中国空间科学技术最新文献_第4页

The Tianwen-1 Guidance, Navigation, and Control for Mars Entry, Descent, and Landing 天文一号火星进入、下降和着陆的制导、导航和控制

IF 0.9 4区工程技术

中国空间科学技术 Pub Date : 2021-10-16 DOI: 10.34133/2021/9846185

Xiangyu Huang, Maodeng Li, Xiaolei Wang, Jinchang Hu, Yu Zhao, Minwen Guo, Chao Xu, Wangwang Liu, Yunpeng Wang, Ce Hao, Lijia Xu

引用次数: 17

A Light Space Manipulator with High Load-to-Weight Ratio: System Development and Compliance Control 高载重比轻型空间机械臂:系统开发与柔度控制

IF 0.9 4区工程技术

中国空间科学技术 Pub Date : 2021-09-28 DOI: 10.34133/2021/9760520

Zhiwei Wu, Yongting Chen, Wenfu Xu

引用次数: 7

Research on a Visual Servo Method of a Manipulator Based on Velocity Feedforward 基于速度前馈的机械手视觉伺服方法研究

IF 0.9 4区工程技术

中国空间科学技术 Pub Date : 2021-09-10 DOI: 10.34133/2021/9763179

Rui Wang, Changchun Liang, Dong Pan, Xiaodong Zhang, Pengfei Xin, Xiaodong Du

引用次数: 10

Nuclear Processes in Dark Interstellar Matter of H(0) Decrease the Hope of Migrating to Exoplanets 黑暗星际物质H(0)中的核过程降低了迁移到系外行星的希望

IF 0.9 4区工程技术

中国空间科学技术 Pub Date : 2021-09-03 DOI: 10.34133/2021/9846852

L. Holmlid

{"title":"Nuclear Processes in Dark Interstellar Matter of H(0) Decrease the Hope of Migrating to Exoplanets","authors":"L. Holmlid","doi":"10.34133/2021/9846852","DOIUrl":"https://doi.org/10.34133/2021/9846852","url":null,"abstract":"It is still generally assumed that interstellar travel will be possible after purely technical development and thus that mankind can move to some suitable exoplanet when needed. However, recent research indicates this not to be the case, since interstellar space is filled with enough ultradense hydrogen H(0) as stable condensed dark matter (Holmlid, Astrophysical Journal 2018) to make interstellar space travel at the required and technically feasible relativistic velocities (Holmlid et al, Acta Astronautica 2020) almost impossible. H(0) can be observed to exist in space from the so-called extended red emission (ERE) features observed in space. A recent review (Holmlid et al., Physica Scripta 2019) describes the properties of H(0). H(0) gives nuclear processes emitting kaons and other particles, with kinetic energies even above 100 MeV after induction for example by fast particle (spaceship) impact. These high particle energies give radiative temperatures of 12000 K in collisions against a solid surface and will rapidly destroy any spaceship structure moving into the H(0) clouds at relativistic velocity. The importance of preserving our ecosystem is pointed out, since travel to suitable exoplanets may be impossible. The possibilities of instead clearing interstellar space from H(0) are discussed, eventually providing tunnels suitable for relativistic interstellar transport. Finding regions with low intensity of ERE could even be a way to identify space-cleaning activities and thus to locate earlier space-travelling civilizations.","PeriodicalId":44234,"journal":{"name":"中国空间科学技术","volume":"149 ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72505339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A High-Efficient Finite Difference Method for Flexible Manipulator with Boundary Feedback Control 柔性机械臂边界反馈控制的高效有限差分法

IF 0.9 4区工程技术

中国空间科学技术 Pub Date : 2021-08-18 DOI: 10.34133/2021/9874563

Fushou Liu, D. Jin

引用次数: 12

Knowledge Graph-Based Image Recognition Transfer Learning Method for On-Orbit Service Manipulation 基于知识图的在轨服务操作图像识别迁移学习方法

