的至少一个预设波形的情况下，则可以确定第一概率分布满足以下公式(5)：
Figure PCTCN2020103124-appb-000006
其中，p (y|θ)表示M个上升沿采样点在波形参数A、t、σ为θ的目标波形上分布的概率，y k表示目标采样点k对应的信号强度，s k(θ)表示波形参数A、t、σ为θ的目标波形在采集目标采样点k时的信号强度。
S203、激光雷达根据P个削顶采样点，确定接收脉冲信号的峰值点接收时间的第二概率分布和峰值点信号强度的第三概率分布。
其中，考虑到若存在削顶现象，则说明接收脉冲信号的峰值点接收时间在削顶部分对应的时间范围内，并且说明接收脉冲信号的峰值点信号强度比削顶部分采样到的信号强度大。例如在图1中的(b)中，可以确定该接收脉冲信号的峰值点接收时间在t1-t2之间，并且接收脉冲信号的峰值点信号强度大于信号强度P。那么利用P个削顶采样点所采集到的采样参数，便可以确定出接收脉冲信号的峰值点接收时间和峰值点信号强度的取值范围，进而确定出峰值点接收时间和峰值点信号强度的概率分布(即第二概率分布和第三概率分布)。
因此，在一种实现方式中，如图6所示，上述根据P个削顶采样点确定第二概率分布，可以包括：
S2031、激光雷达根据P个削顶采样点所对应的接收时间中的最小值和最大值，确定峰值点接收时间的取值范围。
其中，可以根据P个削顶采样点所对应的接收时间中的最小值，确定峰值点接收时间的取值范围的最小值。另外，可以根据P个削顶采样点所对应的接收时间中的最大值，确定峰值点接收时间的取值范围的最大值。
例如，图1中的(b)中，可以看出采样点1和采样点2对应的接收时间，分别为削顶采样点所对应的接收时间中的最小值和最大值。那么根据采样点1和采样点2对应的接收时间，便可以确定出峰值点接收时间的取值范围的最小值和最大值。
S2032、激光雷达根据峰值点接收时间的取值范围，确定第二概率分布。
具体的，在确定峰值点接收时间的取值范围后，便可以根据激光雷达本身的特性等先验信息，确定出在取值范围内峰值点接收时间的概率分布(即第二概率分布)。
在一种可能的设计中，为了便于计算，可以认为峰值点接收时间在取值范围内的概率分布为均匀分布。进而确定峰值点接收时间在峰值点接收时间的取值范围内满足均匀分布的情况下，峰值点接收时间的概率分布，得到第二概率分布。
例如，以接收脉冲信号的波形满足公式(1)为例，则第二概率分布可以反映为波形参数t的概率分布p (t)，表示为：
Figure PCTCN2020103124-appb-000007
其中，t 1表示峰值点接收时间的取值范围的最小值，t 2表示峰值点接收时间的取值范围的最大值。
需要说明的是，还可以利用其他方式确定峰值点接收时间的第二概率分布，例如可以通过对激光雷达进行多次测试，将每次测试得到的接收脉冲信号的峰值点接收时间进行统计，然后根据统计结果确定峰值点接收时间的第二概率分布，对此本申请可以不做限制。
另外，在一种实现方式中，如图6所示，上述根据P个削顶采样点确定第三概率分布，可以包括：
S2033、激光雷达根据P个削顶采样点对应的信号强度，确定峰值点信号强度的取值范围。
例如，图1中的(b)中，可以看出由于削顶现在的存在，因此削顶采样点的信号强度普遍在信号强度P附近，另外由于可以确定峰值点信号强度的最小值要大于削顶采样点的信号强度，因此可以根据P个削顶采样点对应的信号强度确定峰值点信号强度的取值范围的最小值。例如，可以将P个削顶采样点对应的信号强度中最大的信号强度作为峰值点信号强度的取值范围的最小值。
然后，在确定了峰值点信号强度的取值范围的最小值后，便可以进一步确定出峰值点信号强度的取值范围。例如，可以将激光雷达发射的激光脉冲信号的峰值点信号强度作为峰值点信号强度的最大值。然后，已知峰值点信号强度的最大值和最小值，便可以确定出峰值点信号强度的取值范围。
S2034、激光雷达根据峰值点信号强度的取值范围，确定第三概率分布。
与上述S2032类似，在确定出峰值点信号强度的取值范围后，便可以根据激光雷达本身的特性等先验信息，确定出在取值范围内峰值点信号强度的第三概率分布。
在一种可能的设计中，为了便于计算，可以认为峰值点信号强度在取值范围内的概率分布为均匀分布。进而可以通过确定峰值点信号强度在峰值点信号强度的取值范围内满足均匀分布的情况下，峰值点信号强度的概率分布，得到第三概率分布。
例如，以接收脉冲信号的波形满足公式(1)为例，则第三概率分布可以反映为波形参数A的概率分布p (A)，表示为：
