Signal processing method and device of laser ranging system, equipment and storage medium

Abstract

The invention provides a signal processing method and device of a laser ranging system, equipment and a storage medium, relates to the technical field of laser detection, and aims to solve the problem of low precision when laser ranging is performed on a long-distance moving target. The method comprises the following steps: collecting multiple groups of original signals of a target, and carrying out matched filtering on each group of original signals to obtain multiple groups of echo signals; performing accumulation processing on the multiple groups of echo signals to obtain an initial accumulation signal; a motion error compensation method is adopted to calibrate the time axis of the initial accumulation signal to obtain a target accumulation signal, and the motion error compensation method at least comprises time offset error detection and loop filtering; a distance parameter and a radial velocity of the target are calculated based on the target cumulative signal.

Description

Technical Field

[0001] This invention relates to the field of laser detection technology, and in particular to a signal processing method, apparatus, device, and storage medium for a laser ranging system. Background Technology

[0002] In fields such as industrial inspection and autonomous driving, the technology of calculating distance by measuring the round-trip time of a laser pulse between a ranging system and a target is widely used.

[0003] Currently, in long-range ranging scenarios, the signal-to-noise ratio (SNR) drops sharply because the echo signal energy decreases with the square of the distance. A common approach is to accumulate multiple echo signals with high repetition frequencies to improve the SNR and detect weak, effective signals. However, existing signal accumulation techniques have significant drawbacks when dealing with moving targets. When the target exhibits radial motion, the continuous laser echo pulses experience a linear shift in time, leading to pulse broadening and peak attenuation in the directly accumulated signal, ultimately reducing the accuracy of the final ranging result.

[0004] Therefore, there is an urgent need for a laser ranging solution that can accurately measure distant, moving targets to meet the real-time and accurate ranging requirements in highly dynamic scenarios. Summary of the Invention

[0005] This invention provides a signal processing method, apparatus, device, and storage medium for a laser ranging system, which solves the problem of low accuracy in laser ranging of distant, moving targets in the prior art, and realizes accurate measurement of distant moving targets.

[0006] This invention provides a signal processing method for a laser ranging system, comprising the following steps: acquiring multiple sets of raw signals from the target; performing matched filtering on each set of raw signals to obtain multiple sets of echo signals; accumulating the multiple sets of echo signals to obtain an initial accumulated signal; calibrating the time axis of the initial accumulated signal using a motion error compensation method to obtain a target accumulated signal, wherein the motion error compensation method includes at least time offset error detection and loop filtering; and calculating the target's distance parameters and radial velocity based on the target accumulated signal.

[0007] According to the signal processing method of a laser ranging system provided by the present invention, the above-mentioned matched filtering of each group of original signals to obtain multiple groups of echo signals includes: constructing a filtering function using a Gaussian pulse as a template signal; retaining frequency components in the original signal that are consistent with the signal spectrum characteristics of the Gaussian pulse through the filtering function to obtain a preliminary screening signal; suppressing out-of-band high-frequency noise and background light interference in the preliminary screening signal to obtain an echo signal, wherein the out-of-band high-frequency noise is a high-frequency interference signal whose frequency exceeds the inherent spectrum range of the Gaussian pulse signal.

[0008] According to the signal processing method of a laser ranging system provided by the present invention, the above-mentioned accumulation processing of multiple sets of echo signals to obtain an initial accumulated signal includes: sequentially superimposing multiple sets of echo signals according to the acquisition time sequence of each set of echo signals to obtain an initial accumulated signal, wherein the signal-to-noise ratio of the initial accumulated signal is higher than that of the echo signals.

[0009] According to a signal processing method for a laser ranging system provided by the present invention, the above-mentioned method of calibrating the time axis of the initial accumulated signal using a motion error compensation method to obtain the target accumulated signal includes: determining the half-pulse width and noise energy of the initial accumulated signal through time offset error detection, so as to calculate the time offset error of the initial accumulated signal, wherein the half-pulse width is the time width corresponding to when the pulse amplitude reaches half of its maximum value; performing iterative calculation on the time offset error through loop filtering to output the motion error compensation amount; and calibrating the time axis of the initial accumulated signal according to the motion error compensation amount to obtain the target accumulated signal.

[0010] According to a signal processing method for a laser ranging system provided by the present invention, the distance parameters include average distance. The method for calculating the distance parameters and radial velocity of the target based on the target accumulated signal includes: performing peak detection on the target accumulated signal and determining the peak time; calculating the average distance of the target based on the peak time and the speed of light; and calculating the radial velocity of the target based on the motion error compensation amount and the laser pulse repetition frequency.

