Title :
Individual Radio Frequency Interference Identification on VHF Radar Based on SVM Classifier
Author :
Huang, Ligang ; Xu, Jia ; Qian, Lichang
Author_Institution :
Dept. Of Electron. Eng., Tsinghua Univ., Beijing, China
Abstract :
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.
Keywords :
VHF radio propagation; chaos; military radar; particle swarm optimisation; radar interference; radar signal processing; signal classification; support vector machines; PSO; SVM classifier; VHF radar signal; battlefield environment; chaotic characteristics; fingerprint feature; nonlinear characteristic; numerical data; particle swarm optimization; radio frequency interference identification; radio frequency interference transient signal; recognition rate; support vector machine classifier; very high frequency radar signal; Classification algorithms; Feature extraction; Radar; Radiofrequency interference; Support vector machines; Training; Transient analysis; PSO; VHF radar; chaos characteristics; support vector machine;
Conference_Titel :
Computer and Information Technology (CIT), 2012 IEEE 12th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4673-4873-7
DOI :
10.1109/CIT.2012.176
