Robust forward backward based beamformer for a general-rank signal model with real-valued implementation

A robust forward backward (FB) beamformer for an incoherently scattered general-rank signal model with real-valued implementation is proposed based on the uniform linear array (ULA) structure by introducing a preprocessing transformation matrix. With the preprocessing, the computational complexity is reduced significantly due to a real-valued close-form solution for the optimum weight vector; furthermore, the proposed algorithm can achieve a higher output SINR (signal-to-interference-plus-noise ratio) and has lower sensitivity to the diagonal-loading parameters especially for low input SNR (signal-to-noise ratio) scenarios.

► A robust beamformer for an incoherently scattered general-rank model is proposed.
► It is based on the uniform linear array structure with forward backward processing.
► A real-valued close-form solution is provided by introducing a preprocessing transformation.
► Computational complexity of the system is reduced significantly.
► It has achieved a higher output signal-to-interference-plus-noise ratio.