[0011] According to the signal processing method of the laser ranging system provided by the present invention, the distance parameter further includes transient distance, and the method further includes: obtaining the cumulative period corresponding to the calculation of the average distance; and combining the average distance, radial velocity and cumulative period to calculate the transient distance of the target at the end of the cumulative period.

[0012] The present invention also provides a signal processing device for a laser ranging system, comprising the following modules: an acquisition module for acquiring multiple sets of raw signals from a target, performing matched filtering on each set of raw signals to obtain multiple sets of echo signals; an overlay module for accumulating the multiple sets of echo signals to obtain an initial accumulated signal; a calibration module for calibrating the time axis of the initial accumulated signal using a motion error compensation method to obtain a target accumulated signal, wherein the motion error compensation method includes at least time offset error detection and loop filtering; and a calculation module for calculating the target's distance parameters and radial velocity based on the target accumulated signal.

[0013] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the signal processing method of the laser ranging system as described above.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the signal processing method of the laser ranging system as described above.

[0015] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the signal processing method of the laser ranging system as described above.

[0016] The signal processing method, apparatus, device, and storage medium of the laser ranging system provided by this invention effectively improve the detection performance of the laser ranging system for distant moving targets by sequentially executing signal acquisition and filtering, signal accumulation, motion error compensation, and parameter calculation steps. First, by performing matched filtering on multiple sets of raw signals, noise is effectively suppressed and signal peaks are enhanced before accumulation, providing a high-quality signal foundation for subsequent processing. Next, the accumulation processing of multiple sets of echo signals significantly improves the overall signal-to-noise ratio. Then, by employing a motion error compensation method that includes time offset error detection and loop filtering, the time axis of the accumulated signal is dynamically calibrated, effectively overcoming the signal mismatch problem caused by the radial movement of the target and accurately restoring the peak value of the accumulated signal. Finally, based on this calibrated high-quality accumulated signal, the distance parameters and radial velocity of the target are calculated, improving the accuracy of laser ranging of distant, moving targets. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a schematic flowchart of the signal processing method for the laser ranging system provided by the present invention.

[0019] Figure 2 This is a schematic diagram of the waveform after the echo signal is accumulated, as provided by the present invention.

[0020] Figure 3 This is a schematic diagram of the motion error compensation algorithm flow provided by the present invention.

[0021] Figure 4 This is a schematic diagram of the signal processing device of the laser ranging system provided by the present invention.

[0022] Figure 5 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0024] The following is combined Figures 1 to 3 The signal processing method of the laser ranging system of the present invention is described.

[0025] Figure 1 This is a flowchart illustrating the signal processing method of the laser ranging system provided by the present invention, as shown below. Figure 1 As shown, the method includes the following: S101. Collect multiple sets of raw signals from the target, perform matched filtering on each set of raw signals, and obtain multiple sets of echo signals.

[0026] Optionally, a filtering function can be constructed first using a Gaussian pulse as a template signal.

[0027] For example, the constructed filtering function is equivalent to a bandwidth-limited filter in the frequency domain, and its transfer function matches the spectral characteristics of a Gaussian pulse. In practical applications, this filtering function can be implemented using a digital signal processor (DSP) or a field-programmable gate array (FPGA).

[0028] Specifically, in laser ranging systems that employ direct-time-of-flight (dToF) ranging, Gaussian pulses are often used as the transmitted signal, and the received echo signal can be approximated as a Gaussian pulse signal, with its waveform approximately following a Gaussian distribution f~N(width / 2,σ²).

[0029] Where width is the full width at half maximum (FWHM), which represents the time width when the pulse amplitude reaches half of its maximum value; σ is the pulse standard deviation, which characterizes the time broadening characteristics of the pulse waveform.

[0030] In some embodiments, a filtering function can be used to retain frequency components in the original signal that are consistent with the signal spectrum characteristics of a Gaussian pulse, thus obtaining a preliminary filtered signal.

[0031] For example, the matched filter retains only frequency components consistent with the signal spectrum characteristics, thereby effectively suppressing high-frequency noise outside the bandwidth and background light interference. Specifically, the time-domain expression of the echo signal can be represented as: .

[0032] in, τ is the signal peak value, representing the maximum amplitude of the echo pulse, which is related to the target reflectivity and transmission distance; τ is the pulse center time, corresponding to the arrival time and position of the echo pulse; W is Gaussian white noise, satisfying the distribution... , σ noise ² represents the noise variance, which characterizes the power level of the noise.

[0033] In this embodiment of the application, to characterize the quality of the echo signal, the receiver signal-to-noise ratio (SNR) can be defined as the signal peak value S. peak The ratio of the noise to the root mean square (RMS) of the noise: .

[0034] Where SNR is the signal-to-noise ratio, S peak The peak value is the signal peak value, and RMS (noise) is the root mean square (RMS) of the noise.

