LSMI Beamformer with Adaptation based on Estimation Error

In adaptive beamforming, computational cost is a critical factor for the beamformer performance. The newest methods employed in robust adaptive beamforming use complex calculations to achieve the highest SINR values, but the computational cost usually increases. So, methods to reduce this cost maintaining relatively high SINR are desired. The idea is to use simple beamforming methods when the SINR performance is reasonable and a more sophisticated method when it degrades below a certain value. Nonetheless, an algorithm that switches between the delay-and-sum and loaded sample-matrix inversion method is presented.