Lunar Navigation Performance Using the Deep Space Network and Alternate Solutions to Support Precision Landing
As 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 exte
Selection note: Curated because “Lunar Navigation Performance Using the Deep Space Network and Alternate Solutions to Support Precision Landing” covers Navigation, LInear Covariance Analysis, Deep Space Network, Descent and Landing; it materially informs GShips work on autonomous deep space navigation.
Evidence boundary: NTRS provides open full text, but this conference paper was screened for curation rather than independently or domain reviewed; inclusion is contextual, not automatic claim evidence.
Stable record
ntrs-20205010306
Topic
communications-navigation
Type
Conference Paper
Publisher
Johnson Space Center
Authors
Bradley C. Collicott; David C. Woffinden
Year
2021
Editorial state
metadata curated editorial draft
Reviewer
GShips Project editorial synthesis
Official link checked
2026-07-25
Source-supplied abstract
As 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.
Abstract text has not been adopted as a GShips conclusion.
What would change this record?
A newer or corrected version, a retraction, a verified duplicate, a material topic mismatch, a changed access state, or claim-level review would trigger a dated editorial update.
NTRS provides open full text, but this conference paper was screened for curation rather than independently or domain reviewed; inclusion is contextual, not automatic claim evidence.
Source-supplied titles, abstracts, authors, and dates may require correction against the canonical full text.
What would change this page?
A newer or corrected version, retraction, verified duplicate, material topic mismatch, changed access state, or claim-level assessment would change this record.
People, review, and conflicts
Prepared by
GShips Project
Editorial status
metadata-curated-editorial-draft
Editorial reviewer
GShips Project editorial synthesis
Last editorial review
No editorial-review date recorded
Independent review
pending
Independent reviewer
No independent reviewer assigned
Last independent review
No independent-review date exists
Last content edit
Not recorded separately
Official source or link verified
2026-07-25
Declared conflicts
The maintainer intends to explore a commercial venture based on some GShips work. No entity, outside funding, customer, sponsor, or indexed-organization relationship currently exists.