Seeker Optimization Algorithm for Beamforming of Linear Antenna Arrays

This paper presents Seeker Optimization Algorithm (SOA) to the optimization of current excitation weights and uniform inter-element spacing for the optimal design of hyper beam forming of linear antenna arrays. Hyper beam forming is based on sum and difference beam patterns, each raised to the power of hyper beam exponent parameter for linear antenna arrays. In the SOA, the act of human searching capability and understanding are exploited for the purpose of optimization of the hyper beam pattern. In this algorithm, the search direction is based on empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple fuzzy rule. The simulation experiment is performed on 10-, 14-, and 20-element linear antenna arrays with an objective of obtaining maximum Side Lobe Level (SLL) reduction and much more improved first null beam width (FNBW) for SOA. Finally, the SOA based optimal hyper beam forming designs have proven to be superior in achieving the greatest reduction in SLL and much more improved FNBW, keeping the same value of hyper beam exponent.