Radio map update automation for WiFi positioning systems

Abstract

With the proliferation of smartphones and the explosively increasing WiFi hot spots, the so-called “WiFi positioning system” (WPS) has recently received great attention. In the WPS, due to its superior accuracy, the fingerprint-based localization technique is preferred rather than trilateration. In fingerprint-based localization, the location of a device is usually estimated by referring to a radio map, which is the collection of the fingerprints and their collected location information. Thus, the radio map is essential for the fingerprint-based localization technique. In the fingerprint-based localization, recalibration should be made occasionally to maintain the initial accuracy of the WPS. However, the recalibration usually requires considerable time and effort, especially with the WPS covering a large-scale space. We propose two novel methods which more effectively reduce the recalibration cost based on an automatic update of radio maps using user feedback data. The first proposed method for updating radio maps for the purpose of place recognition uses appearance frequencies of APs collected from the user feedback data. The second proposed method for updating radio maps for the purpose of localization utilizes the log-distance path loss (LDPL) model in order to update signal strengths of newly installed APs into the radio map. The experiment for evaluating the first proposed method has been performed on the radio map constructed across the 233 Seoul subway stops. As compared to previous methods, the proposed method turned out to be superior in its ability to update newly installed APs. Also, the proposed method could more effectively be used for the APs with weak signal strengths as well as for the APs with strong signal strengths. Another experiment for evaluating the second proposed method has been conducted on the 4th floor of the KAIST library, Daejeon, Korea. The proposed method improved the overall accuracy of the localization under changing WiFi en...