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Implementation of a novel Fibonacci branch search optimizer for the design of the low sidelobe and deep nulling adaptive beamformer

Part of: EuMW Special issue 2019

Published online by Cambridge University Press:  07 January 2020

Haichuan Zhang Open the ORCID record for Haichuan Zhang [Opens in a new window]  and
Fangling Zeng
Haichuan Zhang*
Affiliation:
School of Electronic Countermeasures, National University of Defense Technology, Hefei, China
Fangling Zeng
Affiliation:
School of Electronic Countermeasures, National University of Defense Technology, Hefei, China
*
Author for correspondence: Haichuan Zhang, E-mail: [email protected]
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Abstract

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

Keywords

Fibonacci branch searchglobal optimal solutioninteractive searchingrobust adaptive beamformershortening fraction
Type
Antenna Design, Modelling and Measurements
Information
International Journal of Microwave and Wireless Technologies , Volume 12 , Special Issue 7: EuMW 2019 Special Issue , September 2020 , pp. 660 - 677
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Copyright
Copyright © Cambridge University Press and the European Microwave Association 2020

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