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publications
Multitree Search for Multisatellite Responsiveness Scheduling Considering Orbital Maneuvering
Published in IEEE Transactions on Aerospace and Electronic Systems, 2021
Rapid and responsive Earth observation satellites enable the evaluation of disaster risk, improve relief effectiveness, and reduce suffering and fatalities in the event of sudden disaster events. One promising method for responsive space satellites is orbital maneuvering. This article describes a multitree search framework for multisatellite responsiveness scheduling considering orbital maneuvering, where multiple ground targets are cooperatively observed by multiple observation satellites over a short period of time. Based on the traditional tree search, the proposed method constructs multiple trees and distributes all the targets to multiple satellites, allowing the observation sequence of a single satellite to be optimized. To apply the tree search algorithm, a tree node collection (TNC) composed of the corresponding nodes in multiple trees is used to represent the state of each satellite. Before the expansion phase, one specific node in the TNC is determined for later expansion. A beam search is then used to optimize the observation sequence. Ground-track adjustment techniques using impulse maneuver are considered for visiting a given target. The proposed framework is more effective than other algorithms and achieves a better performance than the previous best method in a typical multisatellite responsiveness scheduling scenario.
Recommended citation: Zhong Zhang, Nan Zhang, Yifei Jiao, Hexi Baoyin, and Junfeng Li. "Multitree Search for Multisatellite Responsiveness Scheduling Considering Orbital Maneuvering." IEEE Transactions on Aerospace and Electronic Systems 58, no. 3 (2021): 2206-2217. [http://academicpages.github.io/files/paper1.pdf](https://ieeexplore.ieee.org/abstract/document/9623484)
Semi-analytical algorithm for computing satellite-area target visibility
Published in Journal of Tsinghua University (Science and Technology), 2022
Computing the visibility of remote sensing satellites on an area target is an important basic satellite observation mission. The calculational accuracy and efficiency are then very important for satellite imaging scheduling. This paper presents a fast, semi-analytical algorithm for predicting satellite-area target visibility. First, geometric relations are used to define the boundaries of all the area targets described by ordinary arcs with the algorithm then determining the intersections. Then, the cone characteristics and the rectangular field of view of the satellite are used with a fast judgement condition for the visibility. The visibility at each discrete time step is determined analytically with a binary search which is then used to quickly predict the time for the visible window. Numerical examples show that this method is accurate and efficient.
Recommended citation: Zhong Zhang, Zhibo E, Lixia Huang, and Junfeng Li. "Semi-analytical algorithm for computing satellite-area target visibility." Journal of Tsinghua University (Science and Technology) 62, no. 3 (2022): 573-580. http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2021.26.020
Timeline Club: An optimization algorithm for solving multiple debris removal missions of the time-dependent traveling salesman problem model
Published in Astrodynamics, 2022
With the increase of space debris, space debris removal has gradually become a major issue to address by worldwide space agencies. Multiple debris removal missions, in which multiple debris objects are removed in a single mission, are an economical approach to purify the space environment. Such missions can be considered typical time-dependent traveling salesman problems (TDTSPs). In this study, an intelligent global optimization algorithm called Timeline Club Optimization (TCO) is proposed to solve multiple debris removal missions of the TDTSP model. TCO adopts the traditional ant colony optimization (ACO) framework and replaces the pheromone matrix of the ACO with a new structure called the Timeline Club. The Timeline Club records which debris object to be removed next at a certain moment from elitist solutions and decides the probability criterion to generate debris sequences in new solutions. Two hypothetical scenarios, the Iridium-33 mission and the GTOC9 mission, are considered in this study. Simulation results show that TCO offers better performance than those of beam search, ant colony optimization, and the genetic algorithm in multiple debris removal missions of the TDTSP model.
