Robust Array Beamforming via an Improved Chicken Swarm Optimization Approach

Robust array beamforming is a challenging task in radar, sonar and communications due to the influence of direction arrival (DOA) mismatch sensor position errors. However, how enhance robustness key issue antenna arrays. The current paper focuses on novel approach called improved chicken swarm optimization (ICSO) method settle model conventional linearly constrained minimum variance (LCMV) based support vector machine (SVM) against problems as well control sidelobe level (SLL). As far ICSO concerned, considering that particle (PSO) algorithm has outstanding convergence performance early iteration, dominance alpha wolf grey (GWO) innovative mutual attraction mechanism firefly (FA), we introduce these three strategies into solution update (CSO) for achieving better capability. Moreover, an operation removing duplicate solutions proposed utilization population. In terms SVM-based LCMV algorithm, adopt so-called linear ε - insensitive loss function reconstruct final cost by penalizing errors between actual ideal responses. Finally, conduct simulations evaluate intelligent algorithms under scenario without with mismatch, respectively. And results demonstrate developed obtains excellent different scenarios compared PSO, FA, GWO CSO algorithms.