A method and system for autonomous mission planning of remote sensing satellites

Abstract

This invention discloses a method and system for autonomous mission planning of remote sensing satellites. The invention constructs models such as an orbit prediction model, an attitude maneuver model, and a payload model. During the planning process, these models are used for mission sequencing, constraint checking, and generating meta-tasks. The ground only needs to annotate point / line / area related information, payload-related parameters, and necessary mission requirement parameters such as the mission imaging range. The onboard autonomous mission planning system performs path planning, mission decomposition, mission sequencing, constraint checking, and autonomous command generation, generating a sequence of commands related to the mission execution and distributing them to relevant subsystems. The payload, data transmission, control, and satellite operations subsystems then collaborate to complete the mission. After receiving the mission information annotated by the ground, the autonomous mission planning system promptly feeds back the onboard pre-planning information to the ground for use in synchronizing mission status.

Description

Technical Field

[0001] This invention relates to the technical field of autonomous satellite mission planning, and in particular to a method and system for autonomous mission planning of remote sensing satellites. Background Technology

[0002] With technological advancements such as on-board real-time processing and inter-satellite link technologies, remote sensing satellites are exhibiting "intelligent and networked" mission characteristics. The number of remote sensing satellites and their application scope are also continuously expanding, increasing the difficulty for ground control systems to operate them. The traditional "ground planning + on-board execution" approach can no longer meet current mission requirements. The need for ground-based mission requirements to be proposed and on-board mission planning to be conducted is becoming increasingly urgent. On the one hand, this reduces the operational burden on the ground, allowing users to focus only on mission requirements and satellite capabilities without much concern for satellite constraints. On the other hand, on-board systems can also dynamically and precisely plan missions based on real-time satellite resources, improving satellite utilization efficiency.

[0003] Existing on-board mission planning technologies have some shortcomings. They focus more on research into algorithms such as path planning and regional target decomposition, but lack the construction and invocation of on-board model layers during mission planning to achieve constraint checks and complete refined planning based on the real-time status of the on-board mission. At the same time, there is a lack of a mechanism to synchronize planning results with the ground, resulting in a lack of synchronization between the spacecraft and the ground, and the ground cannot keep abreast of the on-board mission status in real time. Summary of the Invention

[0004] This invention provides a method and system for autonomous mission planning of remote sensing satellites. The ground only needs to upload point / line / area related information, payload-related parameters, and necessary mission requirement parameters such as the mission imaging range. The onboard autonomous mission planning system performs path planning, mission decomposition, mission sequencing, constraint checking, and autonomous command generation, generating a sequence of commands related to the mission and distributing them to relevant subsystems. The payload, data transmission, control, and satellite maintenance subsystems then work together to complete the mission. After receiving the mission information uploaded from the ground, the autonomous mission planning system promptly feeds back the onboard pre-planning information to the ground for use in synchronizing mission status.

[0005] Firstly, a method for autonomous mission planning of remote sensing satellites is provided, including:

[0006] Receive mission information sent from the ground and perform mission information legality checks;

[0007] Based on the task information, the objectives are decomposed into multiple cyclical tasks of point objectives / strip objectives;

[0008] The point targets / strip targets decomposed from the target are calculated based on trajectory prediction and attitude capability to determine the attitude path for target switching within the mission and the attitude switching path between missions.

[0009] Tasks are sorted according to the task observation time window, task execution interval, and task priority;

[0010] After inserting the betting task into the task pool, perform constraint checks on the tasks in the task pool.

[0011] Based on the results of path planning, task sequencing, and constraint checking, meta-task information is generated and then transmitted to the ground as a pre-planning result.

[0012] Determine if the planned start time has been reached: if so, adjust the relevant parameters in the meta-task; if not, continue waiting.

[0013] Recalculate and plan the path for task execution based on the current attitude information of the task.

