Bistatic ISAR sparse aperture maneuvering target translational compensation imaging algorithm

Abstract

For bistatic inverse synthetic aperture radar (Bi-ISAR), the non-uniform motion state of maneuvering target and the time-varying bistatic angle make the traditional imaging method of moving target face the problem of translation compensation, and the traditional translation compensation method is not suitable for the return wave in the case of sparse aperture. In this paper, a compensation imaging method combining two-dimension joint linearized Bregman iteration and image contrast search is proposed. The translation compensation problem can be transformed into two-dimension joint compressed sensing sparse reconstruction and moving target motion parameter estimation.The proposed algorithm makes use of the gain of echo twodimension compression, greatly improves the accuracy of translation compensation and the quality of target image and has stronger robustness to noise. The processing results of simulation data verify the effectiveness and superiority of the algorithm.

Research on Bi–ISAR Sparse Aperture High Resolution Imaging Algorithm under Low SNR

“…By reasonably presetting the modal decomposition value, the phenomenon of modal aliasing and end-point effect can be effectively suppressed, which has attracted extensive attention of scholars [27,28]. On the other hand, some scholars have applied deep learning technology to signal noise reduction, but this requires a large number of sample sets and is not supported by systematic mathematical theory [29,30]. A Bi-ISAR sparse aperture imaging algorithm based on CVMD and wavelet threshold de-noising under low SNR is proposed in this paper, the proposed algorithm can avoid the shortcomings mentioned above.…”