{"id":{"repo_id":"ohiolink","oai_identifier":"oai:etd.ohiolink.edu:wright1357843204"},"canonical_url":"https://search.dev.ndltd.org/etd/ohiolink/oai:etd.ohiolink.edu:wright1357843204","repository":{"repo_id":"ohiolink","name":"OhioLINK","base_url":"https://etd.ohiolink.edu/acprod/odb_etd/ws/oai/oai"},"display":{"title":"UHF-SAR and LIDAR Complementary Sensor Fusion for Unexploded Buried Munitions Detection","abstract":"Given the UHF bands properties of foliage and round penetration, a UHF-SAR image contains both above- and below-surface scatterers. The problem of detecting sub-surface objects is problematic due to the presence of above-surface scatterers in the detection images. In case of a single-pass anomaly image or a two-pass change image, the resultinganomalies or changes are due to scatterers above and below the surface, where the above surface anomalies/changes act as confusers. LIDAR digital elevation models (DEM) provide georegistered information about the above-surface objects present in the UHF-SAR scene. Detection of the above-surface objects in the LIDAR domain is used to rule out above-surface false-alarms in the UHF-SAR domain detection images. A complementary sensor fusion algorithm is implemented which exploits the limited ground penetrating capabilities of UHF-SAR and the false-alarm removal using LIDAR. For unitemporal and multitemporal UHF-SAR collections (both containing multiple-passes and multiple- polarizations) anomaly detection and change detection are implemented, respectively. Inthis thesis, various pixel-based and feature-based change detection algorithms are implementedto study the effectiveness of multitemporal change detection algorithms. In addition, incorporation of UHF-SAR multiple-passes and multiple-polarizations further improves detection results. The algorithms are tested using data collected under JIEDDOs Halite-1 program, which provides both UHF-SAR and LIDAR DEM.","abstract_html":"Given the UHF bands properties of foliage and round penetration, a UHF-SAR image contains both above- and below-surface scatterers. The problem of detecting sub-surface objects is problematic due to the presence of above-surface scatterers in the detection images. In case of a single-pass anomaly image or a two-pass change image, the resultinganomalies or changes are due to scatterers above and below the surface, where the above surface anomalies/changes act as confusers. LIDAR digital elevation models (DEM) provide georegistered information about the above-surface objects present in the UHF-SAR scene. Detection of the above-surface objects in the LIDAR domain is used to rule out above-surface false-alarms in the UHF-SAR domain detection images. A complementary sensor fusion algorithm is implemented which exploits the limited ground penetrating capabilities of UHF-SAR and the false-alarm removal using LIDAR. For unitemporal and multitemporal UHF-SAR collections (both containing multiple-passes and multiple- polarizations) anomaly detection and change detection are implemented, respectively. Inthis thesis, various pixel-based and feature-based change detection algorithms are implementedto study the effectiveness of multitemporal change detection algorithms. In addition, incorporation of UHF-SAR multiple-passes and multiple-polarizations further improves detection results. The algorithms are tested using data collected under JIEDDOs Halite-1 program, which provides both UHF-SAR and LIDAR DEM.","abstract_has_math":false,"creators":["Depoy, Randy S., Jr."],"institution":"Wright State University","degree_name":"Master of Science in Engineering (MSEgr)","degree_level":"masters","degree_discipline":"Electrical Engineering","degree_department":null,"school":null,"contributors":["Shaw, Arnab"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-24T03:36:39Z","subjects":["Electrical Engineering","IED","VOIED","detection","change detection","UHF-SAR","UHF","SAR","LIDAR","DEM","digital elevation maps","anomaly detection","AD","CD","false-alarm reduction","false-alarm","fusion","complementary","multiple-sensor","complementary fusion","far-field detection","far-field sensor"],"languages":["English"],"rights":["unrestricted","This thesis or dissertation is protected by copyright: all rights reserved. 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The algorithms are tested using data collected under JIEDDOs Halite-1 program, which provides both UHF-SAR and LIDAR DEM."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf","p.157","33.85 MB"]},{"key":"dc:title","label":"Title","values":["UHF-SAR and LIDAR Complementary Sensor Fusion for Unexploded Buried Munitions Detection"]}]}],"canonical_facts":{"dc:contributor":["Shaw, Arnab"],"dc:creator":["Depoy, Randy S., Jr."],"dc:date":["2012"],"dc:description":["Given the UHF bands properties of foliage and round penetration, a UHF-SAR image contains both above- and below-surface scatterers. The problem of detecting sub-surface objects is problematic due to the presence of above-surface scatterers in the detection images. In case of a single-pass anomaly image or a two-pass change image, the resultinganomalies or changes are due to scatterers above and below the surface, where the above surface anomalies/changes act as confusers. 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