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Received signal strength-based joint parameter estimation algorithm for robust geolocation in LOS/NLOS environments
Technical University Darmstadt, Germany.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Technical University Darmstadt, Germany.
2013 (English)In: Proc. of 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2013, 6471-6475 p.Conference paper, Published paper (Refereed)
Abstract [en]

We consider received-signal-strength-based robust geolocation in mixed line-of-sight/non-line-of-sight propagation environments. Herein, we assume a mode-dependent propagation model with unknown parameters. We propose to jointly estimate the geographical coordinates and propagation model parameters. In order to approximate the maximum-likelihood estimator (MLE), we develop an iterative algorithm based on the well-known expectation and maximization criterion. As compared to the standard ML implementation, the proposed algorithm is simpler to implement and capable of reproducing the MLE. Simulation results show that the proposed algorithm attains the best geolocation accuracy as the number of measurements increases.

Place, publisher, year, edition, pages
2013. 6471-6475 p.
Keyword [en]
Expectation-maximization (EM) criterion, geolocation, line-of-sight (LOS)/non-line-of-sight (NLOS), received signal-strength (RSS)
National Category
Signal Processing Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-123714DOI: 10.1109/ICASSP.2013.6638912OAI: oai:DiVA.org:liu-123714DiVA: diva2:892440
Conference
2013 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, BC, Canada, 26-31 May, 2013
Available from: 2016-01-10 Created: 2016-01-10 Last updated: 2016-03-11

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Fritsche, CarstenGustafsson, Fredrik

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf