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Magnetic Anomaly Detection and Localization Using Orthogonal Basis of Magnetic Tensor Contraction

Huanghuang Jin, Jian Guo, Hongbo Wang, Zhihong Zhuang, Jie Qin, Tonglei Wang

2020IEEE Transactions on Geoscience and Remote Sensing68 citationsDOI

Abstract

In certain scenarios, such as detection of unexploded ordnance (UXO), submarines, and intruders, magnetic anomaly detection (MAD) is an effective method due to the magnetic field advantages of small operating power, strong penetrability, and strong anti-interference ability. However, variability in the background geomagnetic field and low signal-to-noise ratio (SNR) in MAD cannot be avoided. In this article, we propose a MAD method employing an improved orthogonal basis function (OBF) for the magnetic tensor contraction decomposition. The orthogonal basis decomposition approach makes the best use of modeling the MAD output signal, whereas the magnetic tensor contraction aid in avoiding the background field problem. Furthermore, by increasing the baseline length of the magnetic gradiometer, the SNR can also be improved in some manner. A dual magnetic gradiometer framework is introduced to fulfill the demand of the magnetic anomaly localization. From our simulation results, the proposed method improves the SNR of the MAD raw signal and is capable of detecting and locating the magnetic anomaly. Moreover, field test has been carried out to evaluate the performance of the proposed method.

Topics & Concepts

GradiometerMagnetic anomalyMagnetic fieldMagnetometerEarth's magnetic fieldComputer scienceAnomaly detectionSignal-to-noise ratio (imaging)AlgorithmPhysicsArtificial intelligenceGeophysicsOpticsQuantum mechanicsGeophysical and Geoelectrical MethodsGeophysical Methods and ApplicationsEarthquake Detection and Analysis
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