Radar emitter recognition based on wavelet ridge and FSVM

Effective feature extraction and selection are dominant measures to solve the issues of radar emitter signal sorting and classification. Wavelet ridge and high order spectrum analysis are used to extract the features such as the instantaneous frequency, instantaneous phase and amplitude. The feature selection algorithm based on mutual information is provided. Then these obtained discriminative and low dimensional features are fed to a support vector machine classifier based on FCM clustering for multi-class pattern recognition. Experiment results show that the proposed method is efficient for the detection and classification of various complex radar emitter signals.