优化FCM算法在海面目标监视雷达信息处理中的应用

Application of optimal FCM algorithm to information processing of sea-surface target surveillance radar

海面目标监视雷达能够实现目标回波的自动采集、自动跟踪,已在多个工程项目中推广应用.鉴于在海面目标监视雷达对目标侦测过程中,会出现多个反射点、多个回波的目标簇,提出将优化的模糊C-均值(FCM)聚类算法用于目标回波信息处理.该算法基于形状参数的密度法选择初始聚类中心,采用一种基于核依赖的距离函数.实验结果表明,与传统FCM算法相比,优化FCM算法在海面监视雷达对目标信息处理的运用中可以得到更好的聚类效果.

The sea-surface target surveillance radar can implement the automatic acquisition and tracking for the echoes of sea-surface target, which has been applied to many projects. Considering that there would occur target cluster with multiple reflection points and echoes in the process of sea-surface target surveillance radar detecting the targets, this paper brings forward applying an optimal fuzzy C-mean (FCM) clustering algorithm to the target echo information processing. Based on the density method of shape parameters, this algorithm selects the initial clustering center and employs a kernel-based range function. Experimental results show that the optimal FCM algorithm can achieve the better clustering effects than the traditional one, in the application of sea-surface surveillance radar to target information processing.