CN-121978642-A - Low-angle rapid target radar multipath effect compensation method based on time sequence characteristics

CN121978642ACN 121978642 ACN121978642 ACN 121978642ACN-121978642-A

Abstract

The application belongs to the technical field of new generation information, and particularly relates to a low-angle rapid target radar multipath effect compensation method based on time sequence characteristics. The method comprises the steps of obtaining a three-dimensional measurement residual sequence, carrying out continuous wavelet transformation on a pitching residual sequence in the sequence, reconstructing pitching multipath error items, removing the pitching multipath error items from the pitching residual sequence to obtain a compensated pitching residual sequence, carrying out Gaussian inspection on the compensated pitching residual sequence, calculating statistics, judging according to absolute differences between two adjacent statistics, starting the next iteration if iteration is not converged, and outputting a current motion state estimated value and the compensated pitching measurement sequence if iteration is converged, so as to realize the compensation of the multipath effect of the low-angle rapid target radar. The application can realize the effective compensation of the low-angle fast target multipath error item. The method does not involve front-end hardware change, and has good adaptability to the environment.

Inventors

LI CHENGZHANG
HAN WENJUN
ZHANG WEIXUAN
Guan Xiquan
YAN HAI
Zhou Chuihong
WANG JIANWEI

Assignees

中国电子科技集团公司第十四研究所

Dates

Publication Date: 20260505
Application Date: 20260408

Claims (8)

