Adaptive Beamforming Algorithm based on Generalized Opposition-based Simulated Kalman Filter
Kelvin Lazarus, Noordin Nurul Hazlina, Kamil Zakwan Mohd Azmi, Abdul Aziz Nor Hidayati, Zuwairie Ibrahim · UMP Institutional Repository (Universiti Malaysia Pahang) · 2016
In this paper, a new population-based metaheuristic optimization algorithm named Generalized Opposition-based Simulated Kalman Filter (GOBSKF) is proposed as adaptive beamforming algorithm. GOBSKF is an improved version of Simulated Kalman Filter (SKF). Adaptive beamforming algorithm based on GOBSKF is compared with previously published work which is Adaptive Mutated Boolean PSO (AMBPSO) and Minimum Variance Distortionless Response (MVDR) for different noise level. The results show that GOBSKF is proven to be better than AMBPSO and MVDR.