Abstract:
A mean variance mapping optimization algorithm for three types of antenna array synthesis examples is presented. Mean variance mapping optimization is based on the strategic transformation used for mutating the offspring built on mean variance of a certain dynamic population. The first set of examples is based on side-lobe suppression and null control by controlling element positions with mean variance mapping optimization under constraints to beam width. In the second group of examples, mean variance mapping optimization becomes an optimization tool to calculate the amplitude and phase values of antenna array elements to synthesize shaped beams. In the last set of examples, mean variance mapping optimization is used to mitigate the effect of failure elements on the pattern by recalculating the amplitude values of remaining elements. Additionally, a modification that provides a good balance between exploitation and exploration is applied to the mean variance mapping optimization algorithm to improve its stability and accuracy. The simulation results showed that the proposed mean variance mapping optimization is an effective and easy implementable technique for different antenna array synthesis problems.