LPI radar signal recognition based on high-order time-frequency spectrum features
In view of the low recognition rate of traditional low probability of intercept(LPI)radar signal recognition algorithms under low signal-to-noise ratios,a radar signal recognition algorithm based on high-order time-frequency features was proposed.The proposed algorithm firstly obtained the time-frequency distribution of radar signals by time-frequency transform,and then the power calculation of the time-frequency spectrum was done to obtain the high-order time-frequency image of the signal.The gray gradient co-generation matrix and pseudo-Zernike features of the time-frequency image were extracted and formed into a joint feature vector,and finally,the classification recognition of the radar signal was realized by the support vector machine(SVM).The experimental results show that the overall recognition accuracy of the proposed algorithm can reach more than 95%for eight typical radar signals when the signal-to-noise ratio is-6 dB.
radar signal recognitiontime-frequency transformhigh-order time-frequencyfeature extractionsupport vector machine
万方数据
维普
