Fast optimization of sparse array antennas based on improved fruit fly algorithm

Inhalt:
The sparse array antenna optimization is a high dimensional optimization task, and the speed of optimization is usually slow. In order to improve the efficiency to the sparse array antenna’s optimization, under the constraints of fixing the aperture, the number of elements and the minimum element spacing of the sparse array, a linear generation mechanism of candidate solution based on fruit fly algorithm (LGMS-FOA) was applied. Through the best memory information of individual history and group global history, constitute a multi-strategy hybrid co-evolutionary search mechanism. LGNS-FOA is used to optimize the position of element, and the antenna gain calculation method without integration is applied to obtain higher antenna gain and realize the fast calculation.