Magnetic Anomaly Detection Based on Magnetic Gradient Orthonormal Basis Function and Wavelet Packet

In Magnetic Anomaly Detection (MAD), the method of Orthogonal Basis Function (OBF) is very popular and effective when the background noise subjecting Gaussian distribution. However, the effect of OBF method is usually not very good in practical applications, where the magnetic noise caused by the earth is non-Gaussian distribution. In this paper, a method based on the OBF of magnetic gradient signal and wavelet packet denoising is presented. Firstly, the method of wavelet packet is used to reduce the noise of the measured gradient signals, which can whiten the original signal to obey Gaussian distribution. Then the gradient signals is decomposed into seven components with OBF method. Finally, the sum of the decomposed coefficients of OBF is used to determine whether any anomalies are hidden in the noised signal. The simulated and experimental results show that the method can improve the signal-to-noise ratio and detect the magnetic anomalies effectively.