[0035] In the embodiments of this application, the improvement effect of signal-to-noise ratio can be characterized by the available signal-to-noise improvement ratio (SNIR), which is defined as the processed signal-to-noise ratio (SNR). i The difference between the original signal-to-noise ratio (SNR) and the original signal-to-noise ratio (SNR): .

[0036] Where SNIR is the signal-to-noise ratio, and SNR is the signal-to-noise ratio. i SNR is the cumulative signal-to-noise ratio, while SNR is the original signal-to-noise ratio.

[0037] In practical systems, Typical values ​​are in the microvolt range, while the noise standard deviation σ noise It may reach 10%-50% of the signal amplitude.

[0038] Furthermore, out-of-band high-frequency noise and background light interference in the initial screening signal can be suppressed to obtain the echo signal.

[0039] In the embodiments of this application, out-of-band high-frequency noise is a high-frequency interference signal whose frequency exceeds the inherent spectral range of the Gaussian pulse.

[0040] For example, background light noise mainly includes ambient light interference such as solar radiation, and its spectral range is typically wider than the signal spectrum. In practical applications, background light noise can be further suppressed by combining optical bandpass filters with electrical filtering.

[0041] In the embodiments of this application, the optical filter is usually a narrowband filter that matches the laser wavelength, with a bandwidth of 1-2 nm; the electrical filter is a low-pass filter that matches the signal bandwidth, with a cutoff frequency that is usually 1.5-2 times the signal bandwidth.

[0042] Thus, by constructing a filtering function using Gaussian pulses as templates, this application can retain the effective spectral components of the signal to the maximum extent and specifically suppress out-of-band interference, thereby improving signal quality in the initial processing stage.

[0043] S102. Accumulate and process multiple sets of echo signals to obtain the initial accumulated signal.

[0044] In some embodiments, multiple sets of echo signals can be superimposed sequentially according to the acquisition time order of each set of echo signals to obtain an initial accumulated signal.

[0045] The signal-to-noise ratio (SNR) of the initial accumulated signal is higher than that of the echo signal.

[0046] For example, assuming the same target signal is sampled and accumulated n times independently, the accumulated time-domain signal can be expressed as: .

[0047] Where n is the cumulative number of times, usually between 100 and 10000; W i Let be the noise component at the i-th sampling. Accumulation processing can be performed directly in the time domain or through coherent accumulation in the frequency domain.

[0048] Specifically, during multiple accumulation processes, the superimposed Gaussian white noise W as a whole satisfies the independent and identically distributed characteristics, and the accumulated noise term satisfies... Therefore, the signal-to-noise ratio of the echo signal after accumulation processing can be obtained: SNR i : .

[0049] Among them, SNR i Let SNR be the accumulated signal-to-noise ratio, n be the number of accumulations, and SNR be the original signal-to-noise ratio. The improvement in signal-to-noise ratio is: .

[0050] In practical systems, the selection of the number of accumulation iterations requires a trade-off between improving the signal-to-noise ratio (SNR) and ensuring real-time measurement performance. The choice of iterations needs to be optimized based on the system's noise characteristics and signal features. Too many iterations, while improving the SNR, will increase the system's response time; too few iterations may not achieve the desired SNR improvement.

[0051] like Figure 2 The figure shows the waveform of the echo signal after 1000 accumulations with different motion errors. The horizontal axis represents time (nanoseconds, ns), and the vertical axis represents amplitude (least significant bit, LSB).

[0052] For example, when the number of accumulations n=1000, as the motion error (ME) increases, the peak value of the accumulated signal gradually decreases and the pulse width increases.

[0053] Specifically, motion error ME is defined as the total time offset over the accumulated time period. Where Δt is the time offset caused by target motion within a single pulse period. When ME exceeds 1 / 10 of the pulse width, the peak value of the accumulated signal will drop by more than 3dB, severely affecting ranging accuracy.

[0054] In this embodiment, when the target observed by the ranging system is in motion, it has a radial velocity component v relative to the system. This relative motion causes a time delay shift in the received signal. The round-trip time shift Δt can be expressed as: .

[0055] Where Δt is the time offset of a single pulse, v is the radial velocity of the target, PRF is the pulse repetition frequency, and c is the speed of light.

[0056] Specifically, if the system samples and accumulates the echo from the same target n times, then when the target moves away from the system, the accumulated signal can be expressed as: .

[0057] Among them, S r (t) represents the accumulated signal as the target moves away, where i is the sampling index and S is the cumulative signal. peak Let τ be the peak value of the signal, τ be the pulse center time, Δt be the time offset of a single pulse, σ be the pulse standard deviation, and W be the signal peak value. i Let be the noise from the i-th sample.

[0058] At this point, let α = t - τ, x = i, and denote... According to the Euler-Maclaurin formula, the above discrete accumulation process can be approximated as continuous: .