Figure PCTCN2020103124-appb-000008
其中，A 2表示峰值点信号强度的取值范围的最小值，A 1表示峰值点信号强度的取 值范围的最大值。
在另一种可能的设计中，考虑到接收脉冲信号的信号强度与反射接收脉冲信号的对象表面的反射率存在关联关系，例如对象表面的反射率越高对应接收脉冲信号的信号强度通常越强。另外，由于激光雷达所探测的对象多种多样，因此可以将反射接收脉冲信号的对象表面的反射率视为均匀分布。进而可以通过确定在反射接收脉冲信号的对象表面的反射率的概率分布为均匀分布的情况下，峰值点信号强度在峰值点信号强度的取值范围内的概率分布，得到第三概率分布。
另外，还可以利用其他方式确定第三概率分布，例如可以通过对激光雷达进行多次测试，将每次测试得到的接收脉冲信号的峰值点信号强度进行统计，然后根据统计结果确定峰值点信号强度的第三概率分布，对此本申请可以不做限制。
S204、激光雷达确定接收脉冲信号的脉冲宽度的第四概率分布。
例如，可以通过测试激光雷达发出的激光脉冲信号在不同使用场景下得到的接收脉冲信号的脉冲宽度的取值范围以及脉冲宽度在取值范围内的第四概率分布。
在一种可能的设计中，为了便于计算，可以认为脉冲宽度在取值范围内的概率分布为均匀分布。进而可以通过确定在反射接收脉冲信号的对象表面的反射率的概率分布为均匀分布的情况下，峰值点信号强度在峰值点信号强度的取值范围内的概率分布，得到第四概率分布。
例如，以接收脉冲信号的波形满足公式(1)为例，则第四概率分布可以反映为波形参数σ的概率分布p (σ)，表示为：
Figure PCTCN2020103124-appb-000009
其中，σ 1表示脉冲宽度的取值范围的最小值，σ 2表示脉冲宽度的取值范围的最大值。
S205、激光雷达根据第二概率分布、第三概率分布以及第四概率分布，确定预设波形集合中各波形为接收脉冲信号的第五概率分布。
例如，预设波形集合中一种波形(如目标波形)为接收脉冲信号的概率，可以表示为同时满足以下三点的概率：
1)该目标波形的峰值点接收时间为接收脉冲信号的峰值点接收时间；
2)该目标波形的峰值点信号强度为接收脉冲信号的峰值点信号强度；
3)该目标波形的脉冲宽度为接收脉冲信号的脉冲宽度。
也就是说，预设波形集合中一种波形为接收脉冲信号的概率，可以表示为上述三点各自分别发生的概率之积，即p (θ)＝p (t)p (A)p (σ)，其中，p (θ)表示预设波形集合中波形参数A、t、σ为θ的波形为接收脉冲信号的概率。即就是说第五概率分布可以表示为第二概率分布、第三概率分布以及第四概率分布的乘积。
S206、激光雷达根据第一概率分布和第五概率分布，确定接收脉冲信号为预设波形集合中的各波形的第六概率分布。
例如，根据贝叶斯公式可知：第一概率分布可以认为是给定M个上升沿采样点(即M个在接收脉冲信号的波形上分布的采样点)时，接收脉冲信号的波形的概率分布 p (y|θ)，即第一概率分布是关于接收脉冲信号的波形的似然函数L (θ|y)；另外第五概率分布可以认为是接收脉冲信号的波形的先验分布，即p (θ)。那么，在已知L (θ|y)和p (θ)的情况下，便可以利用贝叶斯公式
Figure PCTCN2020103124-appb-000010
计算出接收脉冲信号为预设波形集合中的各波形的第六概率分布P (θ|y)，即接收脉冲信号的波形的后验分布。其中，P (y)可以根据实际需要设定或在计算中可以利用相关算法约去P (y)。
在一种实现方式中，可以利用马尔可夫链蒙特卡洛(Markov Chain Monte Carlo，MCMC)算法来确定第六概率分布，具体的，上述S206可以包括：
根据第一概率分布以及第五概率分布，构建以预设波形集合为状态空间的马尔可夫链，得到马尔可夫链的样本序列{z 1,z 2,...,z m,z m+1,...,z m+n-1,z m+n}。
其中，马尔可夫链的样本序列中各样本分别用于表征一种波形。另外，根据MCMC算法可知，该马尔可夫链的样本序列中样本取值的概率会逐渐向第六概率分布收敛，因此，样本序列{z 1,z 2,...,z m,z m+1,...,z m+n-1,z m+n}中的后n项样本{z m+1,...,z m+n-1,z m+n}用于表征第六概率分布。
在一种可能的设计中，可以利用MCMC算法中的Metropolis-Hastings算法，来构建马尔可夫链。其中，该Metropolis-Hastings算法中的接受分布α(z,z')满足以下公式(6)：
