The active badge location system
ACM Transactions on Information Systems (TOIS)
The Cricket location-support system
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
The smart floor: a mechanism for natural user identification and tracking
CHI '00 Extended Abstracts on Human Factors in Computing Systems
Range-free localization schemes for large scale sensor networks
Proceedings of the 9th annual international conference on Mobile computing and networking
PERCOM '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications
IEEE Transactions on Knowledge and Data Engineering
Enhanced RSSI-Based Real-Time User Location Tracking System for Indoor and Outdoor Environments
ICCIT '07 Proceedings of the 2007 International Conference on Convergence Information Technology
A Scrambling Method for Fingerprint Positioning Based on Temporal Diversity and Spatial Dependency
IEEE Transactions on Knowledge and Data Engineering
Statistical learning theory for location fingerprinting in wireless LANs
Computer Networks: The International Journal of Computer and Telecommunications Networking
Sensor Localization under Limited Measurement Capabilities
IEEE Network: The Magazine of Global Internetworking
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Tracing the location of a specific item has induced abundant applications with the development of wireless sensor networks. In past years, different location algorithms have been proposed for indoor or outdoor environments. Some of these use additional equipments, such as GPS [1-3], Infrared [4], and Ultrasound [5]. However, these equipments will increase the power consumption and system cost. In this paper, we propose a PPM (Priority-based Pattern Matching) algorithm, only use embedded RF chip, to improve the PM (Pattern Matching) algorithm in the indoor environment. The proposed PPM algorithm is different from those algorithms designed for gallery environments [21-25]. PPM is specialized designed for the complicated indoor environments. Experiments show that PPM is outstanding over PM with not only lower training time in 50% but also higher positioning precision in 24.2%-40.7%.