Statistical clutter modeling and parameter estimation for the characterization of buried objects using frequency-domain electromagnetic induction sensing

Mustafa Oezdemir; Eric L. Miller; Alan J. Witten

doi:10.1117/12.396277

22 August 2000 Statistical clutter modeling and parameter estimation for the characterization of buried objects using frequency-domain electromagnetic induction sensing

Mustafa Oezdemir, Eric L. Miller, Alan J. Witten

Author Affiliations +

Proceedings Volume 4038, Detection and Remediation Technologies for Mines and Minelike Targets V; (2000) https://doi.org/10.1117/12.396277
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

The problem of low metal content mine characterization form broadband electromagnetic induction (BEMI) data is addressed. A stochastic model describing the spatial distribution of clutter is developed and methods for estimating and removing this unwanted interference are described and tested. After removing the clutter from the signal, a technique is introduced for extracting from BEMI data information describing the location, orientation and structure of the buried object. Examples are provided for spherical and ellipsoidal mines.

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Mustafa Oezdemir, Eric L. Miller, and Alan J. Witten "Statistical clutter modeling and parameter estimation for the characterization of buried objects using frequency-domain electromagnetic induction sensing", Proc. SPIE 4038, Detection and Remediation Technologies for Mines and Minelike Targets V, (22 August 2000); https://doi.org/10.1117/12.396277

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