Publications [#339019] of Lawrence Carin

Papers Published

1. 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, vol. 37 no. 2 (January, 2001), pp. 595-606, Institute of Electrical and Electronics Engineers (IEEE) [7.937471], [doi]
   (last updated on 2024/12/31)

   Abstract:
   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.

   Keywords:
   Markov processes;Mathematical models;Electromagnetic wave diffraction;Synthetic aperture radar;Feature extraction;Probability density function;Statistical methods;Doppler effect;