Robust adaptive beamforming for multiple-input multiple-output radar with spatial filtering techniques

• Published in: Signal processing Vol. 143; pp. 152 - 160
• Main Authors: Qian, Junhui, He, Zishu, Zhang, Wei, Huang, Yulong, Fu, Ning, Chambers, Jonathon
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.02.2018
• Subjects: Convex quadratic program; Iterative algorithm; MIMO Radar; Robust beamforming; Robust beamforming; MIMO Radar; Iterative algorithm; Convex quadratic program
• ISSN: 0165-1684; 1872-7557
• DOI: 10.1016/j.sigpro.2017.09.004

•A novel robust design of multiple-input multiple-output radar beamforming with full DoFs is proposed.•A novel jointly estimating the desired signal steering vector and the covariance matrix is proposed.•An iterative alternating method to solve two relaxed convex subproblems is derived, whose convergence is analytically proved.•The covariance matrix estimation method is presented via the matrix rank-constrained minimization method.•The proposed beamformer for MIMO radar can flexibly control the robust region and achieve high output performance. In this paper, we consider robust adaptive beamformer design for multiple-input multiple-output (MIMO) radar systems. The desired transmit-receive steering vector is estimated through maximizing the output power subject to constraints upon correlation coefficient and steering vector norm. The original nonconvex problem is reformulated as two reduced dimension semi-definite programming (SDP) problems. An iterative procedure is devised to tackle the two SDP problems, whose convergence is analytically proven. Based on the estimated desired signal, we are then able to obtain the interference covariance matrix via the matrix rank-constrained minimization method. Compared to other robust adaptive beamforming methods for MIMO radar, the proposed approach has the advantages of high efficiency and accuracy. Simulation results are presented to confirm the effectiveness and robustness of the proposed approach.