Marine Predator Algorithm for Linear Antenna Arrays Optimization

This paper introduces the Marine Predator Algorithm (MPA) for optimal pattern synthesis in linear antenna arrays. Its performance is evaluated in terms of Peak Sidelobe Level (PSLL), mean aperture size, mean amplitude, convergence speed, and radiation pattern. The study also investigates the impact of varying the number of elements in the array and explores two optimization models, including amplitude antenna optimization and position antenna optimization. Simulation results validate the effectiveness of MPA, demonstrating significant improvements over uniform arrays, Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Moth-Flame Optimization (MFO), Cut Swarm Optimization (CSO), and Ant Lion Optimization (ALO).