2026-09-19T03:28:44Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1186752022-01-13T07:54:05Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Fadel Adib.
Selby, Nicholas Stearns
Massachusetts Institute of Technology. Department of Mechanical Engineering.
Massachusetts Institute of Technology. Department of Mechanical Engineering
2018-10-22T18:27:49Z
2018-10-22T18:27:49Z
2018
2018
http://hdl.handle.net/1721.1/118675
1057362443
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 51-56).
This thesis aims to enable virtual and augmented reality (VR/AR) systems to track objects accurately through occlusions via RFID localization. Currently, three major obstacles prevent the use of RFID localization in VR/AR systems: (1) there exists a trade-off between measurement speed and ability to deal with multipath, so systems which can produce accurate results either require a highly constrained environment or several seconds to localize; (2) past RFID localization techniques lack robustness to changes in tag orientation; and (3) current RFID orientation extraction methodologies are largely inaccurate. To overcome these challenges, this thesis presents RF-Reality, a new system that leverages a novel OFDM backscatter technique and differential channel estimation algorithm to perform accurate, rapid RFID position and orientation recovery.
by Nicholas Stearns Selby.
S.M.
56 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
Rapid RFID location and orientation recovery
Rapid radio-frequency identification location and orientation recovery
Thesis
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<Abstract>This thesis aims to enable virtual and augmented reality (VR/AR) systems to track objects accurately through occlusions via RFID localization. Currently, three major obstacles prevent the use of RFID localization in VR/AR systems: (1) there exists a trade-off between measurement speed and ability to deal with multipath, so systems which can produce accurate results either require a highly constrained environment or several seconds to localize; (2) past RFID localization techniques lack robustness to changes in tag orientation; and (3) current RFID orientation extraction methodologies are largely inaccurate. To overcome these challenges, this thesis presents RF-Reality, a new system that leverages a novel OFDM backscatter technique and differential channel estimation algorithm to perform accurate, rapid RFID position and orientation recovery.</Abstract>
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