Figure PCTCN2020103124-appb-000011
其中，z为马尔可夫链的样本序列中的一项样本，z'为马尔可夫链的样本序列中z后一项样本，马尔可夫链的样本序列中各样本分别用于表征一种波形，p(y|z')为第一概率分布中波形z'对应的概率，p(y|z)为第一概率分布中波形z对应的概率，p(z')为第五概率分布中波形z'对应的概率，p(z)为第五概率分布中波形z对应的概率，q(z',z)和q(z,z')为马尔可夫链的建议分布。
示例性的，以接收脉冲信号为高斯脉冲，接收脉冲信号的当前信号强度s与当前时间x满足公式(1)：
Figure PCTCN2020103124-appb-000012
为例，对利用Metropolis-Hastings算法构建马尔可夫链的过程进行说明，该过程可以包括以下步骤1-步骤4：
步骤1、随机设置一个初始波形，即马尔可夫链的第一项样本Z 1。
具体的，由于接收脉冲信号满足公式(1)，即可以用一个波形参数θ表示一种波形。因此，初始波形Z 1可以表示为θ 1＝(A 1,t 1,σ 1)。
步骤2、设置Metropolis-Hastings算法的建议分布。
在实际实施过程中，可以参照现有技术中的相关内容设置建议分布。其中，不同建议分布有着不同的收敛速度。对于采用哪种建议分布，本申请可以不做限制。
步骤3、根据建议分布，抽取一个θ 2＝(A 2,t 2,σ 2)。根据接受分布α(z,z')，计算α(θ 1,θ 2)。
步骤4、从区间(0,1)中随机抽取一个数u。若u＜α(θ 1,θ 2)，则确定马尔可夫链的第二项样本Z 2为θ 2；否则，重复步骤3，直至确定出马尔可夫链的第二项样本Z 2。
通过迭代上述步骤3-步骤4，依次确定马尔可夫链的各项样本，进而得到马尔可夫链的样本序列{z 1,z 2,...,z m,z m+1,...,z m+n-1,z m+n}。
S207、根据第六概率分布，从预设波形集合中确定第一预设波形。根据第一预设波形确定接收脉冲信号的峰值点接收时间和峰值点信号强度。
在确定接收脉冲信号为预设波形集合中的各波形的第六概率分布之后，则根据第六概率分布，可以从预设波形集合中确定出可能是接收脉冲信号的波形(即第一预设波形)，例如可以计算第六概率分布的期望得到第一预设波形，或者选择第六概率分布中概率最大的波形作为第一预设波形。然后根据第一预设波形，即可以确定出接收脉冲信号的峰值点接收时间和峰值点信号强度。
在一种可能的设计中，当利用MCMC算法确定第六概率分布的情况下，则第六概率分布，从预设波形集合中确定第一预设波形，可以包括：计算马尔可夫链的样本序列中后n项样本{z m+1,...,z m+n-1,z m+n}的期望，得到第一预设波形。
本实施例所提供信号处理方法，在确定接收脉冲信号的波形的过程中，首先根据采样到的上升沿采样点确定出关于接收脉冲信号的波形的似然函数(即第一概率分布)。然后，根据接收脉冲信号的先验信息，确定出接收脉冲信号的波形的先验分布(即第五概率分布)，其中先验信息包括影响接收脉冲信号波形的各种参数的概率分布，具体包括：接收脉冲信号的峰值点接收时间的概率分布(即第二概率分布)、峰值点信号强度的概率分布(即第三概率分布)以及接收脉冲信号脉冲宽度的概率分布(即第四概率分布)。进而，可以计算出接收脉冲信号的波形的后验分布(即第六概率分布)。然后，根据第六概率分布，可以从预设波形集合中确定出可能是接收脉冲信号的波形(即第一预设波形)。从而根据第一预设波形，即可以确定出接收脉冲信号的峰值点接收时间和峰值点信号强度。通过上述方法，可以更加准确的确定出峰值点信号强度和峰值点接收时间。
以下结合实际仿真结果，对本实施例所提供信号处理方法的有益效果进行介绍：如图7所示，为激光雷达对接收脉冲信号进行采样得到的采样点(图中圆圈所示)以及利用采样点拟合出的接收脉冲信号的波形(图中采样点依次连接得到的波形)。可以看出，图中拟合的接收脉冲信号在虚线圈出的部分存在削顶现象。因此，根据图7所拟合的接收脉冲信号无法准确确定出接收脉冲信号的峰值点信号强度和峰值点接收时间。
然后，分别使用两种方法来拟合接收脉冲信号的波形。第一种，根据多个上升沿采样点，利用最小二乘法拟合出接收脉冲信号的波形，并根据拟合出的波形确定接收脉冲信号的峰值点接收时间和峰值点信号强度。第二种，利用本实施例所提供的信号处理方法，确定接收脉冲信号的波形，并根据拟合出的波形确定接收脉冲信号的峰值点接收时间和峰值点信号强度。其中两种方法所使用的接收脉冲信号的上升沿部分的采样点相同，均为图7中a、b、c和d四个采样点。
