Gradient-Based Fingerprinting for Indoor Localization and Tracking

—Of the different branches of indoor localization research, WiFi fingerprinting has drawn significant attention over the past decade. These localization systems function by comparing WiFi Received Signal Strength Indicator (RSSI) and a pre-established location-specific fingerprint map. However, due to the time-variant wireless signal strength, the RSSI fingerprint map needs to be calibrated periodically, incurring high labor and time costs. In addition, biased RSSI measurements across devices along with transmission power control techniques of WiFi routers further undermine the fidelity of existing fingerprintbased localization systems. To remedy these problems, we propose GIFT which leverages a more stable RSSI gradient. GIFT first builds a gradient-based fingerprint map (Gmap) by comparing absolute RSSI values at nearby positions, and then runs an online extended particle filter to localize the user/device. By incorporating Gmap, GIFT is more adaptive to the time-variant ...

• Type: Journal
• Year: 2016
• Where: TIE
• Authors: Yuanchao Shu, Yinghua Huang, Jiaqi Zhang, Philippe Coue, Peng Cheng, Jiming Chen, Kang G. Shin
• Keywords: TIE 2016