A novel adaptive beamforming with reduced side lobe level using GSA

Abstract

Purpose

The purpose of this paper is to present and solve the problem of adaptive beamforming (ABF) for a uniform linear array (ULA) as an optimization problem. ABF mainly concerns with estimation of weights of antenna array so as to direct the major lobe in the direction of desired user and nulls in the direction of interfering signals with reduced side lobe level (SLL).

Design/methodology/approach

The potential of gravitational search algorithm is explored to optimize multi-objective fitness function for ABF using MATLAB software.

Findings

The performance of the algorithm has been compared by considering different number of interference signals at different power levels. The proposed algorithm presents good convergence rate and accurate steering of main lobe and nulls with reduced SLL compared to the well-known ABF technique, namely, minimum variance distortionless response (MVDR) and previously reported results. The simulation results are presented in tabular form.

Research limitations/implications

The present work is limited to simulation. The researchers are encouraged to solve the problem of ABF using the proposed approach in hardware.

Originality/value

The application of proposed algorithm is to optimize multi-objective function for ABF with reduced SLL in linear antenna arrays.

Citation

Sharma, A. and Mathur, S. (2018), "A novel adaptive beamforming with reduced side lobe level using GSA", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 37 No. 6, pp. 2263-2278. https://doi.org/10.1108/COMPEL-07-2017-0311