Robust adaptive beamforming using modified constant modulus algorithms

Abstract This paper addresses the self-nulling phenomenon also known as self-cancellation in adaptive beamformers. Optimum beamforming requires knowledge of desired signal characteristics, either its statistics, direction-of-arrival, or response vector. Inaccuracies required information lead beamformer to attenuate if it were interference. Self-nulling is caused by having large power (high SNR) relative interference case minimum variance distortion less beamformer, and low constant modulus algorithm (CMA) which leads suppress lock onto signal. The least-square a prominent blind algorithm. We propose two CMA-based algorithms exploit modularity well DOA avoid beamforming. Simulations results verify effectiveness proposed algorithms.