Application of the theory of optimal experiments to adaptive electromagnetic-induction sensing of buried targets.
Journal Article (Journal Article)
A mobile electromagnetic-induction (EMI) sensor is considered for detection and characterization of buried conducting and/or ferrous targets. The sensor may be placed on a robot and, here, we consider design of an optimal adaptive-search strategy. A frequency-dependent magnetic-dipole model is used to characterize the target at EMI frequencies. The goal of the search is accurate characterization of the dipole-model parameters, denoted bythe vector theta; the target position and orientation are a subset of theta. The sensor position and operating frequency are denoted by the parameter vector p and a measurement is represented by the pair (p, O), where O denotes the observed data. The parametersp are fixed for a given measurement, but, in the context of a sequence of measurements p may be changed adaptively. In a locally optimal sequence of measurements, we desire the optimal sensor parameters, P(N+1) for estimation of theta, based on the previous measurements (p(n), On)n=1,N. The search strategy is based on the theory of optimal experiments, as discussed in detail and demonstrated via several numerical examples.
Full Text
Duke Authors
Cited Authors
- Liao, X; Carin, L
Published Date
- August 2004
Published In
Volume / Issue
- 26 / 8
Start / End Page
- 961 - 972
PubMed ID
- 15641727
Electronic International Standard Serial Number (EISSN)
- 1939-3539
International Standard Serial Number (ISSN)
- 0162-8828
Digital Object Identifier (DOI)
- 10.1109/tpami.2004.38
Language
- eng