Service interruption on Monday 11 July from 12:30 to 13:00: all the sites of the CCSD (HAL, Epiciences, SciencesConf, AureHAL) will be inaccessible (network hardware connection).
Skip to Main content Skip to Navigation
Conference papers

Building Complete Training Maps for Indoor Location Estimation

Abstract : Indoor location estimation is a significant task for many ubiquitous and pervasive computing applications, with numerous solutions based on IEEE802.11, bluetooth, ultrasound and infrared technologies. Most of these techniques use the fingerprint-based approach, which needs exhaustive collection of the received signal strengths in various positions of the physical space. In the present work, we exploit the spatial correlation structure of the fingerprints and use the framework of Matrix Completion to build complete training maps from a small number of random sample fingerprints. The experimental evaluation with real data presents the localization accuracy based on complete reconstructed training maps, without making an exhaustive collection of fingerprints.
Complete list of metadata

Cited literature [7 references]  Display  Hide  Download
Contributor : Dimitrios Milioris Connect in order to contact the contributor
Submitted on : Wednesday, May 27, 2015 - 10:14:38 AM
Last modification on : Monday, January 24, 2022 - 10:40:05 AM
Long-term archiving on: : Monday, April 24, 2017 - 3:26:13 PM


Files produced by the author(s)


  • HAL Id : hal-01137421, version 1


Dimitrios Milioris, Milan Bradonjic, Paul Mühlethaler. Building Complete Training Maps for Indoor Location Estimation. IEEE International Conference on Computer Communications (INFOCOM), Apr 2015, Hong Kong, Hong Kong SAR China. ⟨hal-01137421⟩



Record views


Files downloads