[0014] Based on the pre-stored subsystem timings, inter-subsystem constraints, and task information in the meta-task, a delay sequence is autonomously generated, including the task start execution time, the instructions of the relevant subsystems, and the relative intervals between instructions.

[0015] Based on the time in the delay sequence and the relative time between instructions, the data is distributed to the relevant subsystems when the time comes, and the load, data transmission, and control work together to complete the load task.

[0016] In conjunction with the first aspect, in some implementations of the first aspect, the task information received from the ground includes target type, target location information, payload attributes, task imaging range, and priority; the task information validity check is to check the task information encapsulation format, data validity, and data content, including the validity of the enumeration type, the valid range of values, the correlation of parameters, and the position and valid length of parameters. If the task information is valid, proceed to the next step; if it is invalid, discard the task and remain in the waiting task reception mode.

[0017] In conjunction with the first aspect, in some implementations of the first aspect, the decomposition of the target based on task information includes:

[0018] If the task information indicates a point target, then based on the number of target points and the number of cycles in the task information, the target is decomposed into a combination of multiple point targets, and then further decomposed into a single target multiple-cycle task or a multi-target round-robin multiple-cycle task.

[0019] If the mission information indicates a line target or an area target, then, in combination with the constraints of camera swath width, flight direction, and stitching requirements, the region is decomposed into multiple point targets / strip combinations according to at least one of the following algorithms: global grid-based region segmentation algorithm, Gaussian projection-based strip segmentation algorithm, and fixed-width strip segmentation algorithm. Then, based on the attitude maneuvering mode and the number of cycles, it is decomposed into a small-angle step-by-step stitching multiple-cycle task or a strip push-broom stitching multiple-cycle task.

[0020] In conjunction with the first aspect, in some implementations of the first aspect, the inter-task attitude switching path satisfies:

[0021] The attitude path during the mission preparation phase is estimated based on the maximum maneuver range; during the formal planning phase, the path during the mission preparation phase is estimated in conjunction with the current attitude state, thereby determining the attitude switching path between missions.

[0022] In conjunction with the first aspect, in some implementations of the first aspect, the sorting of tasks includes:

[0023] The mission preparation time and recovery time are calculated using the pre-stored payload model on the satellite to determine the entire execution range of the mission.

[0024] Tasks are sorted according to the task observation time window, task execution interval, and task priority;

[0025] The task observation time window is dynamically moved according to the task order to ensure that the time intervals of the two tasks do not conflict.

[0026] In conjunction with the first aspect, in certain implementations of the first aspect, the constraint check includes:

[0027] Based on the onboard pre-stored energy balance model and payload model, the tasks in the task pool are constrained and checked, including whether the energy reserve requirements are met and whether the switching time between targets meets the requirements.

[0028] If the check passes, proceed to the next step; otherwise, delete the task that does not meet the constraints, send an event report to the ground, including the task number and the abnormal event number, and return to and remain in the waiting task receiving mode.

[0029] In conjunction with the first aspect, in certain implementations of the first aspect, the generation of meta-task information includes:

[0030] Based on the results calculated by the load data balancing model, load model, and attitude maneuver model, as well as the results after task sorting, meta-task information is generated, including the task start time, attitude maneuver parameters, and load parameters.

[0031] In conjunction with the first aspect, in some implementations of the first aspect, the autonomous generation of the delay sequence includes:

[0032] Based on the pre-stored payload topology model on the satellite, including the timing of subsystems and the constraints between subsystems, and combined with the mission start imaging / playback time, attitude parameters, payload parameters, and playback duration in the meta-mission information, command generation and parameter replacement operations are performed to autonomously generate a delay sequence containing the execution actions of relevant subsystems.

