Robust adaptive beamforming for general-rank signal models using positive semi-definite covariance constraint
Haihua Chen, Alex B. Gershman · IEEE International Conference on Acoustics Speech and Signal Processing · 2008
In this paper, we develop an improved approach to the worst- case robust adaptive beamforming for general-rank signal models by means of taking into account the positive semi-definite constraint for the mismatched signal covariance matrix. The resulting robust adaptive beamforming problem is solved in an iterative way using semi-definite programming (SDP) at each iteration. Simulation results show that the proposed technique achieves a substantially improved performance as compared to the current robust adaptive beamforming techniques developed for the general-rank signal environments.