Title :
A state space approach to robust adaptive beamforming
Author :
El-Keyi, Amr ; Kirubarajan, Thia ; Gershman, Alex B.
Author_Institution :
Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont.
Abstract :
In this paper, we present a novel approach to implement the robust minimum variance distortionless response (MVDR) beamformer of (S.A. Vorobyov, et al., 2003). This beamformer has been shown to provide excellent robustness against arbitrary but norm bounded mismatches in the desired signal steering vector. However, existing algorithms to solve this problem do not have direct computationally efficient on-line implementations. We develop a new algorithm for the implementation of the robust MVDR beamformer based on state space modelling of the beamforming problem. Our algorithm can be implemented on-line via a second-order extended Kalman filter (EKF) with low computational cost compared to previous second-order cone programming (SOCP) based implementation
Keywords :
Kalman filters; array signal processing; state-space methods; EKF; MVDR beamformer; minimum variance distortionless response; second-order extended Kalman filter; state space modelling; Adaptive arrays; Array signal processing; Communications technology; Computational efficiency; Distortion; Interference; Iterative algorithms; Robustness; Sensor arrays; State-space methods;
Conference_Titel :
Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on
Conference_Location :
Novosibirsk
Print_ISBN :
0-7803-9403-8
DOI :
10.1109/SSP.2005.1628605