Low-Redundancy Large Linear Arrays Synthesis for Aperture Synthesis Radiometers Using Particle Swarm Optimization

Synthesis of thinned linear array geometry with low redundancy is an important problem for one-dimensional aperture synthesis radiometers (ASRs) with high spatial resolution and satisfactory sensitivity. In this paper, a synthesis method of low-redundancy linear array (LRLA) with large numbers of antennas is proposed. Two LRLA patterns are suggested to significantly reduce the tremendous solution space of large LRLA search problem and a strategy is proposed to speed up exploration. Further, particle swarm optimization (PSO) algorithm exploiting the suggested patterns and strategy is applied to the array synthesis. The advantages of the proposed method, in terms of both generating more new large LRLA configurations and reducing computational cost for the large LRLA configuration synthesis problem, are demonstrated by comparing its performance with that of the previously proposed methods. Finally, a number of newly found large LRLA configurations for 28-37 elements are also presented.