Multi-satellite emergency observation task planning method and device and computer equipment
A task planning and task technology, applied in the direction of calculation, calculation model, prediction, etc., can solve the problems of poor stability and low efficiency of satellite emergency task planning methods, and achieve the effects of good stability, fast prediction speed and good applicability
Pending Publication Date: 2021-01-15
NAT UNIV OF DEFENSE TECH
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[0004] Based on this, it is necessary to address the above technical problems and provide a multi-satellite emergency observation task planning method, device and computer equipment that can solve the problems of low efficiency and poor stability of the satellite emergency task planning method
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[0037] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.
[0038]The multi-satellite emergency observation task planning method provided by this application can be applied in the application environment as shown below. Obtain the observation task set to be planned in the satellite mission planning system, input the task feature information contained in the observation task set into the first machine learning model pre-trained with the satellite observation historical task planning data, and obtain task schedulability decision information, Input the task feature information and task schedulability decision information into the seco...
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The invention relates to a multi-satellite emergency observation task planning method and device and computer equipment. The method comprises the steps of obtaining a to-be-planned observation task set in a satellite task planning system, and inputting task feature information contained in the observation task set into a pre-trained first machine learning model to obtain task schedulability decision information, inputting the task feature information and the task schedulability decision information into a pre-trained second machine learning model to obtain first task allocation information, and inputting the first task allocation information into a constraint correction algorithm based on random hill climbing for correction to obtain second task allocation information, and performing taskplanning on the observation task according to the second task allocation information. An initial solution can be provided for a traditional task planning algorithm through the machine learning model,the advantages of high learning capacity and high prediction speed of the machine learning method are utilized, the advantage of good applicability of the traditional task planning algorithm is brought into play, efficiency is high, and stability is good.
Description
technical field [0001] The application relates to the technical field of satellite emergency mission planning, in particular to a multi-satellite emergency observation mission planning method, device and computer equipment. Background technique [0002] With the continuous development of satellite observation technology, earth observation satellites have become an important means of obtaining earthquakes, floods, tsunamis and other emergencies. Observation information can help ground personnel grasp the disaster situation in the disaster area in the first place. When faced with relatively intensive observation requests, a single earth observation satellite is often not efficient enough, and multi-satellite coordinated observation can effectively respond to observation needs. Under emergency conditions, multi-satellite mission planning needs to consider not only complex constraints (onboard storage space, onboard energy consumption, roll angle, etc.), but also the strong time...
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IPC IPC(8): G06Q10/04G06Q10/06G06N20/00
CPCG06Q10/04G06Q10/0631G06N20/00Y02A90/10
Inventor 陈浩罗棕彭双杜春伍江江熊伟欧阳雪钟志农吴晔杨岸然李军陈荦景宁
Owner NAT UNIV OF DEFENSE TECH