Paper Info
Title
Improving RF-based device-free passive localization in cluttered indoor environments through probabilistic classification methods
Abstract
Radio frequency based device-free passive localization has been proposed as an alternative to indoor localization because it does not require subjects to wear a radio device. This technique observes how people disturb the pattern of radio waves in an indoor space and derives their positions accordingly. The well-known multipath effect makes this problem very challenging, because in a complex environment it is impractical to have enough knowledge to be able to accurately model the effects of a subject on the surrounding radio links. In addition, even minor changes in the environment over time change radio propagation sufficiently to invalidate the datasets needed by simple fingerprint-based methods. In this paper, we develop a fingerprinting-based method using probabilistic classification approaches based on discriminant analysis. We also devise ways to mitigate the error caused by multipath effect in data collection, further boosting the classification likelihood. We validate our method in a one-bedroom apartment that has 8 transmitters, 8 receivers, and a total of 32 cells that can be occupied. We show that our method can correctly estimate the occupied cell with a likelihood of 97.2%. Further, we show that the accuracy remains high, even when we significantly reduce the training overhead, consider fewer radio devices, or conduct a test one month later after the training. We also show that our method can be used to track a person in motion and to localize multiple people with high accuracies. Finally, we deploy our method in a completely different commercial environment with two times the area achieving a cell estimation accuracy of 93.8% as an evidence of applicability to multiple environments.
Year
DOI
Venue
2012
10.1109/IPSN.2012.6920958
IPSN
Keywords
Field
DocType
radio links,indoor localization,discriminant analysis,different commercial environment,multi-path,radio devices,device,radio propagation,time change radio propagation,radio frequency,surrounding radio link,multipath channels,fingerprinting-based method,device-free passive localization,fewer radio device,rss footprint,cell estimation,complex environment,indoor space,simple fingerprint-based method,fingerprint based methods,radio waves,probabilistic classification method,probabilistic classification methods,radio equipment,cluttered indoor environment,cluttered indoor environments,multipath effect,radio wave,free passive localization,probability,improving rf based device free passive localization,radio device,accuracy,data collection,multipath,radio link,radio transmitters,time change
Multipath propagation,Data collection,Radio wave,Computer science,Real-time computing,Radio frequency,Boosting (machine learning),Linear discriminant analysis,Probabilistic classification,Radio propagation
Conference
Citations 
PageRank 
References 
53
2.39
18
Authors
6
Name
Order
Citations
PageRank
Chenren Xu151336.00
Bernhard Firner249423.49
Yanyong Zhang33116184.08
Richard Howard431125.10
Jun Li51076.38
Xiaodong Lin6634.32