Authors
Zhou, FuLin, Kaixian
Ren, Aifeng
Cao, Dongjian
Zhang, Zhiya
Ur-Rehman, Masood
Yang, Xiaodong
Alomainy, Akram
Issue Date
2017-10-02Subjects
radio propagationZigbee
Bayesian theorem
RSSI
Gaussian distribution
maximum likelihood estimation
Bayes methods
Metadata
Show full item recordAbstract
A method to locate the position of the user in an indoor environment employing Bayesian theory is presented in this paper. A detailed analysis of the positional accuracy is carried out evaluating effects of two major degradation factors namely the measurement and calculation errors. The proposed technique makes use of the Gaussian distribution of random data in indoor Zigbee propagation model based on received signal strength indicator (RSSI) and the triangular positioning algorithm, maximum likelihood estimation (MLE) and Bayesian theory. It identifies the user's location calculating the maximum probability point. The proposed method offers high accuracy levels with a mean error of 0.1363m as compared to the mean error values of 1.4059m and 0.4291m for the triangular localization and triangular localization with MLE methods, respectively.Citation
Zhou F, Lin K, Ren A, Cao D, Zhang Z, Ur Rehman M, Yang X, Alomainy A (2017) 'RSSI indoor localization through a Bayesian strategy', IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) - Chongqing, IEEE.Publisher
IEEEAdditional Links
https://ieeexplore.ieee.org/document/8054360Type
Conference papers, meetings and proceedingsLanguage
enae974a485f413a2113503eed53cd6c53
10.1109/IAEAC.2017.8054360