81 / 2019-12-13 12:05:00

Robust LCSS Beamforming against DOA Mismatch

IEEE SAM 2020: Full Regular Papers > Adaptive beamforming

One typical adaptive beamforming algorithm is LCMV (Linear Constrained Minimum Variance). The performance of LCMV algorithm relies on the accuracy of the direction of the desired signal and does not take into account where the interference direction is not constant due to its motion. To solve the problem of the fluctuated orientation of interference direction, the LCSS (Linear Constrained Sector Suppressed) approach is a null broadening beamforming based on the correlation matrix of the steering vectors on the predefined sector of direction fluctuation. However, the LCMV beamformer is still sensitive to mismatch between the presumed and actual desired signal direction. In this paper, a robust LCSS (RLCSS) beamformer is presented. The RLCSS algorithm exploits the angle in the region of signal look direction error that has the peak response in the LCSS beampattern in order to determine the quiescent weight of the GSC beamformer and the extended gain vector. Then, utilizing an additional constraint matrix and the extended gain vector in to the LCSS beamformer can provide the robustness against the desired DOA mismatch. Simulation results demonstrate that the RLCSS approach can enhance the LCMV and LCSS beamformers when a mismatch exists. The reconstructed covariance of interference-plus-noise is used especially for the case of high input SNR and small size of snapshot samples available.