CN119849787B - A method and system for autonomous mission planning of remote sensing satellites - Google Patents

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

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CN119849787B
CN119849787B CN202411695537.4A CN202411695537A CN119849787B CN 119849787 B CN119849787 B CN 119849787B CN 202411695537 A CN202411695537 A CN 202411695537A CN 119849787 B CN119849787 B CN 119849787B
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CN119849787A (en
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李小娟
赵文
王卓
姜宇
张磊
杨小瑞
苗壮
胡琦渊
刘廷昊
曲晓宇
马津源
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China Academy of Space Technology CAST
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Abstract

The invention discloses a remote sensing satellite autonomous task planning method and system, wherein models such as an orbit forecasting model, a posture maneuvering model and a load model are constructed, the models are called in the planning process for task sequencing, constraint checking and meta-task generation, necessary task demand parameters such as relevant information of an upper injection point/line/plane, relevant parameters of the load and a task imaging interval are only needed on the ground, operations such as path planning, task decomposition, task sequencing, constraint checking and autonomous instruction generation are carried out through an on-board autonomous task planning system, instruction sequences relevant to executing tasks are generated and distributed to related subsystems, and tasks are completed through cooperation of the load, data transmission, control and satellite task aliquoting systems. And after receiving the task information of the ground surface betting, the autonomous task planning system timely feeds back the on-board pre-planning information to the ground surface for the ground surface synchronous task situation.

Description

Autonomous task planning method and system for remote sensing satellite
Technical Field
The 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
With the technological changes of on-board real-time processing technology, inter-satellite link technology and the like, the remote sensing satellites are characterized by 'intelligentized and networked' tasks, the number and application range of the remote sensing satellites are continuously expanded, the control difficulty of a ground operation control system on the satellites is increased, and the traditional 'ground planning and on-board execution' mode can not meet the current task demands. The ground is required to put forward task demands, and the demands for task planning on board the satellite are becoming increasingly urgent. On one hand, the ground control difficulty can be reduced, a user only needs to pay attention to task demands and satellite capacity and does not need to pay attention to the constraint of satellites too much, on the other hand, the satellite can also dynamically conduct fine task planning according to real-time resources of the satellites, and the use efficiency of the satellites is improved.
The existing on-board task planning technology has some defects, focuses on the research of algorithms such as path planning, regional target decomposition and the like, lacks the construction and the calling of an on-board model layer in the task planning process, realizes constraint inspection and completes the fine planning based on the on-board real-time state, and simultaneously lacks a mechanism for synchronizing a planning result with the ground, so that the on-board task state is not synchronized, and the ground cannot master the on-board task state in real time.
Disclosure of Invention
The invention provides a remote sensing satellite autonomous task planning method and a remote sensing satellite autonomous task planning system, wherein the ground only needs to upload relevant information of points/lines/planes, relevant parameters of loads, required parameters of tasks such as task imaging intervals and the like, the on-board autonomous task planning system is used for carrying out operations such as path planning, task decomposition, task sequencing, constraint checking, autonomous instruction generation and the like, an instruction sequence related to executing tasks is generated and distributed to related subsystems, and the tasks are completed by the cooperation of the load, data transmission, control, star service and other subsystem. And after receiving the task information of the ground surface betting, the autonomous task planning system timely feeds back the on-board pre-planning information to the ground surface for the ground surface synchronous task situation.
In a first aspect, a remote sensing satellite autonomous mission planning method is provided, including:
Receiving task information sent by the ground and checking the validity of the task information;
Performing target decomposition according to the task information to form a plurality of circulating tasks of the point target/the strip target;
Calculating the decomposed point targets/strip targets according to track prediction and gesture capability, and determining gesture paths for target switching in tasks and gesture switching paths between tasks;
sequencing the tasks according to the task observation time window, the task execution interval and the task priority;
After the uploading task is inserted into the task pool, performing constraint checking on the task in the task pool;
Generating meta-task information according to the path planning, task sequencing and constraint checking results, and downloading the generated meta-task information to the ground as a pre-planning result;
judging whether the formal planning starting time is reached, if yes, adjusting related parameters in the meta-task, and if not, continuously waiting;
recalculating and planning a path when the task is executed according to the current attitude information of the task;
According to the on-board pre-stored subsystem time sequence, the inter-subsystem constraint requirement and the task information in the meta-task, a delay sequence is generated autonomously, wherein the delay sequence comprises the task starting execution time, the related subsystem instructions and the relative intervals among the instructions;
and according to the time in the delay sequence and the relative time among the instructions, distributing the time to the related subsystems, and completing load tasks by load, data transmission and control coordination.
