A fast and accurate calibration algorithm for real-time locating systems based on the received signal strength indication

With the recent growth of IEEE 802.11 based Wireless Local Area Networks (WLANs), there has been new research attempts to use the WLAN technology for location estimation applications in deep indoor environments where traditional locating algorithms are not effective. The received signal strength indication (RSSI) fingerprinting that uses WLAN infrastructure is a compelling approach due to its fast online tracking capability and to its accurate location estimation. However, the RSSI requires an exhaustive calibration phase to build a fingerprint database. To mitigate the time consuming property of the calibration process, several studies have proposed a number of propagation prediction models that derive the distance of a target object from RSSI values at the expense of lower location accuracy.In this study, we propose a new locating algorithm that combines the calibration procedure with the fingerprint prediction model. Our simulation results show that our new approach not only reduces the calibration time, but it also provides comparable location accuracy to that of the conventional calibration-based locating algorithm.