{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/44936"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/44936","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Orbit determination using modern filters/smoothers and continuous thrust modeling","abstract":"The development of electric propulsion technology for spacecraft has led to reduced costs and longer lifespans for certain types of satellites. Because these satellites frequently undergo continuous thrust, predicting their motion and performing orbit determination on them has introduced complications for space surveillance networks. One way to improve orbit determination for these satellites is to make use of new estimation techniques. This has been accomplished by applying the Backward Smoothing Extended Kalman Filter (BSEKF) to the problem of orbit determination. The BSEKF outperforms other nonlinear filters because it treats nonlinearities in both the measurement and dynamic functions. The performance of this filter is evaluated in comparison to an existing Extended Semianalytic Kalman Filter (ESKF). The BSEKF was implemented in the R&D Goddard Trajectory Determination System (GTDS) for this thesis while the ESKF was implemented in 1981 and has been tested extensively since then. Radar and optical satellite tracking observations were simulated using an initial truth orbit and were processed by the ESKF and BSEKF to estimate satellite trajectories. The trajectory estimates from each filter were compared with the initial truth orbit and were evaluated for accuracy and convergence speed. The BSEKF provided substantial improvements in accuracy and convergence over the ESKF for the simulated test cases. Additionally, this study used the solutions offered by optimal thrust trajectory analysis to model the perturbations caused by continuous thrust. Optimal thrust trajectory analysis makes use of Optimal Control Theory and numerical optimization techniques to calculate minimum time and minimum fuel trajectories from one orbit to another.","abstract_html":"The development of electric propulsion technology for spacecraft has led to reduced costs and longer lifespans for certain types of satellites. Because these satellites frequently undergo continuous thrust, predicting their motion and performing orbit determination on them has introduced complications for space surveillance networks. One way to improve orbit determination for these satellites is to make use of new estimation techniques. This has been accomplished by applying the Backward Smoothing Extended Kalman Filter (BSEKF) to the problem of orbit determination. The BSEKF outperforms other nonlinear filters because it treats nonlinearities in both the measurement and dynamic functions. The performance of this filter is evaluated in comparison to an existing Extended Semianalytic Kalman Filter (ESKF). The BSEKF was implemented in the R&D Goddard Trajectory Determination System (GTDS) for this thesis while the ESKF was implemented in 1981 and has been tested extensively since then. Radar and optical satellite tracking observations were simulated using an initial truth orbit and were processed by the ESKF and BSEKF to estimate satellite trajectories. The trajectory estimates from each filter were compared with the initial truth orbit and were evaluated for accuracy and convergence speed. The BSEKF provided substantial improvements in accuracy and convergence over the ESKF for the simulated test cases. Additionally, this study used the solutions offered by optimal thrust trajectory analysis to model the perturbations caused by continuous thrust. Optimal thrust trajectory analysis makes use of Optimal Control Theory and numerical optimization techniques to calculate minimum time and minimum fuel trajectories from one orbit to another.","abstract_has_math":false,"creators":["Folcik, Zachary James"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics.","school":null,"contributors":[],"advisors":["Paul J. Cefola and Jonathan P. How."],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008","date_published":"2008","updated_at":"2026-07-22T22:21:42Z","subjects":["Aeronautics and Astronautics."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/44936","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Paul J. Cefola and Jonathan P. How."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics."]},{"key":"dc:creator","label":"Author","values":["Folcik, Zachary James"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2009-03-20T19:33:31Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2009-03-20T19:33:31Z"]},{"key":"dc:date.issued","label":"Date","values":["2008"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Aeronautics and Astronautics."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/44936"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2008.","This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.","Includes bibliographical references (p. 389-394)."]