With reference to the first aspect, in some implementations of the first aspect, the task information sent by the receiving ground includes a target type, target location information, a load attribute, a task imaging interval and a priority, and the task information validity check is to check a task information encapsulation format, data validity and data content, including checking validity of an enumeration type, a valid range of a numerical value, relevance check of a parameter, a parameter location and a valid length, if the task information is legal, entering a next step, if the task information is not legal, discarding the task, and continuously being in a waiting task receiving mode.
With reference to the first aspect, in some implementations of the first aspect, the performing target decomposition according to task information includes:
if the task information indicates the point targets, decomposing the targets into a plurality of point target combinations according to the number of the target points in the task information and the circulation times, and further decomposing the targets into single-target multi-circulation tasks or multi-circulation tasks of multi-target round robin;
If the task information indicates a line target or a surface target, decomposing the region into a plurality of point target/strip combinations according to at least one of a global grid-based region segmentation algorithm, a Gaussian projection-based strip segmentation algorithm and a fixed width-based strip segmentation algorithm by combining constraints of camera breadth, flight direction and splicing requirements, and further decomposing into a small-angle stepping type multi-cycle task or a strip push-broom multi-cycle task according to a gesture maneuvering mode and cycle times.
With reference to the first aspect, in certain implementations of the first aspect, the inter-task gesture switching path satisfies:
And in the formal planning stage, the path of the task preparation stage is estimated by combining the current posture state, so that the posture switching path among tasks is determined.
With reference to the first aspect, in certain implementation manners of the first aspect, the sorting the tasks includes:
calculating the task preparation time and the ending recovery time through a pre-stored load model on the satellite, and determining the whole execution interval of the task;
sequencing the tasks according to the task observation time window, the task execution interval and the task priority;
and dynamically moving in a task observation time window according to the task sequencing condition, so as to ensure that two task time intervals do not conflict.
With reference to the first aspect, in certain implementations of the first aspect, the constraint checking includes:
Performing constraint inspection on tasks in a task pool according to an energy balance model and a load model pre-stored on the satellite, wherein the constraint inspection comprises whether the energy allowance requirement is met and whether the inter-target switching time length is met;
If the task is checked, the next step is carried out, otherwise, the task which does not meet the constraint condition is deleted, an event report including the task number and the abnormal event number is sent to the ground, and meanwhile, the task is returned and kept in a waiting task receiving mode.
With reference to the first aspect, in certain implementation manners of the first aspect, the generating meta-task information includes:
And generating meta-task information including task starting execution time, attitude maneuver parameters and load parameters according to the results of calculation of the load data balance model, the load model and the attitude maneuver model and the results after task sequencing.
With reference to the first aspect, in certain implementation manners of the first aspect, the autonomously generating a delay sequence includes:
According to a pre-stored load topology model on the satellite, which comprises subsystem time sequences and constraint requirements among subsystems, and by combining task imaging/playback starting time, gesture parameters, load parameters and playback time in meta-task information, instruction generation and parameter replacement operations are carried out, and a delay sequence containing related subsystem execution actions is autonomously generated.
