Progressive local rolling optimization inter-satellite cooperative task autonomous planning method

Abstract

A progressive local rolling optimization inter-satellite cooperative task autonomous planning method comprises the following steps: defining a satellite constraint model according to satellite platform resource constraint and load working capability; receiving an inter-satellite cooperation task window annotated by a user, and planning and generating an inter-satellite cooperation task; receiving a data transmission task window uploaded by a user, and planning and generating a data transmission playback task; in an inter-satellite cooperative task window time period, receiving a guiding task from an inter-satellite link in real time, and defining the guiding task as an inter-satellite situation task; performing task preprocessing on the inter-satellite situation task received in the inter-satellite cooperative task; determining the position of the task inserted into the existing task execution sequence by adopting a greedy algorithm, and generating a new task sequence; carrying out data transmission task insertion; performing task constraint condition check to generate a final to-be-executed task; and after a new task is received, rolling planning is performed according to the rolling planning frequency to update the task sequence in real time.

Description

Technical Field

[0001] The invention relates to a progressive local rolling optimization inter-satellite collaborative task autonomous planning method, belonging to the technical field of autonomous task planning on satellites. Background Art

[0002] Autonomous planning of intersatellite collaborative missions means that multiple satellites in a constellation can collaborate efficiently. A satellite can conduct autonomous mission planning in real time based on the guidance information sent by other satellites, quickly obtain the executable mission sequence of the satellite, and achieve the maximum on-orbit flight benefits. With the rapid development of space constellation technology, the types and requirements of intersatellite collaborative missions have become more and more diversified and refined, which brings certain challenges to autonomous mission planning. When a satellite enters the preset intersatellite collaborative mission area, it can automatically enter the intersatellite collaborative mission planning mode. The autonomous mission planning system receives intersatellite guidance information distributed in real time by member satellites through intersatellite links. This information is uncertain and diverse. The planning system classifies and organizes various types of information to form a corresponding situation mission information set. The autonomous mission planning system needs to integrate this information set with the original planning task set to finally form an executable task output sequence, thereby achieving rapid response to intersatellite collaborative missions. Summary of the invention

[0003] The technical problem to be solved by the present invention is: to overcome the shortcomings of the prior art, to propose a progressive local rolling optimization intersatellite collaborative task autonomous planning method, to use a progressive local rolling planning strategy to deal with the suddenness and uncertainty of situation tasks within the collaborative interval; and to quickly obtain the local optimal solution through a greedy algorithm, thereby shortening the task planning processing time, improving the task execution efficiency, and meeting the collaborative detection task's demand for high timeliness.

[0004] The purpose of the present invention is achieved through the following technical solutions:

[0005] A progressive local rolling optimization autonomous planning method for intersatellite collaborative tasks, the steps are as follows:

[0006] 1) According to the satellite platform resource constraints and payload working capacity, the satellite constraint model is defined as follows:

[0007] S={IMTask_t,Vad,SEA,Mvk,SWATH,SDC,FILE};

[0008] Among them, IMTask_t represents the imaging duration of the detection mission, Vad represents the payload field of view, SEA represents the solar altitude angle, Mvk represents the attitude maneuverability, SWATH represents the payload camera width, SDC represents the storage capacity, and FILE represents the record file number.

[0009] 2) Intersatellite collaborative task input: Receive the intersatellite collaborative task window registered by the user, denoted as CorpWin i , according to the task period agreed in the window, plan and generate inter-satellite collaborative tasks, set up the inter-satellite link establishment process for the inter-satellite link subsystem, and have the status of receiving inter-satellite guidance tasks in real time; receive the data transmission task window DtWin registered by the user i , according to the task period agreed in the window, plan and generate the digital transmission playback task DTTask, and perform digital transmission playback on the ground for the recorded data of the observation task;

[0010] Furthermore, the intersatellite collaborative task window and the data transmission task window in step 2) are specifically:

[0011] Interplanetary collaborative task window CorpWin i = {Co_ts i ,Co_te i ,f};

