%0 Conference Paper %1 Guvenc03enhancementsto %A Guvenc, I. %B In GSPx & International Signal Processing Conference %D 2003 %K wlanpos %T Enhancements to rss based indoor tracking systems using kalman filters %U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.79.9319 %X This paper describes the site survey issues when deploying a wireless local area network (WLAN), the implementation of a location system over the deployed network, and the application of a Kalman filtering algorithm to enhance the tracking performance. We have made a site survey in the Electrical and Computer Engineering (EECE) department of University of New Mexico (UNM) to optimally position the access points. Ekahau Positioning Engine 1 was used to find the coverage areas of all available access points throughout the building. After having the network up and running, the signal strength values at certain locations are recorded and an indoor propagation analysis is made. A nearest neighbors algorithm and its variants are used to construct a location system and possible ways of improvements are discussed. Improvements in the estimation error using a Kalman filter algorithm are then presented.

@inproceedings{Guvenc03enhancementsto, abstract = {This paper describes the site survey issues when deploying a wireless local area network (WLAN), the implementation of a location system over the deployed network, and the application of a Kalman filtering algorithm to enhance the tracking performance. We have made a site survey in the Electrical and Computer Engineering (EECE) department of University of New Mexico (UNM) to optimally position the access points. Ekahau Positioning Engine [1] was used to find the coverage areas of all available access points throughout the building. After having the network up and running, the signal strength values at certain locations are recorded and an indoor propagation analysis is made. A nearest neighbors algorithm and its variants are used to construct a location system and possible ways of improvements are discussed. Improvements in the estimation error using a Kalman filter algorithm are then presented.}, added-at = {2010-10-13T16:39:37.000+0200}, author = {Guvenc, I.}, biburl = {https://www.bibsonomy.org/bibtex/2944e32dc23d441aeb42fd8e44ea263cb/kw}, booktitle = {In GSPx & International Signal Processing Conference}, description = {Enhancements to rss based indoor tracking systems using kalman filters}, interhash = {b0d75e5d90d193755a19648afd6f3d72}, intrahash = {944e32dc23d441aeb42fd8e44ea263cb}, keywords = {wlanpos}, timestamp = {2010-10-13T16:39:37.000+0200}, title = {Enhancements to rss based indoor tracking systems using kalman filters}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.79.9319}, year = 2003 }