The second aspect provides a remote sensing satellite autonomous task planning system, which is connected with a ground system, receives task information uploaded by the ground system, and synchronously downloads pre-planning information to the ground system for satellite-ground situation synchronization, wherein the task planning system generates subsystem related instructions and distributes the subsystem related instructions to other subsystems to schedule the other subsystems to complete the whole task, and the remote sensing satellite autonomous task planning system comprises:
the task validity checking module is used for receiving the task information sent by the ground and checking the validity of the task information;
The task decomposition module is used for performing target decomposition according to the task information to form a plurality of circulating tasks of the point target/the strip target;
the gesture planning module is used for calculating the decomposed point targets/strip targets according to track prediction and gesture capability and determining gesture paths for switching targets in tasks and gesture switching paths between tasks;
the task ordering module is used for ordering the tasks according to the task observation time window, the task execution interval and the task priority, and is also used for carrying out constraint check on the tasks in the task pool after the uploading tasks are inserted into the task pool;
The meta-task generating module is used for generating meta-task information according to the path planning, task sequencing and constraint checking results and downloading the generated meta-task information to the ground as a pre-planning result;
The autonomous instruction generation module is used for autonomously generating a delay sequence according to the on-board pre-stored subsystem time sequence, the inter-subsystem constraint requirement and the task information in the meta-task, wherein the delay sequence comprises the task starting execution time, the related subsystem instructions and the relative intervals among the instructions, and the load task is completed by load, data transmission and control according to the delay sequence.
With reference to the second aspect, in certain 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, a pose maneuver model, a trajectory forecast model, and a load topology model, and the system satisfies at least one of:
The task information validity checking module receives task information sent by the ground and comprises a target type, target position information, load attribute, a task imaging interval and priority, wherein the task information validity checking comprises checking the task information packaging format, data validity and data content, including checking the validity of an enumeration type, the valid range of a numerical value, the relevance checking of a parameter, the parameter position and the valid length;
the system also comprises a task preprocessing module, a processing module and a processing module, wherein the task preprocessing module is used for reordering a plurality of targets of line targets or surface targets in task information to form ordered lines or closed intervals;
The task decomposition module is used for receiving the point target task information or the ordered line target or surface target task information and decomposing the target based on the model layer, decomposing the target into a plurality of point target combinations according to the number of target points in the task information and the circulation times if the task information indicates the point target, and further decomposing the point target combinations into single-target multi-circulation tasks or multi-circulation tasks of multi-target round inspection;
The gesture planning module is used for combining a target position, a track estimated result and a gesture maneuvering model prestored in a model layer on a satellite to determine a gesture path for switching a target in a task and a gesture switching path between tasks;
the task ordering module is used for receiving a result after gesture planning, calculating task preparation time and ending recovery time through a load model prestored in a model layer on the satellite, and determining the whole execution interval of the task; the method comprises the steps of carrying out constraint checking on tasks in a task pool according to a pre-stored energy balance model and a load model on a satellite, wherein the constraint checking comprises whether the requirements of energy allowance and the switching time between targets are met or not;
the meta-task generating module is used for receiving tasks passing constraint inspection, generating meta-task information comprising information such as task starting execution time, attitude maneuver parameters, load parameters and the like according to the calculation results of the load data balance model, the load model and the attitude maneuver model of the calling model layer and the results after task sequencing, and downloading the generated meta-task information to the ground as a pre-planning result;
The autonomous instruction generation module is used for performing instruction generation and parameter replacement operation according to a load topology model pre-stored in an on-board model layer and comprising subsystem time sequences and constraint requirements among subsystems, and performing autonomous generation of a time delay sequence containing execution actions of related subsystems by combining task boiled water imaging/playback time, gesture parameters, load parameters and playback time length in meta-task information.
Compared with the prior art, the scheme provided by the invention at least comprises the following beneficial technical effects:
The method builds models such as an orbit forecasting model, a gesture maneuvering model and a loading model, calls the models for task sequencing, constraint checking and meta-task generation in the planning process, divides the task planning into two stages of pre-planning and formal planning, downloads a pre-planning result to the ground in time for satellite-to-ground synchronization, dynamically adjusts the generated meta-task time parameters and other information by combining on-board real-time state dynamics when reaching the formal planning, further refines planning, and improves the use efficiency of satellites.
Drawings
Fig. 1 is a schematic flow chart of a remote sensing satellite autonomous mission planning method.
Fig. 2 is a schematic diagram of a remote sensing satellite autonomous mission planning system.
