Velocity estimation method based on phase unwrapping

Abstract

The present invention provides a velocity estimation method based on phase unwrapping, which belongs to the field of radar signal processing for high-speed rendezvous target miss distance measurement systems. The method first extracts valid data frames containing target motion information based on the signal-to-noise ratio of the baseband echo signal. Then, phase unwrapping is used to obtain the measured two-way distance corresponding to each sampling point of the target echo. The search two-way distance corresponding to each sampling moment before the target impact is then calculated. Considering that target velocity changes relatively slowly in long-range segments, where the non-stationary characteristics of the signal are less pronounced, the error between the search two-way distance and the measured two-way distance within this range is used to reflect the deviation between the search velocity and the target motion velocity. This method can effectively improve the estimation accuracy of non-stationary signals.

Description

Technical Field

[0001] The invention belongs to the field of radar signal processing of a high-speed rendezvous target miss distance measurement system, and particularly relates to a speed estimation method based on phase unwrapping. Background Art

[0002] Due to its active detection method, vector miss distance measurement radar can be used to estimate the motion parameters of targets in close-range, high-speed rendezvous. The existing vector miss distance measurement system first estimates the Doppler frequency of the target echo signal at each moment and the phase difference of the target echo signal received by different antennas from the measurement radar echo. It then performs nonlinear optimal fitting on these Doppler frequency and phase difference sequences to obtain the vector miss distance, which has been widely used. However, due to the extremely short encounter time between the projectile and the target during high-speed rendezvous, the target echo signal exhibits highly non-stationary characteristics. The accuracy of the Doppler frequency and phase difference estimated by frame approximation processing is limited, making it difficult to obtain high-precision velocity measurement results on this basis. Therefore, a velocity estimation method that can estimate non-stationary signals with high measurement accuracy is urgently needed to solve the above problems. Summary of the Invention

[0003] The purpose of the present invention is to propose a velocity estimation method based on phase unwrapping, which can effectively improve the estimation accuracy of non-stationary signals.

[0004] The present invention is achieved through the following technical solutions:

[0005] The velocity estimation method based on phase unwrapping includes the following steps:

[0006] Step S1: In a high-speed intersecting moving target vector miss distance measurement scenario based on a pulse Doppler radar, the pulse Doppler radar radiates electromagnetic wave signals into space through a transmitting antenna, and each receiving antenna receives the electromagnetic wave signals reflected by the target to be measured, and obtains the baseband echo signals of the wave gate where the target of each channel is located after receiving and processing;

[0007] Step S2: dividing the baseband echo signal into short-range segment data and long-range segment data, calculating the signal-to-noise ratio of each frame of the baseband echo signal, and extracting valid data frames containing target motion information using a first signal-to-noise ratio threshold and a second signal-to-noise ratio threshold respectively;

[0008] Step S3: perform mean filtering on the echo signal phase in the valid data frame to obtain the fuzzy phase For this fuzzy phase Perform unwrapping to obtain the unwrapped phase φ i,m (n), and calculate the measured two-way distance R from the target to the transmitting antenna i and the receiving antenna m corresponding to each sampling point based on the expanded phase i,m ;

[0009] Step S4, estimating the Doppler frequency and phase difference information of the baseband echo signal from the valid data frame, and using the least squares method to solve the nonlinear problem to obtain the estimated value of each target motion parameter, the target motion parameters including the target motion trajectory length, target motion speed, target point coordinates and incident angle;

[0010] Step S5: With the target impact time as time 0, the target motion speed estimate obtained in step S4 is set as the initial search speed value, and the search two-way distance corresponding to the initial search speed value is calculated by combining the target coordinate estimate and the target incident angle estimate. And the search two-way distance and measure the two-way distance R i,m For comparison, the measured two-way distance R is obtained i,m The sampling time corresponding to each sampling point in the data is used to complete data alignment;

[0011] Step S6: Set the search speed range with the initial search speed value as the center, and calculate the search speeds within the search speed range. The corresponding search two-way distance And calculate the long distance search round trip distance and measure the two-way distance R i,m The error, the search speed corresponding to the minimum error This is the final target speed estimate.

