A Kalman filtering approach to stochastic tomography

Der Shan Luo, Andrew E. Yagle

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

An isotropic random field is expanded into its circular harmonics. Computation of its Radon transform is equivalent to computation of the nth-order Abel transform of the nth order circular harmonic. A state-space model is fitted to the Abel transform of each order and augmented with a state-space model describing the random field circular harmonic. The latter is derived using backward Markovianization of a two-point boundary value model. The tomographic problem of computing the inverse Radon transform is then solved by using a bank of Kalman filters to estimate each random field harmonic separately. Combining these gives the linear least-squares estimate of the random field. The authors also consider a simpler Wiener-process model of the circular harmonics.

Original languageEnglish (US)
Title of host publicationProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
Editors Anon
PublisherPubl by IEEE
Pages2589-2592
Number of pages4
ISBN (Print)078030033
StatePublished - Dec 1 1991
EventProceedings of the 1991 International Conference on Acoustics, Speech, and Signal Processing - ICASSP 91 - Toronto, Ont, Can
Duration: May 14 1991May 17 1991

Publication series

NameProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
Volume4
ISSN (Print)0736-7791

Other

OtherProceedings of the 1991 International Conference on Acoustics, Speech, and Signal Processing - ICASSP 91
CityToronto, Ont, Can
Period5/14/915/17/91

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Luo, D. S., & Yagle, A. E. (1991). A Kalman filtering approach to stochastic tomography. In Anon (Ed.), Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 2589-2592). (Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing; Vol. 4). Publ by IEEE.