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Performance evaluation of uniform linear array for adaptive beamforming using a novel Fibonacci branch algorithm
Author(s) -
Lei Yingke,
Zhang Haichuan,
Zeng Fangling,
Dong Tianbao
Publication year - 2020
Publication title -
international journal of rf and microwave computer‐aided engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.335
H-Index - 39
eISSN - 1099-047X
pISSN - 1096-4290
DOI - 10.1002/mmce.22043
Subject(s) - benchmark (surveying) , algorithm , mathematical optimization , fibonacci number , heuristic , local search (optimization) , computer science , local optimum , metaheuristic , global optimization , construct (python library) , simulated annealing , mathematics , geodesy , discrete mathematics , programming language , geography
A new metaheuristic algorithm Fibonacci branch search (FBS) based on two innovative criteria rules, tree's branches fundamental structure and interactive searching rules, was introduced in this paper and applied to adaptive beamforming (ABF) field for uniform linear array. The global optima in search space can be reached by FBS during the searching process by the fitness evaluation of optimization rules. In this mode, two types of multidimensional points are to construct the branch structure of FBS based on shortening fraction selected by Fibonacci series. Then, the interactive local optimization and global searching rules are implemented alternately to obtain the optimal solutions, avoiding the search points trapping and stagnating in the local optimum. The performance of global searching ability of FBS has been evaluated by standard benchmark functions. It is also used here to construct an ABF technique as a practical issue to improve the nulling level. The simulation results of implemetation of FBS are compared with the five well‐known heuristic optimization algorithms and verfied the superior of the proposed FBS approach in both locating the global optimal solution and higher precision of nulling improvement in the ABF.