Improved RSSI-Based Euclidean Distance Positioning Algorithm for Large and Dynamic WLAN Environments
In this paper, the authors present an algorithm for RSSI fingerprint positioning based on Euclidean distance for the use in a priori existing larger and dynamically changing WLAN infrastructure environments. Symptomatical for such environments are changing sets of base stations for different calibration points and for calibration phase and positioning phase. The presented algorithm has an accuracy of 2.06m median location estimation error. The algorithm uses four threshold parameters to adapt the calculation to the specific measuring environment.