Genetic Algorithms For Optimizing The Segmentation In Subarray Of ADBF Planar Phased Array

Phased array system usually contains thousands of elements. If the received signal of each element is processed separately, namely every element being a receiving channel, hardware cost for signal processing will increase greatly. To reduce the dimension of signal processor, elements are combined to form subarrays and signal processing is applied at subarray level. So it is necessary to study how to segment subarray.Partition subarray is a complicated nonlinear optimization task and traditional linear optimization algorithms do not work. However, GA(genetic algorithm) referring to natural selection and natural inheritance mechanism is used in the area of signal processing more and more for both its enlarge the searching domain and its searching efficiency. Thus GA is the most powerful tool for the task of subarray segmentation。This paper focus on three pasts: coding and decoding of subarray configuration using GA and the realization of its restrictions; subarray partition based on signal objective GA; subarray partition based on multi objective GA. By using coding and decoding methods of"start point", subarray configuration is successfully converted into binary system codes. Meanwhile in the process of segmentation, illegal elements resulted from decoding are corrected by using boundary determination function; subarrays are not overlap by using element status bit; through neighboring judging criterion, every element in the same subarray are neighbors; array is fulfilled by using neighbor insert method.For subarray segmentation based on one target optimization, by the use of GA under the mainlobe and sidelobe interference,jammer is suppressed as well as the enhancement of sidelobe level of the two sum beam sections and output SINR; Finally discussion is on how to optimize sidelobe level of the two sections of difference beam.For subarray segmentation based on MOGA(Multi-Objective Genetic Algorithm ), MOGA based on weighting coefficients, MOGE based on VEGA(Vector Evaluated Genetic Algorithm) and MOGA based on Pareto are used separately to realize the optimization of five targets including output SINR and sidelobe level of two sections of sum and difference beam at the same time.Computer simulations are given based on the proposed methods and also the results analysis. All these demonstrate the correctness of using GA for subarray segmentation in plane phased array.