Title :
Bayesian filtering for location estimation
Author :
Fox, Dieter ; Hightower, Jeffrey ; Liao, Lin ; Schulz, Dirk ; Borriello, Gaetano
Author_Institution :
Univ. of Washington, Seattle, WA, USA
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.
Keywords :
Bayes methods; Kalman filters; sensor fusion; statistical analysis; ubiquitous computing; Bayesian filtering; Kalman filters; identity estimation; location estimation; measurement uncertainty; multisensor fusion; pervasive computing; statistical tool; Bayesian methods; Cameras; Filtering; Filters; Infrared sensors; Pervasive computing; Sensor systems; Sensor systems and applications; State estimation; Time measurement;
Journal_Title :
Pervasive Computing, IEEE
DOI :
10.1109/MPRV.2003.1228524