[0012] Data transmission task window DtWin i ={Dt_ts i ,Dt_te i ,ST i};

[0013] Among them, Co_ts i Indicates the start time of the intersatellite collaborative mission, Co_te i represents the end time of the intersatellite collaborative mission, f represents the rolling planning frequency of the intersatellite collaborative mission; Dt_ts i Indicates the start time of the data transmission task, Dt_te i Indicates the end time of the data transmission task, ST i Indicates the code of the ground station for the ground data transmission mission;

[0014] Furthermore, the intersatellite collaborative task window in step 2) is characterized by:

[0015] In the global planning, a local space is obtained, namely, the intersatellite collaborative task window, and it is agreed that the rolling planning process is only carried out in the local interval and does not affect the tasks outside the collaborative interval; first, it is determined whether there are tasks that have been planned and are to be executed in the collaborative interval. If so, the priority of such tasks is defined as the lowest, and such tasks are inserted into the sequence according to the planning strategy in the subsequent intersatellite situation task planning process.

[0016] 3) Intersatellite guidance task input: Enter the intersatellite collaborative task window period described in step 2) and receive guidance tasks from the intersatellite link in real time, which are defined as intersatellite situation tasks;

[0017] Furthermore, the intersatellite situation task in step 3) has the characteristics of uncertainty, high dynamics and high timeliness, specifically:

[0018] Intersatellite situational task definition, T = {ID, δ, λ, h, t c ,v,PRI,CONF,Type};

[0019] Where, ID represents the mission number; (δ, λ, h) represents the geographical longitude, latitude, and altitude of the ground-fixed target point; t c represents the target observation transient time, PRI represents the target priority, and CONF represents the target confidence; v represents the target motion velocity vector, which describes the dynamic properties of the input task; Type is used as an index to match the target features in the situation task database, the user-defined detection target attributes, including the detection target type feature information, etc.

[0020] 4) Task preprocessing:

[0021] 41) The visibility of the inter-satellite situation tasks received in the inter-satellite collaborative tasks is judged, and the tasks that are visible and whose visible arc segments are within the collaborative period are stored in the valid task set, which is recorded as TaskVaild. Specifically:

[0022] TaskVaild = {T1,T2,T3...T i}, where T1~T i It indicates that the intersatellite situation tasks that have passed the visibility judgment are stored in order according to the time when the tasks are received.

[0023] 42) Pre-sorting the tasks in the valid task pool TaskVaild described in step 41) according to the hierarchical priority sorting strategy, and the sorting result is defined as IMTask;

[0024] Furthermore, the hierarchical priority sorting strategy in step 42) is specifically:

[0025] First, sort from high to low according to the target confidence CONF, then sort from high to low according to the priority of the user-defined situation task type Type, and then sort from high to low according to the target priority PRI.

[0026] 5) Determine the task insertion position: Use a greedy algorithm to determine the position where the task is inserted into the existing task execution sequence IMTask, and generate a new detection task sequence IMTask_New;

[0027] Furthermore, in step 5), the greedy algorithm defines a greedy strategy, specifically:

[0028] Prioritize tasks with a high CONF, then tasks with a high Type priority, and finally tasks with a high PRI.

[0029] 6) Task conflict resolution: First, determine whether the newly inserted task conflicts with the tasks in the original sequence. If there is a conflict, use the greedy strategy described in step 5) to resolve the conflicting task and update IMTask_New;

[0030] 7) Data transmission task insertion: According to the data transmission task window DtWin described in step 2) i , when it is determined that the digital transmission task window period overlaps with the inter-satellite collaborative task window period, the playback task is defined as a real transmission task, and the digital transmission subsystem is set to perform a recording and playback working mode.

[0031] 8) Generation of tasks to be executed:

[0032] 81) Perform constraint check on IMTask_New and DTTask in combination with the constraint condition S in step 1), delete tasks that fail the constraint check, and update IMTask_New and DTTask;

[0033] 82) Combine IMTask_New, DTWin and the target attitude calculated by the target task visibility determination method, calculate the target attitude maneuvering time, and generate the attitude maneuvering task ATTTask;

[0034] 83) Task merging to produce tasks to be executed;

[0035] 9) Task rolling planning: Determine whether there is a new task entering the queue to be planned. If so, return to step 3), perform rolling planning on the tasks in the queue to be planned according to the rolling planning frequency f, and update IMTask_New in real time.

