Multi-Feature-Based Identification of Smart Noise Jamming
Yan Ya · Radar Science and Technology · 2013
Smart noise jamming has become an important jamming to some new radar systems.To deal with the jamming,an anti-jamming method based on multi-feature is proposed in this paper.We build the models of target echo and jamming by analyzing the principle that digital radio frequency memory(DRFM)produces jamming.The envelop fluctuation parameters,the probability in the phase gate,and the box dimension are extracted to represent the difference of waveform,phase and scale between the target and the jamming.Besides,we extract the approximate entropy feature which means signal complexity and has strong robustness against noise.Finally,the support vector machine(SVM)is designed to classify and recognize the different modes.Experiments show that this model has high correct recognition rate for target echo and jamming and it is little affected by jamming to noise rate(JNR).