[0012] Furthermore, in step S1, in the pulse Doppler radar-based high-speed intersection moving target vector miss distance measurement scenario, the coordinates of the target corresponding to the nth sampling point in the radar measurement coordinate system are set to X(n)=[x(n), y(n), z(n)] T , and its relationship with the target motion parameters is: Among them, (x0, y0, z0) is the target point coordinate, T s is the sampling time interval, L0 is the target motion trajectory length, v0 is the target velocity, α is the incident deflection angle, ranging from 0 to 360 degrees, and β is the incident inclination angle, ranging from -90 to 90 degrees.

[0013] Furthermore, in step S1, the electromagnetic wave signal radiated into space by the pulse Doppler radar signal is a pulse modulated radio frequency signal s T (t) = Re[α t ·rect(t / τ p )·exp(j2πf c t)], where Re(·) represents the real part operation, α t is the transmit pulse amplitude, f c is the carrier frequency of the transmitted signal, τ p is the pulse width, is the unit rectangular window function.

[0014] Furthermore, in step S2, the detection frame length of the long-distance segment data is set to L times the detection frame length of the short-distance segment data, and target detection is performed on each frame signal to obtain a corresponding signal-to-noise ratio. The first signal-to-noise ratio threshold is used to filter out the part with a higher signal-to-noise ratio in the short-distance segment data, and the second signal-to-noise ratio threshold is used to filter out the part with a higher signal-to-noise ratio in the long-distance segment data, where L is an integer.

[0015] Furthermore, in the valid data frame obtained after step S2, the baseband echo signal transmitted by the transmitting antenna i of the pulse Doppler radar and received by the receiving antenna m is s i,m (t) = α i,m (t)rect[(t-τ i,m (t)) / τ p ]exp[-j2πf c τ i,m (t)]+n m (t), where α i,m (t) is the baseband signal amplitude obtained after the electromagnetic wave signal emitted by the transmitting antenna i propagates through space and is reflected by the target to the receiving antenna m, τ i,m (t) is the total time delay experienced by the electromagnetic wave signal emitted by the transmitting antenna i after propagating through space and being reflected by the target to the receiving antenna m, which is expressed as is the distance between the target and the transmitting antenna i, r m (t) is the distance between the target and the receiving antenna m, X(t) = [x(t), y(t), z(t)] T is the coordinate of the target in the radar measurement coordinate system at time t, T i is the coordinate of transmitting antenna i in the radar measurement coordinate system, R m is the coordinate of the receiving antenna m in the radar measurement coordinate system, c represents the propagation speed of electromagnetic waves in space, n m (t) is the zero mean value of receiving antenna m and the variance is Additive complex Gaussian white noise.

[0016] Furthermore, in step S3, the discrete form of the baseband echo signal is s i,m (n) = α i,m (n)rect[(n-τ i,m (n)) / τ p ]exp[-j2πf c τ i,m (n)]+n m(n) Obtain the echo signal phase of each sampling point based on the discrete baseband echo signal, and perform mean filtering on the echo signal phase to obtain the fuzzy phase of each sampling point The periodic variation in the range of [-π,π]rad Expanded into a continuously changing phase Thus, the measured two-way distance R from the target to the transmitting antenna i and the receiving antenna m corresponding to each sampling point is obtained. i,m , whose expression is in, T s is the sampling interval, λ is the carrier wavelength, φ m (n) is the phase noise of the nth sampling point of receiving antenna m.

[0017] Furthermore, in step S4, the Doppler frequency information and phase difference information of the baseband echo signal are obtained by the ESPRIT algorithm, and the nonlinear optimization problem is solved using the least squares method according to the Doppler frequency information. Get the scalar miss distance estimate Target motion speed estimation and target trajectory length estimate According to the phase difference information, construct the criterion function Then we get the nonlinear optimization function Thus, the estimated target coordinates are obtained Target incidence angle estimate Among them, α is the incident deflection angle, β is the incident inclination angle, (x0, y0, z0) is the target point coordinates, is the estimated incident angle, is the estimated incident tilt angle, is the estimated value of the target coordinate, N is the total number of time series, M is the total number of receiving antenna pairs, is the Doppler frequency information of the baseband echo signal obtained by the ESPRIT algorithm, φ j (t i ) is t i The theoretical phase difference corresponding to the moment search parameter, t i The phase difference estimation result of the echo data at time instant.

