A Novel Hybrid IWO/WDO Algorithm for Interference Minimization of Uniformly Excited Linear Sparse Array by Position-Only Control

This letter introduces a novel, fast, efficient, and global optimization algorithm called hybrid invasive weed optimization and wind-driven optimization (IWO/WDO). The proposed algorithm is implemented to synthesize the uniformly excited (an = 1, Øn = 0) linear sparse array pattern having a minimum sidelobe level (SLL), and null control with constraint on beamwidth to minimize the interference effect by optimizing the element position-only. Three examples of (N = 10, 28, and 32)-element linear array synthesis are considered to illustrate the efficacy of the proposed algorithm. The results are compared to those obtained by IWO, WDO, PSO, CLPSO, DE, and BBO algorithms. Simulation studies demonstrate that this algorithm achieves minimum SLL of -23.5, -13.22, and -19.7 dB as compared to -17.35, -10.5, and -15.70 dB obtained by the IWO algorithm for 10-, 28-, and 32-elements array, respectively. Also, it yields a null depth level (NDL) larger than -84.5 dB in all cases. The learning characteristics show a faster convergence at around 100 iterations. The simulation results demonstrate the improved performance of hybrid IWO/WDO algorithm compared to other six algorithms in terms of null control, minimum SLL, beamwidth control, and the rate of convergence.