scholarly journals Multi-Frame Blind Restoration for Image of Space Target With FRC and Branch-Attention

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 183813-183825
Author(s):  
Peijian Zhu ◽  
Chunzhi Xie ◽  
Zhisheng Gao
Keyword(s):  
Blind Restoration ◽  
Space Target

Space Target Image Categorization Based on the Second Representation

2014 ◽  
Vol 35 (5) ◽  
pp. 1247-1251
Author(s):  
Fei-yun Jiang ◽  
Rui Sun ◽  
Xu-dong Zhang ◽  
Chao Li
Keyword(s):  
Image Categorization ◽  
Target Image ◽  
Space Target

Maneuver detection and tracking of a space target based on a joint filter model

2020 ◽  
Author(s):  
Liu Ye ◽  
Zhao Hua ◽  
Liu Chuankai ◽  
Cao Jianfeng ◽  
Wang Junkui
Keyword(s):  
Filter Model ◽  
Detection And Tracking ◽  
Space Target

Study on Dynamic IR Image Generation of Space Target

2014 ◽  
Vol 1044-1045 ◽  
pp. 1343-1348
Author(s):  
Wu Can He ◽  
Shou Yi Liao ◽  
Zuo Yu Zhang ◽  
He Xin Zhang
Keyword(s):  
Infrared Imaging ◽  
Three Dimensional ◽  
Orbit Space ◽  
Guidance System ◽  
Image Generation ◽  
Hardware In The Loop ◽  
Imaging Guidance ◽  
Infrared Star ◽  
Objective Basis ◽  
Space Target

Dynamic IR image generation of space target is one of the key technologies in hardware in the loop simulation for the infrared imaging guidance system. The three-dimensional entity model is created in the Creator, Sinda/Fluint is used to analyze each part of dynamic infrared radiation characteristics from on-orbit Space Target, on the basis of the LRS infrared star catalogues, celestial background modeling is built. In Vega, the dynamic IR image of space target is generated. The simulation results show that the dynamic IR image of Space Target provide the important objective basis for the hardware in the loop simulation for the infrared imaging guidance system.

scholarly journals 3-D IMAGING OF HIGH-SPEED MOVING SPACE TARGET VIA JOINT PARAMETRIC SPARSE REPRESENTATION

2017 ◽  
Vol 58 ◽  
pp. 125-134
Author(s):  
Yuxue Sun ◽  
Meng Jiang ◽  
Ying Luo ◽  
Qun Zhang ◽  
Chunhui Chen
Keyword(s):  
Sparse Representation ◽  
High Speed ◽  
Space Target

Inertia parameter identification of anunknown captured space target

2019 ◽  
Vol 91 (8) ◽  
pp. 1147-1155 ◽  
Author(s):  
Xiaofeng Liu ◽  
Bangzhao Zhou ◽  
Boyang Xiao ◽  
Guoping Cai
Keyword(s):  
Angular Momentum ◽  
Parameter Identification ◽  
Linear Momentum ◽  
Content Type ◽  
Identification Method ◽  
Robot Arms ◽  
Precise Estimation ◽  
Inertia Parameter ◽  
Inertia Parameters ◽  
Space Target

Purpose The purpose of this paper is to present a method to obtain the inertia parameter of a captured unknown space target. Design/methodology/approach An inertia parameter identification method is proposed in the post-capture scenario in this paper. This method is to resolve parameter identification with two steps: coarse estimation and precise estimation. In the coarse estimation step, all the robot arms are fixed and inertia tensor of the combined system is first calculated by the angular momentum conservation equation of the system. Then, inertia parameters of the unknown target are estimated using the least square method. Second, in the precise estimation step, the robot arms are controlled to move and then inertia parameters are once again estimated by optimization method. In the process of optimization, the coarse estimation results are used as an initial value. Findings Numerical simulation results prove that the method presented in this paper is effective for identifying the inertia parameter of a captured unknown target. Practical implications The presented method can also be applied to identify the inertia parameter of space robot. Originality/value In the classic momentum-based identification method, the linear momentum and angular momentum of system, both considered to be conserved, are used to identify the parameter of system. If the elliptical orbit in space is considered, the conservation of linear momentum is wrong. In this paper, an identification based on the conservation of angular momentum and dynamics is presented. Compared with the classic momentum-based method, this method can get a more accurate identification result.

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