Hierarchical multi-orbit multi-mission satellite scheduling method and system

Abstract

The application provides a layered multi-orbit multi-task satellite scheduling method, system, storage medium and electronic equipment, and relates to the technical field of satellite scheduling.The application provides a layered multi-orbit multi-task satellite scheduling method for large-scale satellite task scheduling problems, firstly, a task priority analysis index is provided for the priority of task allocation, so that the rationality of task arrangement is preliminarily ensured;then, a heuristic strategy different from the past is provided in the multi-orbit and multi-task matching stage, and an optimal orbit allocation tool model of multi-task in multi-orbit is innovatively developed, which can provide a high-quality task orbit allocation scheme in a relatively short time, and the optimal precision of the task orbit matching result is improved;finally, a single-orbit task scheduling function based on the time dependence of task value is provided for the single-orbit task scheduling, which is consistent with the profit change of the actual satellite task scheduling, and reflects the time dynamics of the model scheduling.

Description

Technical Field

[0001] This invention relates to the field of satellite scheduling technology, specifically to a hierarchical multi-orbit multi-mission satellite scheduling method, system, storage medium, and electronic device. Background Technology

[0002] Earth Observing Systems (EOS) are widely used to probe the Earth's surface and surrounding atmosphere. Their exceptional imaging capabilities and long service life have played a crucial role in resource exploration, disaster monitoring, urban planning, marine management, and environmental monitoring, leading to the rapid development of the Earth Observing System field. With the surge in the number of EOS and the diversification of user needs, large-scale satellite mission scheduling involving multiple satellites, orbits, and missions is becoming increasingly practical compared to single-satellite scheduling.

[0003] The difficulty in solving these problems lies in two aspects. First, the increased number of satellites brings complexity, including the number of candidate EOS (Electronic Optical Arrays) providing services for the mission, the visible time window, and the number of missions. Second, ensuring reasonable cooperation among multiple satellites makes the constraints more complex.

[0004] Currently, the main algorithms developed for satellite resource scheduling include exact algorithms, heuristic algorithms, and metaheuristic algorithms. While exact algorithms can achieve optimal scheduling results, for Np-Hard problems, the computation time required by exact algorithms typically increases exponentially with the problem size, leading to excessively high time costs. On the other hand, compared to exact algorithms, heuristic and metaheuristic methods can obtain a set of approximate solutions at a lower computational cost and have been widely used to solve large-scale scheduling problems involving multiple satellites and multiple tasks. However, these methods essentially involve searching in the state space, evaluating each search position to obtain a better position, and then searching from that position until the target is reached. Such scheduling results may not have performance guarantees, meaning they are prone to getting trapped in local optima. Summary of the Invention

[0005] (a) Technical problems to be solved

[0006] To address the shortcomings of existing technologies, this invention provides a hierarchical multi-orbit multi-mission satellite scheduling method, system, storage medium, and electronic device, which solves the technical problem of being unable to balance time cost and high-performance scheduling results.

[0007] (II) Technical Solution

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A hierarchical multi-orbit multi-mission satellite scheduling method includes:

[0010] S1, Task set T for receiving user requests i And let the orbital operation cycle index i = 1, and analyze the task priority index of each task by calculating the task priority index. Sort the task set according to the allocation order;

[0011] S2. Select unmarked task priority analysis metrics The biggest task

[0012] S3, Regarding the task Determining available tracks for execution: If the task... There are one or more matching tracks to determine the task. optimal orbit In task set T i Delete task Otherwise, mark the task. No longer participating in task allocation for the current orbital operation cycle;

[0013] S4. Determine if all tasks have been traversed and executed using available tracks. If yes, delete all task markers in the current task set, set i = i + 1, and go to S5; otherwise, go to S2.

[0014] S5. Perform task pruning. Filter out tasks that have timed out in the current task set. Repeat steps S2 to S5 until all tasks are matched with tracks or all remaining unassignable tasks are pruned. Proceed to S6.

[0015] S6. Perform task scheduling for each task on each single track.

