A Fibonacci Branch Search (FBS)-Based Optimization Algorithm for Enhanced Nulling Level Control Adaptive Beamforming Techinique

The present work introduced an adaptive beamformer based on a Fibonacci branch search (FBS) based heuristic algorithm is proposed for uniform linear arrays. The proposed optimization technique inspired by the Fibonacci sequence principle, designated Fibonacci branch search (FBS), used the new tree's fundamental branch structure and interactive searching rules to obtain the global optimal solution in the search space. The branch structure of FBS is selected by two types of multidimensional points on the basis of the shortening fraction formed by the Fibonacci sequence; in this mode, interactive global and local searching rules are implemented alternately to reach optimal solutions, avoiding stagnating in local optima. The proposed FBS is also used to construct an adaptive beamforming technique as a real-time implementation to achieve near-optimal performance due to its simplicity and high convergence; the performance of FBS is compared with that of five typical heuristic optimization algorithms. Simulation results demonstrate the superiority of the proposed FBS approach in locating the optimal solution with higher precision and further improvement in the adaptive beamforming performance.