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Simulation research on classification and identification of typical active jamming against LFM radar
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Paper Abstract

In this paper, models of jamming signals are established based on the mechanism of active jamming signals against LFM radar. Five time-domain characteristics and frequency-domain characteristics of jamming signals are extracted. The decision tree method, BP neural network method and decision tree support vector machine (DTSVM) method are used to establish the classification models, and the simulation is performed for identifying and classifying the jamming signals at different jamming-to-noise ratio (JNR). The result shows that the model based on DTSVM method has better adaptability, smaller calculation and higher recognition success rate at low JNR.

Paper Details

Date Published: 31 December 2019
PDF: 8 pages
Proc. SPIE 11384, Eleventh International Conference on Signal Processing Systems, 113840T (31 December 2019); doi: 10.1117/12.2559607
Show Author Affiliations
Meng Gao, Nanjing Univ. of Science and Technology (China)
Hongtao Li, Nanjing Univ. of Science and Technology (China)
Bixuan Jiao, Nanjing Univ. of Science and Technology (China)
Yancheng Hong, Nanjing Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 11384:
Eleventh International Conference on Signal Processing Systems
Kezhi Mao, Editor(s)

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