Recommended citation: Nan Zhang, Zhong Zhang, and Hexi Baoyin. "Timeline Club: An optimization algorithm for solving multiple debris removal missions of the time-dependent traveling salesman problem model." Astrodynamics (2022): 1-16. https://link.springer.com/article/10.1007/s42064-021-0107-z
Two-Stage Dynamic-Assignment Optimization Method for Multispacecraft Debris Removal
Published in Journal of Guidance, Control, and Dynamic, 2022
The multi-spacecraft debris removal missions can be considered as a specific variant of the time-dependent multiple traveling salesman problem. It is challenging to determine the debris sequences and corresponding rendezvous epochs. This paper presents a two-stage dynamic assignment framework to deal with this problem. Firstly, generate the mission databases which store the debris sequences that can exist in the same mission. Based on the mission databases, the first stage adopts the genetic algorithm to pre-distribute all given targets to different spacecrafts and Timeline Club Optimization to optimize each single spacecraft mission. The near-optimal solutions can be obtained at stage 1. At stage 2, considering reassigning some debris pieces to other appropriate spacecrafts, a hill-climbing-like algorithm provides a further local optimization on the previous near-optimal solutions. Simulation results show that the proposed framework offers better performance than the previous studies in a typical multi-spacecraft debris removal scenario.
Recommended citation: Nan Zhang, Shiyu Chen, Zhong Zhang, and Hexi Baoyin. "Two-Stage Dynamic-Assignment Optimization Method for Multispacecraft Debris Removal." Journal of Guidance, Control, and Dynamics 45, no. 9 (2022): 1750-1759. https://arc.aiaa.org/doi/full/10.2514/1.G006602
GTOC 11: Results from Tsinghua University and Shanghai Institute of Satellite Engineering
Published in Acta Astronautica, 2023
In this paper, the methods and results from Tsinghua University and Shanghai Institute of Satellite Engineering for the 11th Global Trajectory Optimization Competition (GTOC11) are presented. To deal with the complicated “Dyson Sphere” building problem, a three-stage procedure is conducted. First, the pre-analysis is performed to reduce search space. It is found that two-impulse maneuvers between asteroid flybys are near-optimal, the semi-major axis of the “Dyson Ring” should be better at 1.0–1.5 AU, and the larger arrival mass asteroids tend to be selected. Second, the globally optimal trajectory design problem is further divided into two sub-problems, the mothership trajectory design and the asteroid assignment to the “Dyson Ring” power stations. For the first problem, beam search is used to obtain numerous single mothership trajectories based on a pre-constructed flyby trajectory database of 3–8 asteroids. The overall trajectories and asteroids visited are obtained by selecting 10 mothership trajectories with a genetic algorithm. For the second problem, we build a database of optimal rendezvous times for all the 83,453 asteroids at different phase angles to reach power stations of different radii and phase angles, then a greedy algorithm is proposed to obtain the asteroid arrival schedule based on all the asteroids visited by motherships. Finally, local optimization of asteroid sequence and flyby epochs is conducted. The activation time adjustment in combination with indirect continuous-thrust trajectory optimization is used based on the global optimization result. In the final submission, motherships fly by 388 asteroids, and the minimum mass of twelve power stations reaches 94% of the theoretical upper bound, which is defined using the minimum-time orbital transfers with free initial and target phases.
Recommended citation: Zhong Zhang, Nan Zhang, Xiang Guo, Di Wu, Xuan Xie, Jinyuan Li, Jia Yang et al. "GTOC 11: Results from Tsinghua University and Shanghai Institute of Satellite Engineering." Acta Astronautica 202 (2023): 819-828. https://www.sciencedirect.com/science/article/pii/S0094576522003186
Low-Energy Transfer Design of Heliocentric Formation Using Lunar Swingby on the Example of LISA
Published in Aerospace, 2023
Space-based gravitational wave (GW) detection at low frequencies is of great scientific significance and has received extensive attention in recent years. This work designs and optimizes the low-energy transfer of the heliocentric formation of GW detectors, which starts from a geosynchronous transfer orbit and targets an Earth-like orbit. Based on the example of the Laser Interferometer Space Antenna (LISA), the transfer is first designed in two-body dynamical models and then refined in simplified high-fidelity dynamical models that only consider the major orbital perturbations evaluated here. The main contributions of this work are to present an adaptive model continuation technique and to exploit the lunar swingby technique to reduce the problem-solving difficulty and velocity increment of orbital transfer, respectively. The adaptive model continuation technique fully reveals the effect of perturbations and rapidly iterates the solutions to the simplified models. The simulation results show that the lunar swingby does reduce the energy needed to escape the Earth’s sphere of influence. It is found that the gravitation of the Earth–Moon system has a significant contribution to reducing the velocity increment. The solution of low-energy transfer in the simplified models is that the duration is 360.6615 days and the total velocity increment is 0.8468 km/s.
