The objective of this thesis is to design numerical algorithms for estimation of linear discrete-time dynamic system models, which can be written in the block-angular form. These models arise in some applications, such as navigation or communication. The estimation problem for the standard linear discrete-time dynamic systems usually can be solved by using the Kalman filter. However, we realize that for our specific models applying the conventional Kalman filter algorithms is not efficient or may cause numerical instability. In this thesis, we present an approach of using the recursive least squares technique to compute the estimates of the system states. Our approach is computationally efficient because we take full account of the structures of the models and is numerically reliable because we use orthogonal transformations in the computation. / The general approach is then extended to positioning problem. We mainly consider the short-baseline relative positioning with combined code and carrier-phase measurements in global positioning system. Because of much more special structures existing in the mathematical models for positioning; we modify the general approach to further utilize these structures for efficiency. Fixing the integer ambiguity vector and handling its dimension change are also discussed. Finally, the real data tests are given to demonstrate the effectiveness of our algorithm.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.82254 |
| Date | January 2005 |
| Creators | Huang, Mengjun, 1977- |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Master of Science (School of Computer Science.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 002227274, proquestno: AAIMR12465, Theses scanned by UMI/ProQuest. |
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