Remote sensing satellite autonomous task planning method and system

Abstract

The invention discloses a remote sensing satellite autonomous task planning method and system, and the method comprises the steps: constructing an orbit prediction model, an attitude maneuver model, a load model and other models, and calling the models in a planning process for task sorting, constraint checking and meta-task generation; only point / line / surface related information, load related parameters, task imaging intervals and other necessary task demand parameters need to be injected on the ground, path planning, task decomposition, task sorting, constraint check, autonomous instruction generation and other operations are carried out through an on-satellite autonomous task planning system, and an instruction sequence related to task execution is generated and distributed to a related subsystem. The load subsystem, the data transmission subsystem, the control subsystem, the satellite service subsystem and the like cooperate to complete tasks. After the autonomous task planning system receives task information injected on the ground, satellite pre-planning information can be fed back to the ground in time, and the satellite pre-planning information can be used for ground synchronous task situations.

Description

Technical Field

[0001] The present invention relates to the technical field of satellite autonomous mission planning, in particular to a remote sensing satellite autonomous mission planning method and system. Background Art

[0002] With the technological changes in on-board real-time processing technology and inter-satellite link technology, remote sensing satellites have shown "intelligent and networked" mission characteristics. The number and application scope of remote sensing satellites are also expanding. The ground operation and control system has become more difficult to control satellites. The traditional "ground planning + on-board execution" method can no longer meet the current mission requirements. The need for mission planning on the ground has become increasingly urgent. On the one hand, it can reduce the difficulty of ground control. Users only need to pay attention to mission requirements and satellite capabilities, without paying too much attention to satellite constraints. On the other hand, the satellite can also carry out refined mission planning based on the satellite's real-time resources to improve the efficiency of satellite use.

[0003] The existing on-board mission planning technology has some shortcomings. It focuses more on the research of algorithms such as path planning and regional target decomposition. It lacks the construction and calling of the on-board model layer in the mission planning process to realize constraint checking and complete refined planning based on the real-time status on the satellite. At the same time, there is a lack of a mechanism to synchronize planning results with the ground, resulting in the lack of synchronization between the satellite and the ground, and the ground cannot grasp the status of the on-board mission in real time. Summary of the invention

[0004] The present invention provides a remote sensing satellite autonomous task planning method and system. The ground only needs to record point / line / surface related information, payload related parameters, and necessary task requirement parameters such as task imaging interval. The autonomous task planning system on the satellite performs path planning, task decomposition, task sorting, constraint checking, autonomous instruction generation, etc., generates a task-related instruction sequence and distributes it to relevant subsystems. The payload, data transmission, control, satellite affairs and other subsystems cooperate to complete the task. After receiving the task information recorded on the ground, the autonomous task planning system will promptly feedback the on-board pre-planning information to the ground for use by the ground for synchronous task status.

[0005] In a first aspect, a remote sensing satellite autonomous mission planning method is provided, comprising:

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

[0007] Decompose the target according to the task information to form multiple cycle tasks of point target / strip target;

[0008] Decompose the point targets / strip targets and calculate them according to the orbit prediction and attitude capability to determine the attitude path for target switching within the task and the attitude switching path between tasks;

[0009] Sort tasks according to task observation time window, task execution interval, and task priority;

[0010] After inserting the task into the task pool, the constraints of the tasks in the task pool are checked;

[0011] Generate meta-task information based on the results of path planning, task sorting, and constraint checking, and transmit the generated meta-task information to the ground as a pre-planning result;

[0012] Determine whether the formal 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 posture information of the task;

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

[0015] According to the relative time between the moments in the delay sequence and the instructions, they are distributed to the relevant subsystems at the right time, and the load task is completed by the cooperation of load, data transmission and control.

[0016] In combination with the first aspect, in certain implementations of the first aspect, the mission information received from the ground includes target type, target location information, payload attributes, mission imaging interval, and priority; the mission information legitimacy check is to check the mission information encapsulation format, data validity, and data content, including the validity of the enumeration type, the valid range of the value, the correlation check of the parameters, the parameter position, and the valid length. If the mission information is legal, proceed to the next step; if it is illegal, discard the task and continue in the waiting task reception mode.

