Angle and mutual coupling estimation in bistatic MIMO radar based on PARAFAC decomposition

• Published in: Digital signal processing Vol. 65; pp. 1 - 10
• Main Authors: Wen, Fangqing, Xiong, Xiaodong, Zhang, Zijing
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.06.2017
• Subjects: Angle estimation; Bistatic MIMO radar; Mutual coupling; PARAFAC decomposition; Mutual coupling; Bistatic MIMO radar; Angle estimation; PARAFAC decomposition
• ISSN: 1051-2004; 1095-4333
• DOI: 10.1016/j.dsp.2017.02.011

In this paper, a PARAFAC decomposition-based algorithm is developed for joint direction-of-departure and direction-of-arrival estimation in the presence of unknown mutual coupling for bistatic multiple-input multiple-output radar. A three-order tensor is formulated which links the estimations of coupled direction matrices to the PARAFAC model. The coupling effects of the direction matrices are compensated by two selective matrices, and the angles are obtained from the estimated direction matrices. Then the mutual coupling coefficients of the transmitter and the receiver are estimated using the subspace method. Unlike existing algorithms, PARAFAC decomposition before decoupling operation results in more accurate angle estimation, which brings better mutual coupling coefficients estimation than the ESPRIT-Like and unitary HOSVD methods. The proposed algorithm does not require spectral peak searching or eigenvalue decomposition of the received signal covariance matrix, and it can achieve automatic pairing of the estimated angles. The identifiability and computation complexity of the presented algorithm are analysed and Cramer–Rao bounds of joint angle and mutual coupling estimation are derived. Numerical experiments verify the effectiveness and improvement of our algorithm. •A new method is developed for MIMO radar angle estimation with mutual coupling.•The proposed method brings no virtual aperture loss.•It achieves more accurate angle estimation performance than the existing methods.•The proposed method is more efficient with massive antennas.