},{"key":"dc:description.abstract","label":"Abstract","values":["The development of electric propulsion technology for spacecraft has led to reduced costs and longer lifespans for certain types of satellites. Because these satellites frequently undergo continuous thrust, predicting their motion and performing orbit determination on them has introduced complications for space surveillance networks. One way to improve orbit determination for these satellites is to make use of new estimation techniques. This has been accomplished by applying the Backward Smoothing Extended Kalman Filter (BSEKF) to the problem of orbit determination. The BSEKF outperforms other nonlinear filters because it treats nonlinearities in both the measurement and dynamic functions. The performance of this filter is evaluated in comparison to an existing Extended Semianalytic Kalman Filter (ESKF). The BSEKF was implemented in the R&D Goddard Trajectory Determination System (GTDS) for this thesis while the ESKF was implemented in 1981 and has been tested extensively since then. Radar and optical satellite tracking observations were simulated using an initial truth orbit and were processed by the ESKF and BSEKF to estimate satellite trajectories. The trajectory estimates from each filter were compared with the initial truth orbit and were evaluated for accuracy and convergence speed. The BSEKF provided substantial improvements in accuracy and convergence over the ESKF for the simulated test cases. Additionally, this study used the solutions offered by optimal thrust trajectory analysis to model the perturbations caused by continuous thrust. Optimal thrust trajectory analysis makes use of Optimal Control Theory and numerical optimization techniques to calculate minimum time and minimum fuel trajectories from one orbit to another.","(cont.) Because satellite operators are motivated to save fuel, it was assumed that optimal thrust trajectories would be useful to predict thrust perturbed satellite motion. Software was developed to calculate the optimal trajectories and associated thrust plans. A new force model was implemented in GTDS to accept externally generated thrust plans and apply them to a given satellite trajectory. Test cases are presented to verify the correctness of the mathematics and software. Also, test cases involving a real satellite using electric propulsion were executed. These tests demonstrated that optimal thrust modeling could provide order of magnitude reductions in orbit determination errors for a satellite with low-thrust electric propulsion."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Orbit determination using modern filters/smoothers and continuous thrust modeling"]}]}],"canonical_facts":{"dc:contributor.advisor":["Paul J. Cefola and Jonathan P. How."],"dc:contributor.department":["Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics."],"dc:contributor.other":["Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics."],"dc:creator":["Folcik, Zachary James"],"dc:date.accessioned":["2009-03-20T19:33:31Z"],"dc:date.available":["2009-03-20T19:33:31Z"],"dc:date.issued":["2008"],"dc:description":["Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2008.","This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.","Includes bibliographical references (p. 389-394)."],"dc:description.abstract":["The development of electric propulsion technology for spacecraft has led to reduced costs and longer lifespans for certain types of satellites. Because these satellites frequently undergo continuous thrust, predicting their motion and performing orbit determination on them has introduced complications for space surveillance networks. One way to improve orbit determination for these satellites is to make use of new estimation techniques. This has been accomplished by applying the Backward Smoothing Extended Kalman Filter (BSEKF) to the problem of orbit determination. The BSEKF outperforms other nonlinear filters because it treats nonlinearities in both the measurement and dynamic functions. The performance of this filter is evaluated in comparison to an existing Extended Semianalytic Kalman Filter (ESKF). The BSEKF was implemented in the R&D Goddard Trajectory Determination System (GTDS) for this thesis while the ESKF was implemented in 1981 and has been tested extensively since then. Radar and optical satellite tracking observations were simulated using an initial truth orbit and were processed by the ESKF and BSEKF to estimate satellite trajectories. The trajectory estimates from each filter were compared with the initial truth orbit and were evaluated for accuracy and convergence speed. The BSEKF provided substantial improvements in accuracy and convergence over the ESKF for the simulated test cases. Additionally, this study used the solutions offered by optimal thrust trajectory analysis to model the perturbations caused by continuous thrust. Optimal thrust trajectory analysis makes use of Optimal Control Theory and numerical optimization techniques to calculate minimum time and minimum fuel trajectories from one orbit to another.","(cont.) Because satellite operators are motivated to save fuel, it was assumed that optimal thrust trajectories would be useful to predict thrust perturbed satellite motion. Software was developed to calculate the optimal trajectories and associated thrust plans. A new force model was implemented in GTDS to accept externally generated thrust plans and apply them to a given satellite trajectory. Test cases are presented to verify the correctness of the mathematics and software. Also, test cases involving a real satellite using electric propulsion were executed. These tests demonstrated that optimal thrust modeling could provide order of magnitude reductions in orbit determination errors for a satellite with low-thrust electric propulsion."],"dc:description.degree":["S.M."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/44936"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Aeronautics and Astronautics."],"dc:title":["Orbit determination using modern filters/smoothers and continuous thrust modeling"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:21:42Z"}