DOA Estimation Method for Mimo Radar System Based on Weighted Minimization of l1 Norm Method in Real Domain

Abstract

The invention relates to the technical field of an MIMO radar system, especially relates to applications of MIMO radar system DOA estimations, and specifically relates to an MIMO radar system DOA estimation method based on a real domain weighting minimization l1-norm method. The method comprises following steps: reducing dimensions of received data by the use of dimension reduction matrixes; decomposing singular values and acquiring a model corresponding to a sparse representation framework; designing a weight matrix in which diagonal elements correspond to real domain MUSIC spectrums according to the orthogonality of real domain steering vectors and corresponding noise subspaces so as to solve an MMV problem; and estimating object DOA in the MIMO radar system. According to the invention, SNR gains are enhanced through dimension reduction transition, the designed weighting l1-norm better approaches the l0-norm, and sparse solutions are enhanced. Compared with an l1-SVD algorithm and an RV l1-SVD algorithm, the method can achieve a higher resolution.

Description

technical field [0001] The present invention relates to the technical field of MIMO radar systems, in particular to the application of DOA estimation in MIMO radar systems, specifically a method based on real domain weighted minimization l 1 DOA Estimation Method for MIMO Radar Systems by Norm Method. Background technique [0002] In recent years, due to the multiple-input multiple-output (MIMO) array radar system (IEEE Signal Processing Magazine, 2007, 24(5): 106-114) compared with the traditional phased array radar system great attention has been paid to its potential advantages. Angle estimation is a critical issue in MIMO radar systems. For this problem, some subspace-based methods, such as the MUSIC algorithm (IEEE Trans. Antennas and propagation, 1986, 34(3): 276-280) and the ESPRIT algorithm (IEEE Trans. Signal Process., 1989, 37(7): 984-995), which have been applied in angle estimation for MIMO radar systems. On the other hand, using the special structure of MIMO...

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Problems solved by technology

But this faces two major problems: 1) It is only applicable to the single-measurement vector recovery problem

However, the multi-measurement vector recovery problem is involved in the DOA estimation of the MIMO array system; 2) In the MIMO radar system, a two-dimensional complete dictionary is required to recover the sparse array, which may fail when recovering the sparse matrix

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