[0033] Secondly, a remote sensing satellite autonomous mission planning system is provided. This system is connected to a ground system, receives mission information uploaded by the ground system, and synchronously transmits pre-planning information to the ground system for satellite-ground situational synchronization. The mission planning system generates relevant instructions for subsystems and distributes them to other subsystems, scheduling them to complete the entire mission. The remote sensing satellite autonomous mission planning system includes:

[0034] The mission legitimacy check module is used to receive mission information sent from the ground and check the legitimacy of the mission information;

[0035] The task decomposition module is used to decompose the target based on the task information, forming multiple cyclical tasks of point targets / strip targets;

[0036] The attitude planning module is used to calculate the attitude paths for target switching within a mission and attitude switching between missions based on trajectory prediction and attitude capabilities after the target is decomposed into point targets / strip targets.

[0037] The task sorting module is used to sort tasks according to the task observation time window, task execution interval, and task priority; it is also used to perform constraint checks on the tasks in the task pool after the above-mentioned task is inserted into the task pool.

[0038] The meta-task generation module is used to generate meta-task information based on the results of path planning, task sorting, and constraint checking, and then transmit the generated meta-task information as a pre-planning result to the ground.

[0039] The autonomous instruction generation module is used to autonomously generate a delay sequence based on the pre-stored subsystem timing, inter-subsystem constraints, and task information in the meta-task. This sequence includes the task start execution time, instructions from relevant subsystems, and the relative intervals between instructions. The payload, data transmission, and control systems then coordinate to complete the payload task based on the delay sequence.

[0040] In conjunction with the second aspect, in some implementations of the second aspect, the system further includes a model layer; wherein the model layer includes an energy balance model, a data balance model, a load model, an attitude maneuver model, a trajectory prediction model, and a load topology model; the system satisfies at least one of the following:

[0041] The mission validity check module receives mission information sent from the ground, including target type, target location information, payload attributes, mission imaging range, and priority. The mission information validity check examines the mission information encapsulation format, data validity, and data content, including the validity of enumeration types, the valid range of values, parameter correlation, parameter location, and valid length.

[0042] The system also includes a task preprocessing module, which is used to reorder multiple targets of line targets or area targets in the task information to form ordered lines or closed intervals.

[0043] The task decomposition module receives task information for point targets or sorted task information for line targets or area targets and decomposes the targets based on the model layer. If the task information indicates a point target, the target is decomposed into multiple point target combinations according to the number of target points and the number of iterations in the task information, and then decomposed into single-target multiple-loop tasks or multi-target round-robin multiple-loop tasks. If the task information indicates a line target or area target, the region is decomposed into multiple point target / strip combinations according to at least one of the following algorithms: global grid-based region segmentation algorithm, Gaussian projection-based strip segmentation algorithm, and fixed-width strip segmentation algorithm, combined with constraints such as camera swath width, flight direction, and stitching requirements. Then, according to the attitude maneuvering mode and the number of iterations, it is decomposed into small-angle step stitching multiple-loop tasks or strip push-broom stitching multiple-loop tasks.

[0044] The attitude planning module is used to combine the target position and orbit prediction results with the attitude maneuver model pre-stored on the satellite in the model layer to determine the attitude path for target switching within the mission and the attitude switching path between missions. The attitude path planned in the mission preparation phase is predicted according to the maximum maneuver range. In the formal planning phase, the path in the mission preparation phase is predicted in combination with the current attitude state, thereby determining the attitude switching path between missions.

[0045] The task sequencing module receives the results of attitude planning, calculates the task preparation time and recovery time using the payload model pre-stored on the satellite at the model layer, and determines the entire execution interval of the task. It then sorts the tasks according to the task observation time window, the task execution interval, and the task priority. Based on the task sequencing, the module dynamically moves within the task observation time window to ensure that two task time intervals do not conflict. Finally, it performs constraint checks on the tasks in the task pool based on the pre-stored energy balance model and payload model on the satellite, including whether energy margin requirements are met and whether the target switching time meets the requirements.

[0046] The meta-task generation module is used to receive tasks that have passed the constraint check, generate meta-task information based on the results calculated by the load data balance model, load model, attitude maneuver model of the calling model layer, and the results after task sorting, including the task start execution time, attitude maneuver parameters, load parameters, etc., and transmit the generated meta-task information to the ground as a pre-planning result.

