Testing of location systems using WiFi in indoor environments
GUENTHER RETSCHER, ESMOND MOK
Performance of WiFi Positioning Systems
For the achievable positioning accuracy of WiFi location systems usually a value of 3 to 5 m for indoor positioning using signals from several visible access points is claimed by some system manufacturers. The positioning accuracy, however, depends very much on the surrounding environment. Radio signal propagation errors caused by multipath and other error sources and signal interference can degradiate the achievable positioning accuracies significantly. Therefore no general valid numbers for the achievable positioning accuracies can be given. In the following two different WiFi positioning systems are tested in different environments. One test bed was chosen in the Hong Kong Polytechnic University and the second in the Vienna University of Technolgy. Furthermore an approach for the conversion of the measured signal strength to the corresponding distance between the user’s current location and the access point is presented.
Tests of the Ekahau Positioning Engine at the Hong Kong Polytechnic University
At the Hong Kong Polytechnic University the Ekahau WiFi Positioning Engine was tested in two projects at the campus in indoor as well as outdoor areas (see Chan, 2006; Yiu et al., 2006). The WiFi positioning system was developed by the Finish based company Ekahau for the location determination of persons and objects mainly in indoor arreas where WiFi access points are present. In the following selected test results for the location determination of a user are presented.
Before a user can be located, calbration measurements have to be performed in the area where the user has to be located. For that purpose a floor plan is loaded into the Ekahau positioning software and tracking rails must be drawn and placed on the map (see Figure 2). The objective of this is to indicate the possible travel paths of the user. Since the estimated locations determined by the software depend on the rails placed on the map, the rails drawn must be correct and accessible. After the tracking rails were drawn, an empty positioning model has to be created with no signal data. To combine different maps (floor plans) together for a multi-floor investigation, two adjacent maps must be connected by setting up common points which are points with the same horizontal position but with different levels or floors. For example, positions in front of the elevator or around the staircase are suitable for connecting the maps together.
After drawing the tracking rails, the calibration procedure can be started. In the presented tests calibrations were made only along the rails which were already drawn. In the calibration procedure any location on the rails in a distance of 3 to 5 metres may be chosen. On this point signal strength observations are performed while the notebook computer is rotated around 360°. This observations are then stored in the Ekahau database. After finishing the calibration a user can be located in the calibrated area.
University. As can be seen from Figure 3 the achievable positioning accuracies vary quite significantly and range from ± 1.3 to 6.3 m with a few outlieres with even larger positioning errors. The best performance was achieved in the general teaching rooms which are equipped with an access point each. Table 1 summarizes the positioning accuracies in the teaching rooms. In the tests an average value for the positioning accuracy of ± 2.3 m could be achieved. For the points located on the corridor, however, the positioning accuracy was lower. A main reason for that could be that the average signal strength values were higher for the points located inside the teaching rooms than for those located on the corridor. The difference in the signal strength was in the range of 10 to 20 dB for at least three access points with the strongest signal.