scholarly journals Research on Task Satellite Selection Method for Space Object Detection LEO Constellation Based on Observation Window Projection Analysis

Aerospace ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 156
Author(s):  
Shengyu Zhang ◽  
Zhencai Zhu ◽  
Haiying Hu ◽  
Yuqing Li

Aiming at the task planning and scheduling problem of space object detection LEO constellation (SODLC) for detecting space objects in deep space background, a method of SODLC task satellite selection based on observation window projection analysis is proposed. This method projects the spatial relative relationships of the SODLC observation blind zone, observation range, and the initial spatial position of the objects onto the surface of the earth for detectable analysis of satellites and targets and binds the dynamic observation conditions to the satellite trajectory after projection calculation of the visible relationship between target changes. On this basis, combined with the features of SODLC with high orbital symmetry, the task satellite selection is divided into two steps: orbit plane selection and task satellite selection. The orbit planes are selected based on the longitude range of the ascending node with the geographic location of the targets, and the task satellites are selected according to the relative motion relationship between the satellites and the targets together with the constraints of observable conditions. The selection method simplifies the calculation process of scheduling and selecting task satellites. Simulation analysis prove the method has better task satellite selection efficiency. The method has high practical value for task planning and scheduling for event-driven SODLC.

Survey Review ◽  
2019 ◽  
Vol 52 (373) ◽  
pp. 330-340
Author(s):  
A. A. Abedi ◽  
M. R. Mosavi ◽  
K. Mohammadi

2020 ◽  
Vol 44 (3) ◽  
pp. 375-384
Author(s):  
I.G. Zhurkin ◽  
L.N. Chaban ◽  
P.Yu. Orlov

When solving a variety of celestial navigation tasks there is a problem of determining parameters of spacecraft motion and onboard primary payload orientation based on the coordinates of registered star images. Furthermore, unwanted objects, like active satellites, natural and artificial space debris, that reduce the probability of correct recognition may get into the field of view of a satellite sensor. This prompts the necessity to filter out such interference from the star field images. However, if the objects under recognition are bodies located in near-Earth space, in this case, the star images themselves will act as interferences. In addition, since the detection and cataloging of these objects from the Earth’s surface is complicated by their small size, the atmospheric effects, as well as other technical difficulties, it is worthwhile to use the existing equipment onboard spacecrafts to solve this task. The existing recognition algorithms for star groups, as well as their classification, are presented in this paper. Moreover, a structurally topological approach for identifying groups of stars based on the properties of enveloping polygons used in constructing topological star patterns is proposed. Specific features in the construction of topological configurations on the analyzed set of points, as well as the principles of dynamic space object detection within their limits are described. Results of the numerical experiments performed using the developed algorithm on the star field maps and model scenes are presented.


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