Application of a Comprehensive Learning Particle Swarm Optimizer to Unequally Spaced Linear Array Synthesis With Sidelobe Level Suppression and Null Control

Abstract

We present unequally spaced linear array synthesis with sidelobe suppression under constraints to beamwidth and null control using a design technique based on a Comprehensive Learning Particle Swarm Optimizer (CLPSO). CLPSO utilizes a new learning strategy that achieves the goal to accelerate the convergence of the classical PSO. Numerical examples are compared to the existing array designs in the literature and to those found by the other evolutionary algorithms. The synthesis examples that are presented show that the CLPSO algorithm outperforms the common PSO algorithms and a real-coded genetic algorithm (GA).Index Terms-Array synthesis, comprehensive learning particle swarm optimizer (CLPSO), genetic algorithms (GAs), linear array design, null control, particle swarm optimization (PSO), sidelobe suppression.

Design of Linear and Circular Antenna Arrays Using Cuckoo Optimization Algorithm

“…This is done to make a comparison of COA with popular evolutionary techniques that has been considered in the past for the same problem such as PSO [8], comprehensive learning particle swarm optimization (CLPSO) [10], chaotic particle swarm optimization (CPSO) [14] inheritance learning particle swarm optimization (ILPSO) [15] and CS [27]. Moreover, in this work, an attempt has been made to compare COA against other popular evolutionary techniques that have not been applied for this problem.…”

“…There are a number of different nature inspired methods that have been used for antenna array synthesis. Among them are genetic algorithms (GA) [1,2], differential evolution (DE) [2][3][4], ant colony optimization (ACO) [5,6], particle swarm optimization (PSO) [7][8][9][10][11][12][13][14][15][16], modified invasive weed optimization (MIWO) [17], firefly algorithm (FA) [18][19][20], biogeography based optimization (BBO) [21][22][23][24] and cuckoo search (CS) [25]. These methods perform better and provide more flexible results than the classical methods for antenna array synthesis.…”

Array Pattern Synthesis Using 4-bit Discrete Digital Shifters by Classic Particle Swarm Optimization

“…PSO algorithm is an evolution algorithm based on the swarm [11], which has been broadly used in the synthesis of antenna array patterns [3,5,[12][13][14]. For a phase control antenna array using discrete digital phase shifter, classic PSO algorithm which aims at continuous optimization problem cannot be directly applied.…”

Pattern Synthesis of Concentric Circular Antenna Array by Nonlinear Least-Square Method

“…There are a wide variety of techniques that have been developed for the synthesis of linear and planar arrays . To complete this kind of optimization, global optimization methods are usually used, such as genetic algorithms (GA) [3][4][5], particle swarm optimization (PSO) [6,7] and differential evolution (DE) algorithm. A hybrid genetic algorithm is used to synthesize desired far-field radiation patterns of conformal antenna array [3].…”

“…A comparison study between phase-only and amplitudephase synthesis of symmetric dual-pattern linear antenna arrays using floating-point or real-valued genetic algorithms is given in [4]. Unequally spaced linear array synthesis with side lobe suppression under constraints to beam width and null control using a design technique based on a comprehensive learning particle swarm optimizer (CLPSO) is presented in [6]. Differential evolution algorithm is used in the synthesis of antenna arrays in [8][9][10].…”