Name
Abstract | ||
|---|---|---|
With the growing development of smartphones equipped with Wi-Fi technology and the need of inexpensive indoor location systems, many researchers are focusing their efforts on the development of Wi-Fi-based indoor localization methods. However, due to the difficulties in characterizing the Wi-Fi radio signal propagation in such environments, the development of universal indoor localization mechanisms is still an open issue. In this paper, we focus on the calibration of Wi-Fi-based indoor tracking systems to be used by smartphones. The primary goal is to build an accurate and robust Wi-Fi signal propagation representation in indoor scenarios.We analyze the suitability of our approach in a smartphone-based indoor tracking system by introducing a novel in-motion calibration methodology using three different signal propagation characterizations supplemented with a particle filter. We compare the results obtained with each one of the three characterization in-motion calibration methodologies and those obtained using a static calibration approach, in a real-world scenario. Based on our experimental results, we show that the use of an in-motion calibration mechanism considerably improves the tracking accuracy. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/rs11091072 | REMOTE SENSING |
Keywords | Field | DocType |
RSSI-based,particle filter,in-motion calibration,smartphone tracking,path loss model | Computer vision,Android (operating system),Tracking system,Real-time computing,Artificial intelligence,Geology,Calibration | Journal |
Volume | Issue | Citations |
11 | 9 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miguel Martínez del Horno | 1 | 0 | 0.34 |
| Ismael García-varea | 2 | 275 | 36.16 |
| Luis Orozco-Barbosa | 3 | 366 | 55.21 |