1. A low-angle rapid target radar multipath effect compensation method based on time sequence features is characterized by comprising the following steps: s100, acquiring a three-dimensional measurement residual sequence, wherein the three-dimensional measurement residual sequence comprises a distance residual sequence, an azimuth residual sequence and a pitching residual sequence; S200, carrying out continuous wavelet transformation on the pitching residual error sequence, reconstructing pitching multipath error items, and subtracting the pitching multipath error items from the pitching residual error sequence to obtain a compensated pitching residual error sequence; s300, carrying out Gaussian test on the compensated pitching residual sequence, calculating statistic, and comparing the absolute difference between two adjacent statistic with a minimum allowable change threshold value: if the absolute difference between two adjacent statistics is smaller than the minimum allowable change threshold, iteratively converging, and outputting a current motion state estimated value and a compensated pitching measurement sequence; If the absolute difference between two adjacent statistics is not less than the minimum allowable change threshold, the iteration is not converged, the next iteration is started, namely, after the weight of each measuring point is updated, the steps S100, S200 and S300 are executed again.
2. The method for compensating for multipath effects of low angle fast target radar based on time series characteristics as claimed in claim 1, wherein step S100 includes the sub-steps of: S110, establishing a target motion model: Wherein, the A discrete time index representing the current time; Representing the motion state of the target at the current moment and containing the target position information Information on target speed I.e. When (1) When the initial motion state of the target is shown, the previous moment is not existed In the time-course of which the first and second contact surfaces, The time of day is indicated as the last time, Representing the motion state of the target at the last moment; representing a state transfer function; s120, obtaining an estimated value of the target motion state ; S130, extrapolation of target track based on estimated value of target motion state And a target motion model, a sequence of measurement and calculation is obtained Aligned target track sequence Wherein, the method comprises the steps of, Is a positive integer, and represents the total number of times of measurement; Is shown in the first Measuring data obtained at each sampling moment; represent the first Target motion state estimation values at each moment; s140, calculating the measurement residual sequence, namely, measuring the sequence Sequence with target track Making a difference to obtain a measurement residual sequence The following are provided: 。
3. The method for compensating for multipath effects of a low-angle fast target radar based on time sequence features as claimed in claim 2, wherein the target motion model is a free-falling model in three-dimensional space, namely: Wherein, the Target position information indicating the current time; target speed information indicating the current time; target position information indicating the last time; target speed information indicating the last time; is the acceleration of the earth's center, Is a discrete time interval.
4. The method for compensating for multipath effects of low-angle fast target radar based on time sequence features as claimed in claim 3, wherein the estimated value of the motion state of the target is obtained The method is as follows: Obtaining a target motion state estimated value by adopting a weighted least square method: Wherein, the Estimating a target motion state value; In order to participate in the total number of measurements in the batch process, Is an integer and ; Representing a discrete-time index of the time, ; Representing the value of the self-variable that minimizes the right-hand function; Representing a time sequence of target motion states; representing a transpose operation; is a measurement equation; Representing the motion state of the target at the current moment; Is the first A weight matrix for group measurement; for measuring the vector, for a radar apparatus, , Respectively, are measurement vectors Representing measured values of distance, azimuth and pitch, respectively.
5. The method for compensating for multipath effects of low angle fast target radar based on time series characteristics as claimed in claim 1, wherein step S200 includes the sub-steps of: S210, modeling residual errors in the measurement residual error sequence, and decomposing the residual errors into a multipath error term and a Gaussian noise term; S220, performing continuous wavelet transformation on the pitching measurement residual sequence to obtain pitching measurement residual wavelet coefficients : In the formula, Is a mother function of wavelet transformation; Representing scale factors, controlling the expansion and contraction of a mother wavelet, and determining analysis frequency; Controlling the movement position of the mother wavelet along a time axis as a translation factor; characterizing the signal on scale for wavelet coefficients Translation of Time-frequency energy distribution at the location; Is shown in the first Time values of the sampling points; For pitch residual sequence Residual error of time; pitch measurement residual wavelet coefficients The method comprises the following steps of: Wherein, the Wavelet coefficients for multipath error terms in the pitch measurement residual; wavelet coefficients for gaussian noise terms in the pitch measurement residual; S230, reconstructing pitch multipath error term Realizing the estimation of pitching multipath error items; Wherein, the As a mother function of the wavelet transform of the multipath error term, Representing time; representing the current decomposition level; represent the first The first sample point multipath error term Layer wavelet coefficients; representing the number of decomposition levels of the wavelet transform; S240, subtracting a pitching multipath error term from the pitching residual sequence to obtain a compensated pitching residual sequence: the pitch residual sequence after compensation is , wherein, For pitch residual sequence Residual error of time; For pitch residual sequence Multipath error term of time residual.
6. The method for compensating for multipath effects of low-angle fast target radar based on time series characteristics as claimed in claim 5, wherein step S210 is specifically as follows: decomposing residuals in a sequence of measurement residuals The following is shown: Wherein, the Is a multipath error term; is a gaussian noise term; the multipath error term The calculation is as follows: Wherein, the Is a distance multipath error term; Is an azimuth multipath error term; is a pitch multipath error term; Order the ; Wherein, the Representing the amplitude of the pitch multipath error term, The angular frequency representing the pitch multipath error term, Representing the phase of the pitch multipath error term, Is shown in the first Time values of the sampling points.
7. The method for compensating for multipath effects of low angle fast target radar based on time series characteristics as claimed in claim 1, wherein step S300 includes the sub-steps of: S310, performing Gaussian test on the compensated pitching residual sequence, and calculating statistics ; For the index of the number of iterations, ; When (when) At the time of first execution of steps S100 and S200, statistics are calculated After that, let And enter an iterative loop, i.e. execute steps S100, S200, S300 again; When (when) When calculating statistics ; S320, comparing the absolute difference between two adjacent statistics with a minimum allowable change threshold value: (a) If the absolute difference between two adjacent statistics is less than < the minimum allowable change threshold, i.e. The iteration converges, and step S330 is executed; Is the first The test statistics corresponding to the secondary iteration; Is the first The test statistics corresponding to the secondary iteration; is a minimum allowable variation threshold; (b) If the absolute difference between two adjacent statistics is not less than the minimum allowable change threshold, namely If the iteration is not converged, updating the weight of each measuring point in the batch processing process, and starting the next iteration, namely executing the steps S100, S200 and S300 again; S330, outputting the current motion state estimation value and the compensated pitching measurement sequence Outputting the estimated value of the current motion state And compensated pitch measurement sequence : ; ; Wherein, the Is the first A target motion state estimated value after the iteration for the times; to compensate for the post-tilt measurement sequence; To pass through the first Pitch measurement vector estimation values after the iterative process; To pass through the first And (3) a pitch residual sequence after compensation after the iterative process.
8. The method for compensating multipath effect of low-angle fast target radar based on time sequence features as claimed in claim 7, wherein when updating the weight of each measuring point in the batch process, the method is specifically as follows: Initial weight Updated weights Given by the formula: Wherein, the Representing the current decomposition level; represent the first Sampling point(s) The step length of weight adjustment of the layer wavelet coefficient; represent the first In the sampling points, multipath error items are subjected to wavelet decomposition and then are in the first stage Wavelet coefficients of the layers; represent the first In the sampling points, gaussian noise items in pitch measurement residual errors are subjected to wavelet decomposition and then are in the first position Wavelet coefficients of the layers; The number of decomposition levels representing the wavelet transform.

