Relative navigation is a key enabling technology for space missions such as on-orbit servicing and space situational awareness.Given that there are several special advantages of space relative navigation using angles-...Relative navigation is a key enabling technology for space missions such as on-orbit servicing and space situational awareness.Given that there are several special advantages of space relative navigation using angles-only measurements from passive optical sensors,angles-only relative navigation is considered as one of the best potential approaches in the field of space relative navigation.However,angles-only relative navigation is well-known for its range observability problem.To overcome this observability problem,many studies have been conducted over the past decades.In this study,we present a comprehensive review of state-of-the-art space relative navigation based on angles-only measurements.The emphasis is on the observability problem and solutions to angles-only relative navigation,where the review of the solutions is categorized into four classes based on the intrinsic principle:complicated dynamics approach,multi-line of sight(multi-LOS)approach,sensor offset center-of-mass approach,and orbit maneuver approach.Then,the fight demonstration results of angles-only relative navigation in the two projects are briefly reviewed.Finally,conclusions of this study and recommendations for further research are presented.展开更多
Real-time 6 Degree-of-Freedom(DoF)pose estimation is of paramount importance for various on-orbit tasks.Benefiting from the development of deep learning,Convolutional Neural Networks(CNNs)in feature extraction has yie...Real-time 6 Degree-of-Freedom(DoF)pose estimation is of paramount importance for various on-orbit tasks.Benefiting from the development of deep learning,Convolutional Neural Networks(CNNs)in feature extraction has yielded impressive achievements for spacecraft pose estimation.To improve the robustness and interpretability of CNNs,this paper proposes a Pose Estimation approach based on Variational Auto-Encoder structure(PE-VAE)and a Feature-Aided pose estimation approach based on Variational Auto-Encoder structure(FA-VAE),which aim to accurately estimate the 6 DoF pose of a target spacecraft.Both methods treat the pose vector as latent variables,employing an encoder-decoder network with a Variational Auto-Encoder(VAE)structure.To enhance the precision of pose estimation,PE-VAE uses the VAE structure to introduce reconstruction mechanism with the whole image.Furthermore,FA-VAE enforces feature shape constraints by exclusively reconstructing the segment of the target spacecraft with the desired shape.Comparative evaluation against leading methods on public datasets reveals similar accuracy with a threefold improvement in processing speed,showcasing the significant contribution of VAE structures to accuracy enhancement,and the additional benefit of incorporating global shape prior features.展开更多
Spacecraft orbit evasion is an effective method to ensure space safety. In the spacecraft’s orbital plane, the space non-cooperate target with autonomous approaching to the spacecraft may have a dangerous rendezvous....Spacecraft orbit evasion is an effective method to ensure space safety. In the spacecraft’s orbital plane, the space non-cooperate target with autonomous approaching to the spacecraft may have a dangerous rendezvous. To deal with this problem, an optimal maneuvering strategy based on the relative navigation observability degree is proposed with angles-only measurements. A maneuver evasion relative navigation model in the spacecraft’s orbital plane is constructed and the observability measurement criteria with process noise and measurement noise are defined based on the posterior Cramer-Rao lower bound. Further, the optimal maneuver evasion strategy in spacecraft’s orbital plane based on the observability is proposed. The strategy provides a new idea for spacecraft to evade safety threats autonomously. Compared with the spacecraft evasion problem based on the absolute navigation, more accurate evasion results can be obtained. The simulation indicates that this optimal strategy can weaken the system’s observability and reduce the state estimation accuracy of the non-cooperative target, making it impossible for the non-cooperative target to accurately approach the spacecraft.展开更多
基金supported by the National Natural Science Foundation of China(12272168,11802119)Foundation of Science and Technology on Space Intelligent Control Laboratory(6142208200303,2021-JCJQ-LB-010-04).
文摘Relative navigation is a key enabling technology for space missions such as on-orbit servicing and space situational awareness.Given that there are several special advantages of space relative navigation using angles-only measurements from passive optical sensors,angles-only relative navigation is considered as one of the best potential approaches in the field of space relative navigation.However,angles-only relative navigation is well-known for its range observability problem.To overcome this observability problem,many studies have been conducted over the past decades.In this study,we present a comprehensive review of state-of-the-art space relative navigation based on angles-only measurements.The emphasis is on the observability problem and solutions to angles-only relative navigation,where the review of the solutions is categorized into four classes based on the intrinsic principle:complicated dynamics approach,multi-line of sight(multi-LOS)approach,sensor offset center-of-mass approach,and orbit maneuver approach.Then,the fight demonstration results of angles-only relative navigation in the two projects are briefly reviewed.Finally,conclusions of this study and recommendations for further research are presented.
基金supported by the National Natural Science Foundation of China(No.52272390)the Natural Science Foundation of Heilongjiang Province of China(No.YQ2022A009)the Shanghai Sailing Program,China(No.20YF1417300).
文摘Real-time 6 Degree-of-Freedom(DoF)pose estimation is of paramount importance for various on-orbit tasks.Benefiting from the development of deep learning,Convolutional Neural Networks(CNNs)in feature extraction has yielded impressive achievements for spacecraft pose estimation.To improve the robustness and interpretability of CNNs,this paper proposes a Pose Estimation approach based on Variational Auto-Encoder structure(PE-VAE)and a Feature-Aided pose estimation approach based on Variational Auto-Encoder structure(FA-VAE),which aim to accurately estimate the 6 DoF pose of a target spacecraft.Both methods treat the pose vector as latent variables,employing an encoder-decoder network with a Variational Auto-Encoder(VAE)structure.To enhance the precision of pose estimation,PE-VAE uses the VAE structure to introduce reconstruction mechanism with the whole image.Furthermore,FA-VAE enforces feature shape constraints by exclusively reconstructing the segment of the target spacecraft with the desired shape.Comparative evaluation against leading methods on public datasets reveals similar accuracy with a threefold improvement in processing speed,showcasing the significant contribution of VAE structures to accuracy enhancement,and the additional benefit of incorporating global shape prior features.
基金supported by the National Key R&D Program of China (2020YFA0713502)the Special Fund Project for Guiding Local Scientific and Technological Development (2020ZYT003)+1 种基金the National Natural Science Foundation of China (U20B2055,61773021,61903086)the Natural Science Foundation of Hunan Province (2019JJ20018,2020JJ4280)。
文摘Spacecraft orbit evasion is an effective method to ensure space safety. In the spacecraft’s orbital plane, the space non-cooperate target with autonomous approaching to the spacecraft may have a dangerous rendezvous. To deal with this problem, an optimal maneuvering strategy based on the relative navigation observability degree is proposed with angles-only measurements. A maneuver evasion relative navigation model in the spacecraft’s orbital plane is constructed and the observability measurement criteria with process noise and measurement noise are defined based on the posterior Cramer-Rao lower bound. Further, the optimal maneuver evasion strategy in spacecraft’s orbital plane based on the observability is proposed. The strategy provides a new idea for spacecraft to evade safety threats autonomously. Compared with the spacecraft evasion problem based on the absolute navigation, more accurate evasion results can be obtained. The simulation indicates that this optimal strategy can weaken the system’s observability and reduce the state estimation accuracy of the non-cooperative target, making it impossible for the non-cooperative target to accurately approach the spacecraft.
