Bistatic Inverse Synthetic Aperture Radar Imaging Technology Based On Grid Mismatch

Bistatic inverse synthetic aperture radar?ISAR?imaging based on compressed sensing can reconstruct high resolution images with a small amount of observation data,become hot research direction in recent years.The traditional compressed sensing method assumes that the target is on the pre-divided grid.However,when the actual target is not on the grid point exactly?that is,the grid mismatch occurs?,the reconstruction performance will decrease dramatically,resulting in the reduction of the imaging resolution.In view of the problems,the grid mismatch error is introduced in this thesis and propose a new algorithm to solve the grid mismatch problem based on the in-depth study of bistatic ISAR imaging with compressed sensing.The main work is summarized as follows:1.Based on the principle of compressed sensing,using fractal dimension processing method,the distance and azimuth echo signals of bistatic ISAR are reconstructed and reconstructed,and the bistatic ISAR imaging based on compressed sensing is realized.Based on the geometric structure of bistatic ISAR,a bistatic ISAR echo signal model is constructed.Based on the geometric structure of bistatic ISAR,a bistatic ISAR echo signal model is constructed;using the compressed sensing theory,the distance image is recovered by using a phase-preserved basis in distance dimension,in azimuth dimension,the azimuth image is restored directly using the standard Fourier basis,thus the bistatic ISAR distance azimuth image is realized.The simulation results verify the correctness of the bistatic ISAR imaging algorithm studied in this thesis.2.In order to solve the sharp decline of the recovery performance caused by grid mismatch,a basis shift algorithm is proposed in this thesis.The base shift algorithm achieves the effect of refine grid by multiple moving grids?The size of each movement and total distance are controlled within a grid spacing?,reducing the grid mismatch error.At the same time,not increase the cross correlation of the reconstruction matrix,and avoid the defect of the subdivision grid to the signal reconstruction.The final simulation results verify the effectiveness of bistatic ISAR imaging based on the basis shift algorithm.3.In order to solve the problem of increasing the matrix cross correlation brought by the refine grid,the BOMP algorithm is introduced into the bistatic ISAR imaging,and an improved BOMP algorithm is proposed for the bistatic ISAR imaging algorithm.The algorithm inhibition of the cross band of selected column atoms while refine the grid,solves the problem that the subdivision grid enhances the correlation of the matrix,and improves the performance degradation of the bistatic ISAR imaging in the grid mismatch.Considering that the sparse degree of measurement signal on sparse basis is not easy to solve when realized,the iterative termination condition is modified to be based on the termination of threshold detection in this thesis.The ₂l norm of the residual signal is compared with the threshold set in advance,and the iteration is terminated when the threshold exceeds the threshold.Simulation results verify the effectiveness of bistatic ISAR imaging based on the improved BOMP algorithm.The research results in this thesis will provide a new theoretical basis for the safe and reliable high-resolution imaging in the field of space monitoring,navigation guidance and land defense.