{"id":{"repo_id":"maryland","oai_identifier":"oai:drum.lib.umd.edu:1903/19557"},"canonical_url":"https://search.dev.ndltd.org/etd/maryland/oai:drum.lib.umd.edu:1903/19557","repository":{"repo_id":"maryland","name":"University of Maryland","base_url":"https://api.drum.lib.umd.edu/server/oai/request"},"display":{"title":"RESILIENT STATE ESTIMATION FOR MICRO AIR VEHICLES UNDER SENSOR ATTACKS","abstract":"This thesis proposes a solution to the problem of resilient state estimation and sensor fusion in an autonomous micro air vehicle. The setup comprises of redundant sensors that measure the same physical signal. An adversary may spoof a subset of these sensors and send falsified readings to the controller, potentially compromising performance and safety of the system. This work integrates Brooks-Iyengar Sensor fusion algorithm with a generic state estimator as a method to thwart sensor attacks. The algorithm outputs a point estimate and a fusion interval based on an assumed set of faulty sensors. Finally, the thesis illustrates the usefulness of the resilient state estimator with a case study on a MAV flight dataset.","abstract_html":"This thesis proposes a solution to the problem of resilient state estimation and sensor fusion in an autonomous micro air vehicle. The setup comprises of redundant sensors that measure the same physical signal. An adversary may spoof a subset of these sensors and send falsified readings to the controller, potentially compromising performance and safety of the system. This work integrates Brooks-Iyengar Sensor fusion algorithm with a generic state estimator as a method to thwart sensor attacks. The algorithm outputs a point estimate and a fusion interval based on an assumed set of faulty sensors. Finally, the thesis illustrates the usefulness of the resilient state estimator with a case study on a MAV flight dataset.","abstract_has_math":false,"creators":["Prasad, Akshay"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Systems Engineering","school":null,"contributors":[],"advisors":["Chopra, Nikhil"],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017","date_published":"2017","updated_at":"2026-07-24T03:02:31Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://doi.org/10.13016/M2KG48"],"render_values":[{"text":"https://doi.org/10.13016/M2KG48","href":"https://doi.org/10.13016/M2KG48","code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/1903/19557","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Chopra, Nikhil"]},{"key":"dc:contributor.department","label":"Department","values":["Systems Engineering"]},{"key":"dc:creator","label":"Author","values":["Prasad, Akshay"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2017-06-22T06:42:00Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2017-06-22T06:42:00Z"]},{"key":"dc:date.issued","label":"Date","values":["2017"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"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","label":"Identifier","values":["https://doi.org/10.13016/M2KG48"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1903/19557"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis proposes a solution to the problem of resilient state estimation and sensor fusion in an autonomous micro air vehicle. The setup comprises of redundant sensors that measure the same physical signal. An adversary may spoof a subset of these sensors and send falsified readings to the controller, potentially compromising performance and safety of the system. This work integrates Brooks-Iyengar Sensor fusion algorithm with a generic state estimator as a method to thwart sensor attacks. The algorithm outputs a point estimate and a fusion interval based on an assumed set of faulty sensors. Finally, the thesis illustrates the usefulness of the resilient state estimator with a case study on a MAV flight dataset."]},{"key":"dc:title","label":"Title","values":["RESILIENT STATE ESTIMATION FOR MICRO AIR VEHICLES UNDER SENSOR ATTACKS"]}]}],"canonical_facts":{"dc:contributor.advisor":["Chopra, Nikhil"],"dc:contributor.department":["Systems Engineering"],"dc:creator":["Prasad, Akshay"],"dc:date.accessioned":["2017-06-22T06:42:00Z"],"dc:date.available":["2017-06-22T06:42:00Z"],"dc:date.issued":["2017"],"dc:description.abstract":["This thesis proposes a solution to the problem of resilient state estimation and sensor fusion in an autonomous micro air vehicle. The setup comprises of redundant sensors that measure the same physical signal. An adversary may spoof a subset of these sensors and send falsified readings to the controller, potentially compromising performance and safety of the system. This work integrates Brooks-Iyengar Sensor fusion algorithm with a generic state estimator as a method to thwart sensor attacks. The algorithm outputs a point estimate and a fusion interval based on an assumed set of faulty sensors. Finally, the thesis illustrates the usefulness of the resilient state estimator with a case study on a MAV flight dataset."],"dc:identifier":["https://doi.org/10.13016/M2KG48"],"dc:identifier.uri":["http://hdl.handle.net/1903/19557"],"dc:language.iso":["en"],"dc:title":["RESILIENT STATE ESTIMATION FOR MICRO AIR VEHICLES UNDER SENSOR ATTACKS"],"dc:type":["Thesis"]},"updated_at":"2026-07-24T03:02:31Z"}