在分别利用上述两种方法进行100次蒙特卡洛仿真的过程中，在利用第一种方法拟合接收脉冲信号的波形时，时常出现图8所示的拟合出的接收脉冲信号的波形。可以看出，其中拟合出的接收脉冲信号的波形与接收脉冲信号之间存在较大误差。而图 9为利用本实施例所提供的信号处理方法(即第二种方法)，拟合出的接收脉冲信号的波形。可以看出，其中利用本实施例所提供的信号处理方法的拟合表现良好。
进一步的，下表1为分别利用上述两种方法进行100次蒙特卡洛仿真后，利用仿真结果计算出的ToF的统计结果，表2为分别利用上述两种方法进行100次蒙特卡洛仿真后，利用仿真结果计算出的接收脉冲信号的幅度(即峰值点信号强度)的统计结果。
表1
  ToF的平均偏差 ToF的标准差
第一种方法 27.81 250.59
第二种方法 0.14 0.31
表2
  幅度的平均偏差 幅度的标准差
第一种方法 2.9886e+23 2.9886e+24
第二种方法 0.0046 0.0344
从上表1和表2可以看出，利用本申请所提供方法(即表中第二种方法)的激光雷达可以大幅提高探测结果的准确性。
在另一种实施例中，如图10所示，为本申请实施例提供的一种信号处理装置的组成示意图。该信号处理装置30可以为上述方法实施例中激光雷达的一部分，当该信号处理装置30运行时，可以使激光雷达执行上述实施例中所提供的信号处理方法。例如，在具体实现时，信号处理装置30具体可以是图2所示激光雷达中的信号处理模块108。信号处理装置30还可以为激光雷达中的芯片或片上系统。当然，信号处理装置30也可以应用于其他需要确定接收脉冲信号的峰值点接收时间和峰值点信号强度的设备中，以使得上述设备确定出更加准确的接收脉冲信号。
作为一种实现方式，如图10所示，该信号处理装置30可以包括：采样单元301，用于对接收脉冲信号进行N次采样，得到N个采样点，该N个采样点中的每个采样点的采样参数包括采样点对应的接收时间和信号强度，N个采样点包括M个上升沿采样点以及P个削顶采样点，N、M和P分别为大于或等于1的整数。
第一概率确定单元302，用于确定M个上升沿采样点在预设波形集合中的各波形上分布的第一概率分布；其中，预设波形集合中包括至少一个预设波形。
第二概率确定单元303，用于根据P个削顶采样点确定接收脉冲信号的峰值点接收时间的第二概率分布和峰值点信号强度的第三概率分布。
第二概率确定单元303，还用于确定接收脉冲信号的脉冲宽度的第四概率分布。
第三概率确定单元304，用于根据第二概率分布、第三概率分布以及第四概率分布确定预设波形集合中的各波形为接收脉冲信号的第五概率分布。
第四概率确定单元305，用于根据第一概率分布和第五概率分布，确定接收脉冲信号为预设波形集合中的各波形的第六概率分布。
波形确定单元306，用于根据第六概率分布，从预设波形集合中确定第一预设波形。
参数确定单元307，用于根据第一预设波形确定接收脉冲信号的峰值点接收时间和峰值点信号强度。
在一种可能的设计中，第二概率确定单元303，具体用于：根据P个削顶采样点所对应的接收时间中的最小值，确定峰值点接收时间的取值范围的最小值；根据P个削顶采样点所对应的接收时间中的最大值，确定峰值点接收时间的取值范围的最大值。根据峰值点接收时间的取值范围，确定第二概率分布。根据P个削顶采样点对应的信号强度，确定峰值点信号强度的取值范围的最小值。根据峰值点信号强度的取值范围，确定第三概率分布。
在一种可能的设计中，根据峰值点接收时间的取值范围，确定第二概率分布，包括：确定峰值点接收时间在峰值点接收时间的取值范围内满足均匀分布的情况下，峰值点接收时间的概率分布，得到第二概率分布。
在一种可能的设计中，根据峰值点信号强度的取值范围，确定第三概率分布，包括：确定峰值点信号强度在峰值点信号强度的取值范围内满足均匀分布的情况下，峰值点信号强度的概率分布，得到第三概率分布。
在一种可能的设计中，根据峰值点信号强度的取值范围，确定第三概率分布，包括：确定在反射接收脉冲信号的对象表面的反射率的概率分布为均匀分布的情况下，峰值点信号强度在峰值点信号强度的取值范围内的概率分布，得到第三概率分布。
在一种可能的设计中，第二概率确定单元303，具体用于确定脉冲宽度在脉冲宽度的取值范围内满足均匀分布的情况下，脉冲宽度的概率分布，得到第四概率分布。
在一种可能的设计中，第一概率确定单元302，具体用于：确定M个上升沿采样点中每个采样点在预设波形集合中的各波形上分布的概率分布。根据M个上升沿采样点中每个采样点在预设波形集合中的各波形上分布的概率分布，确定第一概率分布。
