Bibliographic Details
| Title: |
A Novel Passive Indoor Localization Method by Fusion CSI Amplitude and Phase Information |
| Authors: |
Xiaochao Dang, Xiong Si, Zhanjun Hao, Yaning Huang |
| Source: |
Sensors, Vol 19, Iss 4, p 875 (2019) |
| Publisher Information: |
MDPI AG, 2019. |
| Publication Year: |
2019 |
| Collection: |
LCC:Chemical technology |
| Subject Terms: |
indoor localization, channel state information, device-free passive, WiFi fingerprint, naive Bayes classification, feature fusion, Chemical technology, TP1-1185 |
| More Details: |
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. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1424-8220 |
| Relation: |
https://www.mdpi.com/1424-8220/19/4/875; https://doaj.org/toc/1424-8220 |
| DOI: |
10.3390/s19040875 |
| Access URL: |
https://doaj.org/article/5203f8ecc6ae4e3189a38f686d303b09 |
| Accession Number: |
edsdoj.5203f8ecc6ae4e3189a38f686d303b09 |
| Database: |
Directory of Open Access Journals |
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