[0059] Where g(x) is the intermediate function, k is the cumulative index, n is the cumulative degree, and g'(x) is the derivative of g(x). The first integral term can be transformed into the Gaussian error function erf: .

[0060] Where erf is the Gaussian error function, π is pi, σ is the pulse standard deviation, α is the intermediate variable t-τ, and Δt is the time offset of a single pulse.

[0061] Furthermore, substituting the above results into the equation yields S. r An approximate expression for (t): .

[0062] Among them, S r (t) is an approximate expression for the accumulated signal as the target moves away, S peak Let σ be the signal peak value, π be the pulse standard deviation, π be the mathematical constant pi, erf be the Gaussian error function, τ be the pulse center time, Δt be the time offset of a single pulse, n be the cumulative count, t be the time variable, and W be the signal peak value. i Let be the noise from the i-th sample.

[0063] Similarly, when the target moves in the opposite direction to the ranging system (i.e., the target moves closer to the system), the time-domain expression of the accumulated signal can be written as: .

[0064] Among them, S l (t) represents the accumulated signal as the target approaches, where i is the sampling index, and S... peak Let τ be the peak value of the signal, τ be the pulse center time, Δt be the time offset of a single pulse, σ be the pulse standard deviation, and W be the signal peak value. i Let be the noise from the i-th sample. Its approximate expression is: .

[0065] Among them, S l (t) is an approximate expression for the accumulated signal when the target approaches, S peak Let σ be the signal peak value, π be the pulse standard deviation, π be the mathematical constant pi, erf be the Gaussian error function, τ be the pulse center time, Δt be the time offset of a single pulse, n be the cumulative count, t be the time variable, and W be the signal peak value. i Let be the noise from the i-th sample.

[0066] Thus, by superimposing multiple sets of echo signals in chronological order, this application enhances the signal components due to coherence and suppresses noise due to randomness, thereby effectively improving the signal-to-noise ratio without changing the essential waveform of the signal and enhancing the detection capability of weak signals.

[0067] S103. The time axis of the initial accumulated signal is calibrated using a motion error compensation method to obtain the target accumulated signal.

[0068] In the embodiments of this application, the motion error compensation method includes at least time offset error detection and loop filtering.

[0069] In some embodiments, the half-pulse width and noise energy of the initial accumulated signal can be determined first by detecting the time offset error, so as to calculate the time offset error of the initial accumulated signal.

[0070] Half pulse width is the time width corresponding to when the pulse amplitude reaches half of its maximum value.

[0071] For example, the relationship between half pulse width (FWHM) and the standard deviation σ of the Gaussian distribution is as follows: .

[0072] In actual calculations, the peak value of the accumulated signal can be detected to find the time point corresponding to half of the peak value, and then the difference between the two time points can be calculated to obtain the half pulse width.

[0073] For example, noise energy E noise The noise variance can be obtained by statistically analyzing the non-peak regions of the signal. Typically, signal segments that are far from the peak value are selected to calculate the noise variance.

[0074] Specifically, a Gardner-like error signal can be constructed. .

[0075] Where T is the equivalent sampling period, and T is the half-pulse width of the echo signal; T half E is the half-pulse width of the accumulated signal. noise denoted as the accumulated noise energy of the signal; k represents the number of iterations in the system calculation.

[0076] In the embodiments of this application, the sign of the error signal e(k) is consistent with the time offset direction, and its mean amplitude is approximately linearly related to the motion error amount ME.

[0077] In some embodiments, the time offset error can be iteratively calculated using loop filtering to output the motion error compensation amount.

[0078] For example, the loop filter employs a proportional-integral (PI) control mechanism, and the update equation is: .

[0079] Where C1 and C2 are the proportional and integral coefficients of the filter, respectively, and MÊ(k) represents the system motion error compensation amount in the k-th iteration. The proportional coefficient C1 mainly affects the system's response speed, while the integral coefficient C2 affects the system's steady-state accuracy. Typically, C1 takes a value of 0.1-0.3, and C2 takes a value of 0.01-0.05.

[0080] Specifically, after several iterations, the motion error compensation amount MÊ will gradually converge to the actual motion error value ME, realizing dynamic error tracking and self-correction. The speed and stability of the convergence process are important indicators for evaluating the performance of the compensation algorithm.

[0081] In practical applications, it is necessary to set appropriate convergence conditions, such as considering convergence as when the error change in several consecutive iterations is less than a certain threshold. At the same time, it is also necessary to design anti-divergence mechanisms to prevent system instability under certain abnormal conditions.

[0082] Furthermore, the initial cumulative signal is calibrated along the time axis based on the motion error compensation amount to obtain the target cumulative signal.

[0083] For example, the compensated cumulative signal can be expressed as: .

