2026-09-19T05:26:36Zhttps://ecommons.cornell.edu/server/oai/requestoai:ecommons.cornell.edu:1813/171632026-05-14T13:50:43Zcom_1813_35col_1813_47
Mohiuddin, Shan
2010-08-05T16:22:12Z
2015-08-05T06:22:45Z
2010-08-05T16:22:12Z
https://hdl.handle.net/1813/17163
6980420
Three papers are presented that develop new estimation algorithms for the relative navigation of high-altitude spacecraft and for systems that have implicitly defined measurement times. The first two papers focus on the use of carrierphase differential GPS techniques with integer ambiguities to estimate the relative states of spacecraft formations operating at altitudes above the GPS constellation. Those papers' contributions include an optimally integrated integer ambiguity factorization method for a square-root information estimator, a robust cycle-slip detection and recovery algorithm, and an extended Kalman filter with an adaptive ionosphere model that allows to make multimodal use of dual-frequency GPS data. The third paper develops a new process noise model and extended Kalman filter that sensibly processes implicitly constrained radio navigation measurements. The filter's models combine dense output RungeKutta numerical integration with a piecewise polynomial approximation to continuous-time white process noise.
en_US
New Estimation Algorithms With Applications To Relative And Absolute Orbit Determination
dissertation or thesis
application/pdf
Publication
Cornell Theses and Dissertations
Mohiuddin, Shan
5893a6ea-7af3-41d7-abc6-04bcd26ab5df
open.access
open.access
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<Abstract>Three papers are presented that develop new estimation algorithms for the relative navigation of high-altitude spacecraft and for systems that have implicitly defined measurement times. The first two papers focus on the use of carrierphase differential GPS techniques with integer ambiguities to estimate the relative states of spacecraft formations operating at altitudes above the GPS constellation. Those papers' contributions include an optimally integrated integer ambiguity factorization method for a square-root information estimator, a robust cycle-slip detection and recovery algorithm, and an extended Kalman filter with an adaptive ionosphere model that allows to make multimodal use of dual-frequency GPS data. The third paper develops a new process noise model and extended Kalman filter that sensibly processes implicitly constrained radio navigation measurements. The filter's models combine dense output RungeKutta numerical integration with a piecewise polynomial approximation to continuous-time white process noise.</Abstract>
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