[0017] In conjunction with the first aspect, in certain implementations of the first aspect, the step of performing target decomposition according to task information includes:

[0018] 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 cycles in the task information, and then decomposed into a single-target multiple-cycle task or a multi-target patrol multiple-cycle task;

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

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

[0021] The attitude path in the task preparation phase is estimated according to the maximum maneuvering range; in the formal planning phase, the path in the task preparation phase is estimated in combination with the current attitude state to determine the attitude switching path between tasks.

[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 end recovery time are calculated through the load model stored on the satellite to determine the entire execution range of the mission;

[0024] Sort tasks according to task observation time window, task execution interval, and task priority;

[0025] Dynamically move in the task observation time window according to the task sorting situation to ensure that the two task time intervals do not conflict.

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

[0027] According to the energy balance model and load model stored on the satellite, the tasks in the task pool are checked for constraints, including whether the energy margin 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 abnormal event number, and return to and continue in the waiting task reception mode.

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

[0030] Based on the calculation results of the load data balance model, load model, attitude maneuver model, and the results of task sorting, meta-task information is generated, including the task start time, attitude maneuver parameters, and load parameters.

[0031] In combination with the first aspect, in some implementations of the first aspect, the autonomously generating a delay sequence includes:

[0032] According to the payload topology model pre-stored on the satellite, including the subsystem timing and the constraints between subsystems, combined with the task start imaging / playback time, attitude parameters, payload parameters, and playback duration in the meta-task information, instructions are generated and parameters are replaced to autonomously generate a delay sequence containing the execution actions of related subsystems.

[0033] In a second aspect, a remote sensing satellite autonomous mission planning system is provided, wherein the remote sensing satellite autonomous mission planning system is connected to a ground system, receives mission information from the ground system, and synchronously transmits pre-planning information to the ground system for satellite-ground situation synchronization; the mission planning system generates subsystem-related instructions and distributes them to other subsystems, and dispatches other subsystems to complete the entire mission; the remote sensing satellite autonomous mission planning system includes:

[0034] Mission validity check module, used to receive mission information sent from the ground and perform mission information validity check;

[0035] Task decomposition module, used to decompose targets according to task information to form multiple cycle tasks of point targets / strip targets;

[0036] The attitude planning module is used to calculate the point target / strip target after decomposition according to the orbit prediction and attitude capability, and determine the attitude path of target switching within the task and the attitude switching path between tasks;

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

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

[0039] The autonomous instruction generation module is used to autonomously generate a delay sequence based on the pre-stored subsystem timing on the satellite, the constraints between subsystems, and the task information in the meta-task, including the task start execution time, the instructions of the relevant subsystems, and the relative intervals between the instructions. The payload, data transmission, and control cooperate to complete the payload task according to 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 orbit prediction model, and a load topology model; and 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 interval, and priority; the mission information validity check is to check the mission information encapsulation format, data validity, and data content, including the validity of enumeration types, the valid range of values, the correlation check of parameters, and the parameter position and valid length.

[0042] The system further comprises a task preprocessing module for reordering multiple targets of line targets or surface targets in the task information to form an ordered line or closed interval;

[0043] The task decomposition module is used to receive point target task information or sorted line target or surface target task information and perform target decomposition based on the model layer; if the task information indicates a point target, then according to the number of target points and the number of cycles in the task information, the target is decomposed into a plurality of point target combinations, and then decomposed into a single target multiple cycle task or a multi-target patrol multiple cycle task; if the task information indicates a line target or a surface target, then in combination with the constraints of the camera width, flight direction, and stitching requirements, according to at least one of a global grid-based region segmentation algorithm, a Gaussian projection-based strip segmentation algorithm, and a fixed-width strip segmentation algorithm, the region is decomposed into a plurality of point target / strip combinations, and then according to 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-scanning stitching multiple cycle task;

[0044] The attitude planning module is used to determine the attitude path for target switching within a mission and the attitude switching path between tasks by combining the target position and orbit estimation results and the attitude maneuver model pre-stored on the satellite in the model layer; the attitude path planned in the mission preparation stage is estimated according to the maximum maneuvering range; in the formal planning stage, the path in the mission preparation stage is estimated in combination with the current attitude state, so as to determine the attitude switching path between tasks;

