The unreasonable observation arrangements in the satellite operation control center(SOCC)may result in the observation data cannot be downloaded as scheduled.Meanwhile,if the operation instructions released by the sat...The unreasonable observation arrangements in the satellite operation control center(SOCC)may result in the observation data cannot be downloaded as scheduled.Meanwhile,if the operation instructions released by the satellite telemetry tracking center(STTC)for the on-board payloads are not injected on the specific satellites in time,the corresponding satellites cannot perform the observation operations as planned.Therefore,there is an urgent need to design an integrated instruction release,and observation task planning(I-IRO-TP)scheme by efficiently collaborating the SOCC and STTC.Motivated by this fact,we design an interaction mechanism between the SOCC and the STTC,where we first formulate the I-IRO-TP problem as a constraint satisfaction problem aiming at maximizing the number of completed tasks.Furthermore,we propose an interactive imaging task planning algorithm based on the analysis of resource distribution in the STTC during the previous planning periods to preferentially select the observation arcs that not only satisfy the requirements in the observation resource allocation phase but also facilitate the arrangement of measurement and control instruction release.We conduct extensive simulations to demonstrate the effectiveness of the proposed algorithm in terms of the number of completed tasks.展开更多
Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delay...Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delays, which is unable to ensure the integrity and timeliness of the information on decision making for satellites. And the optimization of the planning result is affected. Therefore, the effect of communication delay is considered during the multi-satel ite coordinating process. For this problem, firstly, a distributed cooperative optimization problem for multiple satellites in the delayed communication environment is formulized. Secondly, based on both the analysis of the temporal sequence of tasks in a single satellite and the dynamically decoupled characteristics of the multi-satellite system, the environment information of multi-satellite distributed cooperative optimization is constructed on the basis of the directed acyclic graph(DAG). Then, both a cooperative optimization decision making framework and a model are built according to the decentralized partial observable Markov decision process(DEC-POMDP). After that, a satellite coordinating strategy aimed at different conditions of communication delay is mainly analyzed, and a unified processing strategy on communication delay is designed. An approximate cooperative optimization algorithm based on simulated annealing is proposed. Finally, the effectiveness and robustness of the method presented in this paper are verified via the simulation.展开更多
This paper presents the method created by the National University of Defense Technology(NUDT)team in the 10th China Trajectory Optimization Competition,which entails a 3-year observation mission of 180 regions on Jupi...This paper presents the method created by the National University of Defense Technology(NUDT)team in the 10th China Trajectory Optimization Competition,which entails a 3-year observation mission of 180 regions on Jupiter.The proposed method can be divided into three steps.First,a preliminary analysis and evaluation via an analytical method is undertaken to decide whether the third subtask of the mission,i.e.,exploring the Galilean moons,should be ignored.Second,a near-optimal orbit for magnetic field observation is designed by solving an analytical equation.Third,a set of observation windows and their sequence are optimized using a customized genetic algorithm.The final index obtained is 354.505,ranking second out of all teams partaking in the competition.展开更多
基金supported by the Natural Science Foundation of China under Grants U19B2025,62121001,and 62001347in part by Key Research and Development Program of Shaanxi(ProgramNo.2022ZDLGY05-02)in part by Young Talent Support Program of Xi’an Association for Science and Technology(No.095920221337).
文摘The unreasonable observation arrangements in the satellite operation control center(SOCC)may result in the observation data cannot be downloaded as scheduled.Meanwhile,if the operation instructions released by the satellite telemetry tracking center(STTC)for the on-board payloads are not injected on the specific satellites in time,the corresponding satellites cannot perform the observation operations as planned.Therefore,there is an urgent need to design an integrated instruction release,and observation task planning(I-IRO-TP)scheme by efficiently collaborating the SOCC and STTC.Motivated by this fact,we design an interaction mechanism between the SOCC and the STTC,where we first formulate the I-IRO-TP problem as a constraint satisfaction problem aiming at maximizing the number of completed tasks.Furthermore,we propose an interactive imaging task planning algorithm based on the analysis of resource distribution in the STTC during the previous planning periods to preferentially select the observation arcs that not only satisfy the requirements in the observation resource allocation phase but also facilitate the arrangement of measurement and control instruction release.We conduct extensive simulations to demonstrate the effectiveness of the proposed algorithm in terms of the number of completed tasks.
基金supported by the National Science Foundation for Young Scholars of China(6130123471401175)
文摘Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delays, which is unable to ensure the integrity and timeliness of the information on decision making for satellites. And the optimization of the planning result is affected. Therefore, the effect of communication delay is considered during the multi-satel ite coordinating process. For this problem, firstly, a distributed cooperative optimization problem for multiple satellites in the delayed communication environment is formulized. Secondly, based on both the analysis of the temporal sequence of tasks in a single satellite and the dynamically decoupled characteristics of the multi-satellite system, the environment information of multi-satellite distributed cooperative optimization is constructed on the basis of the directed acyclic graph(DAG). Then, both a cooperative optimization decision making framework and a model are built according to the decentralized partial observable Markov decision process(DEC-POMDP). After that, a satellite coordinating strategy aimed at different conditions of communication delay is mainly analyzed, and a unified processing strategy on communication delay is designed. An approximate cooperative optimization algorithm based on simulated annealing is proposed. Finally, the effectiveness and robustness of the method presented in this paper are verified via the simulation.
基金This work was supported by the National Natural Science Foundation of China(No.11972044).
文摘This paper presents the method created by the National University of Defense Technology(NUDT)team in the 10th China Trajectory Optimization Competition,which entails a 3-year observation mission of 180 regions on Jupiter.The proposed method can be divided into three steps.First,a preliminary analysis and evaluation via an analytical method is undertaken to decide whether the third subtask of the mission,i.e.,exploring the Galilean moons,should be ignored.Second,a near-optimal orbit for magnetic field observation is designed by solving an analytical equation.Third,a set of observation windows and their sequence are optimized using a customized genetic algorithm.The final index obtained is 354.505,ranking second out of all teams partaking in the competition.