An Efficient Synthesizing Method for Sparse Linear Scanning Array

This article introduces a novel sparse array synthesis method that provides a possibility to quickly obtain a scanning array with low sidelobe performance. The combination of traditional genetic algorithms and machine learning algorithms greatly reduces the amount of computational time and resources. Both inter element spacing and input amplitude distribution are optimized, and a sparse linear array having 24 elements is synthesized with an aperture of 15.5 wavelength. Compared to traditional genetic algorithms, this method can greatly reduce the synthesis time.