在一种可能的设计中，确定M个上升沿采样点中每个采样点在预设波形集合中的各波形上分布的概率分布，包括：根据在采样目标采样点时噪声的强度的概率分布，确定目标采样点在预设波形集合中的各波形上分布的概率分布；其中，目标采样点包括M个上升沿采样点中任一个。
在一种可能的设计中，目标采样点在预设波形集合中的各波形上分布的概率分布，满足以下公式一：
Figure PCTCN2020103124-appb-000013
其中，p k表示目标采样点k在预设波形集合中目标波形上分布的概率，y k表示目标采样点k对应的信号强度，s k表示目标波形在采集目标采样点k时的信号强度。
在一种可能的设计中，第四概率确定单元305，具体用于：根据第一概率分布以及第五概率分布，构建以预设波形集合为状态空间的马尔可夫链，得到马尔可夫链的样本序列{z 1,z 2,...,z m,z m+1,...,z m+n-1,z m+n}；其中，样本序列中各样本分别用于表征一种波形；样本序列{z 1,z 2,...,z m,z m+1,...,z m+n-1,z m+n}中的后n项样本{z m+1,...,z m+n-1,z m+n}用于表征第六概率分布。波形确定单元306，具体用于计算后n项样本{z m+1,...,z m+n-1,z m+n}的期 望，得到第一预设波形。
在一种可能的设计中，根据第一概率分布以及第五概率分布，构建以预设波形集合为状态空间的马尔可夫链，包括：
利用Metropolis-Hastings算法，构建接受分布α(z,z')满足以下公式二的马尔可夫链：
Figure PCTCN2020103124-appb-000014
其中，z为马尔可夫链的样本序列中的一项样本，z'为马尔可夫链的样本序列中z后一项样本，p(y|z')为第一概率分布中z'对应的概率，p(y|z)为第一概率分布中z对应的概率，p(z')为第五概率分布中z'对应的概率，p(z)为第五概率分布中z对应的概率，q(z',z)和q(z,z')为马尔可夫链的建议分布。
在另一种实施例中，如图11所示为另一种数据传输装置的组成示意图。数据传输装置40包括：一个或多个处理器401以及一个或多个存储器402。一个或多个处理器401与一个或多个存储器402耦合，存储器402用于存储计算机执行指令。示例性地，在一些实施例中，当处理器401执行存储器402存储的指令时，使得该数据传输装置40执行如图5所示的S201-S207以及激光雷达需要执行的其他操作。
本申请实施例还提供一种计算机可读存储介质，该计算机可读存储介质中存储有指令，当该指令运行时，执行执行本申请实施例所提供的方法。
本申请实施例还提供一种包含指令的计算机程序产品。当其在计算机上运行时，使得计算机可以执行本申请实施例所提供的方法。
另外，本申请实施例还提供一种芯片。该芯片包括处理器。当处理器执行计算机程序指令时，使得芯片可以执行本申请实施例提供的方法。该指令可以来自芯片内部的存储器，也可以来自芯片外部的存储器。可选的，该芯片还包括作为通信接口的输入输出电路。
在上述实施例中的功能或动作或操作或步骤等，可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件程序实现时，可以全部或部分地以计算机程序产品的形式来实现。该计算机程序产品包括一个或多个计算机指令。在计算机上加载和执行计算机程序指令时，全部或部分地产生按照本申请实施例所述的流程或功能。所述计算机可以是通用计算机、专用计算机、计算机网络、或者其他可编程装置。所述计算机指令可以存储在计算机可读存储介质中，或者从一个计算机可读存储介质向另一个计算机可读存储介质传输，例如，所述计算机指令可以从一个网站站点、计算机、服务器或者数据中心通过有线(例如同轴电缆、光纤、数字用户线(digital subscriber line，DSL))或无线(例如红外、无线、微波等)方式向另一个网站站点、计算机、服务器或数据中心进行传输。所述计算机可读存储介质可以是计算机能够存取的任何可用介质或者是包括一个或多个可以用介质集成的服务器、数据中心等数据存储设备。所述可用介质可以是磁性介质(例如，软盘、硬盘、磁带)，光介质(例如，DVD)、或者半导体介质(例如固态硬盘(solid state disk，SSD))等。