[0045] The task sorting module is used to receive the results after attitude planning, calculate the task preparation time and end recovery time through the load model pre-stored in the model layer on the satellite, and use it to determine the entire execution interval of the task; sort the tasks according to the task observation time window, task execution interval, and task priority; dynamically move in the task observation time window according to the task sorting situation to ensure that the two task time intervals do not conflict; perform constraint checks on the tasks in the task pool according to the energy balance model and load model pre-stored on the satellite, including whether the energy margin requirements are met and whether the switching time between targets meets the requirements;

[0046] The meta-task generation module is used to receive tasks that pass the constraint check, generate meta-task information according to the results of the load data balance model, load model, attitude maneuver model calculation of the calling model layer, and the results after task sorting, including the task start execution time, attitude maneuver parameters, load parameters and other information, and transmit the generated meta-task information to the ground as a pre-planning result;

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

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

[0049] The present invention constructs models such as orbit prediction model, attitude maneuver model, and payload model. In the planning process, the models are called for task sorting, constraint checking, and generating 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 moment is reached, the generated meta-task time parameters and other information are dynamically adjusted in combination with the real-time status on the satellite, so as to further refine the planning and improve the satellite utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 The figure is a flowchart of a remote sensing satellite autonomous mission planning method.

[0051] Figure 2 This is a schematic diagram of the composition of a remote sensing satellite autonomous mission planning system. DETAILED DESCRIPTION

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

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

[0054] (1) Receive mission information sent from the ground and perform a validity check on the mission information.

[0055] The mission information sent by the ground is received through the mission validity check module, and the mission information is checked for validity. The mission information received from the ground mainly includes the target type, target location information, payload attributes, mission imaging interval, priority and other necessary mission requirements. The mission information validity check is to check the mission information encapsulation format, data validity and data content, mainly including the validity of enumeration types, the valid range of values, the correlation check of parameters, the parameter position and valid length, etc. If the mission information is legal, it goes to step (2). If it is not legal, the mission is discarded and the system continues to wait for mission reception.

[0056] (2) Decompose the target according to the task information to form multiple cyclic tasks of point target / strip target.

[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 a surface target, the task information is sent to the task preprocessing module to reorder the multiple targets in the task information to form an ordered line or a closed interval.

[0058] The task decomposition module receives the task information of point targets or the task information of sorted line targets or surface targets and performs target decomposition. If it is a point target, the target is decomposed into multiple point target combinations according to the number of target points and the number of cycles in the task information, and then decomposed into a single target multiple cycle task or a multi-target patrol multiple cycle task. If it is a line target or surface target, the region is decomposed into multiple point target / strip combinations according to the global grid-based region segmentation algorithm, the Gaussian projection-based strip segmentation algorithm, the fixed width-based strip segmentation algorithm, and other methods in combination with the camera width, flight direction, point target / strip splicing requirements and other constraints; and then decomposed into small-angle step-by-step splicing multiple cycle tasks (for example, for line targets) or strip push-scanning splicing multiple cycle tasks (for example, for surface targets) according to the attitude maneuvering mode and the number of cycles.

[0059] (3) Attitude path planning: The point target / strip target after decomposition is calculated according to the orbit prediction and attitude capability to determine the attitude path for target switching within the task and the attitude switching path between tasks.

[0060] The attitude planning module combines the target position and orbit estimation results with the attitude maneuver model stored on the satellite to determine the attitude path for target switching within the mission and the attitude switching path between tasks. Considering that the attitude state before the mission cannot be estimated during pre-planning, the attitude path in the mission preparation phase is estimated according to the maximum maneuvering range; in the formal planning phase, the path in the mission preparation phase is accurately estimated in combination with the current attitude state, so as to determine the attitude switching path between tasks.

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

[0062] The task sorting module receives the result of attitude planning, combines the pre-stored load model and the real-time status on the satellite, calculates the time for the point / strip targets after task decomposition, and sorts the tasks based on the task imaging interval, priority definition and the task pool on the satellite in the task information. When calculating the time, it is necessary to calculate the playback and broadcast distribution time based on the data balance model and imaging time.

