Cross-Frame Association of Through-Wall Handheld-Radar-Based Detections
Name
Hiebert-mhiebert-meng-eecs-2021-thesis.pdf
Description
Thesis PDF
Size
2.19 MB
Format
Adobe PDF
Checksum (MD5)
d326fa44f3037b496e4ff39b3b814716
Author(s)
Hiebert, Michael
Advisor(s)
Ouedraogo, Raoul
Date Issued
June 2021
Publisher
Massachusetts Institute of Technology
Abstract
Recent work with radar-based detection systems has demonstrated its efficacy in identifying [10], classifying [6] [8] [2] humans and animals, and even recognizing gestures [5] in low-light environments and through walls, cases where conventional vision-based systems fail. Most previous research has involved onsite (edge) gathering of data and offsite (non-edge) processing to produce detections, i.e. the experimental platforms have not been productionized nor tested live in applicable environments. Further, many of the proposed architectures rely on the specific motion paths of subjects to identify them. MIT Lincoln Laboratory’s (MITLL) Group 45 has designed a prototype portable radar system capable of producing similar radar data to that collected in the aforementioned research and then identifying individuals in-frame, solely based on vital-signs and regardless of motion. I propose a computational architecture which can incorporate some of the previous advances with tracking in computer vision to detect and identify individuals while operating on the edge under the compute and power constraints of the handheld radar system in which it will be embedded.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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