Gradient signals analysis of scalar magnetic anomaly using orthonormal basis functions

Magnetic anomaly detection (MAD) is passive and effective approach for detecting the magnetic targets. The orthonormal basis functions (OBFs) method based on one scalar magnetometer is widely used in magnetic anomaly detection, in which the magnetic anomaly signal is decomposed into three OBFs and the coefficients of each function are designed to detect the anomaly. During the detection using one scalar magnetometer, the temporal magnetic variations will affect the detection performance. In order to reduce the influence of magnetic variations on the detection, we focus on the analysis of magnetic gradient signal and obtained four OBFs of gradient signal. Based on the set of OBFs, we propose an improved detection method using the magnetic gradient signal. The proposed method is validated by real-word magnetic noise. The results show that the proposed method has a good detection performance with low signal noise ratio and can be improved the detection probability of weak magnetic anomaly in complex magnetic field environment.