Synthesis of aperiodic linear antenna arrays based on competition over resources optimization

In the recent years, many heuristic optimization algorithms derived from the behavior of biological or physical systems in nature have been developed. In this paper, we propose a new optimization algorithm based on competitive behavior of group animals. The competition gradually results in an increase in population of wealthy group which gives a fast convergence to the optimization algorithm. In the following, after a detailed explanation of the algorithm and pseudo code, we compare it with particle swarm optimizations as a famous heuristic algorithm. The proposed method is used to determine an optimal set of amplitude weights of antennas and element spacing that satisfy the optimal goal during constant first null beamwidth (FNBW) for aperiodic linear array. It is to be noted that the desired prescribed nulls depth and side lobes level is achieved simultaneously with the narrowest possible FNBW. The proposed algorithm on known array antenna synthesis, shows faster and superior results compared to other optimization algorithms.