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Acoustics, Speech, and Signal Processing, 2001 Vol 5. 2001 IEEE International Conference on
Markov modeling of transient scattering and its application in multi-aspect target classification
Salt Lake City, UT, USA
May 07-May 11
ISBN: 0-7803-7041-4
| ASCII Text | x | ||
| Y. Dong, P. Runkle, L. Carin, "Markov modeling of transient scattering and its application in multi-aspect target classification," Acoustics, Speech, and Signal Processing, IEEE International Conference on, vol. 5, pp. 2841-2844, Acoustics, Speech, and Signal Processing, 2001 Vol 5. 2001 IEEE International Conference on, 2001. | |||
| BibTex | x | ||
| @article{ 10.1109/ICASSP.2001.940238, author = {Y. Dong and P. Runkle and L. Carin}, title = {Markov modeling of transient scattering and its application in multi-aspect target classification}, journal ={Acoustics, Speech, and Signal Processing, IEEE International Conference on}, volume = {5}, year = {2001}, isbn = {0-7803-7041-4}, pages = {2841-2844}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICASSP.2001.940238}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Acoustics, Speech, and Signal Processing, IEEE International Conference on TI - Markov modeling of transient scattering and its application in multi-aspect target classification SN - 0-7803-7041-4 SP2841 EP2844 A1 - Y. Dong, A1 - P. Runkle, A1 - L. Carin, PY - 2001 VL - 5 JA - Acoustics, Speech, and Signal Processing, IEEE International Conference on ER - | |||
Transient scattered fields from a general target are composed of wavefronts, resonances and time delays, with these constituents linked to the target geometry. A classifier applied to transient scattering data requires a statistical model for such fundamental constituents. A Markov model is employed to characterize the transient scattered fields-for a set of target-sensor orientation over which the transient scattering is stationary-utilizing a wavefront, resonance, time-delay "alphabet". The Markov model is utilized in a classifier developed for multi-aspect transient scattering data, with a hidden Markov model (HMM) employed to address the generally non-stationary nature of the multi-aspect waveforms. Each state of the HMM is characteristic of a set of target-sensor orientations for which the scattering statistics are stationary, the statistics of which are characterized via the Markov model. The wavefront, resonance and time-delay features are extracted via a modified matching-pursuits algorithm.
Citation:
Y. Dong, P. Runkle, L. Carin, "Markov modeling of transient scattering and its application in multi-aspect target classification," icassp, vol. 5, pp.2841-2844, Acoustics, Speech, and Signal Processing, 2001 Vol 5. 2001 IEEE International Conference on, 2001
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