TY - GEN
T1 - Simultaneous localization and mapping for satellite rendezvous and proximity operations using random finite sets
AU - Schlenker, Lauren
AU - Moretto, Mark
AU - Gaylor, David
AU - Linares, Richard
N1 - Funding Information:
The authors would like to acknowledge the NASA Goddard Space Flight Center Internal Research and Development (IRAD) program for funding this work. Additional thanks to Dr. Martin Adams and Felipe Inostroza at the Universidad de Chile for their advice and recommendations for this work. Thanks also to members of the Satellite Servicing Projects Division at NASA Goddard Spaceflight Center for valuable conversations and the opportunity to observe a real-life spacecraft RPO.
Publisher Copyright:
© 2019, Univelt Inc. All rights reserved.
PY - 2019
Y1 - 2019
N2 - Future space missions require that spacecraft have the capability to autonomously navigate non-cooperative environments for rendezvous and proximity operations (RPO). Current relative navigation filters can have difficulty in these situations, 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. The goal of this work is to demonstrate the feasibility of random finite set (RFS) filters for spacecraft relative navigation and pose estimation. The approach is to formulate satellite relative navigation and pose estimation 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. This work utilizes a filter developed using the framework of RFS which are well suited to multi-target SLAM operations, avoiding data association entirely. Relevant RPO scenarios with simulated flash LIDAR measurements are tested with a Probability Hypothesis Density (PHD) RFS filter embedded in a particle filter to obtain a feature map of a target and a relative pose estimate between the target and observer. Preliminary results show that an RFS-based filter can successfully perform SLAM in a spacecraft relative navigation scenario with no a priori map of the target. These results demonstrate the feasibility of RFS filtering for spacecraft relative navigation and motivate future studies which may expand to tracking space objects for space situational awareness, as well as relative navigation around small bodies.
AB - Future space missions require that spacecraft have the capability to autonomously navigate non-cooperative environments for rendezvous and proximity operations (RPO). Current relative navigation filters can have difficulty in these situations, 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. The goal of this work is to demonstrate the feasibility of random finite set (RFS) filters for spacecraft relative navigation and pose estimation. The approach is to formulate satellite relative navigation and pose estimation 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. This work utilizes a filter developed using the framework of RFS which are well suited to multi-target SLAM operations, avoiding data association entirely. Relevant RPO scenarios with simulated flash LIDAR measurements are tested with a Probability Hypothesis Density (PHD) RFS filter embedded in a particle filter to obtain a feature map of a target and a relative pose estimate between the target and observer. Preliminary results show that an RFS-based filter can successfully perform SLAM in a spacecraft relative navigation scenario with no a priori map of the target. These results demonstrate the feasibility of RFS filtering for spacecraft relative navigation and motivate future studies which may expand to tracking space objects for space situational awareness, as well as relative navigation around small bodies.
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M3 - Conference contribution
AN - SCOPUS:85072982517
SN - 9780877036593
T3 - Advances in the Astronautical Sciences
SP - 3401
EP - 3419
BT - Spaceflight Mechanics 2019
A2 - Topputo, Francesco
A2 - Sinclair, Andrew J.
A2 - Wilkins, Matthew P.
A2 - Zanetti, Renato
PB - Univelt Inc.
T2 - 29th AAS/AIAA Space Flight Mechanics Meeting, 2019
Y2 - 13 January 2019 through 17 January 2019
ER -