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Sensitivity analysis for antenna near-field imaging

Nordebo, Sven LU ; Gustafsson, Mats LU orcid and Persson, Kristin LU (2007) In IEEE Transactions on Signal Processing 55(1). p.94-101
Abstract
Although imaging and inverse scattering problems have been thoroughly studied during the last century, there is only a partial understanding of these complex problems. Most of the efforts have been placed on the development of efficient inversion algorithms and mathematical uniqueness results. In comparison, there are very few results and a limited knowledge about the information content in the inversion data. In this paper, we provide a mathematical framework for sensitivity analysis of antenna near-field imaging problems, based on the multipole expansion of the electromagnetic field and the Fisher information to quantify the quality of data. By exploiting this framework, a fundamental relation for accuracy and resolution is formulated... (More)
Although imaging and inverse scattering problems have been thoroughly studied during the last century, there is only a partial understanding of these complex problems. Most of the efforts have been placed on the development of efficient inversion algorithms and mathematical uniqueness results. In comparison, there are very few results and a limited knowledge about the information content in the inversion data. In this paper, we provide a mathematical framework for sensitivity analysis of antenna near-field imaging problems, based on the multipole expansion of the electromagnetic field and the Fisher information to quantify the quality of data. By exploiting this framework, a fundamental relation for accuracy and resolution is formulated based on the Cramer-Rao bound (CRB). The sensitivity analysis is illustrated using a relevant example with cylindrical measurement data. (Less)
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author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
near-field imaging, estimation theory, inverse, problems, antenna theory, Fisher information
in
IEEE Transactions on Signal Processing
volume
55
issue
1
pages
94 - 101
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • wos:000243281200010
  • scopus:33947383691
ISSN
1053-587X
DOI
10.1109/TSP.2006.885742
language
English
LU publication?
yes
id
38391c04-f51d-4900-a313-2d24196154ff (old id 679416)
date added to LUP
2016-04-01 16:38:08
date last changed
2022-01-28 21:01:25
@article{38391c04-f51d-4900-a313-2d24196154ff,
  abstract     = {{Although imaging and inverse scattering problems have been thoroughly studied during the last century, there is only a partial understanding of these complex problems. Most of the efforts have been placed on the development of efficient inversion algorithms and mathematical uniqueness results. In comparison, there are very few results and a limited knowledge about the information content in the inversion data. In this paper, we provide a mathematical framework for sensitivity analysis of antenna near-field imaging problems, based on the multipole expansion of the electromagnetic field and the Fisher information to quantify the quality of data. By exploiting this framework, a fundamental relation for accuracy and resolution is formulated based on the Cramer-Rao bound (CRB). The sensitivity analysis is illustrated using a relevant example with cylindrical measurement data.}},
  author       = {{Nordebo, Sven and Gustafsson, Mats and Persson, Kristin}},
  issn         = {{1053-587X}},
  keywords     = {{near-field imaging; estimation theory; inverse; problems; antenna theory; Fisher information}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{94--101}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Transactions on Signal Processing}},
  title        = {{Sensitivity analysis for antenna near-field imaging}},
  url          = {{http://dx.doi.org/10.1109/TSP.2006.885742}},
  doi          = {{10.1109/TSP.2006.885742}},
  volume       = {{55}},
  year         = {{2007}},
}