基于MOPSO算法的卫星共形阵列天线多波束形成

针对共形阵列天线多波束方向图综合问题，提出一种基于最大方向性系数方法得到初始非劣解的多目标粒子群算法，求解满足多个期望波束和低副瓣要求的Pareto最优解。算法首先采用多目标分解策略，由多个单波束最优解的加权线性组合得到近最优解的非劣解。然后结合该非劣解，基于粒子空间和目标空间同时约束的局部搜寻策略，使用多目标粒子群算法优化多个波束，并降低副瓣。仿真结果表明，该算法有效地实现了卫星共形阵列天线的多波束形成和低副瓣，且能快速得到Pareto最优解分布。

Multi-beam Forming of Satellite Conformal Array Antenna Based on Multi-objective Particle Swarm Optimization

In this paper, a multi-objective particle swarm optimization (MOPSO) with an initial non-inferior solution from maximizing directivities of conformal antenna array is proposed to get Pareto optimal solutions for desired multi-beam and low sidelobes. The proposed algorithm first uses multi-objective decomposition strategy to get a non-inferior solution by the weighted linear combination of multiple single-beam optimal solution. Then, the local search strategy based on the particle space and target space constraints at the same time in MOPSO is designed to achieve optimization of multi-beam and sidelobes. Results indicate that the approach can effectively get Pareto optimal solutions for multi-beam forming with low sidelobes of the satellite conformal array antenna.