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Application of the theory of optimal experiments to adaptive electromagnetic-induction sensing of buried targets.

Publication ,  Journal Article
Liao, X; Carin, L
Published in: IEEE transactions on pattern analysis and machine intelligence
August 2004

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.

Duke Scholars

Published In

IEEE transactions on pattern analysis and machine intelligence

DOI

EISSN

1939-3539

ISSN

0162-8828

Publication Date

August 2004

Volume

26

Issue

8

Start / End Page

961 / 972

Related Subject Headings

  • Transducers
  • Soil
  • Signal Processing, Computer-Assisted
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Pattern Recognition, Automated
  • Numerical Analysis, Computer-Assisted
  • Information Storage and Retrieval
  • Feedback
  • Electromagnetic Fields
 

Citation

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Liao, X., & Carin, L. (2004). Application of the theory of optimal experiments to adaptive electromagnetic-induction sensing of buried targets. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(8), 961–972. https://doi.org/10.1109/tpami.2004.38
Liao, Xuejun, and Lawrence Carin. “Application of the theory of optimal experiments to adaptive electromagnetic-induction sensing of buried targets.IEEE Transactions on Pattern Analysis and Machine Intelligence 26, no. 8 (August 2004): 961–72. https://doi.org/10.1109/tpami.2004.38.
Liao X, Carin L. Application of the theory of optimal experiments to adaptive electromagnetic-induction sensing of buried targets. IEEE transactions on pattern analysis and machine intelligence. 2004 Aug;26(8):961–72.
Liao, Xuejun, and Lawrence Carin. “Application of the theory of optimal experiments to adaptive electromagnetic-induction sensing of buried targets.IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 8, Aug. 2004, pp. 961–72. Epmc, doi:10.1109/tpami.2004.38.
Liao X, Carin L. Application of the theory of optimal experiments to adaptive electromagnetic-induction sensing of buried targets. IEEE transactions on pattern analysis and machine intelligence. 2004 Aug;26(8):961–972.

Published In

IEEE transactions on pattern analysis and machine intelligence

DOI

EISSN

1939-3539

ISSN

0162-8828

Publication Date

August 2004

Volume

26

Issue

8

Start / End Page

961 / 972

Related Subject Headings

  • Transducers
  • Soil
  • Signal Processing, Computer-Assisted
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Pattern Recognition, Automated
  • Numerical Analysis, Computer-Assisted
  • Information Storage and Retrieval
  • Feedback
  • Electromagnetic Fields