Hybrid Algorithms for Suppression of Sidelobes

Antenna array performance is significantly influenced by the presence of sidelobes, which cause unwanted radiation and interference in undesired directions. Traditional sidelobe suppression methods such as amplitude tapering using Dolph-Chebyshev distributions offer controlled sidelobe levels but suffer from limited adaptability and a trade-off between sidelobe reduction and main lobe width. To overcome these limitations, this paper proposes a hybrid optimization algorithm that combines the Invasive Weed Optimization (IWO) and Intelligent Water Drops (IWD) techniques for improved sidelobe suppression in linear antenna arrays. The hybrid approach leverages the global exploration ability of IWO and the local refinement efficiency of IWD to optimize excitation weights dynamically. A multi-objective fitness function is designed to minimize sidelobe levels while maintaining main beam direction and pattern smoothness. Simulation results demonstrate that the hybrid IWO-IWD algorithm achieves superior sidelobe suppression, faster convergence, and better radiation pattern uniformity compared to conventional tapering and single-algorithm methods. The proposed technique offers a computationally efficient and robust solution suitable for modern adaptive beamforming and phased array applications.