{"id":{"repo_id":"texas","oai_identifier":"oai:repositories.lib.utexas.edu:2152/87405"},"canonical_url":"https://search.dev.ndltd.org/etd/texas/oai:repositories.lib.utexas.edu:2152/87405","repository":{"repo_id":"texas","name":"University of Texas","base_url":"https://repositories.lib.utexas.edu/server/oai/request"},"display":{"title":"Extending the range of low SWaP-C FMCW radar","abstract":"This thesis develops, analyzes, and tests a method to adapt low-cost, automotive-grade radar chipsets for long-range sensing. These disruptive chipsets offer impressive performance at low size, weight, power, and cost (SWaP-C) that could benefit applications with tight SWaP-C budgets such as urban air mobility and urban air logistics. The short range of these radars currently prevents their deployment in long-range applications, so this thesis employs extended measurement intervals coupled with sophisticated motion modeling and signal processing to significantly extend their range. After deriving the optimal maximum likelihood estimator, the thesis presents suboptimal, more efficient techniques for target range estimation that are robust to target motion uncertainty. These techniques are validated in simulation and demonstrated via experiment. The results show that low SWaP-C radar chipsets are capable of operating at low SNR to perform long-range sensing when augmented with this thesis's motion modeling and signal processing techniques. This potent combination of low SWaP-C hardware and advanced signal processing will drive innovation in urban air mobility, urban air logistics, and other areas in need of long-range sensing.","abstract_html":"This thesis develops, analyzes, and tests a method to adapt low-cost, automotive-grade radar chipsets for long-range sensing. These disruptive chipsets offer impressive performance at low size, weight, power, and cost (SWaP-C) that could benefit applications with tight SWaP-C budgets such as urban air mobility and urban air logistics. The short range of these radars currently prevents their deployment in long-range applications, so this thesis employs extended measurement intervals coupled with sophisticated motion modeling and signal processing to significantly extend their range. After deriving the optimal maximum likelihood estimator, the thesis presents suboptimal, more efficient techniques for target range estimation that are robust to target motion uncertainty. These techniques are validated in simulation and demonstrated via experiment. The results show that low SWaP-C radar chipsets are capable of operating at low SNR to perform long-range sensing when augmented with this thesis's motion modeling and signal processing techniques. This potent combination of low SWaP-C hardware and advanced signal processing will drive innovation in urban air mobility, urban air logistics, and other areas in need of long-range sensing.","abstract_has_math":false,"creators":["Lies, William Arthur"],"institution":"The University of Texas at Austin","degree_name":"Master of Science in Engineering","degree_level":"Masters","degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Humphreys, Todd Edwin"],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-05-10","date_published":"2021-05-10","updated_at":"2026-07-24T05:01:02Z","subjects":["FMCW","Urban air mobility","Model reduction","Maximum likelihood","Low SWaP-C","Low-cost sensing","Long-range sensing","Range bin migration"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://dx.doi.org/10.26153/tsw/14354"],"render_values":[{"text":"http://dx.doi.org/10.26153/tsw/14354","href":"http://dx.doi.org/10.26153/tsw/14354","code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/2152/87405","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Humphreys, Todd Edwin"]},{"key":"dc:creator","label":"Author","values":["Lies, William Arthur"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2021-09-02T21:40:53Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2021-09-02T21:40:53Z"]},{"key":"dc:date.issued","label":"Date","values":["2021-05-10"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Engineering"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The University of Texas at Austin"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["FMCW","Urban air mobility","Model reduction","Maximum likelihood","Low SWaP-C","Low-cost sensing","Long-range sensing","Range bin migration"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/2152/87405","http://dx.doi.org/10.26153/tsw/14354"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis develops, analyzes, and tests a method to adapt low-cost, automotive-grade radar chipsets for long-range sensing. 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This potent combination of low SWaP-C hardware and advanced signal processing will drive innovation in urban air mobility, urban air logistics, and other areas in need of long-range sensing."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Extending the range of low SWaP-C FMCW radar"]}]}],"canonical_facts":{"dc:contributor.advisor":["Humphreys, Todd Edwin"],"dc:creator":["Lies, William Arthur"],"dc:date.accessioned":["2021-09-02T21:40:53Z"],"dc:date.available":["2021-09-02T21:40:53Z"],"dc:date.issued":["2021-05-10"],"dc:description.abstract":["This thesis develops, analyzes, and tests a method to adapt low-cost, automotive-grade radar chipsets for long-range sensing. These disruptive chipsets offer impressive performance at low size, weight, power, and cost (SWaP-C) that could benefit applications with tight SWaP-C budgets such as urban air mobility and urban air logistics. The short range of these radars currently prevents their deployment in long-range applications, so this thesis employs extended measurement intervals coupled with sophisticated motion modeling and signal processing to significantly extend their range. After deriving the optimal maximum likelihood estimator, the thesis presents suboptimal, more efficient techniques for target range estimation that are robust to target motion uncertainty. These techniques are validated in simulation and demonstrated via experiment. The results show that low SWaP-C radar chipsets are capable of operating at low SNR to perform long-range sensing when augmented with this thesis's motion modeling and signal processing techniques. 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