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Lunar Navigation Performance Using the Deep Space Network and Alternate Solutions to Support Precision LandingAs human exploration once again targets the surface of the Moon, questions continue to emerge regarding the necessity of Earth-based tracking systems, such as the Deep Space Network, for spacecraft navigation in support of lunar descent and landing. This paper will derive an extensive Deep Space Network sensor model for use in linear covariance analysis and demonstrate the resulting trajectory dispersions and navigation performance in comparison with alternate solutions, such as terrain relative navigation. An in-depth trade study with considerations for various trajectory profiles, time allocated to ground tracking, number of active ground stations, and interaction with other sensors will be conducted to shed significant insight into sensor suite requirements to ensure safe and precise landing on the Moon.
Document ID
20205010306
Acquisition Source
Johnson Space Center
Document Type
Conference Paper
Authors
Bradley C. Collicott
(Universities Space Research Association Columbia, Maryland, United States)
David C. Woffinden
(Johnson Space Center Houston, Texas, United States)
Date Acquired
November 17, 2020
Subject Category
Spacecraft Design, Testing And Performance
Meeting Information
Meeting: AIAA SciTech Forum
Location: Virtual
Country: US
Start Date: January 11, 2021
End Date: January 21, 2021
Sponsors: American Institute of Aeronautics and Astronautics
Funding Number(s)
PROJECT: 335803.04.25.72
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Keywords
Navigation
LInear Covariance Analysis
Deep Space Network
Descent and Landing
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