[0084] in, =MÊ / n. Time axis calibration can be achieved using digital interpolation algorithms, such as linear interpolation, cubic spline interpolation, or sinc interpolation.

[0085] For example, linear interpolation can be used for applications with high real-time requirements, while sinc interpolation can be used for applications with high accuracy requirements.

[0086] Specifically, when the motion error compensation amount hour, The accumulated signal regains optimal coherence, and the signal peak value recovers to the theoretical maximum value.

[0087] In this embodiment, peak recovery can be defined as the ratio of the compensated signal peak value to the theoretical maximum peak value, typically reaching over 95%. In a practical system, the compensation effect can be judged by monitoring peak value changes, and iteration stops when the peak recovery reaches a preset threshold (e.g., 90%).

[0088] Thus, this application calculates the time offset error by combining half-pulse width and noise energy, making the error estimation more accurate and reliable; then, the compensation amount is generated through loop filtering iteration, ensuring the stability and convergence of the time axis calibration.

[0089] S104. Based on the target's accumulated signal, calculate the target's range parameters and radial velocity.

[0090] In this embodiment of the application, the distance parameter may include the average distance.

[0091] In some embodiments, peak detection can be performed on the accumulated signal of the target to determine the peak time, and the average distance of the target can be calculated based on the peak time and the speed of light.

[0092] For example, based on the principle of time-of-flight ranging, the average distance of the target .

[0093] Where c is the speed of light; t peak The peak occurrence time is obtained by finding the location of the maximum value of the accumulated signal after compensation; The reference time for the system to emit laser pulses is usually set to zero or the system's time base.

[0094] Specifically, under long-range ranging conditions, the ranging value R obtained by the system after accumulating the target n times. m This corresponds to the average distance of the target over the accumulated time. This characteristic requires that the target's motion state be fully considered during system design. For targets moving at a constant speed, the average distance can reflect the target's actual position well; however, for targets moving at an accelerated speed, a more complex motion model needs to be considered.

[0095] In some embodiments, the radial velocity of the target can be calculated based on the motion error compensation amount and the laser pulse repetition frequency.

[0096] For example, the radial velocity component is: .

[0097] PRF stands for laser pulse repetition frequency, which is typically in the range of 10kHz-1MHz. is the motion error compensation amount after convergence; n is the cumulative number of iterations.

[0098] Specifically, assuming the target's motion is approximately uniform during the accumulation period, the actual distance of the target at the end of the accumulation period (i.e., the transient distance) is as follows: .

[0099] Where v is the radial velocity, n is the cumulative number of times, PRF is the pulse repetition frequency, and R... m This represents the average distance.

[0100] Thus, this application calculates the average distance based on the peak time of the calibrated signal and uses the converged motion error compensation to back-calculate the radial velocity, so that the final output distance and velocity parameters are derived from the aligned and enhanced high-quality signal, ensuring the reliability of the calculation results.

[0101] In the signal processing method of the laser ranging system provided in this application embodiment, the detection performance of the laser ranging system for distant moving targets is effectively improved by sequentially executing signal acquisition and filtering, signal accumulation, motion error compensation, and parameter calculation steps. First, by performing matched filtering on multiple sets of raw signals, noise can be effectively suppressed and signal peaks enhanced before accumulation, providing a high-quality signal foundation for subsequent processing. Next, multiple sets of echo signals are accumulated, significantly improving the overall signal-to-noise ratio. Then, by employing a motion error compensation method that includes time offset error detection and loop filtering, the time axis of the accumulated signal is dynamically calibrated, effectively overcoming the signal mismatch problem caused by the radial movement of the target, and accurately restoring the peak value of the accumulated signal. Finally, the distance parameters and radial velocity of the target are calculated based on this calibrated high-quality accumulated signal, improving the accuracy of laser ranging of distant, moving targets.

[0102] Optionally, the distance parameters mentioned above may also include transient distance.

[0103] In some embodiments, the cumulative period corresponding to the calculation of the average distance can also be obtained, and the transient distance of the target at the end of the cumulative period can be calculated by combining the average distance, radial velocity and cumulative period.

[0104] For example, the formula for calculating the transient distance R can refer to the formula for calculating the actual distance value at the end of the accumulation period in S104 above. The transient distance reflects the true position of the target at the end of the accumulation period.

[0105] Specifically, by combining motion error compensation amount It can accurately calculate the real-time position of the target at the end of the accumulation period, enabling precise tracking of the trajectory of the moving target. The accuracy of transient distance measurement depends on the combined effect of velocity measurement accuracy and time measurement accuracy.

[0106] Thus, by combining the average distance, radial velocity, and cumulative period to calculate the transient distance, the precise real-time position of the target at the end of the measurement period can be calculated, achieving instantaneous capture of the trajectory of the moving target.

