Wavelet Based Noise Reduction for Magnetic Anomaly Signal Contaminated by 1/f Noise
Xin Hua Nie, Zhong Ming Pan, Wen Na Zhang · Advanced materials research · 2014
Magnetic anomaly detection is a passive method for detection of a ferromagnetic target, and its performance is often limited by external noise with a power spectral density of 1/fa, (0<a<2). In consideration of this kind of noise is non-stationary, self-similarity and long-range correlation, an effective noise reduction method based on the wavelet transform is proposed in this paper. The proposed method is only take one parameter into account, while the hard thresholding and soft thresholding methods utilize the relationship of the variance of the noisy signal. The simulation results show that the performance of our proposed method is superior to that of other methods.