Sparse Space-Time Adaptive Processing Methods For Bistatic SAR Clutter Suppression

Bistatic Synthetic Aperture Radar(SAR)can overcome the limitation of Monostatic SAR’s inability to image forward by placing the transmitter and receiver on different platforms.It has the advantages of high flexibility and strong anti-interference ability.With the continuous improvement of demand,Bistatic SAR needs to achieve not only imaging of stationary ground scenes,but also detection and positioning of moving targets to meet the needs of dynamic scene situation awareness.Clutter suppression is the core key and important prerequisite for achieving Bistatic SAR moving target detection.It will mainly face the problem of severe decline in suppression performance of existing methods due to non-stationary characteristics such as Bistatic configuration.Sparse Space-Time Adaptive Processing is an effective way to achieve Bistatic SAR clutter suppression.By utilizing the sparsity of clutter samples,it can effectively estimate the clutter space-time spectrum with only a small number of samples,effectively improving the clutter suppression performance of Bistatic SAR in complex scenarios.This thesis starts from the sparse Space-Time Adaptive Processing clutter suppression of Bistatic SAR,and carries out theoretical analysis and simulation verification around signal modeling,optimization dictionary construction,space-time spectrum estimation,etc.involved in clutter Space-Time Adaptive Processing.The main contents include:1.Researching the geometric relationship between the Bistatic SAR transmitting and receiving platforms and the target scene,constructing the space-time echo model of Bistatic SAR clutter,analyzing the non-stationary and sparse space-time characteristics of Bistatic SAR clutter,laying a theoretical model foundation for subsequent clutter suppression processing research.2.A Bistatic SAR sparse Space-Time Adaptive Processing clutter suppression method based on Local Mesh Shifting is studied.By optimizing the local dictionary construction method and introducing multi-channel Fourier transform calculation,the problems of low accuracy and low efficiency of search methods are solved,and accurate estimation of Bistatic SAR clutter space-time spectrum is achieved.3.A Bistatic SAR sparse Space-Time Adaptive Processing clutter suppression method based on reduced dimensionality atomic norm minimization(RD-ANM)is proposed.By dimensionality reduction processing of ANM method,the problems of high computational complexity and difficulty in setting regularization parameters for ANM method are solved,and effective suppression of non-uniform and non-stationary clutter in Bistatic SAR is achieved.4.A Bistatic SAR sparse Space-Time Adaptive Processing clutter suppression method based on ADMM(Alternating Direction Method of Multipliers)network is studied.By networking the ADMM solution of ANM method,the problems of difficulty in setting parameters for ADMM method and long iteration process are solved,and accurate and efficient suppression of Bistatic SAR clutter is achieved.The above models and methods have been verified by simulation experiments.The experimental results show that the methods proposed in this thesis can effectively suppress non-stationary clutter in Bistatic SAR.