A Probabilistic Room Location Service for Wireless Networked Environments
UbiComp '01 Proceedings of the 3rd international conference on Ubiquitous Computing
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Design of indoor positioning systems based on location fingerprinting technique
Design of indoor positioning systems based on location fingerprinting technique
Statistical learning theory for location fingerprinting in wireless LANs
Computer Networks and ISDN Systems
Location Fingerprint Analyses Toward Efficient Indoor Positioning
PERCOM '08 Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications
Growing an organic indoor location system
Proceedings of the 8th international conference on Mobile systems, applications, and services
Experimental analysis of IEEE 802.15.4a CSS ranging and its implications
Computer Communications
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We previously developed an analytical model in [8] to predict the precision and accuracy performance of indoor positioning systems using location fingerprints. A by-product of the model is the ability to eliminate unnecessary fingerprints to reduce the number of fingerprints in a radio map for comparison without loss in performance. This model enables computation of an approximate probability distribution of location selection, by employing a proximity graph to extract neighbor and non-neighbor sets of a given fingerprint. However, employing the model 'as is' in a system with many location fingerprints requires determining a single large proximity graph derived from all location fingerprints which may involve significant computational effort. In this paper, we consider two techniques to divide location fingerprints into smaller clusters. Separate proximity graphs for each cluster are now used to predict performance and eliminate unnecessary location fingerprints. Results show that the computational effort can be reduced, creating a more scalable analytical model, while still predicting and enabling good precision performance.