Detailed Description
The invention is described in further detail below with reference to the drawings and the specific embodiments.
As shown in FIG. 1, the invention provides a remote sensing satellite autonomous task planning method, which comprises the following specific implementation steps.
(1) And receiving the task information sent by the ground and checking the validity of the task information.
And receiving task information sent by the ground through a task validity checking module, and checking the validity of the task information. The task information sent by the ground is received and mainly comprises the necessary task demands such as target types, target position information, load attributes, task imaging intervals, priorities and the like. The task information validity check is to check the task information packaging format, the data validity and the data content, and mainly comprises checking the validity of enumeration types, the valid range of numerical values, the relevance check of parameters, the parameter position, the valid length and the like, if the task information is legal, entering the step (2), and if the task information is illegal, discarding the task, and continuously keeping in a waiting task receiving mode.
(2) And performing target decomposition according to the task information to form a plurality of circulating tasks of the point target/the strip target.
And if the task information indicates the point target, sending the task information into a task decomposition module. If the task information indicates a line target or a surface target, the task information is sent to a task preprocessing module, and a plurality of targets in the task information are reordered to form an ordered line or a closed section.
The task decomposition module receives the task information of the point target or the ordered line targets or the surface targets and performs target decomposition. If the target is a point target, decomposing the target into a plurality of point target combinations according to the number of target points and the circulation times in the task information, and further decomposing the target into a single-target multi-circulation task or a multi-circulation task of multi-target round robin. If the target is a line target or a surface target, the region is decomposed into a plurality of point targets/strip combinations according to a global grid-based region segmentation algorithm, a Gaussian projection-based strip segmentation algorithm, a fixed width-based strip segmentation algorithm and other methods by combining constraints such as camera breadth, flight direction and point target/strip splicing requirements, and further decomposed into a small-angle stepping type multi-cycle task (for example, aiming at the line target) or a strip push-broom type multi-cycle task (for example, aiming at the surface target) according to a gesture maneuvering mode and the cycle times.
(3) And (3) gesture path planning, namely calculating the decomposed point targets/strip targets according to track prediction and gesture capability, and determining gesture paths for switching targets in tasks and gesture switching paths among tasks.
And determining a gesture path for switching the targets in the task and a gesture switching path between tasks by combining the target position, the track estimated result and a pre-stored gesture maneuvering model on the satellite through a gesture planning module according to the result of the target decomposition. In the formal planning stage, the paths of the task preparation stage are accurately estimated by combining the current attitude state, so that the inter-task attitude switching paths are determined.
(4) And the task sequencing comprises the steps of calculating the task preparation time and the ending recovery time through a pre-stored load model on the satellite, determining the whole execution interval of the task, and sequencing the tasks according to the task observation time window, the task execution interval and the task priority. The higher the priority is, the earlier the task execution time is, the earlier the task is ordered in the task pool, and meanwhile, the task execution interval can dynamically move in the task observation time window according to the task ordering condition, so that the two task time intervals are ensured not to collide.
The task sequencing module receives the result after gesture planning, combines a pre-stored load model on the satellite and a real-time state on the satellite, calculates time of a point/strip target after task decomposition, and sequences tasks by combining task imaging interval, priority definition and on-board task pool conditions in task information. In performing the time calculation, the playback and broadcast distribution durations need to be calculated from the data balance model and the imaging durations.
(5) Constraint checking, namely after the uploading task is inserted into the task pool, performing constraint checking on the tasks in the task pool.
After the task ordering module inserts the uploading task into the task pool, the task ordering module needs to carry out constraint inspection on the task in the task pool according to an energy balance model and a load model pre-stored on the satellite, wherein the constraint inspection comprises whether the requirement of energy allowance is met, whether the switching duration between targets is met or not, and the like, if the constraint inspection is passed, the task ordering module enters the step (6), otherwise, the task which does not meet the constraint condition is deleted, and an event report is sent to the ground, wherein the event report comprises necessary information such as a task number, an abnormal event number and the like, and meanwhile, the task ordering module returns to the step (1) and is continuously in a task waiting receiving mode.
