Joint shape and centroid position tracking of a cluster of space debris by filtering on Lie groups
| Autor: | A. Giremus, Brice Yver, S. Labsir, T. Benoudiba–Campanini |
|---|---|
| Přispěvatelé: | Laboratoire de l'intégration, du matériau au système (IMS), Université Sciences et Technologies - Bordeaux 1-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS), Centre d'études scientifiques et techniques d'Aquitaine (CESTA), Direction des Applications Militaires (DAM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Université Sciences et Technologies - Bordeaux 1 (UB)-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS) |
| Rok vydání: | 2021 |
| Předmět: |
Computer science
Centroid Lie group 020206 networking & telecommunications 02 engineering and technology Kinematics Curvature Tracking (particle physics) Orbit [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Control and Systems Engineering Signal Processing Orbital motion 0202 electrical engineering electronic engineering information engineering Trajectory 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Electrical and Electronic Engineering Algorithm Software Space debris |
| Zdroj: | Signal Processing Signal Processing, Elsevier, 2021, 183, pp.108027. ⟨10.1016/j.sigpro.2021.108027⟩ Signal Processing, 2021, 183, pp.108027. ⟨10.1016/j.sigpro.2021.108027⟩ |
| ISSN: | 0165-1684 1872-7557 |
| DOI: | 10.1016/j.sigpro.2021.108027 |
| Popis: | International audience; Space surveillance aims at detecting and tracking pieces of debris that are orbiting around the Earth. When the latter are sufficiently close to each other to form a compact cluster, they can be considered as a single extended object. State-of-the-art random-matrix methods estimate the kinematics of the object shape and centroid by assuming that it is ellipsoidal and that the sensor observations are randomly distributed within its volume. However, in accordance with the laws of orbital motion, space debris scatters taking a specific curvature. To intrinsically capture the resulting cluster shape, we propose a novel Lie-group-based parameterization of both the cluster and the sensor measurements. Then, we derive an iterated extended Kalman filter on Lie group to sequentially estimate both the centroid trajectory and the evolution of the extent parameters. Finally, numerical experiments validate the interest of the proposed method compared to a generic Gaussian-process-based extended-object tracking algorithm. |
| Databáze: | OpenAIRE |
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