[0016] Preferably, the task priority analysis indicators in S1 This refers to:

[0017]

[0018]

[0019] in, For custom tasks Weight in the task set;

[0020] This is a task conflict indicator, representing the task... In the set The weights of potential conflicting tasks; The set of visible time windows for tasks sorted as e in the i-th orbital cycle;

[0021] For any task Matchable tracks, For a set of matchable tracks; Indicates the selected window Belongs to the task-visible time window set To indicate task flexibility, representing the task Total length of the visible time window for matchable orbits and mission duration The ratio;

[0022] These are the planned end and start times of the visible time window for task e, which is ranked in the i-th orbital cycle, on orbit o.

[0023] Preferably, the optimal orbital allocation tool model based on multi-orbit systems in S3 completes the optimal orbital matching, including:

[0024] S100, Task and its attributes By comparing with satellite orbital resource attributes, the mission can be obtained. Matchable track set

[0025] in, For the task The geographic information is used to record the latitude and longitude of the task request; For the task The execution time range; For the task The execution duration; for The j-th matching track;

[0026] S200, for the task Generate a random number index and set a threshold π, then perform the task. The random number index of the task is compared with the threshold π: if the random number index of the task is less than or equal to the threshold π, then a random number is generated from the set. Choose one track as Otherwise, based on the optimal matching degree index Pick corresponding As a task optimal orbit

[0027] S300, Output Task optimal orbit

[0028] Preferably, the optimal matching index in S200 This refers to:

[0029]

[0030] in, This represents the number of tasks currently awaiting scheduling on the track.

[0031] Task execution time range Number of visible time windows on feasible internal orbits;

[0032] For orbital satellite observation strips, the subsurface centerline and mission The vertical distance between them;

[0033] Task execution time range The earliest execution time of the visible time window on the feasible track.

[0034] Preferably, the single-track task scheduling strategy based on task value time dependence in S6, which schedules tasks on a single track, includes:

[0035] For any task on a single track If it does not overlap with the visible time window of existing tasks on the track, it is guaranteed to complete at the optimal completion time. Completed previously;

[0036] Otherwise, calculate the maximum profit for task completion based on time dependence. Duration of task execution and the best time to complete the task The ratio between The task scheduling order is determined by sorting the tasks according to their ratios.

[0037] Preferably, they exist on the same single track. In the same situation, introduce the observation profit of task completion. Determine the scheduling order of this part of the tasks:

[0038]

[0039] in, For the task The actual completion time; ν is the decay coefficient of the exponential time-dependent profit function, v>0 and is a constant; For the task The task is completed with the minimum profit.

[0040] A hierarchical multi-orbit multi-mission satellite scheduling system includes:

[0041] The receiving module is used to execute S1 and receive the task set T requested by the user. iAnd let the orbital operation cycle index i = 1, and analyze the task priority index of each task by calculating the task priority index. Sort the task set according to the allocation order;

[0042] The selection module is used to execute S2 and select unlabeled task priority analysis metrics. The biggest task

[0043] The first judgment module is used to execute S3 and process tasks. Determining available tracks for execution: If the task... There are one or more matching tracks to determine the task. optimal orbit In task set T i Delete task Otherwise, mark the task. No longer participating in task allocation for the current orbital operation cycle;

[0044] The second judgment module is used to execute S4 and determine whether all tasks have been traversed and executed on available tracks. If so, delete all task markers in the current task set, set i = i + 1 and proceed to S5; otherwise, proceed to S2.

[0045] The trimming module is used to perform S5, which performs task trimming. It filters out tasks that have timed out in the current task set and repeats steps S2 to S5 until all tasks are matched with tracks or all remaining unassignable tasks are trimmed, then proceeds to S6.

[0046] The scheduling module is used to execute S6 and schedule tasks on each single track.

[0047] A storage medium storing a computer program, wherein the computer program causes a computer to execute the hierarchical multi-orbit multi-task satellite scheduling method described above.

[0048] An electronic device, comprising:

[0049] One or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs including methods for performing the hierarchical multi-orbit multi-mission satellite scheduling method as described above.