[0047] The autonomous command generation module is used to generate commands and replace parameters based on the payload topology model pre-stored in the on-board model layer, including the subsystem timing and the constraints between subsystems, combined with the mission imaging / playback time, attitude parameters, payload parameters and playback duration in the meta-mission information, and autonomously generate a delay sequence containing the execution actions of the relevant subsystems.

[0048] Compared with the prior art, the solution provided by the present invention has at least the following beneficial technical effects:

[0049] This invention constructs models such as orbit prediction model, attitude maneuver model, and payload model. During the planning process, these models are called for task sequencing, constraint checking, and generation of meta-tasks. At the same time, the task planning is divided into two stages: pre-planning and formal planning. The pre-planning results are promptly transmitted to the ground for satellite-ground synchronization. When the formal planning time arrives, the generated meta-task time parameters and other information are dynamically adjusted based on the real-time status of the satellite, further refining the planning and improving the satellite's utilization efficiency. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of a remote sensing satellite autonomous mission planning method.

[0051] Figure 2 This is a schematic diagram of the components of an autonomous mission planning system for remote sensing satellites. Detailed Implementation

[0052] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0053] like Figure 1 As shown, this invention provides a method for autonomous mission planning of remote sensing satellites, and the specific implementation steps are as follows.

[0054] (1) Receive mission information sent from the ground and check the legality of the mission information.

[0055] The task information sent from the ground is received through the task validity check module, and the validity of the task information is checked. The task information sent from the ground mainly includes the target type, target location information, payload attributes, task imaging range, priority and other necessary task requirements. The task information validity check checks the encapsulation format, data validity and data content of the task information. It mainly includes the validity of the enumeration type, the valid range of the values, the correlation of parameters, the position and valid length of parameters, etc. If the task information is valid, it proceeds to step (2). If it is invalid, the task is discarded and it continues to wait for task reception mode.

[0056] (2) Decompose the target based on the task information to form multiple cyclical tasks of point targets / strip targets.

[0057] If the task information indicates a point target, the task information is sent to the task decomposition module. If the task information indicates a line target or an area target, the task information is sent to the task preprocessing module, where multiple targets in the task information are reordered to form ordered lines or closed intervals.

[0058] The task decomposition module receives task information for point targets or sorted task information for line targets or area targets and performs target decomposition. For point targets, based on the number of target points and the number of iterations in the task information, the target is decomposed into multiple point target combinations, and further decomposed into single-target multiple-loop tasks or multi-target round-robin multiple-loop tasks. For line or area targets, considering constraints such as camera swath width, flight direction, and point target / strip stitching requirements, the region is decomposed into multiple point target / strip combinations using methods such as global grid-based region segmentation algorithms, Gaussian projection-based strip segmentation algorithms, and fixed-width strip segmentation algorithms. Then, based on the attitude maneuvering mode and the number of iterations, it is decomposed into small-angle step-by-step stitching multiple-loop tasks (e.g., for line targets) or strip push-broom stitching multiple-loop tasks (e.g., for area targets).

[0059] (3) Attitude path planning: The point targets / strip targets after target decomposition are calculated based on trajectory prediction and attitude capability to determine the attitude path for target switching within the mission and the attitude switching path between missions.

[0060] The results of target decomposition are used by the attitude planning module, combined with target position and orbit prediction results, and pre-stored attitude maneuver models on the satellite, to determine the attitude paths for target switching within the mission and attitude switching paths between missions. Considering that the attitude state before mission execution cannot be predicted during pre-planning, the attitude paths in the mission preparation phase are predicted based on the maximum maneuver range; in the formal planning phase, the paths in the mission preparation phase are accurately predicted based on the current attitude state, thereby determining the attitude switching paths between missions.

