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 Ne = e center dot 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.

Automated summary

This method suppresses noise in vector magnetic anomaly detection by analyzing noise spatial characteristics and finding a projection direction with minimum fluctuations for the projected noise. By processing the projected signal with a vector orthogonal basis functions (OBFs) detector, a 3 dB higher signal to noise ratio (SNR) is achieved compared to traditional OBFs filters, effectively suppressing low-frequency noise and obtaining weak target signals.