Joint Optimization of Peak Sidelobe Level Suppression of Three-Dimensional Linear Array

Abstract

Collaborative beamforming (CB) is a recent technology inspired by antenna array, successfully extending the transmission range and transmission power of a single sensor node in wireless sensor networks (WSNs). However, the random location of sensor nodes that formed virtual antenna array (VAA) yield high peak sidelobe level (PSL) of CB. Thus, previous studies have proposed node selection schemes to further reduce PSL by selecting several sensor nodes to form linear, circular and concentric circular of VAA. Nevertheless, the proposed schemes only suppress the PSL in azimuth direction. Hence, we propose a joint optimization of PSL suppression (JOPS) to mitigate the PSL of beampattern in azimuth and elevation angles by optimizing the inter-element spacing of linear array arranged in three-dimensional spaces. Since the PSL suppression is a complex and non-linear problem, we deployed four optimization algorithms which are Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Backtracking Search Algorithm (ICA) and Imperialist Competitive Algorithm (ICA). The performance of the algorithms is compared in terms of PSL reduction and optimization execution time of 10 and 20 linear array. Based on the results, all algorithms managed to reduce PSL of beampattern in both directions compared to uniform linear array (ULA).