(6) And generating meta-task information, namely generating the meta-task information according to path planning, task sequencing, constraint checking and other operations.
And entering a meta-task generating module through constraint checking tasks, generating meta-task information comprising information such as task starting execution time, attitude maneuver parameters, load parameters and the like according to the calculation results of the call load data balance model, the load model and the attitude maneuver model and the results after task sequencing, and downloading the generated meta-task information to the ground as a pre-planning result.
(7) Judging whether the formal planning starting time is reached, if yes, adjusting relevant parameters in the meta-task, and if not, continuously waiting.
The formal planning start time may be determined based on the orbit characteristics of the satellite and the task preparation time.
(8) And (3) adjusting related parameters in the meta-task, namely calculating parameters such as time length in meta-task information according to the current on-satellite state.
The posture related parameters generally need to be adjusted, and paths when the tasks are executed need to be recalculated and planned according to the current posture information of the tasks.
(9) And generating an instruction autonomously, namely generating a delay sequence autonomously according to the on-board pre-stored subsystem time sequence, the inter-subsystem constraint requirement and the task information in the meta-task, wherein the delay sequence comprises the task starting execution time, the related subsystem instructions and the relative intervals among the instructions.
When the meta-task information is to be unfolded (the unfolding time can be set to be 5s earlier than the task starting time generally), the meta-task information is sent to an autonomous instruction generating module, and the autonomous instruction generating module performs operations such as instruction generation, parameter replacement and the like according to a pre-stored load topology model on the satellite, including subsystem time sequences and constraint requirements among subsystems, in combination with necessary time such as task boiled water imaging/playback time, gesture parameters, load parameters, playback time and the like in the meta-task information, and autonomously generates a delay sequence containing related subsystem execution actions.
(10) And distributing the load tasks to the related subsystems by the task planning system according to the time in the delay sequence and the relative time among the instructions, and completing the load tasks by the coordination of load, data transmission, control and the like.
According to the remote sensing satellite autonomous mission planning method, a remote sensing satellite autonomous mission planning system is constructed, the mission planning system is connected with a ground system, task information uploaded by the ground system is received, and pre-planning information is synchronously downloaded to the ground system for satellite-ground situation synchronization. The task planning system generates subsystem related instructions and distributes the subsystem related instructions to other subsystems, and the other subsystems are scheduled to complete the whole task.
The task planning system comprises a task validity checking module, a task preprocessing module, a task decomposing module, a gesture planning module, a task ordering module, a meta-task generating module, an autonomous instruction generating module and a model layer. The model layer comprises an energy balance model, a data balance model, a load model, a posture maneuver model, an orbit forecast model and a load topology model.
The task validity checking module is used for receiving the task information sent by the ground and checking the validity of the task information. The task information sent by the ground is received and mainly comprises the necessary task demands such as target types, target position information, load attributes, task imaging intervals, priorities and the like. The task information validity check is to check the task information packaging format, the data validity and the data content, and mainly comprises checking the validity of the enumeration type, the valid range of the numerical value, the relevance check of the parameters, the parameter position, the valid length and the like.
The task preprocessing module is used for reordering the line targets or the multiple targets of the surface targets in the task information to form ordered lines or closed intervals.
The task decomposition module is used for receiving the task information of the point target or the ordered line targets or the ordered surface targets and performing target decomposition based on the model layer. If the target is a point target, decomposing the target into a single-target multi-cycle task or a multi-cycle task of multi-target round robin according to the number of the target points in the task information and the cycle times. If the target is a line target or a surface target, the target is decomposed into a small-angle stepping type multi-time circulating task (for example, aiming at the line target) or a strip push-broom type multi-time circulating task (for example, aiming at the surface target) according to the gesture maneuvering mode and the circulating times. The task ordering module is also used for carrying out constraint check on the tasks in the task pool according to the on-board pre-stored energy balance model and the load model after the uploading tasks are inserted into the task pool, wherein the constraint check comprises whether the energy allowance requirement is met, whether the inter-target switching duration meets the requirement or not and the like.
