Title :
Dual-modal indoor mobile localization system based on prediction algorithm
Author :
Wang, Lujia ; Hu, Chao ; Wang, Jinkuan ; Tian, Longqiang ; Meng, Max Q -H
Author_Institution :
Shenzhen Inst. of Adv. Technol., Chinese Acad. of Sci., Shenzhen, China
Abstract :
Object localization defines an important application for wireless sensor networks. In this paper, we present a hybrid of dual-modal mobile localization system to support the object tracking in indoor environment. In order to decrease the system cost and simplify the sensor deployment, we implement the localization by the received radio signal strength approach and the unscented Kalman filter (SPKF) algorithm in active and passive dual-modal architecture. We realize the system by employing the wireless sensor network and the LAN medium Zigbee/802.15.4. Experimental results demonstrate that the hybrid mobile localization system can significantly improve the localization accuracy and robustness, and reduce the cost of communication among sensor nodes while mobile user is moving in the indoor environments.
Keywords :
Kalman filters; indoor radio; mobile radio; wireless LAN; wireless sensor networks; 802.15.4 standard; LAN; Zigbee; active dual-modal architecture; dual-modal indoor mobile localization system; indoor environment; mobile user; object localization; object tracking; passive dual-modal architecture; prediction algorithm; received radio signal strength localization; unscented Kalman filter algorithm; wireless sensor networks; Costs; Frequency estimation; Global Positioning System; Indoor environments; Prediction algorithms; Radar tracking; Radio frequency; Radiofrequency identification; Robustness; Ultrasonic imaging; Unscented Kalman Filter; dual-modal; mobile localization system;
Conference_Titel :
Information and Automation, 2009. ICIA '09. International Conference on
Conference_Location :
Zhuhai, Macau
Print_ISBN :
978-1-4244-3607-1
Electronic_ISBN :
978-1-4244-3608-8
DOI :
10.1109/ICINFA.2009.5204928
