PFMD: A Power Frequency Magnetic Anomaly Signal Detection Scheme Based on Synchrosqueezed Wavelet Transform

Abstract

Magnetic anomaly signal detection (MASD) is a passive method for the detection of visually obscured ferromagnetic objects. This paper proposes a new method for MASD based on the ambient field of power frequency magnetic (power transmission line system). Moreover, a new information extraction technique is extended by employing Synchrosqueezed Wavelet Transform (SSWT) to improve the accuracy of the MASD method. With the extended information extraction technique, the time-frequency information of the anomalies can be efficiently distinguished from the power frequency magnetic anomaly signal. The multi-component of the time-frequency information is separated by extracting the time-frequency ridges in the spectrogram. The complexity of time-frequency information is evaluated using Rayleigh entropy. Compared with the continuous wavelet transform and short-time Fourier transform, the Rayleigh entropy of our method is reduced by 4.1886 and 4.3623, respectively. Finally, the efficiency of the new method is verified by the outfield experiments.