Abstract
The magnetic anomaly signal is polluted by the background noise, and the ferromagnetic target signal is submerged in the noise. To detect the target at low signal-to-noise ratio (SNR), the background noise of magnetic anomaly signal should be suppressed. According to the noise characteristics and the time-frequency characteristics of the ferromagnetic target signal, a method for eliminating the background noise of the magnetic anomaly signal based on wavelet transform is proposed. In this paper, the concept of wavelet transform denoising is introduced, and the wavelet transform denoising algorithm is proposed. The results of simulation and actual verification show that the wavelet transform denoising can effectively remove the noise in the magnetic data and improve the detection ability of the magnetic anomaly at low SNR.
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