Radiation Pattern Reconfigurations of the Antenna Arrays

This book presents a proposed approach for reconfiguring the array patterns of multiple antenna arrays with common excitation weights using optimization genetic algorithms (GA). The proposed methods are based on changing each individual antenna element's phase and amplitude to produce the appropriate radiation pattern. The GA is a powerful optimization technique inspired by the natural process of evolution, which can be used for searching the optimal set of antenna weights. Two strategies for selecting the elements that are shared between the two patterns while maintaining adherence to the appropriate limitations are put forward. The first method uses the central elements of the array as the common elements, while the second method uses the side elements. To achieve lower sidelobe levels, pre-specified common excitation amplitudes can be chosen based on the Gaussian taper. Simulation results demonstrate that the proposed methods can efficiently generate and reconfigure between sum, flat-top, cosecant-squared, and difference patterns, subject to pre-specified constraint masks.