The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
LiFS: low human-effort, device-free localization with fine-grained subcarrier information
Abstract
Device-free localization of people and objects indoors not equipped with radios is playing a critical role in many emerging applications. This paper presents an accurate model-based device-free localization system LiFS, implemented on cheap commercial off-the-shelf (COTS) Wi-Fi devices. Unlike previous COTS device-based work, LiFS is able to localize a target accurately without offline training. The basic idea is simple: channel state information (CSI) is sensitive to a target's location and by modelling the CSI measurements of multiple wireless links as a set of power fading based equations, the target location can be determined. However, due to rich multipath propagation indoors, the received signal strength (RSS) or even the fine-grained CSI can not be easily modelled. We observe that even in a rich multipath environment, not all subcarriers are affected equally by multipath reflections. Our pre-processing scheme tries to identify the subcarriers not affected by multipath. Thus, CSIs on the "clean" subcarriers can be utilized for accurate localization.
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Cites
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Indoor localization without the pain
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Self-citationE-eyes: device-free location-oriented activity identification using fine-grained WiFi signatures
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Widar: Decimeter-Level Passive Tracking via Velocity Monitoring with Commodity Wi-Fi
Qian, K., Wu, C., Yang, Z., Liu, Y., & Jamieson, K. (2017) · Proceedings of the 18th ACM International Symposium on Mobile Ad Hoc Networking and Computing · doi:10.1145/3084041.3084067 · Cited by 328
Self-citationWidar3.0: Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi
Zhang, Y., Zheng, Y., Qian, K., Zhang, G., Liu, Y., Wu, C., & Yang, Z. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3105387 · Cited by 312
Precise Power Delay Profiling with Commodity Wi-Fi
Xie, Y., Li, Z., & Li, M. (2019) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2018.2860991 · Cited by 282
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Self-citation
Metadata
- Authors
- Wang, J., Jiang, H., Xiong, J., Jamieson, K., Chen, X., Fang, D., & Xie, B.
- Venue
- Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking
- Publisher
- ACM
- Published
- 2016-10-03
- Pages
- 243-256
- ISSN
- 1543-5679 (ISSN-L)
- OpenAlex
- W2526606216
- Cited by
- 266
- References
- 40
- FWCI
- 48.52
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Wang, J., Jiang, H., Xiong, J., Jamieson, K., Chen, X., Fang, D., & Xie, B. (2016). LiFS: low human-effort, device-free localization with fine-grained subcarrier information. Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking. https://doi.org/10.1145/2973750.2973776
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