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, den...
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Veröffentlicht in: | IEEE geoscience and remote sensing letters 2022, Vol.19, p.1-4 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 1545-598X 1558-0571 |
DOI: | 10.1109/LGRS.2021.3071133 |