IF 0.9 4区工程技术

中国空间科学技术 Pub Date : 2021-08-06 DOI: 10.34133/2021/9807452

Ao Chen, Yongchun Xie, Yong Wang, Linfeng Li

{"title":"Knowledge Graph-Based Image Recognition Transfer Learning Method for On-Orbit Service Manipulation","authors":"Ao Chen, Yongchun Xie, Yong Wang, Linfeng Li","doi":"10.34133/2021/9807452","DOIUrl":"https://doi.org/10.34133/2021/9807452","url":null,"abstract":"Visual perception provides state information of current manipulation scene for control system, which plays an important role in on-orbit service manipulation. With the development of deep learning, deep convolutional neural networks (CNNs) have achieved many successful applications in the field of visual perception. Deep CNNs are only effective for the application condition containing a large number of training data with the same distribution as the test data; however, real space images are difficult to obtain during large-scale training. Therefore, deep CNNs can not be directly adopted for image recognition in the task of on-orbit service manipulation. In order to solve the problem of few-shot learning mentioned above, this paper proposes a knowledge graph-based image recognition transfer learning method (KGTL), which learns from training dataset containing dense source domain data and sparse target domain data, and can be transferred to the test dataset containing large number of data collected from target domain. The average recognition precision of the proposed method is 80.5%, and the average recall is 83.5%, which is higher than that of ResNet50-FC; the average precision is 60.2%, and the average recall is 67.5%. The proposed method significantly improves the training efficiency of the network and the generalization performance of the model.","PeriodicalId":44234,"journal":{"name":"中国空间科学技术","volume":"62 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2021-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73969241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Guidance Navigation and Control for Chang’E-5 Powered Descent 嫦娥五号动力下降制导导航与控制

IF 0.9 4区工程技术

中国空间科学技术 Pub Date : 2021-07-13 DOI: 10.34133/2021/9823609

Honghua Zhang, Ji Li, Zeguo Wang, Yifeng Guan

{"title":"Guidance Navigation and Control for Chang’E-5 Powered Descent","authors":"Honghua Zhang, Ji Li, Zeguo Wang, Yifeng Guan","doi":"10.34133/2021/9823609","DOIUrl":"https://doi.org/10.34133/2021/9823609","url":null,"abstract":"To achieve the goal of collecting lunar samples and return to the Earth for the Chang’E-5 spacecraft, the lander and ascender module (LAM) of the Chang’E-5 spacecraft successfully landed on the lunar surface on 1 Dec., 2020. The guidance, navigation, and control (GNC) system is one of the critical systems to perform this task. The GNC system of previous missions, Chang’E-3 and Chang’E-4, provides the baseline design for the Chang’E-5 LAM, and the new characteristics of the LAM, like larger mass and liquid sloshing, also bring new challenges for the GNC design. The GNC design for the descent and landing is presented in this paper. The guidance methods implemented in the powered descent are presented in detail for each phase. Propellant consumption and hazard avoidance should be particularly considered in the design. A reconfigurable attitude control is adopted which consists of the quaternion partition control, phase and gain stabilization filter, and dual observer. This controller could provide fast attitude maneuver and better system robustness. For the navigation, an intelligent heterogeneous sensor data fusion method is presented, and it is applied for the inertial measurement unit and velocimeter data. Finally, the flight results of the LAM are shown. Navigation sensors were able to provide valid measurement data during descent, and the thrusters and the main engine operated well as expected. Therefore, a successful soft lunar landing was achieved by the LAM.","PeriodicalId":44234,"journal":{"name":"中国空间科学技术","volume":"76 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75995372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21

A Bridge Neural Network-Based Optical-SAR Image Joint Intelligent Interpretation Framework 基于桥式神经网络的光学- sar图像联合智能解译框架

IF 0.9 4区工程技术

中国空间科学技术 Pub Date : 2021-01-01 DOI: 10.34133/2021/9841456

Meiyu Huang, Yao Xu, Lixin Qian, Weili Shi, Yaqin Zhang, Wei Bao, Nan Wang, Xuejiao Liu, Xueshuang Xiang

