The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A reliable and accurate indoor localization method using phone inertial sensors
Abstract
This paper addresses reliable and accurate indoor localization using inertial sensors commonly found on commodity smartphones. We believe indoor positioning is an important primitive that can enable many ubiquitous computing applications. To tackle the challenges of drifting in estimation, sensitivity to phone position, as well as variability in user walking profiles, we have developed algorithms for reliable detection of steps and heading directions, and accurate estimation and personalization of step length. We've built an end-to-end localization system integrating these modules and an indoor floor map, without the need for infrastructure assistance. We demonstrated for the first time a meter-level indoor positioning system that is infrastructure free, phone position independent, user adaptive, and easy to deploy. We have conducted extensive experiments on users with smartphone devices, with over 50 subjects walking over an aggregate distance of over 40 kilometers. Evaluation results showed our system can achieve a mean accuracy of 1.5m for the in-hand case and 2m for the in-pocket case in a 31m×15m testing area.
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Cites
RADAR: an in-building RF-based user location and tracking system
Bahl, P., & Padmanabhan, V. N. (2002) · Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064) · doi:10.1109/infcom.2000.832252 · Cited by 8,380
The Horus WLAN location determination system
Youssef, M., & Agrawala, A. (2005) · Proceedings of the 3rd international conference on Mobile systems, applications, and services · doi:10.1145/1067170.1067193 · Cited by 1,653
Cited by
Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons
He, S., & Chan, S.-H. G. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2464084 · Cited by 1,355
Dude, where's my card?: RFID positioning that works with multipath and non-line of sight
Wang, J., & Katabi, D. (2013) · Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM · doi:10.1145/2486001.2486029 · Cited by 482
Electronic frog eye: Counting crowd using WiFi
Xi, W., Zhao, J., Li, X.-Y., Zhao, K., Tang, S., Liu, X., & Jiang, Z. (2014) · IEEE INFOCOM 2014 - IEEE Conference on Computer Communications · doi:10.1109/infocom.2014.6847958 · Cited by 398
RGB-D camera based wearable navigation system for the visually impaired
Lee, Y. H., & Medioni, G. (2016) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2016.03.019 · Cited by 143
Yao, S., Zhao, Y., Shao, H., Liu, D., Liu, S., Hao, Y., Piao, A., Hu, S., Lu, S., & Abdelzaher, T. F. (2019) · IEEE INFOCOM 2019 - IEEE Conference on Computer Communications · doi:10.1109/infocom.2019.8737500 · Cited by 52
Metadata
- Authors
- Li, F., Zhao, C., Ding, G., Gong, J., Liu, C., & Zhao, F.
- Venue
- Proceedings of the 2012 ACM Conference on Ubiquitous Computing
- Publisher
- ACM
- Published
- 2012-09-05
- Pages
- 421-430
- OpenAlex
- W2100045669
- Cited by
- 574
- References
- 2
- FWCI
- 67.14
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Li, F., Zhao, C., Ding, G., Gong, J., Liu, C., & Zhao, F. (2012). A reliable and accurate indoor localization method using phone inertial sensors. Proceedings of the 2012 ACM Conference on Ubiquitous Computing. https://doi.org/10.1145/2370216.2370280
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