Robust adaptive beamforming based on fast rank-reducing MVB algorithm

Abstract

In ideal cases, assumptions are made that the direction of the desired signal is accurately known and there are no array position errors. But in practice, some errors of DOA estimation and array geometries will bring the uncertainty of steering vector of the desired signal. Then, investigation is needed to solve the beamforming problem when steering vector error is uncertain. In this paper, we propose a robust adaptive rank-reducing minimum variance beamforming (FRRMVB) algorithm with multi-stage Wiener filter (MSWF) to correct the beam-pointing error. By using MSWF, we construct the signal subspace, and use projection method to correct steering vector of the desired signal. By using the different sampling date in radar resting period and working period, we overcome the problem of interference suppression in low signal-to-interference ratio cases. Simulation results show that the proposed algorithm have high robustness over steering vector error. And the algorithm is suitable for engineering applications.