Noise Suppression for Vector Magnetic Anomaly Detection by Noise Spatial Characteristics Investigation

This letter reports a noise suppression method for vector magnetic anomaly detection (MAD) based on noise spatial characteristics analysis. The environment noise indicates space anisotropy that is essential for noise depression. To find a projection direction
$e$
that allows the projected noise, denoted as
$N_{e} = e\cdot N$
, to have minimum fluctuations, we compute the standard deviation
$\sigma $
of
$N_{e}$
. The projected signal is then processed by a vector orthogonal basis functions (OBFs) detector resulting in a higher signal to noise ratio (SNR) by 3 dB than the traditional OBFs filter. After noise space transformation (NST) processing, the compelling low-frequency noise is suppressed and the weak target signal can be obtained.