[0063] (5) Constraint check: After inserting the task into the task pool, the constraints of the tasks in the task pool are checked.

[0064] After inserting the task into the task pool, the task sorting module needs to perform constraint checks on the tasks in the task pool according to the energy balance model and load model pre-stored on the satellite, including whether the energy margin requirements are met, whether the switching time between targets meets the requirements, etc. If the check passes, it proceeds to step (6); otherwise, it deletes the tasks that do not meet the constraints and sends an event report to the ground, including necessary information such as the task number and abnormal event number, and returns to step (1) to continue waiting for task reception mode.

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

[0066] The tasks that pass the constraint check enter the meta-task generation module. According to the calculation results of the load data balance model, load model, attitude maneuver model, and the results of task sorting, the meta-task information is generated, including the task start time, attitude maneuver parameters, load parameters, etc. The generated meta-task information is transmitted to the ground as the pre-planning result.

[0067] (7) Determine whether the formal planned start time has been reached: if so, adjust the relevant parameters in the meta-task; if not, continue waiting.

[0068] The formal planning start 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 onboard status.

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

[0071] (9) Autonomous generation of instructions: Based on the pre-stored subsystem timing and inter-subsystem constraint requirements on board, as well as the task information in the meta-task, the system autonomously generates a delay sequence, including the task start time, instructions for related subsystems, and the relative intervals between instructions.

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

[0073] (10) Distribution to related subsystems: The task planning system distributes the instructions to related subsystems based on the relative time between the moments in the delay sequence. The load, data transmission, and control systems work together to complete the load task.

[0074] The present invention constructs a remote sensing satellite autonomous mission planning system according to a remote sensing satellite autonomous mission planning method. The mission planning system is connected to a ground system, receives mission information from the ground system, and synchronously transmits pre-planning information to the ground system for satellite-ground situation synchronization. The mission planning system generates subsystem-related instructions and distributes them to other subsystems, scheduling other subsystems to complete the entire mission.

[0075] The mission planning system includes mission legality check module, mission preprocessing module, mission decomposition module, attitude planning module, mission sequencing module, meta-task generation module, autonomous instruction generation module and model layer. The model layer includes energy balance model, data balance model, payload model, attitude maneuver model, orbit prediction model and payload topology model.

[0076] The mission validity check module is used to receive mission information sent by the ground and perform a validity check on the mission information. The mission information received from the ground mainly includes necessary mission requirements such as target type, target location information, payload attributes, mission imaging interval, priority, etc. The mission information validity check is to check the mission information encapsulation format, data validity and data content, mainly including the validity of enumeration types, the valid range of values, the correlation check of parameters, parameter position and valid length, etc.

[0077] The task preprocessing module is used to reorder multiple line targets or surface targets in the task information to form an ordered line or closed interval.

[0078] The task decomposition module is used to receive the task information of point targets or the task information of sorted line targets or surface targets and perform target decomposition based on the model layer. If it is a point target, it is decomposed into a single-target multiple-cycle task or a multi-target patrol multiple-cycle task according to the number of target points and the number of cycles in the task information. If it is a line target or a surface target, it is decomposed into a small-angle step-by-step splicing multiple-cycle task (for example, for a line target) or a strip push-scanning splicing multiple-cycle task (for example, for a surface target) according to the attitude maneuvering mode and the number of cycles. The task sorting module is also used to perform constraint checks on the tasks in the task pool according to the energy balance model and load model pre-stored on the satellite after inserting the upper task into the task pool, including whether the energy margin requirements are met, whether the switching time between targets meets the requirements, etc.

[0079] The attitude planning module is used to determine the attitude path of target switching within the mission and the attitude switching path between tasks by combining the target position and orbit estimation results and the attitude maneuver model stored in the model layer on the satellite. Considering that the attitude state before the task execution cannot be estimated during pre-planning, the attitude path in the task preparation phase is estimated according to the maximum maneuvering range; in the formal planning phase, the path in the task preparation phase is accurately estimated in combination with the current attitude state, so as to determine the attitude switching path between tasks.