尽管结合具体特征及其实施例对本申请进行了描述，显而易见的，在不脱离本申请的精神和范围的情况下，可对其进行各种修改和组合。相应地，本说明书和附图仅 仅是所附权利要求所界定的本申请的示例性说明，且视为已覆盖本申请范围内的任意和所有修改、变化、组合或等同物。显然，本领域的技术人员可以对本申请进行各种改动和变型而不脱离本申请的精神和范围。这样，倘若本申请的这些修改和变型属于本申请权利要求及其等同技术的范围之内，则本申请也意图包括这些改动和变型在内。

Claims (26)

  1. 一种信号处理方法，其特征在于，包括：
    对接收脉冲信号进行N次采样，得到N个采样点，所述N个采样点中的每个采样点的采样参数包括所述采样点对应的接收时间和信号强度，所述N个采样点包括M个上升沿采样点以及P个削顶采样点，N、M和P分别为大于或等于1的整数；
    确定所述M个上升沿采样点在预设波形集合中的各波形上分布的第一概率分布；其中，所述预设波形集合中包括至少一个预设波形；
    根据所述P个削顶采样点确定所述接收脉冲信号的峰值点接收时间的第二概率分布和峰值点信号强度的第三概率分布；
    确定所述接收脉冲信号的脉冲宽度的第四概率分布；
    根据所述第二概率分布、所述第三概率分布以及所述第四概率分布确定所述预设波形集合中的各波形为所述接收脉冲信号的第五概率分布；
    根据所述第一概率分布和所述第五概率分布，确定所述接收脉冲信号为所述预设波形集合中的各波形的第六概率分布；
    根据所述第六概率分布，从所述预设波形集合中确定第一预设波形；
    根据所述第一预设波形确定所述接收脉冲信号的峰值点接收时间和峰值点信号强度。
  2. 根据权利要求1所述的方法，其特征在于，所述根据所述P个削顶采样点确定所述接收脉冲信号的峰值点接收时间的第二概率分布和峰值点信号强度的第三概率分布，包括：
    根据所述P个削顶采样点所对应的接收时间中的最小值，确定所述峰值点接收时间的取值范围的最小值；根据所述P个削顶采样点所对应的接收时间中的最大值，确定所述峰值点接收时间的取值范围的最大值；
    根据所述峰值点接收时间的取值范围，确定所述第二概率分布；
    根据所述P个削顶采样点对应的信号强度，确定所述峰值点信号强度的取值范围的最小值；
    根据所述峰值点信号强度的取值范围，确定所述第三概率分布。
  3. 根据权利要求2所述的方法，其特征在于，所述根据所述峰值点接收时间的取值范围，确定所述第二概率分布，包括：
    确定所述峰值点接收时间在所述峰值点接收时间的取值范围内满足均匀分布的情况下，所述峰值点接收时间的概率分布，得到所述第二概率分布。
  4. 根据权利要求2或3所述的方法，其特征在于，所述根据所述峰值点信号强度的取值范围，确定所述第三概率分布，包括：
    确定所述峰值点信号强度在所述峰值点信号强度的取值范围内满足均匀分布的情况下，所述峰值点信号强度的概率分布，得到所述第三概率分布。
  5. 根据权利要求2或3所述的方法，其特征在于，所述根据所述峰值点信号强度的取值范围，确定所述第三概率分布，包括：
    确定在反射所述接收脉冲信号的对象表面的反射率的概率分布为均匀分布的情况下，所述峰值点信号强度在所述峰值点信号强度的取值范围内的概率分布，得到所述 第三概率分布。
  6. 根据权利要求1-5任一项所述的方法，其特征在于，所述接收脉冲信号的脉冲宽度的第四概率分布，包括：
    确定所述脉冲宽度在所述脉冲宽度的取值范围内满足均匀分布的情况下，所述脉冲宽度的概率分布，得到所述第四概率分布。
  7. 根据权利要求1-6任一项所述的方法，其特征在于，所述确定所述M个上升沿采样点在预设波形集合中的各波形上分布的第一概率分布，包括：
    确定所述M个上升沿采样点中每个采样点在所述预设波形集合中的各波形上分布的概率分布；
    根据所述M个上升沿采样点中每个采样点在所述预设波形集合中的各波形上分布的概率分布，确定所述第一概率分布。
  8. 根据权利要求7所述的方法，其特征在于，所述确定所述M个上升沿采样点中每个采样点在所述预设波形集合中的各波形上分布的概率分布，包括：
    根据在采样目标采样点时噪声的强度的概率分布，确定所述目标采样点在所述预设波形集合中的各波形上分布的概率分布；其中，所述目标采样点包括所述M个上升沿采样点中任一个。
  9. 根据权利要求8所述的方法，其特征在于，所述目标采样点在所述预设波形集合中的各波形上分布的概率分布，满足以下公式一：
    Figure PCTCN2020103124-appb-100001
