Noise Suppression Based on Temporal Coherent and It’s Application to Magnetic Anomaly Detection

Magnetic Anomaly Detection (MAD) is commonly used to detect ferromagnetic objects in the environment because of its passive detection characteristics and well detection performance. The interference of geomagnetic background noise is a major challenge in MAD. To suppress the background noise in the collected signal, this paper proposed a MAD algorithm based on temporal coherence of background noise. Firstly, a set of continuous signals is divided into two segments with the same length, one of which contains magnetic anomaly signals and the other only contains background signals. Then, the temporal coherence of the two signals is used to suppress the magnetic noise of background. Finally, the Orthonormal Basic Function (OBF) is applied in order to find out the magnetic anomaly targets efficiently. Compared with most MAD methods, this method only requires one magnetometer, which can save the cost of the detection system. The experimental results show that this method can effectively suppress the geomagnetic background noises and help the MAD.