Multi-Sensor Fusion and Resilient PVT Techniques for Safe Lunar Landing Missions

In the recent years, many public and private entities have shown growing interest and investment in lunar missions. This increase in lunar and cis-lunar activities has prompted outstanding initiatives promoted by National Aeronautics and Space Administration (NASA) and European Space Agency (ESA). Lunar missions have historically relied upon deep-space Earth ground-segment infrastructures to obtain accurate knowledge of the spacecraft trajectory, but nowadays many studies have been conducted to demonstrate the improvements in terms of user Position, Velocity and Timing (PVT) estimation enabled by a Navigation Constellation around the Moon. The objective of this study is to describe an approach that utilizes sensor-fusion techniques based on a tightly-coupled Extended Kalman Filter (EKF) to integrate lunar GNSS-like One-Way Ranging (OWR) signals with a wide range of on-board observables, such as Inertial Measurement Units (IMU), altimeters, Two-Way Ranging (TWR) with an orbiter in Elliptical Lunar Frozen Orbit (ELFO) and Visual-Based Navigation (VBN) techniques for the estimation of both the spacecraft state and the receiver clock bias and drift, in different phases of a lunar landing at the Shackleton Rim. The VBN algorithms applied for this study are based on seleno-referenced, high-fidelity lunar images (from 30m/px to 5m/px) generated through the Visual Scenario Generator (VSG) module integrated in an innovative tool, developed in the Telespazio Concurrent and Collaborative Design Facility (C2DF), namely Interactive Mission Modeling, Visualization/Validation (IMMV2 ), implementing all the abovementioned functionality in a Digital Twin for Mission digitalization (MDT), End-to-End Testing and Validation. Furthermore, preliminary results in a Hazard Detection (HD) algorithm, that typically works between 2500 and 1500 m of altitude, will be outlined. Finally, a preliminary measurement outlier rejection strategy has been implemented in the loop, as the recent lunar lander missions have demonstrated the importance to identify and reject incorrect measurements that could potentially cause a mission failure.

Authors

Publication Details

Journal
Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM)
Published
2024-10-09
DOI
https://doi.org/10.33012/2024.19849
Citations
3
Primary Topic
Planetary Science and Exploration
Type
article
Field-Weighted Citation Impact
0.99
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article

Multi-Sensor Fusion and Resilient PVT Techniques for Safe Lunar Landing Missions

Michèle Lavagna, Simone Giannattasio, Stefano Silvestrini, Michele Ceresoli et al.
3 citations
Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM)
Planetary Science and Exploration
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article

Multi-Sensor Fusion and Resilient PVT Techniques for Safe Lunar Landing Missions

Michèle Lavagna, Simone Giannattasio, Stefano Silvestrini, Michele Ceresoli, Marco Brancati, Michele Grassi, Alfredo Renga, Roberto Del Prete, Giuseppe Tomasicchio, Luca Andolfi, Arsenio Maria Di Donna, Luca Ostrogovich
article en
3 citations

Abstract

In the recent years, many public and private entities have shown growing interest and investment in lunar missions. This increase in lunar and cis-lunar activities has prompted outstanding initiatives promoted by National Aeronautics and Space Administration (NASA) and European Space Agency (ESA). Lunar missions have historically relied upon deep-space Earth ground-segment infrastructures to obtain accurate knowledge of the spacecraft trajectory, but nowadays many studies have been conducted to demonstrate the improvements in terms of user Position, Velocity and Timing (PVT) estimation enabled by a Navigation Constellation around the Moon. The objective of this study is to describe an approach that utilizes sensor-fusion techniques based on a tightly-coupled Extended Kalman Filter (EKF) to integrate lunar GNSS-like One-Way Ranging (OWR) signals with a wide range of on-board observables, such as Inertial Measurement Units (IMU), altimeters, Two-Way Ranging (TWR) with an orbiter in Elliptical Lunar Frozen Orbit (ELFO) and Visual-Based Navigation (VBN) techniques for the estimation of both the spacecraft state and the receiver clock bias and drift, in different phases of a lunar landing at the Shackleton Rim. The VBN algorithms applied for this study are based on seleno-referenced, high-fidelity lunar images (from 30m/px to 5m/px) generated through the Visual Scenario Generator (VSG) module integrated in an innovative tool, developed in the Telespazio Concurrent and Collaborative Design Facility (C2DF), namely Interactive Mission Modeling, Visualization/Validation (IMMV2 ), implementing all the abovementioned functionality in a Digital Twin for Mission digitalization (MDT), End-to-End Testing and Validation. Furthermore, preliminary results in a Hazard Detection (HD) algorithm, that typically works between 2500 and 1500 m of altitude, will be outlined. Finally, a preliminary measurement outlier rejection strategy has been implemented in the loop, as the recent lunar lander missions have demonstrated the importance to identify and reject incorrect measurements that could potentially cause a mission failure.

Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM)
Openalex Percentile: Top 23%
Planetary Science and Exploration
0.99
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