Walking GPS: A Practical Solution for Localization in Manually Deployed Wireless Sensor Networks
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
OPT: online person tracking system for context-awareness in wireless personal network
REALMAN '06 Proceedings of the 2nd international workshop on Multi-hop ad hoc networks: from theory to reality
B-Spline curve smoothing under position constraints for line generalisation
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
MoteTrack: a robust, decentralized approach to RF-Based location tracking
LoCA'05 Proceedings of the First international conference on Location- and Context-Awareness
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A novel RSSI (Received Signal Strength Indication) refinement algorithm is proposed to enhance the resolution for indoor and outdoor real-time location tracking system. The proposed refinement algorithm is implemented in two separate phases. During the first phase, called the pre-processing step, RSSI values at different static locations are collected and processed to build a calibrated model for each reference node. Different measurement campaigns pertinent to each parameter in the model are implemented to analyze the sensitivity of RSSI. The propagation models constructed for each reference nodes are needed by the second phase. During the next phase, called the runtime process, real-time tracking is performed. Smoothing algorithm is proposed to minimize the dynamic fluctuation of radio signal received from each reference node when the mobile target is moving. Filtered RSSI values are converted to distances using formula calibrated in the first phase. Finally, an iterative trilateration algorithm is used for position estimation. Experiments relevant to the optimization algorithm are carried out in both indoor and outdoor environments and the results validated the feasibility of proposed algorithm in reducing the dynamic fluctuation for more accurate position estimation.