An Improved Adaptive Chaotic Particle Swarm Optimization Algorithm for Antenna Synthesis

The array antenna pattern synthesis has an important application in wireless communications. The traditional optimization method has a poor performance and the standard particle swarm optimization algorithm (SPSOA) is easily trapped in a local optimal solution due to the premature convergence. Therefore, the adaptive chaotic particle swarm optimization algorithm (ACPSOA) is proposed to improve the SPSOA. The ACPSOA adjusts the linearly decreasing weight to the adaptive inertia weight, and then introduces chaos sequence in the iteration process, which improves the search ability of the algorithm and increases the convergence speed. In this work, the ACPSOA is improved and is used to synthesize the array antenna pattern whose efficiency and accuracy are demonstrated by simulation results.