A robust adaptive array beamformer using particle swarm optimization for space–time code division multiple access systems

Abstract

An adaptive beamformer often suffers from severe performance degradation when a mismatch exists in the steering vector of interest. In this study, a new approach to the robust adaptive beamforming technique is proposed based on minimum variance distortionless response (MVDR) for space–time systems. The proposed method combines particle swarm optimization (PSO) and Taylor series expansion to enable the use of direction-of-arrival (DOA) estimation. Taylor series expansion can be robust to pointer errors for the presumed steering vector. However, the Taylor approach is easily trapped at a local minimum, causing errors in DOA estimation. Therefore, a more accurate DOA estimate is necessary for MVDR beamforming. To resolve this problem, a DOA estimation approach featuring a high resolution and low computational load is presented in this paper. An initial DOA estimate is first determined using a PSO estimator. Next, the predominant DOA estimate is sent to the Taylor series expansion-based estimator to form an estimate. Several simulation results are provided to demonstrate the effectiveness of the proposed approach.