摘要
针对复杂环境下传统雷达信号分选处理中由于设定容差难以准确分选的问题,提出一种分层互耦支持向量聚类(SVC)联合类型熵识别的多参数雷达信号分选方法.该方法首先对雷达信号的全脉冲序列进行分层处理,再分别对每个子序列进行SVC聚类,然后引入分层耦合的思想,利用所提取子序列的全部质心,重新进行SVC聚类,将各分层的全脉冲序列中属于同一雷达信号源的子序列连接起来,从而实现对雷达全脉冲序列信号的分选.根据类型熵随信号种类数的增加及信号复杂性的增加而增大的特点,对多参数聚类结果进行类型熵的计算,并将类型熵识别用来辅助信号分选.实验结果表明,对于高脉冲密度环境和复杂的信号形式,提出的方法避免了传统信号分选方法中所面临的容差问题对信号分选的影响,可以实现有效分选.
Focusing on the problem that the conventional radar signal sorting methods based on the tolerance are difficult to accurate sorting in complex and dense pulse environment of modern electronic warfare,a new sorting method is presented based on delaminating coupling and support vector clustering（SVC）.All pulse sequences of radar signals are determined using delaminating processing and then each sub-sequence is separately processed by SVC clustering.Then the idea of delaminating coupling is introduced.And re-SVC clustering is determined by using all centroids of the extracted sub-sequences so that the sub-sequences which belong to the same radar emitter in all pulse sequences of the various layers are connected to achieve the radar full pulse sequence sorting.The character that type-entropy value is getting bigger with the increasing of categories and complexity of pulse signals is used to calculate type-entropy on the multi-parameters clustering results.The type-entropy recognition is used to assist signal sorting.Experimental results show that the system can efficiently sort radar signals in the complex pulses environment and avoid the impact on signal sorting for the tolerance problem in traditional signal sorting methods.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2010年第8期63-67,共5页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(60872108)
第二批中国博士后科学基金特别资助项目(200902411)
第四十三批中国博士后科学基金资助项目(20080430903)
黑龙江省博士后基金资助项目(LBH-Z08129)
哈尔滨科技创新人才研究专项资金资助项目(2008RFQXG030)
中央高校基本科研业务费专项资金资助项目(HEUCFZ1015)
关键词
支持向量聚类
类型熵
雷达信号
信号分选
support vector clustering
type-entropy
radar signal
signal sorting
