Bayesian filtering for location estimation

2003703 citationsJournal Article

Authors

D. Fox · University of Washington

Jeffrey Hightower · University of Washington

Lin Liao · University of Washington

Dirk Schulz · University of Washington

G. Borriello · Intel (United States)

Abstract

Bayesian-filter techniques provide a powerful statistical tool to help manage measurement uncertainty and perform multisensor fusion and identity estimation. The authors survey Bayes filter implementations and show their application to real-world location-estimation tasks common in pervasive computing.

Topics & Keywords

Target Tracking and Data Fusion in Sensor Networks Indoor and Outdoor Localization Technologies Distributed Sensor Networks and Detection Algorithms

Publication Details

Published in: IEEE Pervasive Computing

Volume 2, Issue 3, pp. 24-33

DOI: 10.1109/mprv.2003.1228524

Field-Weighted Citation Impact: 34.26

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Bayesian filtering for location estimation

Authors

Abstract

Topics & Keywords

Publication Details