Research Article
Multivariate analysis for probabilistic WLAN location determination systems
@INPROCEEDINGS{10.1109/MOBIQUITOUS.2005.41, author={M. Youssef and M Abdallah and Ashok Agrawala }, title={Multivariate analysis for probabilistic WLAN location determination systems}, proceedings={2nd International ICST Conference on Mobile and Ubiquitous Systems: Networking and Services}, publisher={IEEE}, proceedings_a={MOBIQUITOUS}, year={2005}, month={11}, keywords={}, doi={10.1109/MOBIQUITOUS.2005.41} }- M. Youssef
M Abdallah
Ashok Agrawala
Year: 2005
Multivariate analysis for probabilistic WLAN location determination systems
MOBIQUITOUS
IEEE
DOI: 10.1109/MOBIQUITOUS.2005.41
Abstract
WLAN location determination systems are gaining increasing attention due to the value they add to wireless networks. In this paper, we present a multivariate analysis technique for enhancing the performance of WLAN location determination systems by taking the correlation between samples from the same access point into account. We show that the autocorrelation between consecutive samples from the same access point can be as high as 0.9. Giving a sequence of correlated signal strength samples from an access point, the technique estimates the user location based on the calculated probability of this sequence from the multivariate distribution. We use a linear autoregressive model to derive the multivariate distribution function for the correlated samples. Using analytical analysis, we show that the proposed technique provides better location accuracy over previous techniques especially for the highly correlated samples in a typical WLAN environment. Implementation of the technique in the Horus WLAN location determination system shows that the average system accuracy is increased by more than 64%. This significant enhancement in the accuracy of WLAN location determination systems helps increase the set of context-aware applications implemented on top of these systems.