[0018] Furthermore, in step S5 and step S6, the calculation of the search round-trip distance is specifically Set the initial search speed and each search speed Then, combined with the estimated value of target coordinates and the estimated value of target incident angle, the initial value of search speed and the search speed before the target hits the target are calculated respectively. The motion trajectory is recorded as the search trajectory, and the target coordinates at any sampling time in the search trajectory are marked as Combining the coordinates of the transmitting antenna and the receiving antenna, the distance between the target position and the transmitting antenna i and the receiving antenna m at any sampling time in the search trajectory can be obtained: and Then we get the values ​​corresponding to the initial search speed and the search speed Search round-trip distance Its expression is

[0019]

[0020] The present invention has the following beneficial effects:

[0021] 1. The present invention first extracts valid data frames containing target motion information based on the signal-to-noise ratio of the baseband echo signal. Secondly, the measured two-way distance corresponding to each sampling point of the target echo is obtained by phase unwrapping. Then, the search two-way distance corresponding to each sampling moment before the target impact is calculated. Considering that the target speed changes relatively slowly in the long-distance segment and the non-stationary characteristics of the signal are not obvious, the error between the search two-way distance and the measured two-way distance in this distance segment is used to reflect the deviation between the search speed and the target motion speed, thereby effectively improving the estimation accuracy of the non-stationary signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The present invention will be further described in detail below with reference to the accompanying drawings.

[0023] Figure 1 Flowchart of the present invention.

[0024] Figure 2 The figure is a schematic diagram of the high-speed rendezvous moving target vector miss distance measurement scenario of the present invention.

[0025] Figure 3 This is the calculation result of the signal-to-noise ratio of each frame data in the close distance segment of the present invention.

[0026] Figure 4 This is the calculation result of the signal-to-noise ratio of each frame data in the long-distance segment of the present invention.

[0027] Figure 5 This is a comparison diagram before and after the mean filtering of the baseband echo signal phase in the valid frame in the present invention.

[0028] Figure 6 This is the short-range echo phase expansion result of the present invention.

[0029] Figure 7 This is the long-distance echo phase expansion result of the present invention.

[0030] Figure 8This is a comparison diagram of the measured two-way distance and the searched two-way distance in the short-range segment of the present invention.

[0031] Figure 9 This is a diagram of the process of measuring the two-way distance and searching the slope of the two-way distance according to the present invention.

[0032] Figure 10 This is a graph showing the slope alignment results of measuring the two-way distance and searching the two-way distance according to the present invention.

[0033] Figure 11 This is a diagram showing the error between searching for the round-trip distance and measuring the round-trip distance according to the present invention.

[0034] Figure 12 This is a distance matching error diagram for each search speed of the present invention.

[0035] Figure 13 This is a diagram showing the speed estimation results of the present invention. DETAILED DESCRIPTION

[0036] like Figure 1 As shown, the velocity estimation method based on phase unwrapping includes the following steps:

[0037] Step S1: In a high-speed intersecting moving target vector miss distance measurement scenario based on a pulse Doppler radar, the pulse Doppler radar radiates electromagnetic wave signals into space through a transmitting antenna, and each receiving antenna receives the electromagnetic wave signals reflected by the target to be measured, and obtains the baseband echo signals of the wave gate where the target of each channel is located after receiving and processing;

[0038] Among them, Figure 2 In this paper, the radar used is a pulse Doppler radar operating in the S band. The antenna array includes two transmitting antennas and eight receiving antennas. Any transmitting antenna is connected to the target simulator. Let the coordinates of the target corresponding to the nth sampling point in the radar measurement coordinate system be X(n) = [x(n), y(n), z(n)] T , and its relationship with the target motion parameters is: Among them, (x0, y0, z0) is the target point coordinate, T s is the sampling interval, L0 is the target trajectory length, i.e., the target movement distance from detection to impact, v0 is the target velocity, α is the incident deflection angle, defined as the angle between the positive coordinate axis and the projection of the target trajectory on the xoy plane, with a value range of 0 to 360 degrees, and β is the incident inclination angle, defined as the angle between the target trajectory and the xoy plane. It takes a positive value when the target moves in the negative direction of the z-axis and a negative value when it moves in the positive direction of the z-axis, with a value range of -90 to 90 degrees. In this embodiment, the target point coordinates are set to (0m, -3m, 3m), the incident deflection angle is 180°, and the incident inclination angle is 0°. The target simulator outputs the echo signals from the eight receiving antennas, which are processed to obtain baseband data.