[0080] The task sorting module is used to receive the results of attitude planning, calculate the task preparation time and end recovery time through the load model pre-stored in the model layer on the satellite, and determine the entire execution interval of the task; sort the tasks according to the task observation time window, task execution interval, and task priority. The higher the priority and the earlier the task execution time, the higher the task is ranked in the task pool. At the same time, the task execution interval can be dynamically moved in the task observation time window according to the task sorting situation to ensure that the two task time intervals do not conflict.

[0081] The meta-task generation module is used to receive tasks that pass the constraint check, and generate meta-task information based on the results of the load data balance model, load model, attitude maneuver model calculations of the calling model layer, and the results of task sorting, including the task start execution time, attitude maneuver parameters, load parameters and other information, and transmit the generated meta-task information to the ground as a pre-planning result.

[0082] The autonomous instruction generation module is used to generate instructions, replace parameters and other operations based on the payload topology model pre-stored in the onboard model layer, including the subsystem timing and the constraints between subsystems, combined with the necessary time such as the mission hot water imaging / playback time, attitude parameters, payload parameters, and playback duration in the meta-task information. It autonomously generates a delay sequence, including the mission start execution time, instructions for related subsystems, and the relative intervals between instructions.

[0083] Although the present invention is disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art may 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 shall be based on the scope defined by the claims of the present invention.

Claims

1. A remote sensing satellite autonomous mission planning method, characterized in that: include: Receive mission information sent from the ground and perform legitimacy checks on the mission information; Decompose the target according to the task information to form multiple cycle tasks of point target / strip target; Decompose the point targets / strip targets and calculate them according to the orbit prediction and attitude capability to determine the attitude path for target switching within the task and the attitude switching path between tasks; Sort tasks according to task observation time window, task execution interval, and task priority; After inserting the task into the task pool, the constraints of the tasks in the task pool are checked; Generate meta-task information based on the results of path planning, task sorting, and constraint checking, and transmit the generated meta-task information to the ground as a pre-planning result; Determine whether the formal planned start time has been reached: if so, adjust the relevant parameters in the meta-task; If it has not arrived yet, then continue to wait; Recalculate and plan the path for task execution based on the current posture information of the task; Based on the pre-stored subsystem timing, inter-subsystem constraint requirements, and task information in the meta-task, the delay sequence is autonomously generated, including the task start execution time, the instructions of the relevant subsystems, and the relative intervals between the instructions; According to the relative time between the moments in the delay sequence and the instructions, they are distributed to the relevant subsystems at the right time, and the load task is completed by the cooperation of load, data transmission and control.

2. The method according to claim 1, characterized in that The mission information received from the ground includes target type, target location information, payload attributes, mission imaging interval, and priority. The mission information legitimacy check is to check the mission information encapsulation format, data validity, and data content, including the validity of enumeration types, the valid range of values, the correlation check of parameters, and the parameter position and valid length. If the mission information is legal, proceed to the next step. If not, discard the mission and continue in the waiting task reception mode.

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

4. The method according to claim 1, characterized in that The inter-task posture switching path satisfies: The attitude path in the task preparation phase is estimated according to the maximum maneuvering range; in the formal planning phase, the path in the task preparation phase is estimated in combination with the current attitude state to determine the attitude switching path between tasks.

5. The method according to claim 1, characterized in that The step of sorting the tasks comprises: The mission preparation time and end recovery time are calculated through the load model stored on the satellite to determine the entire execution range of the mission; Sort tasks according to task observation time window, task execution interval, and task priority; Dynamically move in the task observation time window according to the task sorting situation to ensure that the two task time intervals do not conflict.

6. The method according to claim 1, characterized in that The constraint checking includes: According to the energy balance model and load model stored on the satellite, the tasks in the task pool are checked for constraints, including whether the energy margin 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 abnormal event number, and return to and continue in the waiting task reception mode.

7. The method according to claim 1, characterized in that The generator task information includes: Based on the calculation results of the load data balance model, load model, attitude maneuver model, and the results of task sorting, meta-task information is generated, including the task start execution time, attitude maneuver parameters, and load parameters.

