An In-Door Wireless Localization System in Campus Network

In this paper, an in-door wireless localization algorithm named i-KWNN based on the KWNN algorithm is presented to solve the side effect of anonymous access points (AAP). Kalman filtering is adopted to enhance the tracking performance by smoothing signal strength. Therefore, the typical signal strength value of an access point can be inferred. The experiments show that this method can indirectly decrease the errors of the localization results. Finally, a location based services (LBS) system in the campus wireless LAN in Beihang University is designed and implemented, and WebGIS technology is used to display the user location.