A Probability Density Tapering Approach With Fitness Function Model for Linear ArrayThinning

Abstract

In this paper, a new approach for the synthesis of thinned periodic linear arrays featuring a minimum sidelobe level is presented. The approach is mainly based on the probability tapering iterative Fourier technique (PTIFT) with a fitness function model to determine element distributions for large linear array thinning, which is denoted as FPTIFT here. Namely, the fitness function is used to initialize the starting parameters of the position of the elements. Then, a probability density taper is adopted to model the element distributions across the aperture. Compared with the traditional methods, the proposed FPTIFT acquires a minimum sidelobe level and avoids the problem of local optimum. The efficiency of the FPTIFT method was validated by two representative examples of array thinning with minimum peak sidelobe level. This demonstrates that the FPTIFT inherits PTIFT ad-vantages, and results in high efficiency in reducing the side lobes. Therefore, this proposed FPTIFT can be applied in synthesis and optimization of large-scale antenna arrays.