Cargando…
GMM-Based Adaptive Extended Kalman Filter Design for Satellite Attitude Estimation under Thruster-Induced Disturbances
Star images from star trackers are usually defocused to capture stars over an exposure time for better centroid measurements. While a satellite is maneuvering, the star point on the screen of the camera is affected by the satellite, which results in the degradation of centroid measurement accuracy....
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10180902/ https://www.ncbi.nlm.nih.gov/pubmed/37177418 http://dx.doi.org/10.3390/s23094212 |
_version_ | 1785041445714919424 |
---|---|
author | Kim, Taeho Zewge, Natnael S. Bang, Hyochoong Yoon, Hyosang |
author_facet | Kim, Taeho Zewge, Natnael S. Bang, Hyochoong Yoon, Hyosang |
author_sort | Kim, Taeho |
collection | PubMed |
description | Star images from star trackers are usually defocused to capture stars over an exposure time for better centroid measurements. While a satellite is maneuvering, the star point on the screen of the camera is affected by the satellite, which results in the degradation of centroid measurement accuracy. Additionally, this could result in a worse star vector outcome. For geostationary satellites, onboard thrusters are used to maintain or change orbit parameters under orbit disturbances. Since there is misalignment in the thruster and torque is generated by an impulsive shape signal from the torque command, it is difficult to generate target torque; in addition, it also impacts the star image because the impulsive torque creates a sudden change in the angular velocity in the satellite dynamics. This makes the noise of the star image non-Gaussian, which may require introducing a method for dealing with non-Gaussian measurement noise. To meet this goal, in this study, an adaptive extended Kalman filter is implemented to predict measurement vectors with predicted states. The GMM (Gaussian mixture model) is connected in this sequence, giving weighting parameters to each Gaussian density and resulting in the better prediction of measurement vectors. Simulation results show that the GMM-EKF exhibits a better performance than the EKF for attitude estimation, with 30% improvement in performance. Therefore, the GMM-EKF could be a more attractive approach for use with geostationary satellites during station-keeping maneuvers. |
format | Online Article Text |
id | pubmed-10180902 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101809022023-05-13 GMM-Based Adaptive Extended Kalman Filter Design for Satellite Attitude Estimation under Thruster-Induced Disturbances Kim, Taeho Zewge, Natnael S. Bang, Hyochoong Yoon, Hyosang Sensors (Basel) Article Star images from star trackers are usually defocused to capture stars over an exposure time for better centroid measurements. While a satellite is maneuvering, the star point on the screen of the camera is affected by the satellite, which results in the degradation of centroid measurement accuracy. Additionally, this could result in a worse star vector outcome. For geostationary satellites, onboard thrusters are used to maintain or change orbit parameters under orbit disturbances. Since there is misalignment in the thruster and torque is generated by an impulsive shape signal from the torque command, it is difficult to generate target torque; in addition, it also impacts the star image because the impulsive torque creates a sudden change in the angular velocity in the satellite dynamics. This makes the noise of the star image non-Gaussian, which may require introducing a method for dealing with non-Gaussian measurement noise. To meet this goal, in this study, an adaptive extended Kalman filter is implemented to predict measurement vectors with predicted states. The GMM (Gaussian mixture model) is connected in this sequence, giving weighting parameters to each Gaussian density and resulting in the better prediction of measurement vectors. Simulation results show that the GMM-EKF exhibits a better performance than the EKF for attitude estimation, with 30% improvement in performance. Therefore, the GMM-EKF could be a more attractive approach for use with geostationary satellites during station-keeping maneuvers. MDPI 2023-04-23 /pmc/articles/PMC10180902/ /pubmed/37177418 http://dx.doi.org/10.3390/s23094212 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kim, Taeho Zewge, Natnael S. Bang, Hyochoong Yoon, Hyosang GMM-Based Adaptive Extended Kalman Filter Design for Satellite Attitude Estimation under Thruster-Induced Disturbances |
title | GMM-Based Adaptive Extended Kalman Filter Design for Satellite Attitude Estimation under Thruster-Induced Disturbances |
title_full | GMM-Based Adaptive Extended Kalman Filter Design for Satellite Attitude Estimation under Thruster-Induced Disturbances |
title_fullStr | GMM-Based Adaptive Extended Kalman Filter Design for Satellite Attitude Estimation under Thruster-Induced Disturbances |
title_full_unstemmed | GMM-Based Adaptive Extended Kalman Filter Design for Satellite Attitude Estimation under Thruster-Induced Disturbances |
title_short | GMM-Based Adaptive Extended Kalman Filter Design for Satellite Attitude Estimation under Thruster-Induced Disturbances |
title_sort | gmm-based adaptive extended kalman filter design for satellite attitude estimation under thruster-induced disturbances |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10180902/ https://www.ncbi.nlm.nih.gov/pubmed/37177418 http://dx.doi.org/10.3390/s23094212 |
work_keys_str_mv | AT kimtaeho gmmbasedadaptiveextendedkalmanfilterdesignforsatelliteattitudeestimationunderthrusterinduceddisturbances AT zewgenatnaels gmmbasedadaptiveextendedkalmanfilterdesignforsatelliteattitudeestimationunderthrusterinduceddisturbances AT banghyochoong gmmbasedadaptiveextendedkalmanfilterdesignforsatelliteattitudeestimationunderthrusterinduceddisturbances AT yoonhyosang gmmbasedadaptiveextendedkalmanfilterdesignforsatelliteattitudeestimationunderthrusterinduceddisturbances |