Robust adaptive beamforming via LMS-like target tracking

This paper presents an algorithm implementing robustness in beamforming, by directly reducing localization errors in the presence of pointing errors or a single moving target. Given an initial position, the desired source signal is first estimated using a classical beamforming unit. It is in a second step, processed by an “LMS-like” gradient stochastic estimation procedure of the steering vector, to adaptively track the correct source position. The newly identified source position is projected over the array manifold, then finally transmitted in a feedback loop to the beamforming unit, closing in this way the global algorithm iteration. The simulation results show that robustness is effectively realized without any compromising output SNR loss. Moreover, they prove an efficient tracking behavior in the presence of mobile sources