[0050] (III) Beneficial Effects

[0051] This invention provides a hierarchical multi-orbit, multi-mission satellite scheduling method, system, storage medium, and electronic device. Compared with existing technologies, it has the following advantages:

[0052] This invention proposes a hierarchical multi-orbit, multi-mission satellite scheduling method to address the problem of large-scale satellite mission scheduling. Firstly, in the early stages of multi-orbit and multi-mission matching, a task priority analysis index is proposed to ensure the rationality of task allocation. Secondly, in the multi-orbit and multi-mission matching stage, a novel heuristic strategy is developed to optimize the orbit allocation of multiple missions across multiple orbits. This model can provide high-quality mission orbit allocation schemes in a relatively short time, improving the optimal accuracy of mission orbit matching results. Finally, for single-orbit mission scheduling, a single-orbit mission scheduling function based on the time dependence of mission value is proposed. This aligns with the profit variations in actual satellite mission scheduling and reflects the time dynamics of the model scheduling. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 A block diagram illustrating a hierarchical multi-orbit multi-task satellite scheduling method provided in an embodiment of the present invention;

[0055] Figure 2 This is a structural block diagram of a hierarchical multi-orbit multi-task satellite scheduling system provided in an embodiment of the present invention. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are described clearly and completely. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] This application provides a hierarchical multi-orbit multi-mission satellite scheduling method, system, storage medium, and electronic device, which solves the technical problem of being unable to balance time cost and high-performance scheduling results.

[0058] The technical solution in this application is to solve the above-mentioned technical problems, and the general idea is as follows:

[0059] This invention adopts a divide-and-conquer overall scheduling framework to decompose the large-scale EOS scheduling problem into multiple sub-problems, thereby reducing the complexity of solving the problem; and innovatively proposes a new scheduling method under the divide-and-conquer framework: a two-stage allocation scheduling is performed as the orbital period is updated. The two-stage allocation scheduling includes: task allocation between satellites in different orbits and task scheduling on individual orbits.

[0060] First, in the task allocation phase, an innovative tool model for optimal track allocation of multiple tasks across multiple tracks is proposed; in the optimal track matching process of task allocation, a task priority analysis index is defined to determine the order of task allocation, and tasks are allocated hierarchically based on track cycles; after the task allocation phase, multiple sub-problems for scheduling tasks on each track will be generated.

[0061] Second, in the single-task scheduling stage, a single-track task scheduling function based on the time dependence of task value is proposed, which is in line with the actual production mode and has practical significance.

[0062] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0063] Example:

[0064] like Figure 1 As shown, this embodiment of the invention provides a hierarchical multi-orbit multi-task satellite scheduling method, including:

[0065] S1, Task set T for receiving user requests i And let the orbital operation cycle index i = 1, and analyze the task priority index of each task by calculating the task priority index. Sort the task set according to the allocation order;

[0066] S2. Select unmarked task priority analysis metrics The biggest task

[0067] S3, Regarding the task Determining available tracks for execution: If the task... There are one or more matching tracks to determine the task. optimal orbit In task set T i Delete task Otherwise, mark the task. No longer participating in task allocation for the current orbital operation cycle;

[0068] S4. Determine if all tasks have been traversed and executed using available tracks. If yes, delete all task markers in the current task set, set i = i + 1, and go to S5; otherwise, go to S2.

[0069] S5. Perform task pruning. Filter out tasks that have timed out in the current task set. Repeat steps S2 to S5 until all tasks are matched with tracks or all remaining unassignable tasks are pruned. Proceed to S6.

[0070] S6. Perform task scheduling for each task on each single track.

[0071] This invention proposes a hierarchical multi-orbit, multi-mission satellite scheduling method for large-scale satellite mission scheduling problems. Firstly, in the early stages of multi-orbit and multi-mission matching, a task priority analysis index is proposed to ensure the rationality of task allocation. Secondly, in the multi-orbit and multi-mission matching stage, a novel heuristic strategy is developed to optimize the orbit allocation of multiple missions across multiple orbits. This model can provide high-quality mission orbit allocation schemes in a relatively short time, improving the optimal accuracy of mission orbit matching results. Finally, for single-orbit mission scheduling, a single-orbit mission scheduling function based on the time dependence of mission value is proposed. This aligns with the profit variations in actual satellite mission scheduling and reflects the time dynamics of the model scheduling.

