基于FIR与正交基分解的磁性目标检测方法

Magnetic Object Detection Method Based on FIR and Orthonormalized Functions Decomposition Algorithm

针对磁异常探测中,磁性目标信号被噪声淹没,信噪比较低的情况,提出了FIR与正交基分解相结合的检测方法。先利用FIR低通滤波器滤除高频噪声,保留磁性目标磁异常信号,再利用正交基分解检测算法,大幅度提升磁性目标信号的信噪比,从而实现磁性目标检测。仿真试验结果表明,该方法可以提升磁性目标检测能力,具有一定的工程应用价值。

Aiming at the low SNR in magnetic anomaly detection ,a new algorithm was proposed using FIR low‐pass filter integrated into orthonormalized functions decomposition algorithm .Firstly the FIR low‐pass filter was constructed to filter the high frequency noise in the raw signal .Then the disposed signal was decomposed by orthonormalized functions de‐composition algorithm to increase SNR .The simulation result demonstrated the method can increase the detection ability of magnetic object and possesse engineering application value .