[0039] The electromagnetic wave signal radiated into space by the pulse Doppler radar signal is a radio frequency signal s that has undergone simple pulse modulation. T (t) = Re[α t ·rect(tτ p )·exp(j2πf c t)], where Re(·) represents the real part operation, α t is the transmit pulse amplitude, f c is the carrier frequency of the transmitted signal, τ p is the pulse width, is the unit rectangular window function.

[0040] Step S2: dividing the baseband echo signal into short-range segment data and long-range segment data, calculating the signal-to-noise ratio of each frame of the baseband echo signal, and extracting valid data frames containing target motion information using a first signal-to-noise ratio threshold and a second signal-to-noise ratio threshold respectively;

[0041] Specifically, the simulator outputs the target echo signal according to the set motion parameters. After receiving and processing, the baseband echo signal of the gate where the target of each channel is located is obtained. The total number of frames is 680, and the frame length is 1024 sampling points. Taking into account the low original signal-to-noise ratio of the long-distance segment data, in order to improve the coherent accumulation gain, the detection frame length of the long-distance segment data is set to L = 4 times the detection frame length of the short-distance segment data, that is, the frame length of the long-distance segment data is 4096 sampling points, and the frame length of the short-distance segment data is still 1024 sampling points. Target detection is performed on each frame signal and the corresponding signal-to-noise ratio is output. Figure 2 and Figure 3 The following table shows the signal-to-noise ratio calculation results for each frame of data in the near-distance segment and the far-distance segment, respectively. It can be seen that the signal-to-noise ratio is high only in the first few frames of the near-distance segment, while it is high only in the last few frames of the far-distance segment. Using the first signal-to-noise ratio threshold, the data in the near-distance segment with a higher signal-to-noise ratio is filtered out, while using the second signal-to-noise ratio threshold, the data in the far-distance segment with a higher signal-to-noise ratio is filtered out. These are the valid data frames containing target motion information. In target detection processing, the process of filtering out valid data frames based on signal-to-noise ratio is conventional technology.

[0042] Step S3: perform mean filtering on the baseband echo signal phase in the valid data frame to obtain the fuzzy phase For this fuzzy phase Perform unwrapping to obtain the unwrapped phase φ i,m (n), and calculate the measured two-way distance R from the target to the transmitting antenna i and the receiving antenna m corresponding to each sampling point based on the expanded phase i,m ;

[0043] Among them, in the valid data frame, the baseband echo signal transmitted by the transmitting antenna i of the pulse Doppler radar and received by the receiving antenna m is s i,m (t) = α i,m (t)rect[(t-τ i,m (t)) / τ p ]exp[-j2πf c τ i,m (t)]+n m (t), where α i,m (t) is the baseband signal amplitude obtained after the electromagnetic wave signal emitted by the transmitting antenna i propagates through space and is reflected by the target to the receiving antenna m, τ i,m (t) is the total time delay experienced by the electromagnetic wave signal emitted by the transmitting antenna i after propagating through space and being reflected by the target to the receiving antenna m, which is expressed as r Ti (t) is the distance between the target and the transmitting antenna i, rm(t) is the distance between the target and the receiving antenna m, X(t) = [x(t), y(t), z(t)] T is the coordinate of the target in the radar measurement coordinate system at time t, T i is the coordinate of transmitting antenna i in the radar measurement coordinate system, R m is the coordinate of the receiving antenna m in the radar measurement coordinate system, c represents the propagation speed of electromagnetic waves in space, n m (t) is the zero mean value of receiving antenna m and the variance is Additive complex Gaussian white noise.

[0044] The discrete form of the baseband echo signal is s i,m (n) = α i,m (n)rect[(n-τ i,m (n)) / τ p ]exp[-j2πf c τ i,m (n)]+n m (n), the echo signal phase of each sampling point is obtained according to the discrete baseband echo signal. In order to reduce the influence of phase noise in the echo signal phase, it is necessary to perform mean filtering on it to obtain the fuzzy phase of each sampling point. Before and after treatment Figure 5 shown.

