Adaptive Beamforming Algorithm based on Generalized Opposition-based Simulated Kalman Filter

Abstract

In this paper, a new population-based metaheuristic optimization algorithm named Generalized Opposition-based
\nSimulated Kalman Filter (GOBSKF) is proposed as adaptive beamforming algorithm. GOBSKF is an improved version of
\nSimulated Kalman Filter (SKF). Adaptive beamforming algorithm based on GOBSKF is compared with previously published work
\nwhich is Adaptive Mutated Boolean PSO (AMBPSO) and Minimum Variance Distortionless Response (MVDR) for different noise
\nlevel. The results show that GOBSKF is proven to be better than AMBPSO and MVDR.