Title :
Intelligent Fusion of Wi-Fi and Inertial Sensor-Based Positioning Systems for Indoor Pedestrian Navigation
Author :
Lyu-Han Chen ; Wu, Eric Hsiao-Kuang ; Ming-Hui Jin ; Gen-Huey Chen
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Abstract :
Indoor positioning systems based on wireless local area networks are growing rapidly in importance and gaining commercial interest. Pedestrian dead reckoning (PDR) systems, which rely on inertial sensors, such as accelerometers, gyroscopes, or even magnetometers to estimate users´ movement, have also been widely adopted for real-time indoor pedestrian location tracking. Since both kinds of systems have their own advantages and disadvantages, a maximum likelihood-based fusion algorithm that integrates a typical Wi-Fi indoor positioning system with a PDR system is proposed in this paper. The strength of the PDR system should eliminate the weakness of the Wi-Fi positioning system and vice versa. The intelligent fusion algorithm can retrieve the initial user location and moving direction information without requiring any user intervention. Experimental results show that the proposed positioning system has better positioning accuracy than the PDR system or Wi-Fi positioning system alone.
Keywords :
indoor radio; maximum likelihood estimation; pedestrians; radio direction-finding; sensor fusion; wireless LAN; PDR systems; Wi-Fi indoor positioning system; indoor positioning systems; inertial sensors; initial user location; intelligent fusion algorithm; maximum likelihood-based fusion algorithm; moving direction information; pedestrian dead reckoning systems; real-time indoor pedestrian location tracking; wireless local area networks; Accuracy; Fingerprint recognition; IEEE 802.11 Standards; Indoor environments; Sensor systems; Trajectory; Dead reckoning; WLAN; indoor positioning; received signal strength; sensor;
Journal_Title :
Sensors Journal, IEEE
DOI :
10.1109/JSEN.2014.2330573