[0045] Taking into account the fuzzy phase There is ambiguity, and the phase periodicity is eliminated by unwrapping it, that is, the periodic variation in the range of [-π,π]rad is eliminated. Expanded into a continuously changing phase like Figure 6 and Figure 7They are the phase unwrapping results respectively. The sampling interval of the close distance segment is lower, so the phase change between sampling points (i.e., phase slope) is smaller than that of the long distance segment.

[0046] Get the phase unwrapping result φ i,m (n) After that, the measured two-way distance R from the target to the transmitting antenna i and the receiving antenna m corresponding to each sampling point can be obtained. i,m , whose expression is in, T s is the sampling interval, λ is the carrier wavelength, φ m (n) is the phase noise of the nth sampling point of receiving antenna m.

[0047] Step S4, estimating the Doppler frequency and phase difference information of the baseband echo signal from the valid data frame, and using the least squares method to solve the nonlinear problem to obtain the estimated value of each target motion parameter, the target motion parameters including the target motion trajectory length, target motion speed, target point coordinates and incident angle;

[0048] Specifically, the Doppler frequency information of the baseband echo signal and the phase difference information of the baseband echo signal between different receiving antennas are obtained through the ESPRIT algorithm, and the specific calculation process is the existing technology;

[0049] Solve nonlinear optimization problems using the least squares method based on Doppler frequency information Get the scalar miss distance estimate Target motion speed estimation and target trajectory length estimate According to the echo phase difference information between different receiving antennas, a criterion function is constructed Then we get the nonlinear optimization function Thus, the estimated target coordinates are obtained Target incidence angle estimate Among them, α is the incident deflection angle, β is the incident inclination angle, (x0, y0, z0) is the target point coordinates, is the estimated incident angle, is the estimated incident tilt angle, is the estimated value of the target coordinate, N is the total number of time series, M is the total number of receiving antenna pairs, is the Doppler frequency information of the baseband echo signal obtained by the ESPRIT algorithm, φ j (t i ) is t i The theoretical phase difference corresponding to the moment search parameter, t iPhase difference estimation results of the echo data at the moment. In this embodiment, the target coordinates are estimated to be (0m, -3.00m, 2.98m), the incident deflection angle is estimated to be 179.92°, the incident inclination angle is estimated to be -0.08°, and the initial search speed is 1798.5m / s.

[0050] Step S5: With the target impact time as time 0, the target motion speed estimate obtained in step S4 is set as the initial search speed value, and the search two-way distance corresponding to the initial search speed value is calculated by combining the target coordinate estimate and the target incident angle estimate. And the search two-way distance and measure the two-way distance R i,m For comparison, the measured two-way distance R is obtained i,m The sampling time corresponding to each sampling point in the data is used to complete data alignment;

[0051] Step S6: Set the search speed range with the initial search speed value as the center, and calculate the search speeds within the search speed range. The corresponding search two-way distance And calculate the long distance search round trip distance and measure the two-way distance R i,m The error, the search speed corresponding to the minimum error This is the final target speed estimate.

[0052] In step S5 and step S6, the two-way distance is calculated. The process is the same, specifically, setting the initial value of the search speed and the search speed Then, based on the estimated value of the target point coordinates and the estimated value of the target incident angle, the initial search speed and the search speed before the target lands are calculated. The motion trajectory is recorded as the search trajectory, and the target coordinates at any sampling time in the search trajectory are marked as Combining the coordinates of the transmitting antenna and the receiving antenna, the distance between the target position and the transmitting antenna i and the receiving antenna m at any sampling time in the search trajectory can be obtained: and Then we get the search two-way distance Its expression is In order to keep a certain margin, the length of the generated search trajectory should be slightly larger than the estimated length of the target trajectory. The specific calculation process of the motion trajectory is an existing technology.

[0053] In this embodiment, the initial value of the search speed is 1798.5m / s, so the search speed range is set to 1788.5~1808.5m / s, and the search interval is 0.1m / s, so as to determine the search speed. When setting the search speed range, do not deviate too far from the initial search speed value to avoid meaningless speed searches.

