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Multiaspect classification of airborne targets via physics-based HMMs and matching pursuits

Publication ,  Journal Article
Bharadwaj, P; Runkle, P; Carin, L; Berrie, JA; Hughes, JA
Published in: IEEE Transactions on Aerospace and Electronic Systems
January 1, 2001

Wideband electromagnetic fields scattered from N distinct target-sensor orientations are employed for classification of airborne targets. Each of the scattered waveforms is parsed via physics-based matching pursuits, yielding N feature vectors. The feature vectors are submitted to a hidden Markov model (HMM), each state of which is characterized by a set of target-sensor orientations over which the associated feature vectors are relatively stationary. The N feature vectors extracted from the multiaspect scattering data implicitly sample N states of the target (some states may be sampled more than once), with the state sequence modeled statistically as a Markov process, resulting in an HMM due to the "hidden" or unknown target orientation. In the work presented here, the state-dependent probability of observing a given feature vector is modeled via physics-motivated linear distributions, in lieu of the traditional Gaussian mixtures applied in classical HMMs. Further, we develop a scheme that yields autonomous definitions for the aspect-dependent HMM states. The paradigm is applied to synthetic scattering data for two simple targets.

Duke Scholars

Published In

IEEE Transactions on Aerospace and Electronic Systems

DOI

ISSN

0018-9251

Publication Date

January 1, 2001

Volume

37

Issue

2

Start / End Page

595 / 606

Related Subject Headings

  • Aerospace & Aeronautics
  • 4009 Electronics, sensors and digital hardware
  • 4006 Communications engineering
  • 4001 Aerospace engineering
  • 0909 Geomatic Engineering
  • 0906 Electrical and Electronic Engineering
  • 0901 Aerospace Engineering
 

Citation

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Bharadwaj, P., Runkle, P., Carin, L., Berrie, J. A., & Hughes, J. A. (2001). Multiaspect classification of airborne targets via physics-based HMMs and matching pursuits. IEEE Transactions on Aerospace and Electronic Systems, 37(2), 595–606. https://doi.org/10.1109/7.937471
Bharadwaj, P., P. Runkle, L. Carin, J. A. Berrie, and J. A. Hughes. “Multiaspect classification of airborne targets via physics-based HMMs and matching pursuits.” IEEE Transactions on Aerospace and Electronic Systems 37, no. 2 (January 1, 2001): 595–606. https://doi.org/10.1109/7.937471.
Bharadwaj P, Runkle P, Carin L, Berrie JA, Hughes JA. Multiaspect classification of airborne targets via physics-based HMMs and matching pursuits. IEEE Transactions on Aerospace and Electronic Systems. 2001 Jan 1;37(2):595–606.
Bharadwaj, P., et al. “Multiaspect classification of airborne targets via physics-based HMMs and matching pursuits.” IEEE Transactions on Aerospace and Electronic Systems, vol. 37, no. 2, Jan. 2001, pp. 595–606. Scopus, doi:10.1109/7.937471.
Bharadwaj P, Runkle P, Carin L, Berrie JA, Hughes JA. Multiaspect classification of airborne targets via physics-based HMMs and matching pursuits. IEEE Transactions on Aerospace and Electronic Systems. 2001 Jan 1;37(2):595–606.

Published In

IEEE Transactions on Aerospace and Electronic Systems

DOI

ISSN

0018-9251

Publication Date

January 1, 2001

Volume

37

Issue

2

Start / End Page

595 / 606

Related Subject Headings

  • Aerospace & Aeronautics
  • 4009 Electronics, sensors and digital hardware
  • 4006 Communications engineering
  • 4001 Aerospace engineering
  • 0909 Geomatic Engineering
  • 0906 Electrical and Electronic Engineering
  • 0901 Aerospace Engineering