[0072] The following will detail each step of the above solution:

[0073] In step S1, the task set T requested by the user is received. i And let the orbital operation cycle index i = 1, and analyze the task priority index of each task by calculating the task priority index. Sort the task set according to the allocation order.

[0074] When ground resources receive multiple user-requested tasks, due to limitations in observation resources and technology, it is impossible to execute multiple user-requested tasks simultaneously. Therefore, it is necessary to propose a standard to prioritize the allocation of orbits for multiple tasks. Considering that each user-requested task has user-defined value in its completion, this section includes:

[0075] Customized as That is, the task In the corresponding task set, tasks are prioritized based on their weight; tasks with higher weights are scheduled first. Furthermore, for a task, scheduling is easier if multiple feasible time windows exist. Task flexibility is defined as... In other words, tasks with lower flexibility are prioritized; at the same time, there may be conflicts in feasible time windows between different tasks, which this paper defines as a task conflict index. It indicates the task. Regarding the set of feasible time windows on the orbit set The potential conflict task weights are defined in this embodiment of the invention, and tasks with smaller conflict indices are given priority.

[0076] In summary, this step analyzes the user request task priority metrics. The definition is as follows:

[0077]

[0078]

[0079] in, For custom tasks Weight in the task set;

[0080] This is a task conflict indicator, representing the task... In the set The weights of potential conflicting tasks;

[0081] The set of visible time windows for tasks sorted as e in the i-th orbital cycle;

[0082] For any task Matchable tracks, For a set of matchable tracks;

[0083] Indicates the selected window Belongs to the task-visible time window set To indicate task flexibility, representing the task Total length of the visible time window for matchable orbits and mission duration The ratio;

[0084] These are the planned end and start times of the visible time window for task e, which is ranked in the i-th orbital cycle, on orbit o.

[0085] In step S2, select unlabeled task priority analysis indicators. The biggest task

[0086] In step S3, for the task Determining available tracks for execution: If the task... There are one or more matching tracks to determine the task. optimal orbit In task set Ti Delete task Otherwise, mark the task. No longer participating in task allocation for the current orbital operation cycle

[0087] This invention assumes that the number of visible time windows for each task on each track and the length of one track cycle are known, and that multi-task processing is performed according to custom task weights and analysis metrics. The dynamic changes are allocated across multiple tracks. Building upon the allocation strategy described earlier, this step also introduces an optimal track allocation tool model based on multiple tracks to complete optimal track matching, including:

[0088] S100, Task and its attributes By comparing with satellite orbital resource attributes, the mission can be obtained. Matchable track set

[0089] in, For the task The geographic information is used to record the latitude and longitude of the task request; For the task The execution time range; For the task The execution duration; for The j-th matching track;

[0090] S200, for the task Generate a random number index and set a threshold π, then perform the task. The random number index of the task is compared with the threshold π: if the random number index of the task is less than or equal to the threshold π, then a random number is generated from the set. Choose one track as Otherwise, based on the optimal matching degree index Pick corresponding As a task optimal orbit

[0091] S300, Output Task optimal orbit

[0092] In particular, in order to maximize the utilization of satellite orbit observation resources, this embodiment of the invention introduces the number of currently scheduled tasks in the orbit. Priority The largest; while also considering the clarity and deformation error of the mission observations, the mission to be observed is regarded as having geographic information on the Earth's surface. The point introduces the vertical distance between the sub-center line of the orbital satellite observation strip and the target point to be observed. Prioritize the orbit corresponding to the nearest observation strip to the task point to be observed; take into account the task execution time range required by the user. To ensure sufficient scheduling execution time for tasks in later single-track scheduling, a user-required task execution time range is introduced. Number of visible time windows on feasible inner orbits and the earliest execution time of the visible time window Prioritize the option with the largest number of visible time windows and the earliest execution time of the visible time windows. The earliest orbit.