[0054] Since the filtered valid data only corresponds to a part of the target echo data, the measured two-way distance R i,m In order to accurately calculate the error between the measured two-way distance and the search two-way distance, the measured two-way distance and the search two-way distance should be made to correspond in time and space. Based on this, first calculate the target trajectory segment corresponding to the measured two-way distance, and then calculate the measured two-way distance R i,m Search round-trip distance with different search speeds Taking into account the different sampling intervals in long-distance and short-distance modes and the high signal-to-noise ratio of the short-distance data segment, when aligning the data, only the alignment of the short-distance segment data is considered. The comparison of the short-distance segment when measuring the two-way distance and searching the two-way distance is as follows: Figure 8 As shown, it can be observed that the length of the measured two-way distance sequence is smaller than the search two-way distance sequence.

[0055] Considering that the two-way distance changes rapidly during the intersection phase between the target and the target surface, the two-way distance is divided into multiple sampling intervals and the slope of the two-way distance in each interval is calculated, and the slope is used as a reference for data alignment. Specifically, for the two-way distance R i,m and Divide the sampling interval into multiple sampling intervals with N=32 sampling points and calculate the slope, and then measure the two-way distance R i,m The slope of the smooth processing and intercept the gently changing data segment, the processing process is as follows Figure 9 shown.

[0056] Get the slope sequence K for measuring the two-way distance i,m The slope sequence of the search round-trip distance corresponding to the initial value of the search speed After that, we start to align the data and put the shorter K i,m The curve is continuously translated, and K is calculated after each translation. i,m and The root mean square error is used as the basis for evaluating the alignment effect. Finally, the translation amount corresponding to the minimum root mean square error is obtained by comparison to complete the slope alignment operation. The slope alignment result of receiving antenna 1 is as follows: Figure 10 As shown, after translation, the slope sequence K of the two-way distance is measured i,m (blue line) and the slope sequence of the search round-trip distance corresponding to the initial value of the search speed (Red line) Alignment is complete. At this point, the measured two-way distance and the searched two-way distance are aligned in time based on the obtained translation, so an estimate of the target impact time can also be obtained.

[0057] After the data alignment is completed, the error between the search round-trip distance and the measured round-trip distance corresponding to the initial search speed value is as follows: Figure 11 As shown. It can be observed that when the data is aligned in time, K i,m and The error in the close-range segment (after sampling point 46080) is small. This error is caused by the error between the initial value of the velocity search and the target velocity. The distance error changes rapidly by about 15 meters in the period after the waveform switch (sampling points 41664 to 46080). This error is caused by the unstable state of the radar system in the period after the waveform switch. The phase of the radar waveform remains basically unchanged for a period of time after switching to the close-range waveform. During this period, the measured two-way distance calculated by the expanded phase also remains basically unchanged. Therefore, the measured two-way distance cannot reflect the target's movement status during this period, while the search two-way distance is still changing steadily during this period, resulting in a sudden change in the distance error.

[0058] Considering that the radial velocity of the target in the long-distance data segment changes slowly, K i,m and The error in the long distance segment is used as the evaluation basis for evaluating the degree of two-way distance matching. Figure 12 For example, the distance error in the data segment of sampling points 5000 to 15000 changes steadily without jitter, which can reflect the deviation of speed estimation. Suppose the target's two-way distance change during the phase instability after waveform switching is ΔR switch , according to the formula and formula It can be seen that when the search speed is consistent with the target's true speed, K i,m and The error is It can be seen that when the search speed is consistent with the target real speed, the error ΔR in the entire selected data segment is ΔR switch The average value fluctuates around the average. If there is a deviation between the search speed and the target speed, ΔR will tend to increase or decrease within this data segment. Therefore, the standard deviation of ΔR, std(ΔR), can be used as the distance matching error to evaluate the deviation between the search speed and the target's true speed.

[0059] With the initial speed search value as the center, after defining the speed search range and interval, the distance matching error std(ΔR) corresponding to each search speed is calculated in turn. The search speed corresponding to the minimum distance matching error is the final speed estimation result. Figure 12 is the distance matching error corresponding to each search speed of a single antenna. The speed value at the lowest point of the curve is the speed estimation result of the current receiving antenna.

[0060] In the Matlab environment, a graphical user interface (GUI) was designed and implemented using the GUIDE tool. The interface integrates the velocity estimation algorithm based on phase unwrapping. The platform can be used to load data, perform phase unwrapping processing, and finally obtain the target velocity estimation result, such as Figure 13 shown.

