A mixing vector based an affine combination of two adaptive filters for sensor array beamforming

Abstract

In this paper, a novel beamformer for adaptive combination of two adaptive filters is proposed for interference mitigation of sensor array. The proposed approach adaptively combines two individual filters by coefficient weights vector instead of one scale parameter and takes the constraint of affine combination into consideration rather than previous studies. Due to the more degrees of freedom offered by the mixing vector, the proposed beamformer significantly improves the convergence and tracking performances of the combined filter under both stationary and non-stationary environments, respectively. Based on the generalized sidelobe canceller (GSC) structure, the optimal mixing vector is derived by Lagrange method, and then several new effective iterative algorithms are developed for its updating in practical implementation. Furthermore, theoretical discussions of the convergent performances and complexities of the proposed iterative algorithms are also investigated to verify the feasibility of the proposed beamformer. Moreover, the proposed methods in application of beamforming for interference mitigation of antenna array are simulated based space-time processing technique. When compared to existing methods, the proposed approach exhibits faster convergence rate and higher output signal to interference plus noise ratio (SINR). Its good behavior is illustrated through simulation results.