Distributed Passive Radar Imaging Approach Based On Multiple Input Multiple Output System

Distributed passive radar imaging based on multiple input multiple output system refers to a kind of imaging approach that uses transmitter and receiver to observe the target at the same time.Any pair of its transmitters and receivers can form an observation channel,so it can obtain more and wider scope information about the target.This thesis studies distributed passive radar imaging approach based on multiple input multiple output system,focusing on radar imaging based on multiple mesaurement vectors(MMV)model,the grid mismatch problem of imaging and the imaging approach based on gridless compressed sensing.The contents are divided into four parts shown as follows.1.This thesis derived a distributed passive radar echo signal model based on multiple input multiple output system.After that,the non-uniform sparse characteristics of the spatial spectrum of the received sigal by distributed passive radar have been studied,and the model for compressed sensing based distributed passive radar is established.2.A distributed passive radar imaging algorithm based on MMV and truncated singular value decomposition(SVD)is proposed.In order to address the problem of poor imaging accuracy under low SNR ratio of traditional imaging approaches,a distributed passive radar imaging model based on MMV is established.After that,a sparse Bayesian learning imaging algorithm based on truncated SVD is proposed to enhance the robustness of the imaging model to noise by eliminating singular values are obvious for noise amplification.Simulation results verify that the proposed approach has smaller reconstruction error.3.The algorithm based on the OFF-GRID model for distributed passive radar imaging is proposed.A OFF-GRID model of distributed passive radar based on Taylor approximation is established to address the OFF-GRID problem caused by the discretization of the imaging scene.Then,an algorithm based on localized refined grid search is proposed to address the OFF-GRID problme.Simulation results verify that the proposed algorithm effectively solves the OFF-GRID problem.4.The appraoch based on the girdless compressed sensing for distributed passive radar imaging has been studied.The gridless compressed sensing can establish its sparse representation model and conduct the sparse recovery directly in the continuous-valued parameter space without any OFF-GRID peoblem.Therefore,an model based on gridless compressed sensing for distributed passive radar imaging is established.An alternating direction method of multipliers is introduced for model solving to imaging.Simulation results verify that the proposed approach has smaller reconstruction error than the traditional approach.