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Open AccessArticle

A Novel Passive Indoor Localization Method by Fusion CSI Amplitude and Phase Information

1
College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China
2
Gansu Province Internet of Things Engineering Research Center, Lanzhou 730070, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(4), 875; https://doi.org/10.3390/s19040875
Received: 1 December 2018 / Revised: 3 February 2019 / Accepted: 15 February 2019 / Published: 20 February 2019
(This article belongs to the Special Issue Smart Monitoring and Control in the Future Internet of Things)
With the rapid development of wireless network technology, wireless passive indoor localization has become an increasingly important technique that is widely used in indoor location-based services. Channel state information (CSI) can provide more detailed and specific subcarrier information, which has gained the attention of researchers and has become an emphasis in indoor localization technology. However, existing research has generally adopted amplitude information for eigenvalue calculations. There are few research studies that have used phase information from CSI signals for localization purposes. To eliminate the signal interference existing in indoor environments, we present a passive human indoor localization method named FapFi, which fuses CSI amplitude and phase information to fully utilize richer signal characteristics to find location. In the offline stage, we filter out redundant values and outliers in the CSI amplitude information and then process the CSI phase information. A fusion method is utilized to store the processed amplitude and phase information as a fingerprint database. The experimental data from two typical laboratory and conference room environments were gathered and analyzed. The extensive experimental results demonstrate that the proposed algorithm is more efficient than other algorithms in data processing and achieves decimeter-level localization accuracy. View Full-Text
Keywords: indoor localization; channel state information; device-free passive; WiFi fingerprint; naive Bayes classification; feature fusion indoor localization; channel state information; device-free passive; WiFi fingerprint; naive Bayes classification; feature fusion
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MDPI and ACS Style

Dang, X.; Si, X.; Hao, Z.; Huang, Y. A Novel Passive Indoor Localization Method by Fusion CSI Amplitude and Phase Information. Sensors 2019, 19, 875.

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