Adaptive Extended Kalman Filtering Strategies for Autonomous Relative Navigation of Formation Flying Spacecraft

To enhance the capabilities of onboard autonomous guidance, navigation and control systems, this thesis presents the development of two adaptive extended Kalman filter navigation algorithms for spacecraft formation flying. The proposed adaptive filters are capable of updating the internal noise characteristics of the Kalman filter in real time, and are viable in all orbit scenarios, including highly elliptical orbits in the presence of perturbations. The first Kalman filter approach uses maximum likelihood estimation techniques to derive analytical adaptations laws for the filter, and the second approach uses an embedded fuzzy logic system based on a covariance-matching analysis of the filter residuals. Numerical simulations of three spacecraft formations are used to demonstrate that the proposed adaptive navigation algorithms are appreciably more robust to filter initialization errors, dynamics modelling deficiencies, and measurement noise than the standard extended Kalman filter.

Name thesis:degree_name

Master of Applied Science (M.App.Sc.)

Level thesis:degree_level

Master's

Discipline thesis:degree_discipline

Engineering, Aerospace

Grantor dc:publisher

Carleton University

Year dc:date.issued

2019

Author dc:creator

• Fraser, Cory Tyler

Statement dc:rights

• Copyright © 2019 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.

Language dc:language.iso

en

DOI

10.22215/etd/2018-13421

OAI identifier oai:identifier

oai:carleton.scholaris.ca:20.500.14718/39552