8. The method according to claim 1, characterized in that The autonomously generated delay sequence comprises: According to the payload topology model pre-stored on the satellite, including the subsystem timing and the constraints between subsystems, combined with the task start imaging / playback time, attitude parameters, payload parameters, and playback duration in the meta-task information, instructions are generated and parameters are replaced to autonomously generate a delay sequence containing the execution actions of related 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 the mission information from the ground system, and synchronously transmits the pre-planning information to the ground system for satellite-ground situation synchronization; the mission planning system generates subsystem-related instructions and distributes them to other subsystems, scheduling other subsystems to complete the entire mission; The remote sensing satellite autonomous mission planning system comprises: Mission validity check module, used to receive mission information sent from the ground and perform mission information validity check; Task decomposition module, used to decompose targets according to task information to form multiple cycle tasks of point targets / strip targets; The attitude planning module is used to calculate the point target / strip target after decomposition according to the orbit prediction and attitude capability, and determine the attitude path of target switching within the task and the attitude switching path between tasks; The task sorting module is used to sort tasks according to task observation time window, task execution interval, and task priority; it is also used to perform constraint checks on tasks in the task pool after inserting the previous task into the task pool; A meta-task generation module is used to generate meta-task information based on the results of path planning, task sorting, and constraint checking, and transmit the generated meta-task information to the ground as a pre-planning result; The autonomous instruction generation module is used to autonomously generate a delay sequence based on the pre-stored subsystem timing on the satellite, the constraints between subsystems, and the task information in the meta-task, including the task start execution time, the instructions of the relevant subsystems, and the relative intervals between the instructions. The payload, data transmission, and control cooperate to complete the payload task according to 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 track prediction model and a load topology model; and 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 interval, and priority; the mission information validity check is to check the mission information encapsulation format, data validity, and data content, including the validity of enumeration types, the valid range of values, the correlation check of parameters, and the parameter position and valid length. The system further comprises a task preprocessing module for reordering multiple targets of line targets or surface targets in the task information to form an ordered line or closed interval; The task decomposition module is used to receive point target task information or sorted line target or surface target task information and perform target decomposition based on the model layer; if the task information indicates a point target, then according to the number of target points and the number of cycles in the task information, the target is decomposed into a plurality of point target combinations, and then decomposed into a single target multiple cycle task or a multi-target patrol multiple cycle task; if the task information indicates a line target or a surface target, then in combination with the constraints of the camera width, flight direction, and stitching requirements, according to at least one of a global grid-based region segmentation algorithm, a Gaussian projection-based strip segmentation algorithm, and a fixed-width strip segmentation algorithm, the region is decomposed into a plurality of point target / strip combinations, and then according to 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-scanning stitching multiple cycle task; The attitude planning module is used to determine the attitude path for target switching within a mission and the attitude switching path between tasks by combining the target position and orbit estimation results and the attitude maneuver model pre-stored on the satellite in the model layer; the attitude path planned in the mission preparation stage is estimated according to the maximum maneuvering range; in the formal planning stage, the path in the mission preparation stage is estimated in combination with the current attitude state, so as to determine the attitude switching path between tasks; The task sequencing module is used to receive the results of attitude planning, calculate the task preparation time and end recovery time through the load model pre-stored in the model layer on the satellite, and determine the entire execution interval of the task; Sort tasks according to task observation time window, task execution interval, and task priority; dynamically move in the task observation time window according to task sorting to ensure that the two task time intervals do not conflict; perform constraint checks on tasks in the task pool according to the energy balance model and load model pre-stored on the satellite, including whether the energy margin requirements are met and whether the switching time between targets meets the requirements; The meta-task generation module is used to receive tasks that pass the constraint check, generate meta-task information according to the results of the load data balance model, load model, attitude maneuver model calculation of the calling model layer, and the results after task sorting, including the task start execution time, attitude maneuver parameters, load parameters and other information, and transmit the generated meta-task information to the ground as a pre-planning result; The autonomous instruction generation module is used to generate instructions and replace parameters based on the payload topology model pre-stored in the onboard model layer, including the subsystem timing and constraints between subsystems, combined with the mission hot water imaging / playback time, attitude parameters, payload parameters, and playback duration in the meta-task information, and autonomously generate a delay sequence containing the execution actions of related subsystems.

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