摘要
为了解决雷达信号分选中准确性与实时性相矛盾的问题,提出了一种基于数据流聚类的动态信号分选框架。该框架分为在线和离线两部分,在线部分利用网格帧保存侦察数据的概要信息;离线部分通过网格聚类算法对网格帧进行聚类分选,并得到分选结果。仿真实验表明,该框架能够分选高密度复杂侦察数据流,对噪声不敏感,且无需先验知识支撑,能够较好地满足信号分选准确性和实时性的需要。
In order to solve the contradiction between the accuracy and the real-time in radar signal sorting, a dynamic signal sorting frame based on data stream clustering is proposed. The frame can be divided into two parts, or online part and offline part. In online part, the reconnaissance data is transformed and saved as grid frame. In offline part, the grid frame is sorted with the algorithm of grid-based clustering. Experimental results show that the proposed frame can sort the high density and complex reconnaissance data stream without any prior knowledge, and is not sensitive to the influence of noise. The requirement of accuracy and real-time in signal sorting can be satisfied with this frame.
出处
《电讯技术》
北大核心
2011年第9期65-68,共4页
Telecommunication Engineering
关键词
雷达信号分选
数据流
网格聚类
实时性
radar signal sorting
data stream
grid-based clustering
real-time
