An Orthonormalized Basis Function based narrowband filtering algorithm for Magnetic Anomaly Detection

Abstract

Countries around the world have paid more and more attention to Magnetic Anomaly Detection (MAD), which is used to detect some magnetic substance. The Orthonormalized Basis Function (OBF) algorithm is a kind of effective method to detect the target signal embedded in the background noise. But in the case that the OBF algorithm does not work well in non-Gaussian noise, an improved algorithm is proposed to enhance the detection capability in this paper. Firstly, a narrowband FIR filter is designed to filter the signal out of the frequency band of the target signal according to the spectrum characteristics of the original signal. Then the filtered signal is decomposed by the OBF algorithm. And the experiment results show that The OBF based on narrowband filtering algorithm can increase the Signal to Noise Ratio (SNR) and enhance the accuracy of the target signal detection. Compared to using the traditional OBF algorithm directly, the improved method has better ability to detect magnetic objects.