Double-base MIMO radar angle estimating method based on cross-correlation matrixes

Abstract

The invention discloses a double-base MIMO radar angle estimating method based on cross-correlation matrixes. The method mainly solves that problem that a double-base MIMO radar angle is large in calculation and complex in computation. The achieving steps are as follows: (1) conducting matching and filtering on a radar echo signal, and forming data according to an emission array and a receiving array; (2) respectively constructing cross covariance matrixes by utilizing the formed data; (3) respectively obtaining rectangular projection operators in guide vector null space of the emission array and the receiving array through linear independence of a covariance matrix row vector; (4) obtaining the position of a target relative to the emission array and the receiving array; (5) respectively obtaining rectangular projection operators in guide vector null space of a synchronized array through linear independence of an autocorrelation covariance matrix row vector of the data after matching and filtration, and constructing a cost function for matching angles. The double-base MIMO radar angle estimating method based on cross-correlation matrixes achieves high-precision MIMO radar target angle estimation with small calculation and can be used for locating a target in a radar and communication.

Description

technical field [0001] The invention belongs to the technical field of radar, and in particular relates to a bistatic MIMO radar angle estimation method, which can be used for radar target parameter estimation and detection. Background technique [0002] The estimation of bistatic MIMO radar target relative to the position DOD of transmitting array and the position DOA of receiving array has aroused many scholars' research interest. Most of the research methods are based on eigendecomposition algorithms. For example, K.T.Wong et al. proposed a two-dimensional multiple signal classification algorithm MUSIC on pages 1235 to 1245 of IEEE Transaction On Antenna and Propagation, Volume 48, Issue 8. X. Zhang et al proposed a dimensionality reduction MUSIC algorithm on pages 1161 to 1163 of IEEE Communications Letters, Volume 14, Issue 12. The performance of these two algorithms is similar. Chen Duofang et al. proposed the ESPRIT algorithm for bistatic MIMO radar in Electronics ...

AI Technical Summary

Problems solved by technology

The estimation performance of this algorithm is better than that of the CCM-ESPRIT and JSVD algorithms, but the number of elements in the azimuth and elevation dimensions is limited, which greatly limits the array arrangement; in addition, the azimuth and elevation data received by the L-shaped array involved in this algorithm are independent of each other , while the DOD and DOA data received by the bistatic MIMO radar are contained in the same data, therefore, this algorithm cannot be directly applied to the bistatic MIMO radar angle estimation

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