Thumbnail
Access Restriction
Open

Author Dautta, Manik ♦ Faruque, Rumana Binte ♦ Islam, Rakibul
Source United States Department of Energy Office of Scientific and Technical Information
Content type Text
Language English
Subject Keyword CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS ♦ DETECTION ♦ DISTRIBUTION ♦ ELECTROMAGNETIC FIELDS ♦ INTERFACES ♦ LOSSES ♦ MAGNETIC DIPOLES ♦ MATHEMATICAL MODELS ♦ NOISE ♦ PROBABILITY ♦ SIGNALS ♦ SIGNAL-TO-NOISE RATIO ♦ SIMULATION
Abstract Magnetic Anomaly Detection (MAD) system uses the principle that ferromagnetic objects disturb the magnetic lines of force of the earth. These lines of force are able to pass through both water and air in similar manners. A MAD system, usually mounted on an aerial vehicle, is thus often employed to confirm the detection and accomplish localization of large ferromagnetic objects submerged in a sea-water environment. However, the total magnetic signal encountered by a MAD system includes contributions from a myriad of low to Extremely Low Frequency (ELF) sources. The goal of the MAD system is to detect small anomaly signals in the midst of these low-frequency interfering signals. Both the Range of Detection (R{sub d}) and the Probability of Detection (P{sub d}) are limited by the ratio of anomaly signal strength to the interfering magnetic noise. In this paper, we report a generic mathematical model to estimate the signal-to-noise ratio or SNR. Since time-variant electro-magnetic signals are affected by conduction losses due to sea-water conductivity and the presence of air-water interface, we employ the general formulation of dipole induced electromagnetic field propagation in stratified media [1]. As a first step we employ a volumetric distribution of isolated elementary magnetic dipoles, each having its own dipole strength and orientation, to estimate the magnetic noise observed by a MAD system. Numerical results are presented for a few realizations out of an ensemble of possible realizations of elementary dipole source distributions.
ISSN 0094243X
Educational Use Research
Learning Resource Type Article
Publisher Date 2016-07-12
Publisher Place United States
Volume Number 1754
Issue Number 1


Open content in new tab

   Open content in new tab