Nonlinear Optimization Algorithm-Based Digital Active Phased Array Antenna Sidelobe Blanking Beam Pattern Synthesis

Recently, research has been proposed using a few components in digital active phased array antennas to achieve sidelobe blanking beam patterns without the need for additional antennas, aiming to mitigate the degradation of radar detection performance caused by interference signals such as clutter and jamming entering through the sidelobes. To precisely obtain the desired sidelobe blanking beam pattern, simulations are required to manually vary the parameters of the components (such as magnitude, phase, and position) and derive an optimal solution. In this study, instead of a manual approach, a reliable synthesis of optimal sidelobe blanking beam patterns is proposed based on pattern synthesis methods and nature-inspired nonlinear optimization algorithms (that is, genetic algorithm and particle swarm optimization) with the magnitude, phase and position of array elements as variables. A comparison of the algorithmic results for the synthesis of the optimal sidelobe blanking beam patterns was performed. The optimization results showed that both algorithms successfully generated patterns capable of blanking sidelobes, with the particle swarm optimization demonstrating convergence at higher fitness levels.