2026-09-18T21:59:05Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1270792021-07-05T14:03:20Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Moe Z. Win.
Miller, Samuel(Samuel John)
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
2020-09-03T17:45:55Z
2020-09-03T17:45:55Z
2020
2020
https://hdl.handle.net/1721.1/127079
1191823989
Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, May, 2020
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 71-87).
Location-aware devices enable new services such as localization and tracking of objects within existing wireless communication networks like cellular mobile, Wi-Fi, and radio. To ensure these services are also available in the evolving millimeter wave (mmWave) communication infrastructure, it is important to develop algorithms that enable mmWave devices, like radars and 5G nodes, to localize and track objects. The main challenges that these algorithms must address is localizing objects that are not carrying sensing equipment, synchronizing devices exclusively via the mmWave band, and solving a data association uncertainty problem to reliably track objects of interest. Our development of the Multistatic Networking with mmWave Radar Arrays for Positioning (MiNiMAP) system solved these challenges by implementing mmWave processing in a multistatic network, scheduling, and radar synchronization algorithms. Through the use of these three algorithms in addition to Bayesian filtering, MiNiMAP is capable of tracking a single object with a network of mmWave radars. Indoor localization experiments validate MiNiMAP's overall system performance and the impact of each algorithm.
by Samuel Miller.
S.M.
S.M. Massachusetts Institute of Technology, Department of Aeronautics and Astronautics
87 pages
eng
Massachusetts Institute of Technology
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
http://dspace.mit.edu/handle/1721.1/7582
Aeronautics and Astronautics.
Object tracking in mmWave radar networks
Thesis
application/pdf
2020-09-03T17:45:54Z
Publication
Master
Aero
unknown
unknown
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<Abstract>Location-aware devices enable new services such as localization and tracking of objects within existing wireless communication networks like cellular mobile, Wi-Fi, and radio. To ensure these services are also available in the evolving millimeter wave (mmWave) communication infrastructure, it is important to develop algorithms that enable mmWave devices, like radars and 5G nodes, to localize and track objects. The main challenges that these algorithms must address is localizing objects that are not carrying sensing equipment, synchronizing devices exclusively via the mmWave band, and solving a data association uncertainty problem to reliably track objects of interest. Our development of the Multistatic Networking with mmWave Radar Arrays for Positioning (MiNiMAP) system solved these challenges by implementing mmWave processing in a multistatic network, scheduling, and radar synchronization algorithms. Through the use of these three algorithms in addition to Bayesian filtering, MiNiMAP is capable of tracking a single object with a network of mmWave radars. Indoor localization experiments validate MiNiMAP's overall system performance and the impact of each algorithm.</Abstract>
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