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Erin-Ee-Lin Lau,Wan-Young Chung 대한전자공학회 2007 ITC-CSCC :International Technical Conference on Ci Vol.2007 No.7
A RSSI-based (Received Signal Strength Indication) real-time location tracking system in combination with several refining algorithms was designed and fabricated. The refinement algorithms are implemented in three phases. Firstly, 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. RSSI smoothing algorithm is proposed to minimize the dynamic fluctuation of radio signal received from each reference node when the blind node 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 each optimization algorithms are carried out in an open outdoor environment and the combined results validated the feasibility of proposed algorithms in reducing the dynamic fluctuation for more accurate position estimation.
LAU, Erin-Ee-Lin,CHUNG, Wan-Young The Institute of Electronics, Information and Comm 2008 IEICE transactions on fundamentals of electronics, Vol.91 No.7
<P>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.</P>