Accuracy Refinement Algorithm for Mobile Target Location Tracking by Radio Signal Strength Indication Approach
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E91-A No.7 pp.1659-1665
- Publication Date
- 2008/07/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e91-a.7.1659
- Type of Manuscript
- Special Section PAPER (Special Section on Multi-dimensional Mobile Information Networks)
- Category
Authors
Keyword
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Erin-Ee-Lin LAU, Wan-Young CHUNG, "Accuracy Refinement Algorithm for Mobile Target Location Tracking by Radio Signal Strength Indication Approach" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 7, pp. 1659-1665, July 2008, doi: 10.1093/ietfec/e91-a.7.1659.
Abstract: 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.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.7.1659/_p
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@ARTICLE{e91-a_7_1659,
author={Erin-Ee-Lin LAU, Wan-Young CHUNG, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Accuracy Refinement Algorithm for Mobile Target Location Tracking by Radio Signal Strength Indication Approach},
year={2008},
volume={E91-A},
number={7},
pages={1659-1665},
abstract={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.},
keywords={},
doi={10.1093/ietfec/e91-a.7.1659},
ISSN={1745-1337},
month={July},}
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TY - JOUR
TI - Accuracy Refinement Algorithm for Mobile Target Location Tracking by Radio Signal Strength Indication Approach
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1659
EP - 1665
AU - Erin-Ee-Lin LAU
AU - Wan-Young CHUNG
PY - 2008
DO - 10.1093/ietfec/e91-a.7.1659
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 7
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - July 2008
AB - 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.
ER -
English