[0093] In summary, the optimal matching index in S200 This refers to:

[0094]

[0095] in, This represents the number of tasks currently awaiting scheduling on the track.

[0096] Task execution time range Number of visible time windows on feasible internal orbits; For orbital satellite observation strips, the subsurface centerline and mission The vertical distance between them;

[0097] Task execution time range The earliest execution time of the visible time window on the feasible track.

[0098] In step S4, determine whether all tasks have been traversed and executed on available tracks. If so, delete all task markers in the current task set, set i = i + 1, and proceed to S5; otherwise, proceed to S2.

[0099] In step S5, task pruning is performed. Tasks that have timed out are filtered out in the current task set. Steps S2 to S5 are repeated until all tasks are matched with tracks or the remaining unassignable tasks are pruned, and then proceed to S6.

[0100] In the task allocation phase, this embodiment of the invention uses an optimal track allocation tool model for multiple tasks on multiple tracks, as well as a task priority analysis index proposed in the optimal track matching process of task allocation. After the above-mentioned iteration termination condition is met, the task allocation based on track cycle hierarchical allocation is finally completed. After the task allocation phase, multiple sub-problems for scheduling tasks on each track are generated and transferred to the task scheduling phase in S6.

[0101] In step S6, task scheduling is performed on each task on each single track.

[0102] This step, based on a single-track task scheduling strategy that considers the time dependence of task value, schedules tasks on a single track, specifically including:

[0103] For any task on a single track If it does not overlap with the visible time window of existing tasks on the track, it is guaranteed to complete at the optimal completion time. Completed previously;

[0104] Otherwise, calculate the maximum profit for task completion based on time dependence. Duration of task execution and the best time to complete the task The ratio between The task scheduling order is determined by sorting the tasks according to their ratios.

[0105] Specifically, they exist on the same single orbit. In the same situation, introduce the observation profit of task completion. Determine the scheduling order of this part of the tasks (compare the total task completion observation profit under different orders, and select the scheduling order with the larger total profit to execute):

[0106]

[0107] in, For the task The actual completion time; ν is the decay coefficient of the exponential time-dependent profit function, ν>0 and is a constant; For the task The task is completed with the minimum profit.

[0108] In the single-task scheduling stage, the embodiments of the present invention complete the task scheduling on each single track through a single-track task scheduling function based on the time dependence of task value, which is in line with the actual production mode and has practical significance.

[0109] like Figure 2 As shown, this embodiment of the invention provides a hierarchical multi-orbit multi-task satellite scheduling system, including:

[0110] The receiving module is used to execute S1 and receive the task set T requested by the user. i And let the orbital operation cycle index i = 1, and analyze the task priority index of each task by calculating the task priority index. Sort the task set according to the allocation order;

[0111] The selection module is used to execute S2 and select unlabeled task priority analysis metrics. The biggest task

[0112] The first judgment module is used to execute S3 and process tasks. Determining available tracks for execution: If the task... There are one or more matching tracks to determine the task. optimal orbit In task set T i Delete task Otherwise, mark the task. No longer participating in task allocation for the current orbital operation cycle;

[0113] The second judgment module is used to execute S4 and determine whether all tasks have been traversed and executed on available tracks. If so, delete all task markers in the current task set, set i = i + 1 and proceed to S5; otherwise, proceed to S2.

[0114] The trimming module is used to perform S5, which performs task trimming. It filters out tasks that have timed out in the current task set and repeats steps S2 to S5 until all tasks are matched with tracks or all remaining unassignable tasks are trimmed, then proceeds to S6.

[0115] The scheduling module is used to execute S6 and schedule tasks on each single track.

[0116] This invention provides a storage medium storing a computer program, wherein the computer program causes a computer to execute the hierarchical multi-orbit multi-task satellite scheduling method described above.

[0117] This invention provides an electronic device, comprising:

[0118] One or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs including methods for performing the hierarchical multi-orbit multi-mission satellite scheduling method as described above.

