基于先验信息库的多源混合信号快速识别模型
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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.
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.
引文
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[2] HUANG G Q,YUAN Y J,WANG X,et al. Specific emitter identification based on nonlinear dynamical characteristics[J]. Canadian Journal of Electrical&Computer Engineering,2016,39(1):34-41.
[3] ZHU J D,ZHAO Y J,TANG J,et al. Automatic recognition of radar signals based on time-frequency image character[J]. Defence Science Journal,2013,63(3):308-314.
[4] LIANG K Q,HUANG Z,HU D X,et al. An individual emitter recognition method combining bispectrum with wavelet entropy[C]∥IEEE International Conference on Progress in Informatics and Computing. IEEE,2016:206-210.
[5] WANG S Q,ZHANG D F,BI D Y,et al. Radar emitter signal recognition based on sample entropy and fuzzy entropy[C]∥Sino-Foreign Interchange Conference on Intelligent Science and Intelligent Data Engineering. Springer-Verlag,2011:637-643.
[6] XU Y L,WANG J M,XU Z J,et al. Fingerprint feature extraction method for emitters based on wavelet entropy[J]. Journal of Data Acquisition&Processing,2014,29(4):631-635.
[7]普运伟,金炜东,胡来招.雷达辐射源信号瞬时频率派生特征分类方法[J].哈尔滨工业大学学报,2009,41(1):136-140.
[8]普运伟,金炜东,朱明,等.雷达辐射源信号模糊函数主脊切面特征提取方法[J].红外与毫米波学报,2008,27(2):133-137.
[9]普运伟,金炜东,朱明,等.核模糊C均值算法的聚类有效性研究[J].计算机科学,2007,34(2):207-210.
[10]陈杨,陈新年,颜振亚,等.一种综合雷达信号侦察预处理方法[J].现代雷达,2016,38(4):78-81.
[11]江海清,唐浦钊,关文硕.基于脉冲描述字的信号调制识别技术研究[J].北京理工大学学报,2013,33(11):1183-1188.
[12] AKAY O,BOUDREAUX-BARTELS G F. Fractional convolution and correlation via operator methods and an application to detection of linear FM signals[J].IEEE Transactions on Signal Processing,2001,49(5):979-993.
[13]普运伟,侯文太,郭媛蒲同,等.基于模糊函数三维特征的雷达辐射源信号分选方法[EB/OL].控制与决策:1-7(2018-06-26)[2018-07-02]. https:∥doi.org/10. 13195/j. kzyjc,2018. 0144.
[14]张伟.雷达信号分选方法与性能分析[D].西安:西安电子科技大学,2014.
[15]陈昌孝,何明浩,徐璟,等.基于模糊函数相像系数的雷达辐射源信号分选[J].电波科学学报,2014,29(2):260-264.