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Advanced methods of data processing in magnetic anomaly detection (MAD) systems are investigated. Raw signals of MAD based on component magnetic sensors are transformed into energy signals in the space of specially constructed orthonormalized functions. This procedure provides a considerable improvement of the SNR thus enabling reliable target detection.(More)
In many applications, the detection of a visually obscured magnetic target is followed by the characterization of the target, i.e. localization and magnetic moment estimation. Effective target characterization may reduce the detection false alarm rate as well as direct the searcher toward the target. We address the characterization of a static magnetic(More)
—Magnetic anomaly detection (MAD) is a passive method used to detect visually obscured ferromagnetic objects by revealing the anomalies in the ambient Earth magnetic field. In this paper, we propose a method for MAD employing the high-order crossing (HOC) approach, which relies on the magnetic background nature. HOC is an alternative method for spectral(More)
A network of remote magnetic sensors is used for detection of ferromagnetic objects. The magnetic sensors are arranged in gradiometric pairs in order to cancel background noise. For an effective noise cancellation the sensors' readings are synchronized by a smart synchronization technique. Data from the sensors are transmitted via a wireless link, managed(More)
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