[0119] It is understood that the hierarchical multi-orbit multi-mission satellite scheduling system, storage medium and electronic device provided in the embodiments of the present invention correspond to the hierarchical multi-orbit multi-mission satellite scheduling method provided in the embodiments of the present invention. The explanation, examples and beneficial effects of the relevant contents can be referred to the corresponding parts of the hierarchical multi-orbit multi-mission satellite scheduling method, and will not be repeated here.

[0120] In summary, compared with existing technologies, it has the following beneficial effects:

[0121] 1. This invention proposes a hierarchical multi-orbit, multi-mission satellite scheduling method for large-scale satellite mission scheduling problems. Firstly, in the early stages of multi-orbit and multi-mission matching, a task priority analysis index is proposed to ensure the rationality of task allocation. Secondly, in the multi-orbit and multi-mission matching stage, a novel heuristic strategy is developed to optimize the orbit allocation of multiple missions across multiple orbits. This model can provide high-quality mission orbit allocation schemes in a relatively short time, improving the optimal accuracy of mission orbit matching results. Finally, for single-orbit mission scheduling, a single-orbit mission scheduling function based on the time dependence of mission value is proposed. This aligns with the profit changes in actual satellite mission scheduling and reflects the time dynamics of the model scheduling.

[0122] 2. In the task allocation phase, this embodiment of the invention uses an optimal track allocation tool model for multiple tasks on multiple tracks, as well as a task priority analysis index proposed in the optimal track matching process of task allocation. After the above-mentioned iteration termination condition is met, the task allocation based on track cycle hierarchical allocation is finally completed. After the task allocation phase, multiple sub-problems for scheduling tasks on each track are generated and the process moves to the task scheduling phase.

[0123] 3. In the single-task scheduling stage, the embodiments of the present invention complete the task scheduling on each single track through a single-track task scheduling function based on the time dependence of task value, which is in line with the actual production mode and has practical significance.

[0124] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0125] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A hierarchical multi-orbit multi-task satellite scheduling method, characterized in that, include: S1, Task set for receiving user requests And set the orbital cycle index. Analysis indicators are obtained by calculating the task priority of each task. Sort the task set according to the allocation order; S2. Select unmarked task priority analysis metrics The biggest task ; S3, Regarding the task Determining available tracks for execution: If the task... There are one or more matching tracks to determine the task. optimal orbit and in the task set Delete task Otherwise, mark the task. No longer participating in task allocation for the current orbital operation cycle; S4. Determine if all tasks have been traversed and executed using available tracks. If so, delete all task markers in the current task set. Then proceed to S5; otherwise proceed to S2. S5. Perform task pruning. Filter out tasks that have timed out in the current task set. Repeat steps S2 to S5 until all tasks are matched with tracks or all remaining unassignable tasks are pruned. Proceed to S6. S6. Perform task scheduling for each task on each single track; The task priority analysis indicators in S1 , refers to: = = in, For custom tasks Weight in the task set; This is a task conflict indicator, representing the task... In the set The weights of potential conflicting tasks; In the first The order in each orbital operation cycle is as follows: The set of time windows in which tasks are visible; For any task Matchable tracks, For a set of matchable tracks; Indicates the selected window Belongs to the task-visible time window set ; To indicate task flexibility, representing the task Total length of the visible time window for matchable orbits and mission duration The ratio; The first The planned end and start times of the time window for task e, which is ranked in a specific orbital cycle, are visible on orbit o. The optimal orbit allocation tool model based on multiple orbits in S3 completes the optimal orbit matching, including: S100, Task and its attributes By comparing with satellite orbital resource attributes, the mission can be obtained. Matchable track set ; in, For the task The geographic information is used to record the latitude and longitude of the task request; For the task The execution time range; For the task The execution duration; for The One matchable track; S200, for the task Generate random number index and set threshold Then the task Random number index and threshold Comparison: If the task's random number index threshold At that time, it will be random in the set. Choose one track as Otherwise, based on the optimal matching degree index ,Pick corresponding As a task optimal orbit ; S300, Output Task optimal orbit .