The gesture planning module is used for determining a gesture path for switching the targets in the tasks and a gesture switching path between the tasks by combining the target positions, the track estimated result and a gesture maneuvering model prestored in a model layer on the satellite. In the formal planning stage, the paths of the task preparation stage are accurately estimated by combining the current attitude state, so that the inter-task attitude switching paths are determined.
The task sequencing module is used for receiving the result after gesture planning, calculating the task preparation time and the ending recovery time through a load model prestored in a model layer on the satellite and determining the whole execution interval of the task, and sequencing the tasks according to the task observation time window, the task execution interval and the task priority. The higher the priority is, the earlier the task execution time is, the earlier the task is ordered in the task pool, and meanwhile, the task execution interval can dynamically move in the task observation time window according to the task ordering condition, so that the two task time intervals are ensured not to collide.
The meta-task generating module is used for receiving tasks passing constraint inspection, generating meta-task information comprising information such as task starting execution time, attitude maneuver parameters, load parameters and the like according to the calculation results of the load data balance model, the load model and the attitude maneuver model of the calling model layer and the results after task sequencing, and downloading the generated meta-task information to the ground as a pre-planning result.
The autonomous instruction generation module is used for carrying out operations such as instruction generation, parameter replacement and the like according to a load topology model pre-stored in an on-board model layer and comprising subsystem time sequences and constraint requirements among subsystems, and combining with necessary time such as task boiled water imaging/playback time, gesture parameters, load parameters, playback time length and the like in meta-task information, and autonomously generating a delay sequence comprising task starting execution time, instructions of related subsystems and relative intervals among the instructions.
While the invention has been described in terms of the preferred embodiment, it is not intended to limit the invention, but it will be apparent to those skilled in the art that variations and modifications can be made without departing from the spirit and scope of the invention, and therefore the scope of the invention is defined in the appended claims.

Claims (10)

1.一种遥感卫星自主任务规划方法，其特征在于，包括：1. A method for autonomous mission planning of remote sensing satellites, characterized in that it includes: 接收地面发送的任务信息并进行任务信息合法性检查；Receive mission information sent from the ground and perform mission information legality checks; 根据任务信息进行目标分解，形成点目标/条带目标的多次循环任务；Based on the task information, the objectives are decomposed into multiple cyclical tasks of point objectives/strip objectives; 将目标分解后的点目标/条带目标，根据轨道预报以及姿态能力进行计算，确定任务内目标切换的姿态路径，以及任务间姿态切换路径；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. 