Individual Radio Frequency Interference Identification on VHF Radar Based on SVM Classifier

To realize individual radio frequency interference identification on the very high frequency (VHF) radar signals, a nonlinear characteristic, namely, the chaotic characteristics of the radio frequency interference transient signal is studied and proved to be the fingerprint features of the individual radio frequency interference on VHF radar signals. Furthermore, the support vector machine classifier based on particle swarm optimization(PSO) is designed. Finally, The numerical and real data have proved that this method is not only effective but also still has a high recognition rate in the case of small samples to adapt to the battlefield environment, and has broad application prospects.