Linear Antenna Array Optimization Using Particle Swarm Optimization Algorithm

The design of efficient antenna arrays is critical for achieving high directivity and low sidelobe levels (SLLs) in modern communication systems, radar applications, and satellites. The optimization of linear antenna array parameters, including excitation amplitude, phase, and element positioning, is a challenging task due to the non-linear and complex inter-dependencies between these variables. Traditional deterministic approaches often suffer from high computational complexity and risk of being trapped in local optima. In this study, the particle swarm optimization (PSO) algorithm is applied to address these challenges. The parameters that are optimized include the elements' excitation amplitude, excitation phase, and positions. PSO is a stochastic algorithm that is known for solving N-dimensional optimization problems. The PSO algorithm is utilized to decide a set of parameters for the array's antenna elements, which provide the desired reduction levels for the sidelobes. The results were verified by comparing them with a similar study that used PSO for linear antenna array optimization. The results showed that the proposed research is very efficient and exhibits a consistent performance with the literature study.