摘要
先验信息库识别是雷达信号分选的前置环节,可以有效提高前端处理效率并指导未知信号分选识别。随着复杂体制雷达大规模应用,信号参数空间严重交叠,传统处理方法面临严峻考验。该文提出一种结合传统脉冲描述字、瞬时频率特征及模糊函数主脊切面特征的先验信息库构建方法,首先,对信号进行多维度表征,然后,使用相像系数度量特征间相似性,最后,利用具备有效性评价的核模糊聚类算法对未知信号进行自动聚类。实验结果表明,所提方法可在传统方法几乎失效的情况下有效稀疏多源混合雷达信号,准确过滤未知信号,并为未知信号分选提供指导。
The identification of the apriori information database is the upfront segment of radar signal sorting,which can effectively improve the efficiency of front-end processing as well as guide the sorting of the unknown signals. The signals parameter space is severely overlapped due to the large-scale application of radar mechanisms with complex systems,so the traditional processing methods are facing severe challenges. A constructing method of apriori information database library that combines traditional pulse description words (PDW) and the features of instantaneous frequency (IF) and ambiguity function main ridge (AFMR) is proposed. First,signal can be described in multidimension. Then,similarities between the features would be measured according to resemblance coefficients (RC). Finally,the kernel fuzzy clustering algorithm with valisity assessment is used to automatically cluster the unknown signals. The experimental results show that the proposed method can effectively simplify the multi-source hybrid radar signals when the traditional method is almost ineffective. At the same time,the unknown signals can be accurately filtered,and the method provides a guidance for the classification of unknown signals.
作者
普运伟
马蓝宇
郭媛蒲
侯文太
PU Yunwei;MA Lanyu;GUO Yuanpu;HOU Wentai(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China;Computer Center,Kunming University of Science and Technology,Kunming 650500, China)
出处
《西北大学学报（自然科学版）》
CAS
CSCD
北大核心
2019年第4期588-596,共9页
Journal of Northwest University（Natural Science Edition）
基金
国家自然科学基金资助项目(61561028)
关键词
先验信息库
复杂电磁环境
雷达辐射源
模糊函数主脊切面
信号分选识别
apriori information database
complex clectromagnetic environment
radar emitter signal
ambiguity function main ridge
signal sorting and recognition
