J4 ›› 2016, Vol. 43 ›› Issue (1): 30-35.doi: 10.3969/j.issn.1001-2400.2016.01.006

• Original Articles • Previous Articles     Next Articles

Iterative dimension-reduced robust adaptive beamformer for MIMO radar

YU Hongbo;FENG Dazheng;XIE Hu   

  1. (National Key Lab. of Radar Signal Processing, Xidian Univ., Xi'an  710071, China)
  • Received:2014-07-20 Online:2016-02-20 Published:2016-04-06
  • Contact: YU Hongbo E-mail:15991279495@126.com

Abstract:

Aiming at the transmitted and received steering vectors mismatch problem, an iterative dimension-reducing robust adaptive beamformer for MIMO radar is presented. The General Linear Combined(GLC) method is applied in MIMO radar to obtain the enhanced covariance matrix estimation, and the transmitted and received steering vectors mismatch model is established. The cost function is established based on the desired signal output power maximum principle to estimate the transmitted and received steering vectors. The bi-iteration method is proposed to solve the cost function and it is merely necessary to find out two low-dimensional convex quadratically constrained quadratic programming(QCQP) problems in per iteration. Simulation results show that the proposed method can obtain the higher output signal-to-noise-plus-interference(SINR) under the condition of severe steering vector mismatch than the conventional robust beamformers, and that the proposed method can converge fast so that it has the lower computational complexity.

Key words: multiple-input multiple-output(MIMO) radar, robust beamformer, quadratically constrained quadratic programming(QCQP), bi-iteration, dimension-reduced