[0107] Optionally, the motion error compensation method in S103 above can be a motion error compensation algorithm based on a Gardner-like ring structure. This Gardner-like ring structure includes at least a time offset error detector and a loop filter.

[0108] The following explains the process of motion error compensation for Gardner-like ring structures.

[0109] For example, such as Figure 3 As shown, the motion error compensation process may include the following: S301, echo signal.

[0110] For example, the received echo signal sequence S(t) is processed by matched filtering and contains a time offset caused by the target motion. The signal sequence is digitized at a sampling frequency, typically 5-10 times the pulse width, to ensure sufficient timing resolution.

[0111] For example, for a pulse with a pulse width of 10ns, the sampling frequency should reach 500MHz-1GHz.

[0112] S302, Matched Filtering.

[0113] For example, a matched filter function is constructed using a Gaussian pulse as a reference template to suppress out-of-band noise and enhance the detection capability of signal peaks. The design of the matched filter is based on the maximum signal-to-noise ratio criterion, and its impulse response is h(t) = s(Tt), where s(t) is the Gaussian pulse template and T is the pulse duration.

[0114] In practical digital implementation, it can be achieved using a finite impulse response (FIR) filter.

[0115] S303, including motion error signal accumulation.

[0116] For example, multiple sets of matched-filtered echo signals can be accumulated in chronological order. When a motion error ME exists, the signal center will shift by Δt, resulting in accumulated error.

[0117] In practical systems, a segmented accumulation strategy can be adopted, where the signal is first divided into several segments for preliminary accumulation, and then the accumulation results of each segment are time-aligned and finally accumulated to reduce the impact of motion errors.

[0118] S304, Error Detection.

[0119] For example, the time offset error e(k) of the current accumulated signal is calculated by a time offset error detector.

[0120] Specifically, the error detector detects time shifts by comparing the energy difference between the first and second half-cycles, based on the symmetry of the signal waveform.

[0121] S305, Calculate the time offset error.

[0122] For example, based on the half-pulse width of the accumulated signal and the noise energy, according to the formula Calculate the time offset error. In practical calculations, integration can be achieved using numerical integration methods, such as the rectangular method or the trapezoidal method.

[0123] S306, Extract motion error.

[0124] For example, the time offset error e(k) is input into the loop filter, and the estimated motion error compensation amount is obtained by iterative calculation. .

[0125] Specifically, the loop filter employs a second-order phase-locked loop structure, including a proportional path and an integral path, used to improve tracking speed and ensure steady-state accuracy, respectively. The filter bandwidth is designed based on the target motion characteristics.

[0126] S307, Motion Error Compensation.

[0127] For example, based on the motion error compensation amount Time axis calibration of the echo signal is performed to compensate for motion errors and align the main peaks of the accumulated signal.

[0128] Specifically, various interpolation methods can be used, such as linear interpolation and cubic spline interpolation, and the choice should be made based on the accuracy requirements and computational complexity. For high-precision applications, higher-order interpolation algorithms are usually required.

[0129] S308, accumulate the echo signal, and iteratively execute S304.

[0130] For example, the signal after motion error compensation can be accumulated to form a pulse signal; this pulse signal can then be input again into the error detection and loop filtering steps to achieve iterative analysis.

[0131] Specifically, the number of iterations is typically 3-5, which strikes a good balance between compensation effectiveness and computational complexity. After each iteration, the compensation effect is determined by monitoring changes in the signal peak value.

[0132] S309, Output distance information.

[0133] For example, peak detection is performed on the compensated and accumulated pulse signal, and the peak occurrence time t is recorded. peak And calculate the target distance parameters and motion parameters based on the dToF ranging principle.

[0134] Specifically, distance calculation can include three parameters: average distance, transient distance, and radial velocity. Peak detection can employ a parabolic fitting method, fitting a parabola to three sampling points near the peak to find the precise peak location, thus improving the accuracy of time measurement.

[0135] Thus, this application employs a motion error compensation algorithm with a Gardner ring-like structure, utilizing time symmetry for adaptive delay estimation and dynamic correction to achieve high-precision time synchronization of the echo signal, effectively improving the ranging accuracy of moving targets. This algorithm combines timing recovery technology from communication systems with signal processing requirements in laser ranging, solving the signal mismatch problem in moving target ranging through improved error detection methods and loop filtering design. This enables effective compensation of motion errors under low signal-to-noise ratio conditions, improving the accuracy and reliability of moving target ranging.

[0136] The signal processing device of the laser ranging system provided by the present invention is described below. The signal processing device of the laser ranging system described below and the signal processing method of the laser ranging system described above can be referred to in correspondence.

