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Improved trilinear decomposition‐based method for angle estimation in multiple‐input multiple‐output radar
Author(s) -
Li Jianfeng,
Zhou Ming
Publication year - 2013
Publication title -
iet radar, sonar and navigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.489
H-Index - 82
eISSN - 1751-8792
pISSN - 1751-8784
DOI - 10.1049/iet-rsn.2012.0345
Subject(s) - vandermonde matrix , algorithm , matrix (chemical analysis) , radar , computer science , transformation matrix , least squares function approximation , transformation (genetics) , matrix decomposition , mathematics , telecommunications , eigenvalues and eigenvectors , statistics , physics , biochemistry , materials science , chemistry , classical mechanics , quantum mechanics , estimator , composite material , gene , kinematics
The joint direction of departure and direction of arrival estimation in bistatic multiple‐input multiple‐output radar is considered and an algorithm for the joint estimation is proposed. Through unitary transformation, the transmit direction matrix is transformed to be real‐valued, and through data expansion based on the structure of the Vandermonde‐like matrix, the receive array is twice as long as that of the conventional method. Then the trilinear decomposition can be used to obtain the estimations of the expanded receive direction matrix and real‐valued transmit direction matrix, which contain the angle information. Finally the angles can be jointly estimated by using normalisation and least squares. The proposed algorithm requires no spectral peak searching and can achieve automatically paired estimations of angles, and it has better angle estimation performance and can detect more targets than the conventional trilinear decomposition‐based method. Simulation results verify the performance of the proposed algorithm.

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