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

Meng Gao; Hongtao Li; Bixuan Jiao; Yancheng Hong

doi:10.1117/12.2559607

31 December 2019 Simulation research on classification and identification of typical active jamming against LFM radar

Meng Gao, Hongtao Li, Bixuan Jiao, Yancheng Hong

Proceedings Volume 11384, Eleventh International Conference on Signal Processing Systems; 113840T (2019) https://doi.org/10.1117/12.2559607
Event: Eleventh International Conference on Signal Processing Systems, 2019, Chengdu, China

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.

Citation Download Citation

Meng Gao, Hongtao Li, Bixuan Jiao, and Yancheng Hong "Simulation research on classification and identification of typical active jamming against LFM radar", Proc. SPIE 11384, Eleventh International Conference on Signal Processing Systems, 113840T (31 December 2019); https://doi.org/10.1117/12.2559607

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