[0061] (4) Task Sequencing: The preparation time and recovery time of the task are calculated using the pre-stored payload model on the satellite to determine the entire execution interval of the task. The tasks are sorted according to the task observation time window, the task execution interval, and the task priority. The higher the priority and the earlier the task execution time, the higher the task is sorted in the task pool. At the same time, the task execution interval can be dynamically moved within the task observation time window according to the task sorting to ensure that the time intervals of the two tasks do not conflict.

[0062] The task sorting module receives the attitude planning results and, combined with the pre-stored payload model and real-time onboard status, performs time calculations on the point / strip targets after task decomposition. It then sorts the tasks based on the task imaging range, priority definition, and onboard task pool information. During time calculation, the playback and broadcast distribution durations are calculated according to the data balancing model and imaging duration.

[0063] (5) Constraint check: After inserting the above task into the task pool, a constraint check is performed on the tasks in the task pool.

[0064] After inserting the assigned task into the task pool, the task sorting module needs to perform constraint checks on the tasks in the task pool based on the pre-stored energy balance model and payload model on the satellite, including whether the energy reserve requirement is met and whether the switching time between targets meets the requirements. If the check is passed, proceed to step (6); otherwise, delete the task that does not meet the constraint conditions and send an event report to the ground, including the task number, abnormal event number and other necessary information, and return to step (1) to remain in the waiting task receiving mode.

[0065] (6) Generate meta-task information: Generate meta-task information based on operations such as path planning, task sorting, and constraint checking.

[0066] Tasks that pass the constraint check enter the meta-task generation module. Based on the results calculated by calling the load data balance model, load model, attitude maneuver model, and the results after task sorting, meta-task information is generated, including the task start time, attitude maneuver parameters, load parameters, etc. The generated meta-task information is then transmitted to the ground as a pre-planning result.

[0067] (7) Determine if the formal planning start time has been reached: If it has, adjust the relevant parameters in the meta-task; if it has not, continue to wait.

[0068] The formal planning and launch time can be determined based on the satellite's orbital characteristics and the mission preparation time.

[0069] (8) Adjust relevant parameters in the meta-task: Calculate parameters such as duration in the meta-task information based on the current satellite status.

[0070] Generally, it is necessary to adjust attitude-related parameters and recalculate and plan the path for task execution based on the current attitude information of the task.

[0071] (9) Autonomous command generation: Based on the pre-stored subsystem timing and inter-system constraints, as well as the task information in the meta-task, autonomously generate a delay sequence, including the task start execution time, the instructions of the relevant subsystems, and the relative interval between instructions.

[0072] The generated meta-task information is sent to the autonomous command generation module when it is ready to be deployed (the deployment time can generally be set to 5 seconds before the mission start time). The autonomous command generation module performs operations such as command generation and parameter replacement based on the pre-stored payload topology model on the satellite, including the subsystem timing and the constraints between subsystems, combined with the necessary time in the meta-task information such as the mission water imaging / playback time, attitude parameters, payload parameters, and playback duration. It autonomously generates a delay sequence containing the execution actions of the relevant subsystems.

[0073] (10) Distribute to relevant subsystems: The task planning system distributes the task to the relevant subsystems according to the time in the delay sequence and the relative time between instructions. The load, data transmission, control and other systems work together to complete the load task.

[0074] This invention constructs an autonomous mission planning system for remote sensing satellites based on the autonomous mission planning method for remote sensing satellites. The mission planning system is connected to the ground system, receives mission information uploaded by the ground system, and synchronously transmits pre-planning information to the ground system for satellite-ground situational awareness synchronization. The mission planning system generates relevant instructions for subsystems and distributes them to other subsystems, scheduling them to complete the entire mission.

[0075] The mission planning system includes a mission validity check module, a mission preprocessing module, a mission decomposition module, an attitude planning module, a mission sequencing module, a meta-task generation module, an autonomous command generation module, and a model layer. The model layer includes an energy balance model, a data balance model, a payload model, an attitude maneuvering model, a trajectory prediction model, and a payload topology model.

