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Inverse scattering with sparse Bayesian vector regression

Publication ,  Journal Article
Yu, Y; Krishnapuram, B; Carin, L
Published in: Inverse Problems
December 1, 2004

A Bayesian formulation is employed to develop a sparse vector regression model. The model is used to characterize the connection between measured vector scattered-field data x and the underlying target responsible for these fields, characterized by the parameter vector t. The scattering data x may be measured at multiple positions and/or at multiple frequencies. The statistical model is trained using a set of data D = {xn, tn} n=1N established from a measurement and/or a forward model. Given observed scattered fields x, the model yields the expected target parameters t, as well as the associated accuracy of this estimate, defined in terms of 'error bars'. After developing the theory, we consider scattering from dielectric targets buried under a lossy half-space. We address examples for which the actual target responsible for the scattered fields is not matched to that used in the regression model, as well as scattering data with large additive noise.

Duke Scholars

Published In

Inverse Problems

DOI

ISSN

0266-5611

Publication Date

December 1, 2004

Volume

20

Issue

6

Related Subject Headings

  • Applied Mathematics
  • 4904 Pure mathematics
  • 4901 Applied mathematics
  • 0105 Mathematical Physics
  • 0102 Applied Mathematics
  • 0101 Pure Mathematics
 

Citation

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Yu, Y., Krishnapuram, B., & Carin, L. (2004). Inverse scattering with sparse Bayesian vector regression. Inverse Problems, 20(6). https://doi.org/10.1088/0266-5611/20/6/S13
Yu, Y., B. Krishnapuram, and L. Carin. “Inverse scattering with sparse Bayesian vector regression.” Inverse Problems 20, no. 6 (December 1, 2004). https://doi.org/10.1088/0266-5611/20/6/S13.
Yu Y, Krishnapuram B, Carin L. Inverse scattering with sparse Bayesian vector regression. Inverse Problems. 2004 Dec 1;20(6).
Yu, Y., et al. “Inverse scattering with sparse Bayesian vector regression.” Inverse Problems, vol. 20, no. 6, Dec. 2004. Scopus, doi:10.1088/0266-5611/20/6/S13.
Yu Y, Krishnapuram B, Carin L. Inverse scattering with sparse Bayesian vector regression. Inverse Problems. 2004 Dec 1;20(6).
Journal cover image

Published In

Inverse Problems

DOI

ISSN

0266-5611

Publication Date

December 1, 2004

Volume

20

Issue

6

Related Subject Headings

  • Applied Mathematics
  • 4904 Pure mathematics
  • 4901 Applied mathematics
  • 0105 Mathematical Physics
  • 0102 Applied Mathematics
  • 0101 Pure Mathematics