A Novel Composite Genetic Algorithms for Optimization of Antenna Array Patterns

All the parameters of beamforming are usually optimized simultaneously in implementing the optimization of antenna array pattern with multiple objectives and parameters by genetic algorithms (GAs). Firstly, this paper analyzes the performance of fitness functions of previous algorithms. It shows that original algorithms make the fitness functions too complex leading to large amount of calculation, and also the selection of the weight of parameters more sensitive due to many parameters optimized simultaneously. This paper proposes a kind of algorithm of composite beamforming, which detaches the antenna array into two parts corresponding to optimization of different objective parameters respectively. New algorithm substitutes the previous complex fitness function for two simpler functions. Both theoretical analysis and simulation results show that this method simplifies the selection of weighting parameters. Furthermore, the algorithm has better performance in lowering side lobe and interferences in comparison with conventional algorithms of beam forming in the case of little widening the main lobe