[0076] The mission validity check module receives mission information transmitted from the ground and performs validity checks on this information. The mission information received from the ground mainly includes essential mission requirements such as target type, target location information, payload attributes, mission imaging range, and priority. The mission information validity check examines the mission information encapsulation format, data validity, and data content. This primarily includes checking the validity of enumerated types, the valid range of values, parameter correlation, parameter location, and valid length.

[0077] The task preprocessing module is used to reorder multiple targets of line or area targets in the task information to form ordered lines or closed intervals.

[0078] The task decomposition module receives task information for point targets or sorted task information for line or area targets and decomposes the targets based on the model layer. For point targets, it decomposes them into single-target multi-loop tasks or multi-target round-robin multi-loop tasks based on the number of target points and the number of loops in the task information. For line or area targets, it decomposes them into small-angle step-by-step multi-loop tasks (e.g., for line targets) or strip push-broom multi-loop tasks (e.g., for area targets) based on the attitude maneuver mode and the number of loops. The task sorting module also performs constraint checks on the tasks in the task pool after inserting the assigned tasks into the task pool, based on the pre-stored onboard energy balance model and payload model, including whether energy margin requirements are met and whether the target switching time meets requirements.

[0079] The attitude planning module combines target position and orbit prediction results with the attitude maneuver model pre-stored onboard at the model layer to determine the attitude path for target switching within a mission, as well as the attitude switching path between missions. Considering that the attitude state before mission execution cannot be predicted during pre-planning, the attitude path during the mission preparation phase is predicted based on the maximum maneuver range. During the formal planning phase, the path from the mission preparation phase is accurately predicted based on the current attitude state, thereby determining the attitude switching path between missions.

[0080] The task sorting module receives the results of attitude planning and calculates the task preparation and recovery times using the payload models pre-stored on the satellite at the model layer. This determines the entire execution interval of the task. Tasks are then sorted based on the task observation time window, the task execution interval, and the task priority. Higher priority tasks, executed earlier, are ranked higher in the task pool. The task execution interval can dynamically shift within the task observation time window based on the task sorting, ensuring that two task time intervals do not conflict.

[0081] The meta-task generation module receives tasks that have passed the constraint check, generates meta-task information based on the results calculated by the load data balance model, load model, and attitude maneuver model of the calling model layer, as well as the results after task sorting. This meta-task information includes the task start time, attitude maneuver parameters, load parameters, etc., and is then transmitted to the ground as a pre-planning result.

[0082] The autonomous command generation module is used to generate commands and replace parameters based on the payload topology model pre-stored in the on-board model layer, including the timing of subsystems and the constraints between subsystems, combined with the necessary time in the meta-mission information such as the mission water imaging / playback time, attitude parameters, payload parameters, and playback duration. It autonomously generates a delay sequence, including the mission start execution time, commands of relevant subsystems, and the relative intervals between commands.

[0083] Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope defined in the claims of the present invention.

Claims

1. A method for autonomous mission planning of remote sensing satellites, characterized in that, include: Receive mission information sent from the ground and perform mission information legality checks; Based on the task information, the objectives are decomposed into multiple cyclical tasks of point objectives / strip objectives; The point targets / strip targets decomposed from the target are calculated based on trajectory prediction and attitude capability to determine the attitude path for target switching within the mission and the attitude switching path between missions. Tasks are sorted according to the task observation time window, task execution interval, and task priority; After inserting the betting task into the task pool, perform constraint checks on the tasks in the task pool. Based on the results of path planning, task sequencing, and constraint checking, meta-task information is generated and then transmitted to the ground as a pre-planning result. Determine if the planned start time has been reached: If so, adjust the relevant parameters in the meta-task; If it is not time, then continue to wait; Recalculate and plan the path for task execution based on the current attitude information of the task. Based on the pre-stored subsystem timings, inter-subsystem constraints, and task information in the meta-task, a delay sequence is autonomously generated, including the task start execution time, the instructions of the relevant subsystems, and the relative intervals between instructions. Based on the time in the delay sequence and the relative time between instructions, the data is distributed to the relevant subsystems when the time comes, and the load, data transmission, and control work together to complete the load task.

