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Main Authors: de Badyn, Mathias Hudoba, Binz, Jonas, Iannelli, Andrea, Smith, Roy S.
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2411.19033
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author de Badyn, Mathias Hudoba
Binz, Jonas
Iannelli, Andrea
Smith, Roy S.
author_facet de Badyn, Mathias Hudoba
Binz, Jonas
Iannelli, Andrea
Smith, Roy S.
contents In this paper, a distributed dual-quaternion multiplicative extended Kalman filter for the estimation of poses and velocities of individual satellites in a fleet of spacecraft is analyzed. The proposed algorithm uses both absolute and relative pose measurements between neighbouring satellites in a network, allowing each individual satellite to estimate its own pose and that of its neighbours. By utilizing the distributed Kalman consensus filter, a novel sensor and state-estimate fusion procedure is proposed that allows each satellite to improve its own state estimate by sharing data with its neighbours over a communication link. A leader-follower approach, whereby only a subset of the satellites have access to an absolute pose measurement is also examined. In this case, followers rely solely on the information provided by their neighbours, as well as relative pose measurements to those neighbours. The algorithm is tested extensively via numerical simulations, and it is shown that the approach provides a substantial improvement in performance over the scenario in which the satellites do not cooperate. A case study of satellites swarming an asteroid is presented, and the performance in the leader-follower scenario is also analyzed.
format Preprint
id arxiv_https___arxiv_org_abs_2411_19033
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Distributed Dual Quaternion Extended Kalman Filtering for Spacecraft Pose Estimation
de Badyn, Mathias Hudoba
Binz, Jonas
Iannelli, Andrea
Smith, Roy S.
Optimization and Control
In this paper, a distributed dual-quaternion multiplicative extended Kalman filter for the estimation of poses and velocities of individual satellites in a fleet of spacecraft is analyzed. The proposed algorithm uses both absolute and relative pose measurements between neighbouring satellites in a network, allowing each individual satellite to estimate its own pose and that of its neighbours. By utilizing the distributed Kalman consensus filter, a novel sensor and state-estimate fusion procedure is proposed that allows each satellite to improve its own state estimate by sharing data with its neighbours over a communication link. A leader-follower approach, whereby only a subset of the satellites have access to an absolute pose measurement is also examined. In this case, followers rely solely on the information provided by their neighbours, as well as relative pose measurements to those neighbours. The algorithm is tested extensively via numerical simulations, and it is shown that the approach provides a substantial improvement in performance over the scenario in which the satellites do not cooperate. A case study of satellites swarming an asteroid is presented, and the performance in the leader-follower scenario is also analyzed.
title Distributed Dual Quaternion Extended Kalman Filtering for Spacecraft Pose Estimation
topic Optimization and Control
url https://arxiv.org/abs/2411.19033