Object tracking in mmWave radar networks

Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, May, 2020

Bibliographic Details
Main Author: Miller, Samuel(Samuel John)
Other Authors: Moe Z. Win.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2020
Subjects:
Online Access:https://hdl.handle.net/1721.1/127079
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author Miller, Samuel(Samuel John)
author2 Moe Z. Win.
author_facet Moe Z. Win.
Miller, Samuel(Samuel John)
author_sort Miller, Samuel(Samuel John)
collection MIT
description Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, May, 2020
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spelling mit-1721.1/1270792020-09-04T03:17:42Z Object tracking in mmWave radar networks Miller, Samuel(Samuel John) Moe Z. Win. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Aeronautics and Astronautics. 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 2020-09-03T17:45:55Z 2020-09-03T17:45:55Z 2020 2020 Thesis https://hdl.handle.net/1721.1/127079 1191823989 eng 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 87 pages application/pdf Massachusetts Institute of Technology
spellingShingle Aeronautics and Astronautics.
Miller, Samuel(Samuel John)
Object tracking in mmWave radar networks
title Object tracking in mmWave radar networks
title_full Object tracking in mmWave radar networks
title_fullStr Object tracking in mmWave radar networks
title_full_unstemmed Object tracking in mmWave radar networks
title_short Object tracking in mmWave radar networks
title_sort object tracking in mmwave radar networks
topic Aeronautics and Astronautics.
url https://hdl.handle.net/1721.1/127079
work_keys_str_mv AT millersamuelsamueljohn objecttrackinginmmwaveradarnetworks