    其中，p k表示所述目标采样点k在所述预设波形集合中目标波形上分布的概率，y k表示所述目标采样点k对应的信号强度，s k表示所述目标波形在采集所述目标采样点k时的信号强度。
  10. 根据权利要求1-9任一项所述的方法，其特征在于，所述根据所述第一概率分布和所述第五概率分布，确定所述接收脉冲信号为所述预设波形集合中的各波形的第六概率分布，包括：
    根据所述第一概率分布以及所述第五概率分布，构建以所述预设波形集合为状态空间的马尔可夫链，得到所述马尔可夫链的样本序列{z 1,z 2,...,z m,z m+1,...,z m+n-1,z m+n}；其中，所述样本序列中各样本分别用于表征一种波形；所述样本序列{z 1,z 2,...,z m,z m+1,...,z m+n-1,z m+n}中的后n项样本{z m+1,...,z m+n-1,z m+n}用于表征所述第六概率分布；
    所述根据所述第六概率分布，从所述预设波形集合中确定第一预设波形，包括：
    计算所述后n项样本{z m+1,...,z m+n-1,z m+n}的期望，得到所述第一预设波形。
  11. 根据权利要求10所述的方法，其特征在于，所述根据所述第一概率分布以及所述第五概率分布，构建以所述预设波形集合为状态空间的马尔可夫链，包括：
    利用Metropolis-Hastings算法，构建接受分布α(z,z')满足以下公式二的马尔可夫链：
    Figure PCTCN2020103124-appb-100002
    其中，z为所述马尔可夫链的样本序列中的一项样本，z'为所述马尔可夫链的样本序列中z后一项样本，p(y|z')为所述第一概率分布中z'对应的概率，p(y|z)为所述第一概率分布中z对应的概率，p(z')为所述第五概率分布中z'对应的概率，p(z)为所述第五概率分布中z对应的概率，q(z',z)和q(z,z')为所述马尔可夫链的建议分布。
  12. 一种信号处理装置，其特征在于，包括：
    采样单元，用于对接收脉冲信号进行N次采样，得到N个采样点，所述N个采样点中的每个采样点的采样参数包括所述采样点对应的接收时间和信号强度，所述N个采样点包括M个上升沿采样点以及P个削顶采样点，N、M和P分别为大于或等于1的整数；
    第一概率确定单元，用于确定所述M个上升沿采样点在预设波形集合中的各波形上分布的第一概率分布；其中，所述预设波形集合中包括至少一个预设波形；
    第二概率确定单元，用于根据所述P个削顶采样点确定所述接收脉冲信号的峰值点接收时间的第二概率分布和峰值点信号强度的第三概率分布；
    所述第二概率确定单元，还用于确定所述接收脉冲信号的脉冲宽度的第四概率分布；
    第三概率确定单元，用于根据所述第二概率分布、所述第三概率分布以及所述第四概率分布确定所述预设波形集合中的各波形为所述接收脉冲信号的第五概率分布；
    第四概率确定单元，用于根据所述第一概率分布和所述第五概率分布，确定所述接收脉冲信号为所述预设波形集合中的各波形的第六概率分布；
    波形确定单元，用于根据所述第六概率分布，从所述预设波形集合中确定第一预设波形；
    参数确定单元，用于根据所述第一预设波形确定所述接收脉冲信号的峰值点接收时间和峰值点信号强度。
  13. 根据权利要求12所述的装置，其特征在于，所述第二概率确定单元，具体用于：
    根据所述P个削顶采样点所对应的接收时间中的最小值，确定所述峰值点接收时间的取值范围的最小值；根据所述P个削顶采样点所对应的接收时间中的最大值，确定所述峰值点接收时间的取值范围的最大值；
    根据所述峰值点接收时间的取值范围，确定所述第二概率分布；
    根据所述P个削顶采样点对应的信号强度，确定所述峰值点信号强度的取值范围的最小值；
    根据所述峰值点信号强度的取值范围，确定所述第三概率分布。
  14. 根据权利要求13所述的装置，其特征在于，所述根据所述峰值点接收时间的取值范围，确定所述第二概率分布，包括：确定所述峰值点接收时间在所述峰值点接收时间的取值范围内满足均匀分布的情况下，所述峰值点接收时间的概率分布，得到所述第二概率分布。
  15. 根据权利要求13或14所述的装置，其特征在于，所述根据所述峰值点信号 强度的取值范围，确定所述第三概率分布，包括：确定所述峰值点信号强度在所述峰值点信号强度的取值范围内满足均匀分布的情况下，所述峰值点信号强度的概率分布，得到所述第三概率分布。
