Fingerprint Location Database Construction for Enhancing Accuracy of WiFi based Indoor Localization

We proposed Wireless LAN (WLAN) localization method that enhances database construction based on weighting factor and analyses the characteristic of the WLAN received signals. The weighting factor plays a key role as it determines the importance of Received Signal Strength Indication (RSSI) value from number of received signals (frequency). The fingerprint method is the most widely used method in WLANbased positioning methods because it has high location accuracy compare to other indoor positioning methods. We analyses WLAN RSSI characteristic from anechoic chamber test, and analyze the causes of various distributions of RSSI and its influence on location accuracy in indoor environments. In addition, we proposed enhanced weighting factor algorithm for accurate database construction and compare location accuracy of proposed algorithm with conventional algorithm by computer simulations and tests.