Data fusion for reconstruction algorithms via different sensors in geophysical sensing
Nordebo, Sven LU ; Gustafsson, Mats LU
and Soldovieri, Francesco
(2011)
In Journal of Geophysics and Engineering
8(3).
p.54-60
- Abstract
- Abstract in Undetermined
Information fusion via multimodal inverse problems and different sensors is addressed using a Fisher information analysis approach. The Fisher information measure is inherently additive, and it facilitates an appropriate weighting of the measurement data that is statistically optimal and can hence be useful with reconstruction algorithms in geophysical sensing. Given that there exists proper knowledge about the sensor noise statistics, correlations and spectral contents, as well as a correct forward model, the Fisher information is a natural measure of information because it is closely linked to the statistical maximum likelihood principle. To illustrate the concept of data correlation based on statistical... (More) - Abstract in Undetermined
Information fusion via multimodal inverse problems and different sensors is addressed using a Fisher information analysis approach. The Fisher information measure is inherently additive, and it facilitates an appropriate weighting of the measurement data that is statistically optimal and can hence be useful with reconstruction algorithms in geophysical sensing. Given that there exists proper knowledge about the sensor noise statistics, correlations and spectral contents, as well as a correct forward model, the Fisher information is a natural measure of information because it is closely linked to the statistical maximum likelihood principle. To illustrate the concept of data correlation based on statistical Fisher information analysis, two simple and generic examples are employed in electrical resistivity and electromagnetic tomography, which are motivated by geophysical applications, such as tunnel detection. The examples demonstrate that a properly weighted data fusion can be of crucial importance for an ill-posed multimodal inverse problem. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2018546
- author
- Nordebo, Sven
LU
; Gustafsson, Mats
LU
and Soldovieri, Francesco
- organization
- publishing date
- 2011
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- data fusion, inverse problems, Fisher information, electrical impedance tomography
- in
- Journal of Geophysics and Engineering
- volume
- 8
- issue
- 3
- pages
- 54 - 60
- publisher
- IOP Publishing
- external identifiers
-
- wos:000294161500007
- scopus:80052163966
- ISSN
- 1742-2140
- DOI
- 10.1088/1742-2132/8/3/S06
- project
- EIT_ISTIMES Integrated System for Transport Infrastructures surveillance and Monitoring by Electromagnetic Sensing
- language
- English
- LU publication?
- yes
- id
- 3bd070a1-c609-4a44-b8a5-42dc449f45cc (old id 2018546)
- date added to LUP
- 2016-04-01 10:26:41
- date last changed
- 2022-01-25 23:15:06
@article{3bd070a1-c609-4a44-b8a5-42dc449f45cc,
abstract = {{Abstract in Undetermined<br/>Information fusion via multimodal inverse problems and different sensors is addressed using a Fisher information analysis approach. The Fisher information measure is inherently additive, and it facilitates an appropriate weighting of the measurement data that is statistically optimal and can hence be useful with reconstruction algorithms in geophysical sensing. Given that there exists proper knowledge about the sensor noise statistics, correlations and spectral contents, as well as a correct forward model, the Fisher information is a natural measure of information because it is closely linked to the statistical maximum likelihood principle. To illustrate the concept of data correlation based on statistical Fisher information analysis, two simple and generic examples are employed in electrical resistivity and electromagnetic tomography, which are motivated by geophysical applications, such as tunnel detection. The examples demonstrate that a properly weighted data fusion can be of crucial importance for an ill-posed multimodal inverse problem.}},
author = {{Nordebo, Sven and Gustafsson, Mats and Soldovieri, Francesco}},
issn = {{1742-2140}},
keywords = {{data fusion; inverse problems; Fisher information; electrical impedance tomography}},
language = {{eng}},
number = {{3}},
pages = {{54--60}},
publisher = {{IOP Publishing}},
series = {{Journal of Geophysics and Engineering}},
title = {{Data fusion for reconstruction algorithms via different sensors in geophysical sensing}},
url = {{http://dx.doi.org/10.1088/1742-2132/8/3/S06}},
doi = {{10.1088/1742-2132/8/3/S06}},
volume = {{8}},
year = {{2011}},
}