A Statistical Region-based Compressive Sensing Indoor Path-Tracking System - École polytechnique
Conference Papers Year : 2011

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

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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Dates and versions

hal-00905070 , version 1 (15-11-2013)

Identifiers

  • HAL Id : hal-00905070 , version 1

Cite

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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