2. The method according to claim 1, characterized in that, The task information received from the ground includes target type, target location information, payload attributes, task imaging range, and priority. The task information validity check examines the task information encapsulation format, data validity, and data content, including the validity of enumeration types, the valid range of values, parameter correlation, parameter position, and valid length. If the task information is valid, the process proceeds to the next step; if it is invalid, the task is discarded, and the system remains in the waiting mode for task reception.

3. The method according to claim 1, characterized in that, The step of decomposing the target based on task information includes: If the task information indicates a point target, then based on the number of target points and the number of cycles in the task information, the target is decomposed into a combination of multiple point targets, and then further decomposed into a single target multiple-cycle task or a multi-target round-robin multiple-cycle task. If the mission information indicates a line target or an area target, then, in combination with the constraints of camera swath width, flight direction, and stitching requirements, the region is decomposed into multiple point targets / strip combinations according to at least one of the following algorithms: global grid-based region segmentation algorithm, Gaussian projection-based strip segmentation algorithm, and fixed-width strip segmentation algorithm. Then, based on the attitude maneuvering mode and the number of cycles, it is decomposed into a small-angle step-by-step stitching multiple-cycle task or a strip push-broom stitching multiple-cycle task.

4. The method according to claim 1, characterized in that, The inter-task attitude switching path satisfies: The attitude path during the mission preparation phase is estimated based on the maximum maneuver range; during the formal planning phase, the path during the mission preparation phase is estimated in conjunction with the current attitude state, thereby determining the attitude switching path between missions.

5. The method according to claim 1, characterized in that, The sorting of tasks includes: The mission preparation time and recovery time are calculated using the pre-stored payload model on the satellite to determine the entire execution range of the mission. Tasks are sorted according to the task observation time window, task execution interval, and task priority; The task observation time window is dynamically moved according to the task order to ensure that the time intervals of the two tasks do not conflict.

6. The method according to claim 1, characterized in that, The constraint check includes: Based on the onboard pre-stored energy balance model and payload model, the tasks in the task pool are constrained and checked, including whether the energy reserve requirements are met and whether the switching time between targets meets the requirements. If the check passes, proceed to the next step; otherwise, delete the task that does not meet the constraints, send an event report to the ground, including the task number and the abnormal event number, and return to and remain in the waiting task receiving mode.

7. The method according to claim 1, characterized in that, The generated meta-task information includes: Based on the results calculated by the load data balancing model, load model, and attitude maneuver model, as well as the results after task sorting, meta-task information is generated, including the task start time, attitude maneuver parameters, and load parameters.

8. The method according to claim 1, characterized in that, The autonomously generated delay sequence includes: Based on the pre-stored payload topology model on the satellite, including the timing of subsystems and the constraints between subsystems, and combined with the mission start imaging / playback time, attitude parameters, payload parameters, and playback duration in the meta-mission information, command generation and parameter replacement operations are performed to autonomously generate a delay sequence containing the execution actions of relevant subsystems.

