{"id":{"repo_id":"nps","oai_identifier":"oai:calhoun.nps.edu:10945/55638"},"canonical_url":"https://search.dev.ndltd.org/etd/nps/oai:calhoun.nps.edu:10945/55638","repository":{"repo_id":"nps","name":"Naval Postgraduate School","base_url":"https://calhoun.nps.edu/server/oai/request"},"display":{"title":"A technology analysis to support acquisition of UAVs for Gulf Coalition Forces operations","abstract":"This thesis examines the potential effect of unmanned aerial vehicles in the Decisive Storm operations. This analysis of UAV technology will assist Gulf Coalition Forces decision makers in their selection of the most suitable and cost-effective unmanned aerial vehicles to support detection operations. This study uses Map Aware Non-Uniform Automata, an agent-based simulation software platform, for the computational experiments. It models the operational area, system entities for the Gulf Coalition Forces, and the Houthi militia's attempts to cross the Saudi-Yemini border. The software collects relevant data that can be translated into measures of mission effectiveness. Results from 10,400 simulation runs of Houthi efforts to infiltrate the operational area are analyzed using descriptive statistics, linear regression, and partition trees. These results, which include a significantly increased percentage of infiltrators being detected by Gulf Coalition Forces and improved time to detect them, support the use of UAVs in detection missions. Computer experimentations and analyses reveal the most significant capabilities the UAV should have to achieve operational goals. These significant capabilities fall within the U.S. Department of Defense's Group 3 UAV classification. Therefore, the Gulf Coalition Forces should consider procuring UAVs in that category to enhance detection in the operational area.","abstract_html":"This thesis examines the potential effect of unmanned aerial vehicles in the Decisive Storm operations. This analysis of UAV technology will assist Gulf Coalition Forces decision makers in their selection of the most suitable and cost-effective unmanned aerial vehicles to support detection operations. This study uses Map Aware Non-Uniform Automata, an agent-based simulation software platform, for the computational experiments. It models the operational area, system entities for the Gulf Coalition Forces, and the Houthi militia's attempts to cross the Saudi-Yemini border. The software collects relevant data that can be translated into measures of mission effectiveness. Results from 10,400 simulation runs of Houthi efforts to infiltrate the operational area are analyzed using descriptive statistics, linear regression, and partition trees. These results, which include a significantly increased percentage of infiltrators being detected by Gulf Coalition Forces and improved time to detect them, support the use of UAVs in detection missions. Computer experimentations and analyses reveal the most significant capabilities the UAV should have to achieve operational goals. These significant capabilities fall within the U.S. Department of Defense's Group 3 UAV classification. Therefore, the Gulf Coalition Forces should consider procuring UAVs in that category to enhance detection in the operational area.","abstract_has_math":false,"creators":["Alobaidli, Mohamed A."],"institution":"Monterey, CA; Naval Postgraduate School","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Systems Engineering (SE)","school":null,"contributors":[],"advisors":["Hernandez, Alejandro S."],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-06","date_published":"2017-06","updated_at":"2026-07-27T20:26:05Z","subjects":[],"languages":[],"rights":["Copyright is reserved by the copyright owner."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10945/55638","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Hernandez, Alejandro S."]},{"key":"dc:contributor.department","label":"Department","values":["Systems Engineering (SE)"]},{"key":"dc:creator","label":"Author","values":["Alobaidli, Mohamed A."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["Jun-17"]},{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2017-08-14T16:49:02Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2017-08-14T16:49:02Z"]},{"key":"dc:date.issued","label":"Date","values":["2017-06"]},{"key":"dc:publisher","label":"Institution","values":["Monterey, CA; Naval Postgraduate School"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Copyright is reserved by the copyright owner."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10945/55638"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Reissued 27 Sep 2018 to reflect correct spelling of “Yemeni” throughout."]},{"key":"dc:description.abstract","label":"Abstract","values":["This thesis examines the potential effect of unmanned aerial vehicles in the Decisive Storm operations. This analysis of UAV technology will assist Gulf Coalition Forces decision makers in their selection of the most suitable and cost-effective unmanned aerial vehicles to support detection operations. This study uses Map Aware Non-Uniform Automata, an agent-based simulation software platform, for the computational experiments. It models the operational area, system entities for the Gulf Coalition Forces, and the Houthi militia's attempts to cross the Saudi-Yemini border. The software collects relevant data that can be translated into measures of mission effectiveness. Results from 10,400 simulation runs of Houthi efforts to infiltrate the operational area are analyzed using descriptive statistics, linear regression, and partition trees. These results, which include a significantly increased percentage of infiltrators being detected by Gulf Coalition Forces and improved time to detect them, support the use of UAVs in detection missions. Computer experimentations and analyses reveal the most significant capabilities the UAV should have to achieve operational goals. These significant capabilities fall within the U.S. Department of Defense's Group 3 UAV classification. Therefore, the Gulf Coalition Forces should consider procuring UAVs in that category to enhance detection in the operational area."]},{"key":"dc:title","label":"Title","values":["A technology analysis to support acquisition of UAVs for Gulf Coalition Forces operations"]}]}],"canonical_facts":{"dc:contributor.advisor":["Hernandez, Alejandro S."],"dc:contributor.department":["Systems Engineering (SE)"],"dc:creator":["Alobaidli, Mohamed A."],"dc:date":["Jun-17"],"dc:date.accessioned":["2017-08-14T16:49:02Z"],"dc:date.available":["2017-08-14T16:49:02Z"],"dc:date.issued":["2017-06"],"dc:description":["Reissued 27 Sep 2018 to reflect correct spelling of “Yemeni” throughout."],"dc:description.abstract":["This thesis examines the potential effect of unmanned aerial vehicles in the Decisive Storm operations. This analysis of UAV technology will assist Gulf Coalition Forces decision makers in their selection of the most suitable and cost-effective unmanned aerial vehicles to support detection operations. This study uses Map Aware Non-Uniform Automata, an agent-based simulation software platform, for the computational experiments. It models the operational area, system entities for the Gulf Coalition Forces, and the Houthi militia's attempts to cross the Saudi-Yemini border. The software collects relevant data that can be translated into measures of mission effectiveness. Results from 10,400 simulation runs of Houthi efforts to infiltrate the operational area are analyzed using descriptive statistics, linear regression, and partition trees. These results, which include a significantly increased percentage of infiltrators being detected by Gulf Coalition Forces and improved time to detect them, support the use of UAVs in detection missions. Computer experimentations and analyses reveal the most significant capabilities the UAV should have to achieve operational goals. These significant capabilities fall within the U.S. Department of Defense's Group 3 UAV classification. Therefore, the Gulf Coalition Forces should consider procuring UAVs in that category to enhance detection in the operational area."],"dc:identifier.uri":["https://hdl.handle.net/10945/55638"],"dc:publisher":["Monterey, CA; Naval Postgraduate School"],"dc:rights":["Copyright is reserved by the copyright owner."],"dc:title":["A technology analysis to support acquisition of UAVs for Gulf Coalition Forces operations"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T20:26:05Z"}