The Horus WLAN location determination system
Proceedings of the 3rd international conference on Mobile systems, applications, and services
Location estimation from multiple survey sets
Proceedings of the 2006 international conference on Wireless communications and mobile computing
The Horus location determination system
Wireless Networks
Location aware computing for academic environments
Welcome to Mobile Content Quality of Experience
A taxonomy for radio location fingerprinting
LoCA'07 Proceedings of the 3rd international conference on Location-and context-awareness
CrowdInside: automatic construction of indoor floorplans
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Hi-index | 0.02 |
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 signi?cant enhancement in the accuracy of WLAN location determination systems helps increase the set of context-aware applications implemented on top of these systems.