{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/162724"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/162724","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"High-Speed Simulator for Millimeter-Wave Synthetic Aperture Radar","abstract":"The past few years have witnessed growing interest in using millimeter-wave signals for non-line-of-sight (NLOS) perception tasks, with applications in robotics, augmented reality, and smart-homes. However, existing systems suffer from a lack of large mmWave datasets, resulting in limited accuracy and generalizability compared to their line-of-sight, camera-based counterparts. We present the design, implementation, and evaluation of mmSim, a new, high-speed millimeter-wave (mmWave) simulator capable of producing large synthetic datasets to help drive the field of mmWave-based NLOS perception. mmSim introduces two main contributions to improve the speed over existing mmWave simulators. First, it pre-selects areas of the object, which will produce reflections towards each simulated antenna location, allowing it to minimize future computation. Second, it introduces a coarse-to-fine approach to allow early, less critical steps to operate at lower resolutions, while maintaining the high resolution in later steps required for high-accuracy images. These techniques, combined with other performance optimizations, allow mmSim to achieve an over 24x improvement in speed over state-of-the-art mmWave simulators.","abstract_html":"The past few years have witnessed growing interest in using millimeter-wave signals for non-line-of-sight (NLOS) perception tasks, with applications in robotics, augmented reality, and smart-homes. However, existing systems suffer from a lack of large mmWave datasets, resulting in limited accuracy and generalizability compared to their line-of-sight, camera-based counterparts. We present the design, implementation, and evaluation of mmSim, a new, high-speed millimeter-wave (mmWave) simulator capable of producing large synthetic datasets to help drive the field of mmWave-based NLOS perception. mmSim introduces two main contributions to improve the speed over existing mmWave simulators. First, it pre-selects areas of the object, which will produce reflections towards each simulated antenna location, allowing it to minimize future computation. Second, it introduces a coarse-to-fine approach to allow early, less critical steps to operate at lower resolutions, while maintaining the high resolution in later steps required for high-accuracy images. These techniques, combined with other performance optimizations, allow mmSim to achieve an over 24x improvement in speed over state-of-the-art mmWave simulators.","abstract_has_math":false,"creators":["Kuka, Adrian"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","school":null,"contributors":[],"advisors":["Adib, Fadel"],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-05","date_published":"2025-05","updated_at":"2026-07-22T22:21:57Z","subjects":[],"languages":[],"rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"rights_urls":["https://rightsstatements.org/page/InC-EDU/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/162724","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Adib, Fadel"]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. 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However, existing systems suffer from a lack of large mmWave datasets, resulting in limited accuracy and generalizability compared to their line-of-sight, camera-based counterparts. We present the design, implementation, and evaluation of mmSim, a new, high-speed millimeter-wave (mmWave) simulator capable of producing large synthetic datasets to help drive the field of mmWave-based NLOS perception. mmSim introduces two main contributions to improve the speed over existing mmWave simulators. First, it pre-selects areas of the object, which will produce reflections towards each simulated antenna location, allowing it to minimize future computation. Second, it introduces a coarse-to-fine approach to allow early, less critical steps to operate at lower resolutions, while maintaining the high resolution in later steps required for high-accuracy images. These techniques, combined with other performance optimizations, allow mmSim to achieve an over 24x improvement in speed over state-of-the-art mmWave simulators."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.Eng."]},{"key":"dc:title","label":"Title","values":["High-Speed Simulator for Millimeter-Wave Synthetic Aperture Radar"]}]}],"canonical_facts":{"dc:contributor.advisor":["Adib, Fadel"],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science"],"dc:creator":["Kuka, Adrian"],"dc:date.accessioned":["2025-09-18T14:29:09Z"],"dc:date.available":["2025-09-18T14:29:09Z"],"dc:date.issued":["2025-05"],"dc:description.abstract":["The past few years have witnessed growing interest in using millimeter-wave signals for non-line-of-sight (NLOS) perception tasks, with applications in robotics, augmented reality, and smart-homes. However, existing systems suffer from a lack of large mmWave datasets, resulting in limited accuracy and generalizability compared to their line-of-sight, camera-based counterparts. We present the design, implementation, and evaluation of mmSim, a new, high-speed millimeter-wave (mmWave) simulator capable of producing large synthetic datasets to help drive the field of mmWave-based NLOS perception. mmSim introduces two main contributions to improve the speed over existing mmWave simulators. First, it pre-selects areas of the object, which will produce reflections towards each simulated antenna location, allowing it to minimize future computation. Second, it introduces a coarse-to-fine approach to allow early, less critical steps to operate at lower resolutions, while maintaining the high resolution in later steps required for high-accuracy images. These techniques, combined with other performance optimizations, allow mmSim to achieve an over 24x improvement in speed over state-of-the-art mmWave simulators."],"dc:description.degree":["M.Eng."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/162724"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"dc:rights.uri":["https://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["High-Speed Simulator for Millimeter-Wave Synthetic Aperture Radar"],"dc:type":["Thesis"],"thesis:degree_name":["Master","Master of Engineering in Electrical Engineering and Computer Science"]},"updated_at":"2026-07-22T22:21:57Z"}