根据任务观测时间窗口、任务执行区间、任务优先级对任务进行排序；Tasks are sorted according to the task observation time window, task execution interval, and task priority; 在将上注任务插入任务池后，对任务池中的任务进行约束检查；After inserting the betting task into the task pool, perform constraint checks on the tasks in the task pool. 根据路径规划、任务排序、约束检查的结果，生成元任务信息，并将生成的元任务信息作为预规划结果下传至地面；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. 判断是否达到正式规划启动时间：若到时，则调整元任务中相关参数；若未到时，则持续等待；Determine if the planned start time has been reached: if so, adjust the relevant parameters in the meta-task; if not, continue waiting. 根据任务当前的姿态信息重新计算并规划任务执行时的路径；Recalculate and plan the path for task execution based on the current attitude information of the task. 根据星上预存分系统时序、分系统间约束要求，以及元任务中的任务信息，自主生成延时序列，包括任务开始执行时刻、相关分系统的指令以及指令之间的相对间隔；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. 根据延时序列中的时刻和指令间的相对时间，到时分发给相关分系统，由载荷、数传、控制配合完成载荷任务。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.根据权利要求1所述的方法，其特征在于，接收地面发送的任务信息包括目标类型、目标位置信息、载荷属性、任务成像区间、优先级；任务信息合法性检查是对任务信息封装格式、数据有效性以及数据内容进行检查，包括对枚举类型的有效性、以及数值的有效范围、参数的关联性检查、参数位置和有效长度进行检查，若任务信息合法，则进入下一步，若不合法，则丢弃该任务，持续处于等待任务接收模式。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 is to check the task information encapsulation format, data validity, and data content, including checking the validity of the enumeration type, the valid range of the values, the correlation of parameters, the position of parameters, and the valid length. 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. 3.根据权利要求1所述的方法，其特征在于，所述根据任务信息进行目标分解，包括：3. The method according to claim 1, wherein the step of decomposing the target based on the task information includes: 若任务信息指示点目标，则根据任务信息中的目标点个数以及循环次数，将目标分解为多个点目标组合，进而分解为单目标多次循环任务或者多目标轮巡的多次循环任务；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. 若任务信息指示线目标或面目标，则结合相机幅宽、飞行方向、拼接要求的约束，按照基于全球网格的区域分割算法、基于高斯投影的条带分割算法、基于固定宽度的条带分割算法中的至少一项，将区域分解为多个点目标/条带组合，进而根据姿态机动模式以及循环次数，分解为小角度步进式拼接多次循环任务或者条带推扫拼接多次循环任务。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.根据权利要求1所述的方法，其特征在于，所述任务间姿态切换路径满足：4. The method according to claim 1, wherein the inter-task attitude switching path satisfies: 任务准备阶段的姿态路径按照最大机动范围来预估；在正式规划阶段，结合当前姿态状态对任务准备阶段的路径进行预估，从而确定任务间姿态切换路径。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.根据权利要求1所述的方法，其特征在于，所述对任务进行排序，包括：5. The method according to claim 1, wherein the sorting of tasks includes: 通过星上预存的载荷模型，计算任务准备时长和结束恢复时长，用于确定任务的整个执行区间；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. 根据任务观测时间窗口、任务执行区间、任务优先级对任务进行排序；Tasks are sorted according to the task observation time window, task execution interval, and task priority; 根据任务排序情况在任务观测时间窗口动态移动，确保两个任务时间区间不冲突。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.根据权利要求1所述的方法，其特征在于，所述约束检查包括：6. The method according to claim 1, wherein the constraint check comprises: 根据星上预存的能源平衡模型、载荷模型对任务池中的任务进行约束检查，包括是否满足能源余量要求、目标间切换时长是否满足要求；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. 若通过检查则进入下一步；否则删除不符合约束条件的任务，并向地面发送事件报告，包括任务号、异常事件编号，同时返回并持续处于等待任务接收模式。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.根据权利要求1所述的方法，其特征在于，所述生成元任务信息，包括：7. The method according to claim 1, wherein the generation of meta-task information includes: 根据调用载荷数据平衡模型、载荷模型、姿态机动模型计算的结果，以及任务排序后的结果，生成元任务信息，包括任务开始执行时刻、姿态机动参数、载荷参数。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.