DocumentCode :
3570494
Title :
An adaptive ranging model under changeable environment
Author :
Jiyuan Sun ; Kai Ruan ; Mengjiao Zhang ; Yangrui Zhu ; Xiaohui Chen
Author_Institution :
Coll. of Comput. & Inf. Technol., China Three Gorges Univ., Yichang, China
fYear :
2014
Firstpage :
110
Lastpage :
114
Abstract :
Due to the complexity of the indoor environment, this paper proposes an adaptive ranging T-S model (ADRTS). The new model can be through self-learning to range and improve the ranging accuracy. The proposed method exploits the adaptive to range precisely under the changeable environments. Compared with the classical ranging model, the proposed model is with high accuracy under the indoor environment about localization, and it is feasible and simple. In the indoor environment, the simulation experiment indicates that this method is feasible and effective for improving ranging accuracy and will help to improve the accuracy of localization of node.
Keywords :
distance measurement; indoor navigation; learning (artificial intelligence); radionavigation; sensor placement; telecommunication computing; wireless sensor networks; Takagi-Sugeno model; adaptive ranging T-S model; changeable environment; indoor environment; indoor localization; self-learning model; Accuracy; Adaptation models; Analytical models; Computational modeling; Distance measurement; Mathematical model; Wireless sensor networks; Adaptive Ranging; FUZZY-TS model; Wireless Sensors Networks; changeable environments;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Science and Systems Engineering (CCSSE), 2014 IEEE International Conference on
Print_ISBN :
978-1-4799-6396-6
Type :
conf
DOI :
10.1109/CCSSE.2014.7224519
Filename :
7224519
Link To Document :
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