A General Approach to Terrain Relative Navigation for Planetary Landing
Abstract
We describe an algorithm for navigation state estimation during planetary descent to enable precision landing. The algorithm automatically produces 2D-to-3D correspondences between descent images and a surface map and 2D-to-2D correspondences through a sequence of descent images. These correspondences are combined with inertial measurements in an extended Kalman filter that estimates lander position, velocity and attitude as well as the time varying biases of the inertial measurements. The filter tightly couples inertial and camera measurements in a resource-adaptive and hence real-time capable fashion. Results from a sounding rocket test, covering the dynamic profile of typical planetary landing scenarios, show estimation errors of magnitude 0.16 m/s in velocity and 6.4 m in position at touchdown. These results vastly improve current state of the art and meet the requirements of future planetary exploration missions. N I.
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More persistent feature tracking, in which a feature is initially detected and is then repeatedly detected in future frames, improves accuracy of the state estimate in TRN since longer tracks correspond to higher signal to noise ratios.
“More persistent feature tracking, in which a feature is initially detected and is then repeatedly detected in future frames, improves accuracy of the state estimate in TRN since longer tracks correspond to higher signal to noise ratios [20].”
From Lunar Terrain Relative Navigation Using a Convolutional Neural Network for Visual Crater Detection (2020) · cites this paper as [20]
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Vision-Aided Inertial Navigation for Spacecraft Entry, Descent, and Landing
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Self-citationLunar Terrain Relative Navigation Using a Convolutional Neural Network for Visual Crater Detection
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- Authors
- Johnson, A., Ansar, A., Matthies, L., Trawny, N., Mourikis, A., & Roumeliotis, S.
- Affiliations
- Jet Propulsion Laboratory (US)
- University of Minnesota (US)
- Venue
- AIAA Infotech@Aerospace 2007 Conference and Exhibit
- Published
- 2007-05-07
- OpenAlex
- W2055415212
- Cited by
- 55
- References
- 17
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 1 · 2023: 3 · 2022: 4 · 2021: 8 · 2020: 1 · 2019: 2 · 2018: 5 · 2017: 4 · 2015: 6 · 2014: 1 · 2013: 3 · 2012: 2
- FWCI
- 4.00
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- AIAA Infotech@Aerospace 2007 Conference and Exhibit (publishedVersion)
- Funders
- National Aeronautics and Space Administration
- Jet Propulsion Laboratory
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
- Physical Sciences › Engineering › Aerospace Engineering › Spacecraft Dynamics and Control
- Keywords
- terrain relative navigation, planetary landing, precision landing, extended Kalman filter
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