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
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.
Document type :
Conference papers
Complete list of metadatas
https://hal-polytechnique.archives-ouvertes.fr/hal-00905070
Contributor : Dimitrios Milioris <>
Submitted on : Friday, November 15, 2013 - 5:35:52 PM Last modification on : Wednesday, September 16, 2020 - 5:04:11 PM
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⟩