A method is proposed to select the target sequence for a J 2-perturbed multiple debris rendezvous mission aimed at removing dozens of debris from several thousand debris candidates running on sun-synchronous orbits (SSO). The solving methodology proceeds in two steps: Firstly, the variance of the right ascension of ascending node (RAAN) of the debris group is used for narrowing down the potential debris candidate; secondly, the debris of the candidate group that has closest RAAN to the current debris is chosen as the next debris. The low thrust near-minimum-fuel trajectories of each rendezvous leg are obtained by the indirect optimization method. The proposed approach is demonstrated for the problem of the 8th China Trajectory Optimization Competition (CTOC). The radar cross section (RCS) of the debris is also considered in the first step since the primary performance index of the competition is to maximize the total RCS of the debris visited. The results show that the proposed approach achieves better performance within a competition period. Of the many rendezvous sequences found, the best one submitted for the competition obtained a total RCS of 184 by accomplishing rendezvous with 70 debris within a transfer duration of one year.
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We are very grateful to the organizers of the 8th China Trajectory Optimization Competition for the interesting and complex problem. Most methods presented in this paper were developed under the National Natural Science Foundation of China (Nos. 11172036, 11572037, and 11402021) and the Excellent Young Scholars Research Fund of Beijing Institute of Technology (No. 2015YG0101).
Shuge Zhao received his B.S. degree in detection, guidance, and control techniques from Shenyang Ligong University, Shenyang, China, in 2009, M.S. degree in control science and engineering from Beihang University, Beijing, China, in 2012, and Ph.D. degree in flight vehicle design from Beijing Institute of Technology, Beijing, China, in 2016. From 2016, he is a postdoctoral fellow at the Second Research Academy of China Aerospace Science and Industry Corporation. His research interests include orbital dynamics and control, and spacecraft trajectory optimization.
Jingrui Zhang received her B.S. and M.S. degrees in automation instrument and flight mechanics from Harbin Institute of Technology, Harbin, China, in 1996 and 1998, respectively, and Ph.D. degree in automatic control from the University of Picardie-Jule Verne, Picardie, France, in 2002. From 2002 to 2004, she was a postdoctoral fellow at the Department of Mechanical Engineering, Tsinghua University, Beijing, China. She is currently a professor at Beijing Institute of Technology, Beijing, China. Her research interests include rapid maneuver and stabilization of spacecraft attitude control, formation flying, and rendezvous and docking.
Kaiheng Xiang received his B.S. and Ph.D. degrees in flight vehicle design from Beihang University, Beijing, China, in 1993 and 1999, respectively. From 2000 to 2002, he was a postdoctoral fellow at the China Academy of Space Technology, Beijing, China. He is currently a research fellow at the Second Research Academy of China Aerospace Science and Industry Corporation, Beijing, China. His research interests include orbital dynamics and the system design of spacecraft.
Rui Qi received his B.S. and Ph.D. degrees in flight vehicle design from Beihang University, Beijing, China, in 2008 and 2013, respectively. From May 2015 to May 2016, he was a visiting professor at McGill University, working with Professor Arun Misra on the study of active debris removal using tethered space-tug. He is currently an assistant professor at Beijing Institute of Technology, Beijing, China. His research interests include active debris removal, formation flying, and orbital mechanics.
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Zhao, S., Zhang, J., Xiang, K. et al. Target sequence optimization for multiple debris rendezvous using low thrust based on characteristics of SSO. Astrodyn 1, 85–99 (2017). https://doi.org/10.1007/s42064-017-0007-4
- multiple debris rendezvous
- sun-synchronous orbits (SSO)
- low thrust
- optimal control