根据权利要求1所述的方法，其特征在于，所述自主生成延时序列，包括：8. The method according to claim 1, wherein the autonomous generation of the delay sequence comprises: 根据星上预存的载荷拓扑模型，包括分系统时序以及分系统间的约束要求，结合元任务信息中的任务开始成像/回放时刻、姿态参数、载荷参数、回放时长，进行指令生成、参数替换操作，自主生成包含相关分系统执行动作的延时序列。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. 9.一种遥感卫星自主任务规划系统，其特征在于，所述遥感卫星自主任务规划系统与地面系统相连，接收地面系统上注的任务信息，并将预规划信息同步下传至地面系统，用于星地态势同步；任务规划系统生成分系统相关指令并分发给其他分系统，调度其他分系统完成整个任务；所述遥感卫星自主任务规划系统包括：9. A remote sensing satellite autonomous mission planning system, characterized in that the remote sensing satellite autonomous mission planning 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 other subsystems to complete the entire mission; the remote sensing satellite autonomous mission planning system includes: 任务合法性检查模块，用于接收地面发送的任务信息并进行任务信息合法性检查；The mission legitimacy check module is used to receive mission information sent from the ground and perform mission information legitimacy checks. 任务分解模块，用于根据任务信息进行目标分解，形成点目标/条带目标的多次循环任务；The task decomposition module is used to decompose the target based on the task information, forming multiple cyclical tasks of point targets/strip targets; 姿态规划模块，用于将目标分解后的点目标/条带目标，根据轨道预报以及姿态能力进行计算，确定任务内目标切换的姿态路径，以及任务间姿态切换路径；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. 任务排序模块，用于根据任务观测时间窗口、任务执行区间、任务优先级对任务进行排序；还用于在将上注任务插入任务池后，对任务池中的任务进行约束检查；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. 生成元任务模块，用于根据路径规划、任务排序、约束检查的结果，生成元任务信息，并将生成的元任务信息作为预规划结果下传至地面；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. 自主指令生成模块，用于根据星上预存分系统时序、分系统间约束要求，以及元任务中的任务信息，自主生成延时序列，包括任务开始执行时刻、相关分系统的指令以及指令之间的相对间隔，由载荷、数传、控制根据延时序列配合完成载荷任务。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.根据权利要求9所述的系统，其特征在于，所述系统还包括模型层；其中模型层包括能源平衡模型、数据平衡模型、载荷模型、姿态机动模型、轨道预报模型和载荷拓扑模型；所述系统满足以下至少一项：10. The system according to claim 9, characterized in that the system further comprises a model layer; wherein the model layer comprises 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: 任务合法性检查模块接收地面发送的任务信息包括目标类型、目标位置信息、载荷属性、任务成像区间、优先级；任务信息合法性检查是对任务信息封装格式、数据有效性以及数据内容进行检查，包括对枚举类型的有效性、以及数值的有效范围、参数的关联性检查、参数位置和有效长度进行检查；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. 所述系统还包括任务预处理模块，用于将任务信息中线目标或面目标的多个目标进行重新排序，形成有序的线或者封闭的区间；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. 任务分解模块用于接收到点目标任务信息或者经过排序的线目标或面目标的任务信息并基于模型层进行目标分解；若任务信息指示点目标，则根据任务信息中的目标点个数以及循环次数，将目标分解为多个点目标组合，进而分解为单目标多次循环任务或者多目标轮巡的多次循环任务；若任务信息指示线目标或面目标，则结合相机幅宽、飞行方向、拼接要求的约束，按照基于全球网格的区域分割算法、基于高斯投影的条带分割算法、基于固定宽度的条带分割算法中的至少一项，将区域分解为多个点目标/条带组合，进而根据姿态机动模式以及循环次数，分解为小角度步进式拼接多次循环任务或者条带推扫拼接多次循环任务；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. 姿态规划模块用于结合目标位置以及轨道预估结果、星上在模型层预存的姿态机动模型，确定任务内目标切换的姿态路径，以及任务间姿态切换路径；在任务准备阶段规划的姿态路径按照最大机动范围来预估；在正式规划阶段，结合当前姿态状态对任务准备阶段的路径进行预估，从而确定任务间姿态切换路径；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. 任务排序模块用于接收姿态规划后的结果，通过星上在模型层预存的载荷模型，计算任务准备时长和结束恢复时长，用于确定任务的整个执行区间；根据任务观测时间窗口、任务执行区间、任务优先级对任务进行排序；根据任务排序情况在任务观测时间窗口动态移动，确保两个任务时间区间不冲突；根据星上预存的能源平衡模型、载荷模型对任务池中的任务进行约束检查，包括是否满足能源余量要求、目标间切换时长是否满足要求；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. 生成元任务模块用于接收通过约束检查的任务，根据调用模型层的载荷数据平衡模型、载荷模型、姿态机动模型计算的结果，以及任务排序后的结果，生成元任务信息，包括任务开始执行时刻、姿态机动参数、载荷参数信息，并将生成的元任务信息作为预规划结果下传至地面；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. 自主指令生成模块用于根据星上模型层预存的载荷拓扑模型，包括分系统时序以及分系统间的约束要求，结合元任务信息中的任务开水成像/回放时刻、姿态参数、载荷参数、回放时长，进行指令生成、参数替换操作，自主生成包含相关分系统执行动作的延时序列。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.
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