9. A remote sensing satellite autonomous mission planning system, characterized in that, The remote sensing satellite autonomous mission planning system is connected to the ground system, receives mission information uploaded by the ground system, and synchronously transmits pre-planning information to the ground system for satellite-ground situational synchronization; the mission planning system generates relevant instructions for the subsystem and distributes them to other subsystems, scheduling other subsystems to complete the entire mission. The remote sensing satellite autonomous mission planning system includes: The mission legitimacy check module is used to receive mission information sent from the ground and check the legitimacy of the mission information; The task decomposition module is used to decompose the target based on the task information, forming multiple cyclical tasks of point targets / strip targets; The attitude planning module is used to calculate the attitude paths for target switching within a mission and attitude switching between missions based on trajectory prediction and attitude capabilities after the target is decomposed into point targets / strip targets. The task sorting module is used to sort tasks according to the task observation time window, task execution interval, and task priority; it is also used to perform constraint checks on the tasks in the task pool after the above-mentioned task is inserted into the task pool. The meta-task generation module is used to generate meta-task information based on the results of path planning, task sorting, and constraint checking, and then transmit the generated meta-task information as a pre-planning result to the ground. The autonomous instruction generation module is used to autonomously generate a delay sequence based on the pre-stored subsystem timing, inter-subsystem constraints, and task information in the meta-task. This sequence includes the task start execution time, instructions from relevant subsystems, and the relative intervals between instructions. The payload, data transmission, and control systems then coordinate to complete the payload task based on the delay sequence.

10. The system according to claim 9, characterized in that, The system further includes a model layer; wherein the model layer includes an energy balance model, a data balance model, a load model, an attitude maneuver model, a trajectory prediction model, and a load topology model; the system satisfies at least one of the following: The mission validity check module receives mission information sent from the ground, including target type, target location information, payload attributes, mission imaging range, and priority. The mission information validity check examines the mission information encapsulation format, data validity, and data content, including the validity of enumeration types, the valid range of values, parameter correlation, parameter location, and valid length. The system also includes a task preprocessing module, which is used to reorder multiple targets of line targets or area targets in the task information to form ordered lines or closed intervals. The task decomposition module receives task information for point targets or sorted task information for line targets or area targets and decomposes the targets based on the model layer. If the task information indicates a point target, the target is decomposed into multiple point target combinations according to the number of target points and the number of iterations in the task information, and then decomposed into single-target multiple-loop tasks or multi-target round-robin multiple-loop tasks. If the task information indicates a line target or area target, the region is decomposed into multiple point target / strip combinations according to at least one of the following algorithms: global grid-based region segmentation algorithm, Gaussian projection-based strip segmentation algorithm, and fixed-width strip segmentation algorithm, combined with constraints such as camera swath width, flight direction, and stitching requirements. Then, according to the attitude maneuvering mode and the number of iterations, it is decomposed into small-angle step stitching multiple-loop tasks or strip push-broom stitching multiple-loop tasks. The attitude planning module is used to combine the target position and orbit prediction results with the attitude maneuver model pre-stored on the satellite in the model layer to determine the attitude path for target switching within the mission and the attitude switching path between missions. The attitude path planned in the mission preparation phase is predicted according to the maximum maneuver range. In the formal planning phase, the path in the mission preparation phase is predicted in combination with the current attitude state, thereby determining the attitude switching path between missions. The task sequencing module receives the results of attitude planning and calculates the task preparation time and recovery time using the payload model pre-stored in the model layer on the satellite, which is used to determine the entire execution interval of the task. The tasks are sorted according to the task observation time window, task execution interval, and task priority; the tasks are dynamically moved within the task observation time window according to the task sorting to ensure that the two task time intervals do not conflict; the tasks in the task pool are constrained and checked according to the on-board pre-stored energy balance model and payload model, including whether the energy reserve requirements are met and whether the switching time between targets meets the requirements. The meta-task generation module is used to receive tasks that have passed the constraint check, generate meta-task information based on the results calculated by the load data balance model, load model, attitude maneuver model of the calling model layer, and the results after task sorting, including the task start execution time, attitude maneuver parameters, load parameter information, and transmit the generated meta-task information to the ground as a pre-planning result. The autonomous command generation module is used to generate commands and replace parameters based on the payload topology model pre-stored in the on-board model layer, including the subsystem timing and the constraints between subsystems, combined with the mission imaging / playback time, attitude parameters, payload parameters and playback duration in the meta-mission information, and autonomously generate a delay sequence containing the execution actions of the relevant subsystems.

Images