Open AccessSynthesis of a Sparse Planar Phased Array Antenna with Reduced Side-Lobe Level and Beam-Width using Particle Swarm Optimization
Author(s) -
Sivaranjan Goswami,
Kumaresh Sarmah,
Kandarpa Kumar Sarma,
Nikos E. Mastorakis
Publication year - 2021
Publication title -
international journal of circuits, systems and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.156
H-Index - 13
ISSN - 1998-4464
DOI - 10.46300/9106.2021.15.148
Subject(s) - sparse array , side lobe , phased array , particle swarm optimization , antenna array , array gain , planar array , computer science , antenna (radio) , matrix (chemical analysis) , sensor array , algorithm , telecommunications , materials science , machine learning , composite material
Computer aided synthesis of sparse array is a popular area of research worldwide for the application in radar and wireless communication. The trend is observing new heights with the launch of 5G millimeter wave wireless communication. A sparse array has a fewer number of elements than a conventional antenna array. In this work, a sparse array is synthesized from a 16×16 uniform rectangular array (URA). The synthesis includes an artificial neural network (ANN) model for estimation of the excitation weights of the URA for a given scan-angle. The weights of the sparse array are computed by the Hadamard product of the weight matrix of the URA with a binary matrix that is obtained using particle swarm optimization (PSO). The objective function of the optimization problem is formulated to ensure that the PSLL is minimized for multiple scan-angles. It is shown from experimental analysis that apart from minimizing the PSLL, the proposed approach yields a narrower beam-width than the original URA