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- Publisher Website: 10.1109/INFOCOM41043.2020.9155293
- Scopus: eid_2-s2.0-85090297989
- WOS: WOS:000620945800243
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Conference Paper: MmTrack: Passive Multi-Person Localization Using Commodity Millimeter Wave Radio
Title | MmTrack: Passive Multi-Person Localization Using Commodity Millimeter Wave Radio |
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Authors | |
Issue Date | 2020 |
Citation | Proceedings - IEEE INFOCOM, 2020, v. 2020-July, p. 2400-2409 How to Cite? |
Abstract | Passive human localization and tracking using RF signals have been studied for over a decade. Most of the existing solutions, however, can only track a single moving subject due to the coarse multipath resolvability limited by bandwidth and antenna number. In this paper, we break down the limitations by leveraging the emerging 60GHz millimeter-wave radios. We present mmTrack, the first system that passively localizes and tracks multiple users simultaneously using a single commodity 60GHz radio. The design of mmTrack consists of three key components. First, we significantly improve the spatial resolution, limited by the small aperture of the compact 60GHz array, by performing digital beamforming over all receive antennas. Second, we propose a novel multi-target detection approach that tackles the near-far-effect and measurement noise. Finally, we devise a robust clustering technique to accurately recognize multiple targets and estimate the respective locations, from which their individual trajectories are further derived by a continuous tracking algorithm. We implement mmTrack on a commodity 802.11ad device and evaluate it in indoor environments. Our experiments demonstrate that mmTrack detects and counts multiple users precisely with an error ≤ 1 person for 97.8% of the time and achieves a respective median location error of 9.9 cm and 19.7 cm for dynamic and static targets. |
Persistent Identifier | http://hdl.handle.net/10722/303695 |
ISSN | 2023 SCImago Journal Rankings: 2.865 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Wu, Chenshu | - |
dc.contributor.author | Zhang, Feng | - |
dc.contributor.author | Wang, Beibei | - |
dc.contributor.author | Ray Liu, K. J. | - |
dc.date.accessioned | 2021-09-15T08:25:50Z | - |
dc.date.available | 2021-09-15T08:25:50Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Proceedings - IEEE INFOCOM, 2020, v. 2020-July, p. 2400-2409 | - |
dc.identifier.issn | 0743-166X | - |
dc.identifier.uri | http://hdl.handle.net/10722/303695 | - |
dc.description.abstract | Passive human localization and tracking using RF signals have been studied for over a decade. Most of the existing solutions, however, can only track a single moving subject due to the coarse multipath resolvability limited by bandwidth and antenna number. In this paper, we break down the limitations by leveraging the emerging 60GHz millimeter-wave radios. We present mmTrack, the first system that passively localizes and tracks multiple users simultaneously using a single commodity 60GHz radio. The design of mmTrack consists of three key components. First, we significantly improve the spatial resolution, limited by the small aperture of the compact 60GHz array, by performing digital beamforming over all receive antennas. Second, we propose a novel multi-target detection approach that tackles the near-far-effect and measurement noise. Finally, we devise a robust clustering technique to accurately recognize multiple targets and estimate the respective locations, from which their individual trajectories are further derived by a continuous tracking algorithm. We implement mmTrack on a commodity 802.11ad device and evaluate it in indoor environments. Our experiments demonstrate that mmTrack detects and counts multiple users precisely with an error ≤ 1 person for 97.8% of the time and achieves a respective median location error of 9.9 cm and 19.7 cm for dynamic and static targets. | - |
dc.language | eng | - |
dc.relation.ispartof | Proceedings - IEEE INFOCOM | - |
dc.title | MmTrack: Passive Multi-Person Localization Using Commodity Millimeter Wave Radio | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/INFOCOM41043.2020.9155293 | - |
dc.identifier.scopus | eid_2-s2.0-85090297989 | - |
dc.identifier.volume | 2020-July | - |
dc.identifier.spage | 2400 | - |
dc.identifier.epage | 2409 | - |
dc.identifier.isi | WOS:000620945800243 | - |