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Multifunction Radar Signal Environment Cognition Based Time-Frequency Analysis and Fuzzy SVM

The paper presents the reasonable environment cognition model for multifunction radar based on time-frequency analysis and fuzzy Support Vector Machines (SVMs). Aim to extract the signal modulation characteristics corresponding to different multifunction radar task, the Smoothness Pseudo Wigner-Ville distribution and kernel principle component analysis are proposed to extract features of radar signals. Then, these discriminative and low dimensional features achieved are fed to the classifier which is designed based on fuzzy SVM. In simulation experiments, the proposed FVM classifier attains over 82% overall average correct classification rate for five classical multifunction radar signals. Experimental results show that the proposed methodology is efficient for complex multifunction radar signals detection and target environment cognition.