基于模糊聚类的粒子群算法在雷达组网优化布站中的应用

Application of PSO in Embattling Optimization of Radar Network Based on Fuzzy C-Means Clustering

提出了一种基于模糊C-均值聚类的粒子群算法,将其应用于雷达组网优化布站。定性分析了雷达组网布站原则并对其量化,建立了优化布站的数学模型。为加快求解速度,结合模糊c一均值聚类对标准粒子群算法进行了改进,给出了基于模糊C-均值聚类的粒子群算法在该优化问题中的设计方法,并与标准粒子群算法和遗传算法进行了仿真对比。结果表明,该方法能够快速得出雷达组网优化布站方案,验证了雷达组网布站模型的可行性和改进算法的有效性。

An optimal particle swarm optimization based on fuzzy C-means clustering, which can be applied to embattling optimization of radar network is put forward. The embattling principle is analyzed and the mathematical model is established. To accelerate solving velocity, the particle swarm optimization is improved, and the design method of particle swarm optimization based on fuzzy C-means clustering is presented. Finally, the particle swarm optimization and the genetic algorithm to this problem are simulated, and the feasibility of the model and the validity of the improved algorithm are verified.