The active badge location system
ACM Transactions on Information Systems (TOIS)
The Cricket location-support system
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
WLAN Location Determination via Clustering and Probability Distributions
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Multi-Camera Multi-Person Tracking for EasyLiving
VS '00 Proceedings of the Third IEEE International Workshop on Visual Surveillance (VS'2000)
Practical robust localization over large-scale 802.11 wireless networks
Proceedings of the 10th annual international conference on Mobile computing and networking
LOCATOR: location estimation system For wireless LANs
Proceedings of the 2nd ACM international workshop on Wireless mobile applications and services on WLAN hotspots
IEEE Transactions on Wireless Communications
Estimating signal strengths in the design of an indoor wireless network
IEEE Transactions on Wireless Communications
Transmission techniques for radio LAN's-a comparative performance evaluation using ray tracing
IEEE Journal on Selected Areas in Communications
| Hi-index | 0.00 |
Location determination of mobile users within a building has attracted much attention lately due to its many applications in mobile networking including network intrusion detection problems. However, it is challenging due to the complexities of the indoor radio propagation characteristics exacerbated by the mobility of the user. A common practice is to mechanically generate a table showing the radio signal strength at different known locations in the building. A mobile user's location at an arbitrary point in the building is determined by measuring the signal strength at the location in question and determining the location by referring to the above table using a LMSE (least mean square error) criterion. Obviously, this is a very tedious and time consuming task. This paper proposes a novel and automated location determination method called ARIADNE. Using a two dimensional construction floor plan and only a single actual signal strength measurement, ARIADNE generates an estimated signal strength map comparable to those generated manually by actual measurements. Given the signal measurements for a mobile, a proposed clustering algorithm searches that signal strength map to determine the current mobile's location. The results from ARIADNE are comparable and may even be superior to those from existing localization schemes.