摘要
目标编群是态势估计的基础。传统模型大多采用空间上的聚类算法来实现目标编群,但这种方法误分率较高,效果并不十分理想。文章提出了一种新的态势估计中目标编群问题的处理模型。该模型首先应用神经网络对目标目的地做出判断,然后融合多相似性加权测度算法,完成对观测目标的编群。最后运用该模型给出了一个分析示例。
Target clustering is an important component in situation assessment.Traditional theoretical models all make prediction of their behavior after the target clustering.Spatial clustering algorithm and its improved methods are often used to accomplish the process in current solution.This paper presents the model of using the neural networks to predict the target destination in the process.And on this basis,completion the target clustering with the integration of the weighted similarity measure based on multi-clustering algorithm.
出处
《舰船电子工程》
2010年第3期115-118,共4页
Ship Electronic Engineering
关键词
态势估计
目标编群
神经网络
多相似性加权测度
situation assessment
target clustering
neural networks
weighted similarity measure based on multi-clustering
