TrackCC: A Practical Wireless Indoor Localization System Based on Less-Expensive Chips
The School of Computer Science and Information Security, Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin 541004, China
Mobile E-Business Collaborative Innovation Center of Hunan Province, Key Laboratory of Hunan Province for Mobile Business Intelligence, Hunan University of Commerce, Changsha 410205, China
The Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada
The Department of Computer and Information Engineering, Hechi University, Hechi 546300, China
Author to whom correspondence should be addressed.
Received: 26 April 2017 / Revised: 9 June 2017 / Accepted: 9 June 2017 / Published: 15 June 2017
This paper aims at proposing a new wireless indoor localization system (ILS), called TrackCC, based on a commercial type of low-power system-on-chip (SoC), nRF24LE1. This type of chip has only l
output power levels and acute fluctuation for a received minimum power level in operation, which give rise to many practical challenges for designing localization algorithms. In order to address these challenges, we exploit the Markov theory to construct a
-sized state transition matrix to remove the fluctuation, and then propose a priority-based pattern matching algorithm to search for the most similar match in the signal map to estimate the real position of unknown nodes. The experimental results show that, compared to two existing wireless ILSs, LANDMARC and SAIL, which have meter level positioning accuracy, the proposed TrackCC can achieve the decimeter level accuracy on average in both line-of-sight (LOS) and non-line-of-sight (NLOS) senarios.
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MDPI and ACS Style
Li, X.; Zheng, Y.; Cai, J.; Yi, Y. TrackCC: A Practical Wireless Indoor Localization System Based on Less-Expensive Chips. Sensors 2017, 17, 1391.
Li X, Zheng Y, Cai J, Yi Y. TrackCC: A Practical Wireless Indoor Localization System Based on Less-Expensive Chips. Sensors. 2017; 17(6):1391.
Li, Xiaolong; Zheng, Yan; Cai, Jun; Yi, Yunfei. 2017. "TrackCC: A Practical Wireless Indoor Localization System Based on Less-Expensive Chips." Sensors 17, no. 6: 1391.
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