[0137] Figure 4 This is a structural diagram of a signal processing device for a laser ranging system provided in an embodiment of this application. The signal processing device 400 of the laser ranging system includes: an acquisition module 401, a superposition module 402, a calibration module 403, and a calculation module 404.

[0138] The module comprises: an acquisition module 401, used to acquire multiple sets of raw signals from the target, perform matched filtering on each set of raw signals to obtain multiple sets of echo signals; an overlay module 402, used to accumulate the multiple sets of echo signals to obtain an initial accumulated signal; a calibration module 403, used to calibrate the time axis of the initial accumulated signal using a motion error compensation method to obtain the target accumulated signal, wherein the motion error compensation method includes at least time offset error detection and loop filtering; and a calculation module 404, used to calculate the target's distance parameters and radial velocity based on the target accumulated signal.

[0139] In some embodiments, the acquisition module 401 is specifically used to: construct a filtering function using a Gaussian pulse as a template signal; retain frequency components in the original signal that are consistent with the signal spectrum characteristics of the Gaussian pulse through the filtering function to obtain a preliminary screening signal; suppress out-of-band high-frequency noise and background light interference in the preliminary screening signal to obtain an echo signal, wherein the out-of-band high-frequency noise is a high-frequency interference signal whose frequency exceeds the inherent spectrum range of the Gaussian pulse.

[0140] In some embodiments, the accumulation module 402 is specifically used to sequentially superimpose multiple sets of echo signals according to the acquisition time sequence of each set of echo signals to obtain an initial accumulated signal, wherein the signal-to-noise ratio of the initial accumulated signal is higher than that of the echo signal.

[0141] In some embodiments, the calibration module 403 is specifically used to: determine the half-pulse width and noise energy of the initial accumulated signal by detecting the time offset error, so as to calculate the time offset error of the initial accumulated signal, where the half-pulse width is the time width corresponding to when the pulse amplitude reaches half of its maximum value; perform iterative calculation on the time offset error by loop filtering, and output the motion error compensation amount; and perform time axis calibration on the initial accumulated signal according to the motion error compensation amount to obtain the target accumulated signal.

[0142] In some embodiments, the distance parameter includes the average distance, and the calculation module 404 is specifically used for: performing peak detection on the target accumulated signal and determining the peak time; calculating the average distance of the target based on the peak time and the speed of light; and calculating the radial velocity of the target based on the motion error compensation amount and the laser pulse repetition frequency.

[0143] In some embodiments, the distance parameters further include transient distance, and the acquisition module 401 also acquires the cumulative period corresponding to the calculation of the average distance; combining the average distance, radial velocity and cumulative period, the calculation module 404 is also used to calculate the transient distance of the target at the end of the cumulative period.

[0144] In the signal processing device of the laser ranging system provided in this application embodiment, the detection performance of the laser ranging system for distant moving targets is effectively improved by sequentially executing signal acquisition and filtering, signal accumulation, motion error compensation, and parameter calculation steps. First, by performing matched filtering on multiple sets of raw signals, noise can be effectively suppressed and signal peaks enhanced before accumulation, providing a high-quality signal foundation for subsequent processing. Next, multiple sets of echo signals are accumulated, significantly improving the overall signal-to-noise ratio. Then, by employing a motion error compensation method that includes time offset error detection and loop filtering, the time axis of the accumulated signal is dynamically calibrated, effectively overcoming the signal mismatch problem caused by the radial movement of the target, and accurately restoring the peak value of the accumulated signal. Finally, the distance parameters and radial velocity of the target are calculated based on this calibrated high-quality accumulated signal, improving the accuracy of laser ranging of distant, moving targets.

[0145] Figure 5 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 5As shown, the electronic device 500 may include a processor 510, a communication interface 520, a memory 540, and a communication bus 550. The processor 510, communication interface 520, and memory 540 communicate with each other via the communication bus 550. The processor 510 can call logical instructions in the memory 540 to execute a signal processing method for the laser ranging system. This method includes: acquiring network topology information and observed infection state vectors of the target network, whereby the observed infection state vectors characterize the infection state of nodes in the network; calculating source estimation vectors using a tag propagation algorithm based on the network topology information and observed infection state vectors, whereby the source estimation vectors characterize the initial confidence of each node as a propagation source; inputting the network topology information, observed infection state vectors, and source estimation vectors into a conditional diffusion model, generating source location vectors by performing a reverse denoising process, whereby the conditional diffusion model is a generative model that uses conditional information to guide denoising; and determining the location of the network propagation source nodes based on the source location vectors.

