An infrasonic signal detection method based on the time-frequency domain signal energy statistic

Infrasound signal detection is a major procedure in events monitoring, The commonly used STA/LTA (Short Term Average to Long Term Average) and PMCC (the Progressive Multiple Cross-Correlation) methods have too many false detections. So, a algorithm based on TFSES (the Time-Frequency domain Signal Energy Statistic) is proposed according to the distribution difference between the target infrasound signal and the noise in the frequency domain. Firstly, the narrow band frequency division method is used to transform the waveform into the Time-Frequency domain. Then, calculate the ratio of local average energy to that of the global. The signal is detected at the grid while the ratio is greater than the threshold. The method is tested by using the actual monitoring data from the International Monitoring System infrasound stations, and the experimental results are compared with PMCC. It is obvious that the TFSES method in this paper has a good performance in weak infrasound signal detection, can remarkably reduce the amount of false detections.