{"title":"A Bridge Neural Network-Based Optical-SAR Image Joint Intelligent Interpretation Framework","authors":"Meiyu Huang, Yao Xu, Lixin Qian, Weili Shi, Yaqin Zhang, Wei Bao, Nan Wang, Xuejiao Liu, Xueshuang Xiang","doi":"10.34133/2021/9841456","DOIUrl":"https://doi.org/10.34133/2021/9841456","url":null,"abstract":"The current interpretation technology of remote sensing images is mainly focused on single-modal data, which cannot fully utilize the complementary and correlated information of multimodal data with heterogeneous characteristics, especially for synthetic aperture radar (SAR) data and optical imagery. To solve this problem, we propose a bridge neural network- (BNN-) based optical-SAR image joint intelligent interpretation framework, optimizing the feature correlation between optical and SAR images through optical-SAR matching tasks. It adopts BNN to effectively improve the capability of common feature extraction of optical and SAR images and thus improving the accuracy and application scenarios of specific intelligent interpretation tasks for optical-SAR/SAR/optical images. Specifically, BNN projects optical and SAR images into a common feature space and mines their correlation through pair matching. Further, to deeply exploit the correlation between optical and SAR images and ensure the great representation learning ability of BNN, we build the QXS-SAROPT dataset containing 20,000 pairs of perfectly aligned optical-SAR image patches with diverse scenes of high resolutions. Experimental results on optical-to-SAR crossmodal object detection demonstrate the effectiveness and superiority of our framework. In particular, based on the QXS-SAROPT dataset, our framework can achieve up to 96% high accuracy on four benchmark SAR ship detection datasets.","PeriodicalId":44234,"journal":{"name":"中国空间科学技术","volume":"22 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73510530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

Dynamic Simulation of Space Debris Cloud Capture Using the Tethered Net 利用系留网捕获空间碎片云的动态模拟

IF 0.9 4区工程技术

中国空间科学技术 Pub Date : 2021-01-01 DOI: 10.34133/2021/9810375

Qingtao Wang, D. Jin, X. Rui

{"title":"Dynamic Simulation of Space Debris Cloud Capture Using the Tethered Net","authors":"Qingtao Wang, D. Jin, X. Rui","doi":"10.34133/2021/9810375","DOIUrl":"https://doi.org/10.34133/2021/9810375","url":null,"abstract":"Space debris, especially the space debris cloud, has threatened severely the safety of future space missions. In the framework of multibody system dynamics, a computational approach is proposed in this study to investigate the dynamics of net deployment and capture of space debris cloud using this net subject to large overall motions and large deformations. To obtain high simulation fidelity of capturing space debris cloud, the gradient deficient beam element of the absolute nodal coordinate formulation (ANCF) is employed to discretize threads which are woven into the net. The normal contact force between the net and the debris cloud and among debris particles is computed by using the penalty method. Some deployment examples are presented to investigate the influences of shooting velocity of bullets and microgravity as well as the angle between the traveling direction of the net and the microgravity direction on the deployment characteristics of the tethered net. Other capturing examples are given to clarify the effect of the deployment area of the net at the moment it starts to contact with the debris cloud on the capture rate and to demonstrate the effectiveness of the proposed approach for capturing space debris cloud using the net in microgravity conditions.","PeriodicalId":44234,"journal":{"name":"中国空间科学技术","volume":"22 8","pages":""},"PeriodicalIF":0.9,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72602768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Design and Realization of Recovery System of Chang’e-5 Reentry Spacecraft 嫦娥五号再入航天器回收系统的设计与实现

IF 0.9 4区工程技术

中国空间科学技术 Pub Date : 2021-01-01 DOI: 10.34133/2021/9898756

Wei Huang, W. Rong, Dahai Liu, Changhong Jiang, He Jia, Jinjin Bao, Jishou Fang

引用次数: 6