2026-09-19T14:47:21Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1231252026-06-06T00:54:55Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
John N. Tsitsiklis and Josh Erling.
Velez, Alexandria.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2019-12-05T18:04:49Z
2019-12-05T18:04:49Z
2019
2019
https://hdl.handle.net/1721.1/123125
1128277010
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 55-56).
The incorporation of advanced digital processing technologies including high-bandwidth networks, low-cost commercial components, and advanced FPGAs into novel radio frequency (RF) sensors has resulted in significantly increased sensor capabilities while at the same time dramatically increasing the size of the data associated with test events. This work focuses on the development of management tools to analyze these large datasets to increase overall situational awareness and as a result, sensor performance which requires the development of advanced algorithms designed to address data decimation, parallelization of processing, and novel detection and filtering techniques among others. These algorithms are developed and optimized through post-processing existing MIT-LL sensor data in MATLAB.
by Alexandria Velez.
M.Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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
Electrical Engineering and Computer Science.
Utilizing I/Q data to enhance radar detection and accuracy metrics
Utilizing In-phase and quadrature data to enhance radar detection and accuracy metrics
Thesis
application/pdf
2019-12-05T18:04:49Z
Publication
Master
EECS
unknown
unknown
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