[0036] An electronic device, comprising:

[0037] Processor; and

[0038] a memory for storing computer program instructions;

[0039] When the computer program instructions are loaded and executed by the processor, the processor executes the progressive local rolling optimization intersatellite collaborative mission autonomous planning method.

[0040] A computer program product stored on a non-transitory computer-readable medium includes program codes for implementing the incremental local rolling optimization inter-satellite collaborative mission autonomous planning method.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] (1) The present invention adopts a local rolling planning strategy for inter-satellite situation tasks to effectively deal with the suddenness and uncertainty of inter-satellite situation tasks within the inter-satellite coordination period.

[0043] (2) The present invention uses a greedy algorithm to quickly obtain the local optimal solution, shortens the task planning processing time, improves the task execution efficiency, and meets the collaborative detection task's demand for high timeliness. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 The present invention is a flow chart of rolling planning of intersatellite situation tasks;

[0045] Figure 2 This is a schematic diagram of the greedy strategy task sorting of the present invention;

[0046] Figure 3 Insert a conflict resolution process diagram for the task of the present invention. DETAILED DESCRIPTION

[0047] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0048] A progressive local rolling optimization method for autonomous planning of intersatellite collaborative tasks, such as Figure 1 As shown, the specific steps are:

[0049] 1) According to the satellite platform resource constraints and payload working capacity, the satellite constraint model is defined as follows:

[0050] S={IMTask_t,Vad,SEA,Mvk,SWATH,SDC,FILE};

[0051] Among them, IMTask_t represents the imaging duration of the detection mission, Vad represents the payload field of view angle, SEA represents the solar altitude angle, Mvk represents the attitude maneuverability, SWATH represents the payload camera width, SDC represents the storage capacity, and FILE represents the record file number.

[0052] 2) Intersatellite collaborative task input: Receive the intersatellite collaborative task window registered by the user, denoted as CorpWin i , according to the task period agreed in the window, plan and generate inter-satellite collaborative tasks, set up the inter-satellite link establishment process for the inter-satellite link subsystem, and have the status of receiving inter-satellite guidance tasks in real time; receive the data transmission task window DtWin registered by the user i , according to the task period agreed in the window, plan and generate the digital transmission playback task DTTask, and perform digital transmission playback on the ground for the recorded data of the observation task;

[0053] Furthermore, the intersatellite collaborative task window and the data transmission task window in step 2) are specifically:

[0054] Interplanetary collaborative task window CorpWin i = {Co_ts i ,Co_te i ,f};

[0055] Data transmission task window DtWin i ={Dt_ts i ,Dt_te i ,ST i};

[0056] Among them, Co_ts i Indicates the start time of the intersatellite collaborative mission, Co_te i represents the end time of the intersatellite collaborative mission, f represents the rolling planning frequency of the intersatellite collaborative mission; Dt_ts i Indicates the start time of the data transmission task, Dt_te i Indicates the end time of the data transmission task, ST i Indicates the code of the ground station for the ground data transmission mission;

[0057] Furthermore, the intersatellite collaborative task window in step 2) is characterized by:

[0058] In the global planning, a local space is obtained, namely, the intersatellite collaborative task window, and it is agreed that the rolling planning process is only carried out in the local interval and does not affect the tasks outside the collaborative interval; first, it is determined whether there are tasks that have been planned and are to be executed in the collaborative interval. If so, the priority of such tasks is defined as the lowest, and such tasks are inserted into the sequence according to the planning strategy in the subsequent intersatellite situation task planning process.

