Multichannel SAR-GMTI image domain two-step processing method

Abstract

The invention discloses a multichannel SARGMTI image domain two-step processing method. The method comprises the following steps of performing time delay compensation and channel equalization processing on echo signals subjected to distance pulse compression by taking a reference channel as a benchmark; sequentially carrying out azimuth spectrum compression and dechirping processing on the registered signals, and transferring data to a two-dimensional image domain; performing combined clutter suppression processing on each channel image outside the reference channel and the reference channel image in the two-dimensional image domain to obtain a clutter suppression result; performing constant false alarm detection on each clutter suppression result to obtain a moving target detection result; returning to the image domain before clutter suppression according to the moving target detection result, extracting the joint pixel data of each moving target one by one to perform local joint optimal processing for spectrum estimation, and estimating the radial speed of the moving target; and marking each moving target in the reference channel image, and performing repositioning processing onthe moving targets. According to the invention, high-probability detection and high-precision speed measurement and positioning of a ground moving target can be realized while a static scene is imaged.

Description

technical field [0001] The invention belongs to the technical field of radar signal processing, and in particular relates to a two-step processing method in the multi-channel SAR-GMTI image domain. Background technique [0002] Synthetic Aperture Radar (SAR) transmits broadband signals in the range direction, and forms a long synthetic aperture in the azimuth direction when the platform moves relative to the scene, and can obtain two-dimensional high-resolution images of the ground static scene, while the ground moving target display technology ( Ground Moving Target Indication (GMTI for short) can achieve effective detection and display of ground moving targets by suppressing ground clutter that is far stronger than the target. As a combination of the two, Synthetic Aperture Radar Ground Moving Target Display Technology (SAR-GMTI) can detect and measure moving targets while acquiring high-resolution images of ground static scenes, and locate them at the corresponding positi...

AI Technical Summary

Problems solved by technology

[0003] In practical applications, SAR-GMTI mainly focuses on solving two problems: First, although the backscatter coefficient of moving targets is usually stronger than that of static clutter, in the case of low resolution, the moving target has a smaller size Small, usually appear as a point in a resolution unit, thus submerged in numerous clutter scattering points, so a reliable clutter suppression algorithm is needed to obtain a high enough signal-to-noise ratio to achieve effective detection of moving targets ; Second, the radial velocity of the moving target will cause additional Doppler shift, which will cause it to deviate from its actual position in the image azimuth, so it is necessary to estimate the radial velocity of the moving target with high precision, and then compensate Only by changing the azimuth offset can the moving target be accurately relocated to its true position

[0004] However, in practical applications, the first type of method mainly has two problems: First, the optimal type of method needs to calculate the global covariance matrix when the position of the moving target is unknown, and calculate the peak value of the signal-to-noise ratio pixel by pixel Point search, which will cause a huge computational burden for SAR-GMTI data with a large amount of two-dimensional data; second, when there are channel errors, registration errors, and moving target defocusing, the moving target signal It leaks into its neighboring pixels, resulting in a large deviation when estimating the covariance matrix of clutter and noise data, thereby reducing the effect of clutter suppression, which in turn affects the detection probability and speed measurement accuracy

The second type of method is non-optimal. The energy gain of the moving target after clutter suppression is related to its radial velocity. At certain speeds, the energy of the moving target will be greatly lost after clutter suppression, so that the ideal detection probability and Speed ​​measurement accuracy

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