A high-accuracy event discrimination method in optical fiber perimeter security system

In the dual Mach-Zehnder perimeter security system, it is difficult to achieve pattern recognition accurately and efficiently. To solve this problem, a pattern recognition method based on short-time Fourier transform(STFT) and singular value decomposition was proposed. In order to realize the accurate distinction of three different events, the method consisted of three steps. Firstly, the time-frequency information was obtained by the short-time Fourier transform of the interference signal, finding the event endpoint and filtering the signal according to the information; And then, the singular value of the time-frequency information was got. The characteristic vectors were defined by the characteristic of singular value, according to the physical meaning of the singular value. Finally, SVM was used to classify the events. In order to verify the effectiveness of the method, a fence system of 2 km long for experiment was built. 360 sets of interference signal data of three events (climbing the fence, knocking the cable, and waggling the fence) were collected, each event had 120 sets of data. The result of experiments demonstrates that the proposed scheme can discriminate three common invasive events with a high recognition rate. The recognition rates of the three events were all above 90%. The scheme also improve signal processing speed of the system, which has high application value.