DocumentCode :
2227352
Title :
Radar active blanket jamming sorting based on resemblance coefficient cluster
Author :
Tang Zhu ; Zhang Bing ; Li Guang-qiang ; Zhang Chen-long
Author_Institution :
Dept. of Grad. Manage., Air Force Early Warning Acad., Wuhan, China
fYear :
2013
fDate :
5-8 Aug. 2013
Firstpage :
1
Lastpage :
6
Abstract :
A sorting method based on resemblance coefficient cluster is put forward to effectively improve the sorting accuracy of radar active blanket jamming. In the method, resemblance coefficient of blanket jamming is used to replace traditional Euclidean distance; resemblance entropy index is deemed as the symbol for whether iteration comes to an end or not. Besides, K-means classifier is improved accordingly. Improved clustering classifier is used for sorting of radar blanket jamming signals. Simulation experiment proves that the method can improve identification rate of types of radar blanket jamming signals in an efficient way and it is characterized by excellent universality.
Keywords :
jamming; radar signal processing; radar tracking; sorting; K means classifier; clustering classifier; radar active blanket jamming sorting; resemblance coefficient cluster; resemblance entropy index; Accuracy; Entropy; Frequency modulation; Jamming; Noise; Radar; Sorting; Resemblance coefficient; blanket jamming; cluster; identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, Communication and Computing (ICSPCC), 2013 IEEE International Conference on
Conference_Location :
KunMing
Type :
conf
DOI :
10.1109/ICSPCC.2013.6663924
Filename :
6663924
Link To Document :
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