Multi-objective design of monopulse antenna with Two-lbests based multi-objective particle swarm optimizer

Monopulse antennas form an important methodology of realizing tracking radar and they are based on the simultaneous comparison of sum and difference signals to compute the angle-error and to steer the antenna patterns in the direction of the target (i.e., the boresight direction). In this study, we consider the synthesis problem of difference patterns in monopulse antennas from the perspective of Multi-objective Optimization (MO). The synthesis problem is recast as an MO problem, where the Maximum Side-Lobe Level (MSLL) and Beam Width (BW) of principal lobe are taken as the two objectives to be minimized simultaneously. The approached Pareto Fronts are obtained for different number of elements and subarrays using the Two-lbests based multi-objective particle swarm optimizer (2LB-MOPSO). The quality of solutions obtained is compared with the help of Pareto Fronts on the basis of the two objectives to investigate the dependence of the number of elements and the number of sub-arrays on the final solution. Then we find the best compromise solutions for 20 element array and compare the results with standard single objective Particle Swarm Optimization (PSO) that has been reported in literature so far for the synthesis problem. Our experimental results indicate the 2LB-MOPSO yields much better final results as compared to the standard single-objective approach over all considered test cases.