Between Dec 19, 2024 and Jan 2, 2025, datasets can be submitted to DRUM but will not be processed until after the break. Staff will not be available to answer email during this period, and will not be able to provide DOIs until after Jan 2. If you are in need of a DOI during this period, consider Dryad or OpenICPSR. Submission responses to the UDC may also be delayed during this time.
 

Spacecraft Relative Navigation Using Random Finite Sets

Loading...
Thumbnail Image

Persistent link to this item

Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

Spacecraft Relative Navigation Using Random Finite Sets

Published Date

2019-05

Publisher

Type

Thesis or Dissertation

Abstract

Future space missions require that spacecraft have onboard capability to autonomously navigate non-cooperative environments for rendezvous and proximity operations (RPO). Current relative navigation filters can have difficulty in these situations when optical sensors are used, diverging due to complications with data association, high measurement uncertainty, and clutter, particularly when detailed a priori maps of the target object or spacecraft do not exist. This thesis demonstrates the feasibility of random finite set (RFS) filters for spacecraft relative navigation and pose estimation. A generalized RPO scenario is formulated as a simultaneous localization and mapping (SLAM) problem, in which an observer spacecraft seeks to simultaneously estimate the location of features on a target object or spacecraft as well as its relative position, velocity and attitude. An RFS-based filter called the Gaussian Mixture Probability Hypothesis Density (GMPHD) is used. Simulated flash LIDAR measurements are tested, using a GMPHD filter embedded in a particle filter to obtain a feature map of a target and a relative pose estimate between the target and observer over time. Results show that an RFS-based filter such as the one used can successfully perform SLAM in a spacecraft relative navigation scenario with no a priori map of the target, and that the formulation behind RFS-based filtering is potentially well suited to spacecraft relative navigation.

Description

University of Minnesota M.S. thesis. May 2019. Major: Aerospace Engineering and Mechanics. Advisor: Richard Linares. 1 computer file (PDF); xviii, 69 pages.

Related to

Replaces

License

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Other identifiers

Suggested citation

Schlenker, Lauren. (2019). Spacecraft Relative Navigation Using Random Finite Sets. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/206138.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.