Optimization of Schelkunoff Array Using Binary and Real Coded Genetic Algorithm

Antenna array synthesis using Schelkunoff polynomial method is widely used for anti-jamming purpose in military communication where people communicate to each other in presence of other users. Antenna pattern synthesis using Schelkunoff polynomial method may produce high side lobe level. In this paper, optimization methods are used to generate array pattern with reduced side lobe level without much change of main beam width. First, thinned Schelkunoff array are designed by optimization using binary genetic algorithm (BGA) and in the second case, real coded genetic algorithm (RGA) is used to optimize the amplitude of feeding current of the Schelkunoff array to reduce side lobe level. A comparative study between performances of thinned Schelkunoff array using BGA and non-linear amplitude optimized Schelkunoff array using RGA is presented. The research work, presented here may be useful in practical antenna design for anti-jamming purpose, like, military radar communication or adaptive beam forming in smart antenna for mobile communication.