[0061] In order to verify the accuracy of the velocity measurement results of this method, a target simulator is used to generate multiple sets of echo data. Table 1 shows the motion parameter information and velocity estimation results of each set of data. Targets 1 to 6 correspond to six sets of echo data respectively.

[0062] Table 1 Simulator data information and speed estimation results

[0063]

[0064] Verification with simulator data shows that the phase-unwrapping-based velocity estimation method can achieve highly accurate velocity estimates, with velocity estimation errors ranging from 0 m / s to 0.6 m / s for each channel. Based on the specific conditions of each antenna, the velocity estimate output by the antenna with the best slope matching results and the smallest range matching error can be selected as the final velocity estimate to achieve a more reliable velocity estimate.

[0065] The above description is merely a preferred embodiment of the present invention and therefore cannot be used to limit the scope of the present invention. In other words, equivalent changes and modifications made according to the scope of the patent application and the contents of the specification should still fall within the scope of the patent of the present invention.

Claims

1. A velocity estimation method based on phase unwrapping, characterized by: The steps include: Step S1: In a high-speed intersecting moving target vector miss distance measurement scenario based on a pulse Doppler radar, the pulse Doppler radar radiates electromagnetic wave signals into space through a transmitting antenna, and each receiving antenna receives the electromagnetic wave signals reflected by the target to be measured, and obtains the baseband echo signals of the wave gate where the target of each channel is located after receiving and processing; Step S2: dividing the baseband echo signal into short-range segment data and long-range segment data, calculating the signal-to-noise ratio of each frame of the baseband echo signal, and extracting valid data frames containing target motion information using a first signal-to-noise ratio threshold and a second signal-to-noise ratio threshold respectively; Step S3: perform mean filtering on the echo signal phase in the valid data frame to obtain the fuzzy phase For this fuzzy phase Perform unwrapping to obtain the unwrapped phase φ i,m (n), and calculate the measured two-way distance R from the target to the transmitting antenna i and the receiving antenna m corresponding to each sampling point based on the expanded phase i,m ; Step S4, estimating the Doppler frequency and phase difference information of the baseband echo signal from the valid data frame, and using the least squares method to solve the nonlinear problem to obtain the estimated value of each target motion parameter, the target motion parameters including the target motion trajectory length, target motion speed, target point coordinates and incident angle; Step S5: With the target impact time as time 0, the target motion speed estimate obtained in step S4 is set as the initial search speed value, and the search two-way distance corresponding to the initial search speed value is calculated by combining the target coordinate estimate and the target incident angle estimate. And the search two-way distance and measure the two-way distance R i,m For comparison, the measured two-way distance R is obtained i,m The sampling time corresponding to each sampling point in the data is used to complete data alignment; Step S6: Set the search speed range with the initial search speed value as the center, and calculate the search speeds within the search speed range. The corresponding search two-way distance And calculate the long distance search round trip distance and measure the two-way distance R i,m The error, the search speed corresponding to the minimum error This is the final target speed estimate.

2. The velocity estimation method based on phase unwrapping according to claim 1, characterized in that: In step S1, in the pulse Doppler radar-based high-speed intersection moving target vector miss distance measurement scenario, the coordinates of the target corresponding to the nth sampling point in the radar measurement coordinate system are set to X(n)=[x(n), y(n), z(n)] T , and its relationship with the target motion parameters is: Among them, (x0, y0, z0) is the target point coordinate, T s is the sampling time interval, L0 is the target motion trajectory length, v0 is the target velocity, α is the incident deflection angle, ranging from 0 to 360 degrees, and β is the incident inclination angle, ranging from -90 to 90 degrees.

3. The velocity estimation method based on phase unwrapping according to claim 2, characterized in that: In step S1, the electromagnetic wave signal radiated into space by the pulse Doppler radar signal is a pulse modulated radio frequency signal s T (t) = Re[α t ·rect(tτ p )·exp(j2πf c t)], where Re(·) represents the real part operation, α t is the transmit pulse amplitude, f c is the carrier frequency of the transmitted signal, τ p is the pulse width, is the unit rectangular window function.

