GSAWM for Beamforming and Directivity of Linear Antenna Arrays

In this paper, a new evolutionary optimization algorithm named gravitational search algorithm with wavelet mutation (GSAWM) is adopted for optimal design of hyper beam pattern of linear antenna arrays. Hyper beam is derived from sum and difference beam patterns associated with hyper beam exponent parameter for the array. In GSAWM, particles are considered as objects and their performances are measured by their masses. All these objects attract each other by gravity forces, and these forces produce global movements of all objects towards the objects with heavier masses. GSAWM guarantees the exploitation step of the algorithm and it is apparently free from premature convergence. Extensive simulation results justify superior optimization capability of GSAWM over the afore-mentioned optimization techniques. By optimization of current excitation weights and uniform inter-element spacing, GSAWM achieves optimized hyper beam with much greater reduction in side lobe level (SLL), improved directivity and much more improved first null beam width (FNBW), keeping the same value of hyper beam exponent. The whole simulation experiment has been performed for 10-, 14-, and 20-element linear antenna arrays.