Recommended citation: Jia Yang, Zhong Zhang, Fanghua Jiang, and Junfeng Li. "Low-Energy Transfer Design of Heliocentric Formation Using Lunar Swingby on the Example of LISA." Aerospace 10, no. 1 (2023): 18. https://www.mdpi.com/2226-4310/10/1/18?src=738910
Multi-Trajectory Combination for Multiple Ground Target Observation by Maneuvering On-Orbit Satellites
Published in IEEE Transactions on Aerospace and Electronic Systems, 2023
Compared with launching new satellites, it is an economic scheme to use on-orbit satellites to maneuver to meet users particular needs for Earth observation. This paper studies the mission design method of on-orbit satellite maneuver for observing large-scale ground targets within a given duration. This paper divides the original large-scale sequence optimization problem into two small-scale subproblems that are easy to optimize: short-sequence trajectory generation and multi-trajectory combination optimization. The multi-trajectory combination framework, including database generation, multi-trajectory combination selection, trajectory patching, and trajectory keeping, is adopted to optimize the observation sequence and design the satellite trajectory. In two specific scenarios, the fuel-optimal scenario and accurate revisit observation scenario, the proposed framework shows competitive optimization performance compared with existing tree search algorithms. In addition, this paper provides a known optimal result for the 11th China Trajectory Optimization Competition problem.
Recommended citation: Nan Zhang, Zhong Zhang, Yifei Jiao and Hexi Baoyin, "Multi-Trajectory Combination for Multiple Ground Target Observation by Maneuvering On-Orbit Satellites," in IEEE Transactions on Aerospace and Electronic Systems, 2023. (Early Access) https://ieeexplore.ieee.org/abstract/document/10218327
Global trajectory optimization of multi-spacecraft successive rendezvous using multi-tree search
Published in Journal of Guidance, Control, and Dynamics, 2023
This paper investigates the global optimization of multi-spacecraft successive rendezvous trajectories, which is divided here into three subproblems: target assignment, sequence optimization, and rendezvous time optimization. A method consisting of two novel algorithms is proposed to solve these subproblems. First, a multi-tree search framework is developed to assign multiple targets to each spacecraft and simultaneously optimize the rendezvous sequence for every single spacecraft. Specifically, a novel algorithm of local search combined with beam search is proposed. Second, this paper converts the rendezvous time optimization problem into a multi-stage decision problem. Based on a critical rendezvous-epoch-dependent characteristic found in this subproblem, the number of state variables is thereby reduced. A novel dual dynamic programming algorithm is proposed and combined with dynamic programming to solve for the globally optimal rendezvous epochs efficiently. The global optimality is guaranteed by Bellman principle of optimality, which is the first time in such problem to our knowledge. The proposed method achieves state-of-the-art performance in several typical fuel-optimal scenarios of active debris removal. This open-sourced method is non-database-dependent and contains only one design stage, which is expected to be adopted in other successive rendezvous missions.
Recommended citation: Zhong Zhang, Nan Zhang, Zherui Chen, Fanghua Jiang, and Junfeng Li. "Global trajectory optimization of multi-spacecraft successive rendezvous using multi-tree search." Journal of Guidance, Control, and Dynamics, 2023. (Accepted) https://arc.aiaa.org/doi/10.2514/1.G007764
talks
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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