Research On Multidimensional Target Parameter Estimation For MIMO Radar Based On Compressed Sensing

As a new system of radar, MIMO radar has obvious advantages compared with the traditional phased array radar in target detection, beam forming and parameter estimation. In the practical applications of MIMO radar, the targets often only occupy a small number of resolution elements, that is, the target echo signal of MIMO radar is sparse. Therefore, the compressed sensing theory can be applied to the target estimation problem in MIMO radar. In this paper, we design a robust anti-noise adaptive regularized SLO algorithm, and study the problem of estimating the multidimensional parameters of MIMO radar under the condition of ill conditioned sensing matrix and array element failure. The main contents are as follows:(1)In order to improve the anti-noise ability and robustness of SLO algorithm, an adaptive regularization SLO algorithm is proposed. We set the estimated value of residuals in the first iteration and the deviation value of sparse signal estimation before and after the iteration in SLO algorithm as the choice of the regularization parameter. Thus, the signal sparsity and the weight of error tolerance can be adjusted adaptively in the external circulation. During the optimization, the signal sparsity and the weight of error tolerance are maintained for balance. Therefore, reconstruction error of the sparse signal can be effectively reduced, and ability of anti-interference for the SLO algorithm is improved as well.(2)Aiming at the problem that the SLO algorithm is invalid in MIMO radar due to the ill-conditioned sensing matrix, modified truncated singular value decomposition is used to improve the ill-conditioned sensing matrix of MIMO radar.In order to test the performance of the MIMO radar parameter estimation algorithm under the ill conditioned sensing matrix, the testing software of estimation of MIMO radar target parameters under ill-conditioned sensing matrix based on LabVIEW is developed.(3)In order to solve the problem that the target parameter estimation performance of the MIMO radar is reduced due to the failure of the array element,the matrix completion is used to estimate the target parameters of the array MIMO radar. A small amount of random perturbation of the Gauss distribution is superimposed on the lost echo data of the failed matrix element, which can satisfy the matrix completion condition. Then, the matrix completion and the iterative weighted lq method are used to obtain the rough estimation of the target scene vector. Finally, according to the rough estimation value and the sensing matrix of the target scene, the target data received by the fault array element is reconstructed. Thus,the 3D parameters of the target can be estimated with high accuracy.