An Adaptive Weighted Magnetic Anomaly Detection Based on Full Magnetic Gradient Orthonormal Basis Function

Magnetic gradient tensor has enjoyed great popularity in magnetic anomaly detection recently. The detection method using the full magnetic gradient orthonormal basis function has been proven to be effective in extracting the target’s magnetic anomaly signal. However, the six energy components obtained by the FMG-OBF detector vary with true energy terms (influenced by the orientation of the target's magnetic moment and the moving trajectories), noise energy terms and middle terms, which largely affects the performance of the total energy. In this paper, an adaptive weighting FMG-OBF method which is based on the sigmoid function to assign appropriate weights for normalized energy components according to their detection performance, is proposed to tackle this concern. Experiments have demonstrated that the proposed method has a higher signal-to-noise ratio from the perspective of signal energy and is less affected by the OTMM compared with the original method.