Description

Low-angle rapid target radar multipath effect compensation method based on time sequence characteristics Technical Field The invention relates to the technical field of new generation information, in particular to a low-angle rapid target radar multipath effect compensation method based on time sequence characteristics. Background In the invention, "low angle" refers to a pitch angle of radar detection on a target being lower than 2 degrees, and "fast" refers to a movement speed of the target being greater than 100m/s. Low elevation target detection is a key challenge for radar devices, one of the key difficulties being the severe impact of multipath error. Multipath effect refers to the phenomenon that electromagnetic waves emitted by a radar reach a target after being reflected by the ground or sea surface, so as to form a plurality of nonlinear propagation paths. When the angle is low, the multipath effect can lead to the distortion of the amplitude and the phase of the radar signal, larger non-Gaussian multipath error is generated, and the angle measurement precision can be deteriorated to more than 5-6 times of the conventional precision. In response to this problem, the academic and engineering community has conducted related research from both front-end hardware and back-end processing. In terms of hardware, phase center stabilization and multipath mitigation are achieved through the hybrid choke antenna. In the processing aspect, the angular deviation caused by multipath is restrained by constructing a compensation factor of the delay difference of the direct signal and the multipath signal. However, the existing radar multipath effect compensation method generally compensates multipath effects based on single frame signals, does not consider the continuity relation of target motion, and the compensation factors are highly correlated with factors such as terrain, so that the low-angle radar detection multipath error compensation requirements in various scenes are difficult to cover. Disclosure of Invention In order to solve the problems in the prior art and compensate the multipath effect of the low-angle rapid target radar, the application provides a method for compensating the multipath effect of the low-angle rapid target radar based on time sequence characteristics. The following scheme is adopted: a low-angle rapid target radar multipath effect compensation method based on time sequence features comprises the following steps: s100, acquiring a three-dimensional measurement residual sequence, wherein the three-dimensional measurement residual sequence comprises a distance residual sequence, an azimuth residual sequence and a pitching residual sequence; S200, carrying out continuous wavelet transformation on the pitching residual error sequence, reconstructing pitching multipath error items, and subtracting the pitching multipath error items from the pitching residual error sequence to obtain a compensated pitching residual error sequence; s300, carrying out Gaussian test on the compensated pitching residual sequence, calculating statistic, and comparing the absolute difference between two adjacent statistic with a minimum allowable change threshold value: if the absolute difference between two adjacent statistics is smaller than the minimum allowable change threshold, iteratively converging, and outputting a current motion state estimated value and a compensated pitching measurement sequence; If the absolute difference between two adjacent statistics is not less than the minimum allowable change threshold, the iteration is not converged, the next iteration is started, namely, after the weight of each measuring point is updated, the steps S100, S200 and S300 are executed again. Further, step S100 includes the following sub-steps: S110, establishing a target motion model: Wherein, the A discrete time index representing the current time; Representing the motion state of the target at the current moment and containing the target position information Information on target speedI.e.When (1)When the initial motion state of the target is shown, the previous moment is not existedIn the time-course of which the first and second contact surfaces,The time of day is indicated as the last time,Representing the motion state of the target at the last moment; representing a state transfer function; s120, obtaining an estimated value of the target motion state ; S130, extrapolation of target track based on estimated value of target motion stateAnd a target motion model, a sequence of measurement and calculation is obtainedAligned target track sequenceWherein, the method comprises the steps of,Is a positive integer, and represents the total number of times of measurement; Is shown in the first Measuring data obtained at each sampling moment; represent the first Target motion state estimation values at each moment; s140, calculating the measurement residual sequence, namely, measuring the sequence Sequence with ta