4. The velocity estimation method based on phase unwrapping according to claim 2, characterized in that: In step S2, the detection frame length of the long-distance segment data is set to L times the detection frame length of the short-distance segment data, target detection is performed on each frame signal to obtain a corresponding signal-to-noise ratio, a first signal-to-noise ratio threshold is used to filter out a portion of the short-distance segment data with a higher signal-to-noise ratio, and a second signal-to-noise ratio threshold is used to filter out a portion of the long-distance segment data with a higher signal-to-noise ratio, where L is an integer.

5. The velocity estimation method based on phase unwrapping according to claim 4, characterized in that: In the valid data frame obtained after step S2, the baseband echo signal transmitted by the transmitting antenna i of the pulse Doppler radar and received by the receiving antenna m is s i,m (t) = α i,m (t)rect[(t-τ i,m (t)) / τ p ]exp[-j2πf c τ i,m (t)]+n m (t), where α i,m (t) is the baseband signal amplitude obtained after the electromagnetic wave signal emitted by the transmitting antenna i propagates through space and is reflected by the target to the receiving antenna m, τ i,m (t) is the total time delay experienced by the electromagnetic wave signal emitted by the transmitting antenna i after propagating through space and being reflected by the target to the receiving antenna m, which is expressed as is the distance between the target and the transmitting antenna i, r m (t) is the distance between the target and the receiving antenna m, X(t) = [x(t), y(t), z(t)] T is the coordinate of the target in the radar measurement coordinate system at time t, T i is the coordinate of transmitting antenna i in the radar measurement coordinate system, R m is the coordinate of the receiving antenna m in the radar measurement coordinate system, c represents the propagation speed of electromagnetic waves in space, n m (t) is the zero mean value of receiving antenna m and the variance is Additive complex Gaussian white noise.

6. The velocity estimation method based on phase unwrapping according to claim 5, characterized in that: In step S3, the discrete form of the baseband echo signal is s i,m (n) = α i,m (n)rect[(n-τ i,m (n)) / τ p ]exp[-j2πf c τ i,m (n)]+n m (n) Obtain the echo signal phase of each sampling point based on the discrete baseband echo signal, and perform mean filtering on the echo signal phase to obtain the fuzzy phase of each sampling point The periodic variation in the range of [-π,π]rad Expanded into a continuously changing phase Thus, the measured two-way distance R from the target to the transmitting antenna i and the receiving antenna m corresponding to each sampling point is obtained. i,m , whose expression is in, T s is the sampling interval, λ is the carrier wavelength, φ m (n) is the phase noise of the nth sampling point of receiving antenna m.

7. The velocity estimation method based on phase unwrapping according to claim 6, characterized in that: In step S4, the Doppler frequency information and phase difference information of the baseband echo signal are obtained by the ESPRIT algorithm, and the nonlinear optimization problem is solved using the least squares method based on the Doppler frequency information. Get the scalar miss distance estimate Estimated target speed and target trajectory length estimate According to the phase difference information, construct the criterion function Then we get the nonlinear optimization function Thus, the estimated target coordinates are obtained Target incidence angle estimate Among them, α is the incident deflection angle, β is the incident inclination angle, (x0, y0, z0) is the target point coordinates, is the estimated incident angle, is the estimated incident tilt angle, is the estimated value of the target coordinate, N is the total number of time series, M is the total number of receiving antenna pairs, is the Doppler frequency information of the baseband echo signal obtained by the ESPRIT algorithm, φ j (t i ) is t i The theoretical phase difference corresponding to the moment search parameter, t i The phase difference estimation result of the echo data at time instant.

8. The velocity estimation method based on phase unwrapping according to claim 7, characterized in that: In the steps S5 and S6, the two-way distance is calculated as follows: Set the initial search speed and each search speed Then, combined with the estimated value of target coordinates and the estimated value of target incident angle, the initial value of search speed and the search speed before the target hits the target are calculated respectively. The motion trajectory is recorded as the search trajectory, and the target coordinates at any sampling time in the search trajectory are marked as Combining the coordinates of the transmitting antenna and the receiving antenna, the distance between the target position and the transmitting antenna i and the receiving antenna m at any sampling time in the search trajectory can be obtained: and Then we get the values ​​corresponding to the initial search speed and the search speed Search round-trip distance Its expression is

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