  16. 根据权利要求13或14所述的装置，其特征在于，所述根据所述峰值点信号强度的取值范围，确定所述第三概率分布，包括：确定在反射所述接收脉冲信号的对象表面的反射率的概率分布为均匀分布的情况下，所述峰值点信号强度在所述峰值点信号强度的取值范围内的概率分布，得到所述第三概率分布。
  17. 根据权利要求12-16任一项所述的装置，其特征在于，所述第二概率确定单元，具体用于确定所述脉冲宽度在所述脉冲宽度的取值范围内满足均匀分布的情况下，所述脉冲宽度的概率分布，得到所述第四概率分布。
  18. 根据权利要求12-17任一项所述的装置，其特征在于，所述第一概率确定单元，具体用于：
    确定所述M个上升沿采样点中每个采样点在所述预设波形集合中的各波形上分布的概率分布；
    根据所述M个上升沿采样点中每个采样点在所述预设波形集合中的各波形上分布的概率分布，确定所述第一概率分布。
  19. 根据权利要求18所述的装置，其特征在于，所述确定所述M个上升沿采样点中每个采样点在所述预设波形集合中的各波形上分布的概率分布，包括：
    根据在采样目标采样点时噪声的强度的概率分布，确定所述目标采样点在所述预设波形集合中的各波形上分布的概率分布；其中，所述目标采样点包括所述M个上升沿采样点中任一个。
  20. 根据权利要求19所述的装置，其特征在于，所述目标采样点在所述预设波形集合中的各波形上分布的概率分布，满足以下公式一：
    Figure PCTCN2020103124-appb-100003
    其中，p k表示所述目标采样点k在所述预设波形集合中目标波形上分布的概率，y k表示所述目标采样点k对应的信号强度，s k表示所述目标波形在采集所述目标采样点k时的信号强度。
  21. 根据权利要求12-20任一项所述的装置，其特征在于，所述第四概率确定单元，具体用于根据所述第一概率分布以及所述第五概率分布，构建以所述预设波形集合为状态空间的马尔可夫链，得到所述马尔可夫链的样本序列{z 1,z 2,...,z m,z m+1,...,z m+n-1,z m+n}；其中，所述样本序列中各样本分别用于表征一种波形；所述样本序列{z 1,z 2,...,z m,z m+1,...,z m+n-1,z m+n}中的后n项样本{z m+1,...,z m+n-1,z m+n}用于表征所述第六概率分布；
    所述波形确定单元，具体用于计算所述后n项样本{z m+1,...,z m+n-1,z m+n}的期望，得到所述第一预设波形。
  22. 根据权利要求21所述的装置，其特征在于，所述根据所述第一概率分布以及所述第五概率分布，构建以所述预设波形集合为状态空间的马尔可夫链，包括：
    利用Metropolis-Hastings算法，构建接受分布α(z,z')满足以下公式二的马尔可夫 链：
    Figure PCTCN2020103124-appb-100004
    其中，z为所述马尔可夫链的样本序列中的一项样本，z'为所述马尔可夫链的样本序列中z后一项样本，p(y|z')为所述第一概率分布中z'对应的概率，p(y|z)为所述第一概率分布中z对应的概率，p(z')为所述第五概率分布中z'对应的概率，p(z)为所述第五概率分布中z对应的概率，q(z',z)和q(z,z')为所述马尔可夫链的建议分布。
  23. 一种信号处理装置，其特征在于，所述信号处理装置包括一个或多个处理器，所述一个或多个处理器和一个或多个存储器耦合；所述一个或多个存储器存储有计算机指令；
    当所述一个或多个处理器执行所述计算机指令时，使得所述信号处理装置执行如权利要求1-11中任一项所提供的信号处理方法。
  24. 一种芯片，其特征在于，所述芯片包括处理电路和接口；所述处理电路用于从存储介质中调用并运行所述存储介质中存储的计算机程序，以执行如权利要求1-11中任一项所提供的信号处理方法。
  25. 一种激光雷达，其特征在于，所述激光雷达包括权利要求12-23任一项所提供的信号处理装置，或者，所述激光雷达包括权利要求24所提供的芯片。
  26. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质中存储有指令；当所述指令运行时，执行上述权利要求1-11任一项所提供的信号处理方法。
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