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A Statistical Region-based Compressive Sensing Indoor Path-Tracking System

Dimitrios Milioris 1, 2 Philippe Jacquet 1
1 HIPERCOM - High performance communication
Inria Paris-Rocquencourt, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, X - École polytechnique, CNRS - Centre National de la Recherche Scientifique : UMR
2 UP11 - Université Paris-Sud - Paris 11
Abstract : In this paper, a hybrid path tracking system is presented, which exploits the efficiency of a Kalman filter in conjunction with the power of compressive sensing to represent accurately sparse signals and a region-based multivariate Gaussian model. The experimental evaluation reveals an increased localization performance, while maintaining a low computational complexity.
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https://hal-polytechnique.archives-ouvertes.fr/hal-00905070
Contributor : Dimitrios Milioris <>
Submitted on : Friday, November 15, 2013 - 5:35:52 PM
Last modification on : Monday, August 23, 2021 - 3:20:44 AM

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  • HAL Id : hal-00905070, version 1

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Dimitrios Milioris, Philippe Jacquet. A Statistical Region-based Compressive Sensing Indoor Path-Tracking System. ACM International Symposium on Mobile Ad Hoc Networking and Computing, May 2011, Paris, France. ⟨hal-00905070⟩

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