Array Antenna Pattern Synthesis using Improved Particle Swarm Optimization (IPSO) Algorithm

Abstract

Antenna arrays are used in many different systems, including radar, military systems, and wireless communications. The design of the antenna array has a significant impact on how well the communication system performs. The large number of pieces and the large sidelobe levels provide the biggest design hurdles for such arrays. The antenna arrays have recently been heavily thinned using optimization approaches that take advantage of evolutionary algorithms in order to lower power consumption and enhance the radiation pattern by lowering sidelobe levels. A global optimum for this kind of algorithm is not guaranteed, though, because of the stochastic nature of the resolution techniques. This work characterizes the optimal pattern synthesis of a linear array antenna using the Improved Particle Swarm Optimization (IPSO) algorithm. The main aim is to obtain a low Side Lobe Level (SLL) that avoids interference and a narrow beam width for acquiring high directivity to obtain the optimal solution established on the action of the swarm that adopts the fitness function. To achieve these targets, we analyze the optimization of the excitation amplitude and inter-element spacing of the array. In this article, we have presented the optimal power pattern obtained by two different types of excitation amplitude distributions for both uniformly spaced linear arrays and non-uniformly spaced linear arrays. In the first case of amplitude distribution, namely, non-uniform distribution of excitation amplitude, synthesis of the array pattern for three different values of inter-element spacing as well as optimized spacing are presented for different array sizes. In the second case, optimal thinning of a uniformly spaced array as well as a non-uniformly spaced (optimized) array has been presented. The IPSO algorithm provides a radiation pattern that is used to determine the set of antenna array parameters. The design of an antenna array using the IPSO algorithm gives significant enhancements when compared with a uniformly excited and uniformly spaced array. The flexibility as well as ease of implementation of the IPSO algorithm are evident from this analysis, showing the algorithm’s usefulness in electromagnetic optimization problems.