{"id":{"repo_id":"nps","oai_identifier":"oai:calhoun.nps.edu:10945/34944"},"canonical_url":"https://search.dev.ndltd.org/etd/nps/oai:calhoun.nps.edu:10945/34944","repository":{"repo_id":"nps","name":"Naval Postgraduate School","base_url":"https://calhoun.nps.edu/server/oai/request"},"display":{"title":"The path prediction of cyclones with Kalman filters","abstract":"The Kalman filter is used to provide estimates of the position and velocity of a storm based upon observation of the storm's longitude and latitude. Nonstationary noise is shown to degrade the performance of the filter and cause tracking divergence. Time varying values for the noise covariance matricies R and Q, and the addition of an external forcing function to the filter, effectively compensated for this tracking error. Results for the simulations show significant performance advantages of using an external forcing function in the system.","abstract_html":"The Kalman filter is used to provide estimates of the position and velocity of a storm based upon observation of the storm's longitude and latitude. Nonstationary noise is shown to degrade the performance of the filter and cause tracking divergence. Time varying values for the noise covariance matricies R and Q, and the addition of an external forcing function to the filter, effectively compensated for this tracking error. Results for the simulations show significant performance advantages of using an external forcing function in the system.","abstract_has_math":false,"creators":["Taskin, Dogan"],"institution":"Monterey, CA; Naval Postgraduate School","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Electrical and Computer Engineering","school":null,"contributors":[],"advisors":["Titus, Harold A."],"committee_chairs":[],"committee_members":[],"year":1990,"date_issued":"1990-09","date_published":"1990-09","updated_at":"2026-07-27T20:25:53Z","subjects":[],"languages":[],"rights":["Copyright is reserved by the copryright owner."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10945/34944","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Titus, Harold A."]},{"key":"dc:contributor.department","label":"Department","values":["Electrical and Computer Engineering"]},{"key":"dc:creator","label":"Author","values":["Taskin, Dogan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["1990-09"]},{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2013-08-01T21:15:55Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2013-08-01T21:15:55Z"]},{"key":"dc:date.issued","label":"Date","values":["1990-09"]},{"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 copryright owner."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10945/34944"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The Kalman filter is used to provide estimates of the position and velocity of a storm based upon observation of the storm's longitude and latitude. Nonstationary noise is shown to degrade the performance of the filter and cause tracking divergence. Time varying values for the noise covariance matricies R and Q, and the addition of an external forcing function to the filter, effectively compensated for this tracking error. Results for the simulations show significant performance advantages of using an external forcing function in the system."]},{"key":"dc:title","label":"Title","values":["The path prediction of cyclones with Kalman filters"]}]}],"canonical_facts":{"dc:contributor.advisor":["Titus, Harold A."],"dc:contributor.department":["Electrical and Computer Engineering"],"dc:creator":["Taskin, Dogan"],"dc:date":["1990-09"],"dc:date.accessioned":["2013-08-01T21:15:55Z"],"dc:date.available":["2013-08-01T21:15:55Z"],"dc:date.issued":["1990-09"],"dc:description.abstract":["The Kalman filter is used to provide estimates of the position and velocity of a storm based upon observation of the storm's longitude and latitude. Nonstationary noise is shown to degrade the performance of the filter and cause tracking divergence. Time varying values for the noise covariance matricies R and Q, and the addition of an external forcing function to the filter, effectively compensated for this tracking error. Results for the simulations show significant performance advantages of using an external forcing function in the system."],"dc:identifier.uri":["https://hdl.handle.net/10945/34944"],"dc:publisher":["Monterey, CA; Naval Postgraduate School"],"dc:rights":["Copyright is reserved by the copryright owner."],"dc:title":["The path prediction of cyclones with Kalman filters"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T20:25:53Z"}