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Data fusion for reconstruction algorithms via different sensors in geophysical sensing

Publiceringsår: 2011
Språk: Engelska
Sidor: 54-60
Publikation/Tidskrift/Serie: Journal of Geophysics and Engineering
Volym: 8
Nummer: 3
Dokumenttyp: Artikel i tidskrift
Förlag: IOP Publishing


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.


  • Electrical Engineering, Electronic Engineering, Information Engineering
  • data fusion
  • inverse problems
  • Fisher information
  • electrical impedance tomography


  • EIT_ISTIMES Integrated System for Transport Infrastructures surveillance and Monitoring by Electromagnetic Sensing
  • Electromagnetic theory-lup-obsolete
  • ISSN: 1742-2140

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