[0146] Furthermore, the logical instructions in the aforementioned memory 540 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0147] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the signal processing method of the laser ranging system provided by the above methods. The method includes: acquiring multiple sets of raw signals of the target; performing matched filtering on each set of raw signals to obtain multiple sets of echo signals; accumulating the multiple sets of echo signals to obtain an initial accumulated signal; calibrating the time axis of the initial accumulated signal using a motion error compensation method to obtain a target accumulated signal, wherein the motion error compensation method includes at least time offset error detection and loop filtering; and calculating the target's distance parameters and radial velocity based on the target accumulated signal.

[0148] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a signal processing method for the laser ranging system provided by the methods described above. This method includes: acquiring multiple sets of raw signals from a target; performing matched filtering on each set of raw signals to obtain multiple sets of echo signals; accumulating the multiple sets of echo signals to obtain an initial accumulated signal; calibrating the time axis of the initial accumulated signal using a motion error compensation method to obtain a target accumulated signal, wherein the motion error compensation method includes at least time offset error detection and loop filtering; and calculating the target's distance parameters and radial velocity based on the target accumulated signal.

[0149] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0150] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0151] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A signal processing method for a laser ranging system, characterized by, The method comprises: Collecting a plurality of groups of original signals of a target, performing matched filtering on each group of original signals to obtain a plurality of groups of echo signals; Cumulatively processing the plurality of groups of echo signals to obtain an initial cumulative signal; Calibrating a time axis of the initial cumulative signal by using a motion error compensation method to obtain a target cumulative signal, the motion error compensation method at least comprising time offset error detection and loop filtering; Based on the target cumulative signal, calculating a distance parameter and a radial velocity of the target.

2. The signal processing method of a laser ranging system according to claim 1, wherein, The matched filtering on each group of original signals to obtain a plurality of groups of echo signals comprises: Constructing a filter function with a Gaussian pulse as a template signal; Retaining frequency components in the original signal consistent with signal spectrum characteristics of the Gaussian pulse by the filter function to obtain a preliminary screening signal; Suppressing out-of-band high-frequency noise and background light interference in the preliminary screening signal to obtain the echo signal, the out-of-band high-frequency noise being a high-frequency interference signal with a frequency exceeding a signal inherent frequency spectrum range of the Gaussian pulse.

3. The signal processing method of a laser ranging system according to claim 1, wherein, The cumulatively processing the plurality of groups of echo signals to obtain an initial cumulative signal comprises: Stacking the plurality of groups of echo signals in turn according to a time sequence of collecting each group of echo signals to obtain the initial cumulative signal, a signal-to-noise ratio of the initial cumulative signal being higher than a signal-to-noise ratio of the echo signal.

4. The signal processing method of a laser ranging system according to claim 1, wherein, The calibrating a time axis of the initial cumulative signal by using a motion error compensation method to obtain a target cumulative signal comprises: Determining a half pulse width and noise energy of the initial cumulative signal by time offset error detection to calculate a time offset error of the initial cumulative signal, the half pulse width being a time width corresponding to a half of a maximum pulse amplitude; Iteratively operating the time offset error by loop filtering to output a motion error compensation amount; Calibrating a time axis of the initial cumulative signal according to the motion error compensation amount to obtain the target cumulative signal.

5. The signal processing method of a laser ranging system according to claim 1, wherein, The distance parameter comprises an average distance, and the calculating a distance parameter and a radial velocity of the target based on the target cumulative signal comprises: Performing peak value detection on the target cumulative signal to determine a peak time; Calculating an average distance of the target based on the peak time and a speed of light; Calculating a radial velocity of the target based on the motion error compensation amount and a laser pulse repetition frequency.

6. The signal processing method of a laser ranging system according to claim 5, wherein, The distance parameter further comprises a transient distance, and the method further comprises: Obtaining a cumulative period corresponding to calculation of the average distance; Combining the average distance, the radial velocity and the cumulative period to calculate a transient distance of the target at the end of the cumulative period.

7. A signal processing device for a laser ranging system, characterized by The device comprises: An acquisition module configured to collect a plurality of groups of original signals of a target, perform matched filtering on each group of original signals to obtain a plurality of groups of echo signals; A stacking module configured to cumulatively process the plurality of groups of echo signals to obtain an initial cumulative signal; A calibration module configured to calibrate a time axis of the initial cumulative signal by using a motion error compensation method to obtain a target cumulative signal, the motion error compensation method at least comprising time offset error detection and loop filtering; A calculating module configured to calculate a range parameter and a radial velocity of the target based on the target accumulated signal.

8. An electronic device comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, The processor implements the signal processing method of the laser ranging system as claimed in any one of claims 1 to 6 when executing the computer program. 9.A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by the processor, implements the signal processing method of the laser ranging system as claimed in any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that, The computer program, when executed by the processor, implements the signal processing method of the laser ranging system as claimed in any one of claims 1 to 6. The computer program, when executed by the processor, implements the signal processing method of the laser ranging system as claimed in any one of claims 1 to 6.

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