{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/121378"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/121378","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Radar-based in-cabin sensing using 60 GHz stepped-frequency continuous-wave radar","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-08-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-08-01","abstract_has_math":false,"creators":["Yao, Chun-Kai (Sean)"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Soltanaghai, Elahe"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-08","date_published":"2023-08","updated_at":"2026-07-22T22:24:57Z","subjects":["Stepped-frequency Continuous-wave (sfcw) Radar","In-cabin Sensing","Digital Signal Processing"],"languages":["en","eng"],"rights":["Copyright 2023 Chun-Kai (Sean) Yao"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/121378","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Soltanaghai, Elahe"]},{"key":"dc:creator","label":"Author","values":["Yao, Chun-Kai (Sean)"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-08","2023-07-19"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Stepped-frequency Continuous-wave (sfcw) Radar","In-cabin Sensing","Digital Signal Processing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 Chun-Kai (Sean) Yao"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/121378"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-08-01","The student, Chun-Kai (Sean) Yao, accepted the attached license on 2023-07-18 at 19:14.","The student, Chun-Kai (Sean) Yao, submitted this Thesis for approval on 2023-07-18 at 19:15.","This Thesis was approved for publication on 2023-07-19 at 11:03.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19734 on 2023-12-04 at 17:18:52","Child safety in vehicles has become a critical concern, with numerous fatalities and injuries occurring due to improper seatbelt usage and heatstroke deaths from children being left in hot cars. To address this issue, this research presents a radar-based in-cabin sensing system designed to monitor the occupants' presence in the car and classify them as children, adults, or pets for targeted safety measures. The proposed method combines occupancy detection and vital sign detection to provide accurate information about the occupants and their health status. Our approach employs a Stepped-Frequency Continuous-Wave (SFCW) millimeter wave radar, which offers a high resolution and signal-to-noise ratio. We explore three methods for occupancy detection: power loss profiling, Fast Fourier Transform (FFT), and Multiple Signal Classification (MUSIC). Vital sign detection is achieved using Doppler-based techniques. We developed a robust in-cabin sensing that utilizes the benefits from occupancy detection and vital sign detection to complement each other to achieve more robust sensing and promising accuracy. Preliminary results demonstrate the potential of this system, but further research and access to super-computational resources are required to optimize the processing methods, improve memory management, and incorporate reinforcement learning techniques. Our goal is to significantly reduce the number of child-related fatalities and injuries in motor vehicles by enhancing vehicle safety through advanced sensing and detection technologies."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Radar-based in-cabin sensing using 60 GHz stepped-frequency continuous-wave radar"]}]}],"canonical_facts":{"dc:contributor":["Soltanaghai, Elahe"],"dc:creator":["Yao, Chun-Kai (Sean)"],"dc:date":["2023-08","2023-07-19"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-08-01","The student, Chun-Kai (Sean) Yao, accepted the attached license on 2023-07-18 at 19:14.","The student, Chun-Kai (Sean) Yao, submitted this Thesis for approval on 2023-07-18 at 19:15.","This Thesis was approved for publication on 2023-07-19 at 11:03.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19734 on 2023-12-04 at 17:18:52","Child safety in vehicles has become a critical concern, with numerous fatalities and injuries occurring due to improper seatbelt usage and heatstroke deaths from children being left in hot cars. To address this issue, this research presents a radar-based in-cabin sensing system designed to monitor the occupants' presence in the car and classify them as children, adults, or pets for targeted safety measures. The proposed method combines occupancy detection and vital sign detection to provide accurate information about the occupants and their health status. Our approach employs a Stepped-Frequency Continuous-Wave (SFCW) millimeter wave radar, which offers a high resolution and signal-to-noise ratio. We explore three methods for occupancy detection: power loss profiling, Fast Fourier Transform (FFT), and Multiple Signal Classification (MUSIC). Vital sign detection is achieved using Doppler-based techniques. We developed a robust in-cabin sensing that utilizes the benefits from occupancy detection and vital sign detection to complement each other to achieve more robust sensing and promising accuracy. Preliminary results demonstrate the potential of this system, but further research and access to super-computational resources are required to optimize the processing methods, improve memory management, and incorporate reinforcement learning techniques. Our goal is to significantly reduce the number of child-related fatalities and injuries in motor vehicles by enhancing vehicle safety through advanced sensing and detection technologies."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/121378"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Chun-Kai (Sean) Yao"],"dc:subject":["Stepped-frequency Continuous-wave (sfcw) Radar","In-cabin Sensing","Digital Signal Processing"],"dc:title":["Radar-based in-cabin sensing using 60 GHz stepped-frequency continuous-wave radar"],"dc:type":["text"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:57Z"}