Linear Array Geometry Synthesis Using Genetic Algorithm for Optimum Side Lobe Level and Null

Adaptive antenna arrays for radar and communication applications have been the subject of considerable interest during the last few decades. This paper describes the synthesis method of linear array geometry for side lobe level and null control using the Genetic Algorithm. Genetic Algorithm is an iterative stochastic optimizer that works on the concept of survival of the population values based on the fitness value.  An adaptive genetic algorithm has been used in linear array to optimize the excitation levels of the elements resulting in a radiation pattern with minimum side lobe level and desired null position. The algorithm encodes each parameter into binary sequences, called a gene, and a set of genes is a chromosome. These chromosomes undergo natural selection, mating, and mutation, to arrive at the final optimal solution. Two design examples are illustrated to show the optimization of linear antenna array using genetic algorithm. MATLAB simulations are done for performance evaluation.