Genetic Algorithm-Based Beamforming Using Power Pattern Function

Shuoguang Wang, Shiyong Li, Houjun Sun

Abstract: To solve the beamforming problems of small-scale array, this paper describes a new method using power pattern function and genetic algorithm. Compared with the traditional antenna beamforming methods which utilize the envelope of the radiation pattern, this method can control all the sidelobes quantitatively and form the desired array pattern. For a small-scale array, its envelope is difficult to be quantified and obtained. The proposed method in this paper is more intuitive and reliable to control the sidelobe levels. Using the power pattern optimization method, it can obtain an improved array pattern and fast convergence in small-scale arrays design. Numerical results are presented to verify the convergence and computational efficiency of the proposed method.