2. The hierarchical multi-orbit multi-mission satellite scheduling method as described in claim 1, characterized in that, The optimal matching index in S200 , refers to: in, This represents the number of tasks currently awaiting scheduling on the track. Task execution time range Number of visible time windows on feasible internal orbits; For orbital satellite observation strips, the subsurface centerline and mission The vertical distance between them; Task execution time range The earliest execution time of the visible time window on the feasible track.

3. The hierarchical multi-orbit multi-mission satellite scheduling method as described in claim 1, characterized in that, The single-track task scheduling strategy based on task value time dependence in S6 schedules tasks on a single track, including: For any task on a single track If it does not overlap with the visible time window of an existing task on the track, it will ensure completion at the optimal time node. Completed previously; Otherwise, calculate the maximum profit for task completion based on time dependence. Duration of task execution and the best time to complete the task The ratio between The task scheduling order is determined by sorting the tasks according to their ratio values.

4. The hierarchical multi-orbit multi-mission satellite scheduling method as described in claim 3, characterized in that, Existing on the same single orbit In the same situation, introduce the observation profit of task completion. Determine the scheduling order of this part of the tasks: in, For the task The actual completion timeline; The decay coefficient is the coefficient of the exponential time-dependent profit function. >0 and is a constant; For the task The task is completed with the minimum profit.

5. A hierarchical multi-orbit multi-mission satellite scheduling system, characterized in that, include: The receiving module is used to execute S1 and receive user request task sets. And set the orbital cycle index. Analysis indicators are obtained by calculating the task priority of each task. Sort the task set according to the allocation order; The selection module is used to execute S2 and select unlabeled task priority analysis metrics. The biggest task ; The first judgment module is used to execute S3 and process tasks. Determining available tracks for execution: If the task... There are one or more matching tracks to determine the task. optimal orbit and in the task set Delete task Otherwise, mark the task. No longer participating in task allocation for the current orbital operation cycle; The second judgment module is used to execute S4, determine whether all tasks have been traversed and executed on available tracks, and if so, delete all task markers in the current task set. Then proceed to S5; otherwise proceed to S2. The trimming module is used to perform S5, which performs task trimming. It filters out tasks that have timed out in the current task set and repeats steps S2 to S5 until all tasks are matched with tracks or all remaining unassignable tasks are trimmed, then proceeds to S6. The scheduling module is used to execute S6 and schedule tasks for each single track. The task priority analysis indicators in S1 , refers to: = = in, For custom tasks Weight in the task set; This is a task conflict indicator, representing the task... In the set The weights of potential conflicting tasks; In the first The order in each orbital operation cycle is as follows: The set of time windows in which tasks are visible; For any task Matchable tracks, For a set of matchable tracks; Indicates the selected window Belongs to the task-visible time window set ; To indicate task flexibility, representing the task Total length of the visible time window for matchable orbits and mission duration The ratio; The first The planned end and start times of the time window for task e, which is ranked in a specific orbital cycle, are visible on orbit o. The optimal orbit allocation tool model based on multiple orbits in S3 completes the optimal orbit matching, including: S100, Task and its attributes By comparing with satellite orbital resource attributes, the mission can be obtained. Matchable track set ; in, For the task The geographic information is used to record the latitude and longitude of the task request; For the task The execution time range; For the task The execution duration; for The One matchable track; S200, for the task Generate random number index and set threshold Then the task Random number index and threshold Comparison: If the task's random number index threshold At that time, it will be random in the set. Choose one track as Otherwise, based on the optimal matching degree index ,Pick corresponding As a task optimal orbit ; S300, Output Task optimal orbit .

6. A storage medium, characterized in that, It stores a computer program, wherein the computer program causes the computer to execute the hierarchical multi-orbit multi-task satellite scheduling method as described in any one of claims 1 to 4.

7. An electronic device, characterized in that, include: One or more processors; Memory; And one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs including methods for performing the hierarchical multi-orbit multi-mission satellite scheduling method as described in any one of claims 1 to 4.

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