[0059] 3) Intersatellite guidance task input: Enter the intersatellite collaborative task window period described in step 2) and receive guidance tasks from the intersatellite link in real time, which are defined as intersatellite situation tasks;

[0060] Furthermore, the intersatellite situation task in step 3) has the characteristics of uncertainty, high dynamics and high timeliness, specifically:

[0061] Intersatellite situational task definition, T = {ID, δ, λ, h, t c ,v,PRI,CONF,Type};

[0062] Where, ID represents the mission number; (δ, λ, h) represents the geographical longitude, latitude, and altitude of the ground-fixed target point; t crepresents the target observation transient time, PRI represents the target priority, and CONF represents the target confidence; v represents the target motion velocity vector, which describes the dynamic properties of the input task; Type is used as an index to match the target features in the situation task database, the user-defined detection target attributes, including the detection target type feature information, etc.

[0063] 4) Task preprocessing:

[0064] 41) The visibility of the inter-satellite situation tasks received in the inter-satellite collaborative tasks is judged, and the tasks that are visible and whose visible arc segments are within the collaborative period are stored in the valid task set, which is recorded as TaskVaild. Specifically:

[0065] TaskVaild = {T1,T2,T3...T i}, where T1~T i It indicates that the intersatellite situation tasks that have passed the visibility judgment are stored in order according to the time when the tasks are received.

[0066] 42) The tasks in the effective task pool TaskVaild described in step 41) are pre-sorted according to the hierarchical priority sorting strategy, and the sorting result is defined as IMTask. The task sorting diagram is shown in Figure 2 As shown;

[0067] Furthermore, the hierarchical priority sorting strategy in step 42) is specifically:

[0068] First, sort from high to low according to the target confidence CONF, then sort from high to low according to the priority of the user-defined situation task type Type, and then sort from high to low according to the target priority PRI.

[0069] 5) Determine the task insertion position: Use a greedy algorithm to determine the position of the task to be inserted into the existing task execution sequence IMTask, and generate a new detection task sequence IMTask_New. The task insertion process diagram is shown in Figure 3 As shown;

[0070] Furthermore, in step 5), the greedy algorithm defines a greedy strategy, specifically:

[0071] Prioritize tasks with a high CONF, then tasks with a high Type priority, and finally tasks with a high PRI.

[0072] 6) Task conflict resolution: First, determine whether the newly inserted task conflicts with the tasks in the original sequence. If there is a conflict, use the greedy strategy described in step 5) to resolve the conflicting task and update IMTask_New;

[0073] 7) Data transmission task insertion: According to the data transmission task window DtWin described in step 2) i , when it is determined that the digital transmission task window period overlaps with the inter-satellite collaborative task window period, the playback task is defined as a real transmission task, and the digital transmission subsystem is set to perform a recording and playback working mode.

[0074] 8) Generation of tasks to be executed:

[0075] 81) Perform constraint check on IMTask_New and DTTask in combination with the constraint condition S in step 1), delete tasks that fail the constraint check, and update IMTask_New and DTTask;

[0076] 82) Combine IMTask_New, DTWin and the target attitude calculated by the target task visibility determination method, calculate the target attitude maneuvering time, and generate the attitude maneuvering task ATTTask;

[0077] 83) Task merging to produce tasks to be executed;

[0078] 9) Task rolling planning: Determine whether there is a new task entering the queue to be planned. If so, return to step 3), perform rolling planning on the tasks in the queue to be planned according to the rolling planning frequency f, and update IMTask_New in real time.

[0079] The contents not described in detail in the specification of the present invention belong to the common knowledge of those skilled in the art.

[0080] Although the present invention has been 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 to the technical solution of the present invention by using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope of the technical solution of the present invention.

Claims

1. A progressive local rolling optimization intersatellite collaborative task autonomous planning method, characterized in that: include: 1) According to the satellite platform resource constraints and payload working capacity, define the satellite constraint model, denoted as S; 2) Intersatellite collaborative task input: Receive the intersatellite collaborative task window registered by the user, denoted as CorpWin i , according to the task period agreed in the window, plan and generate inter-satellite collaborative tasks, set up the inter-satellite link establishment process for the inter-satellite link subsystem, and have the status of receiving inter-satellite guidance tasks in real time; receive the data transmission task window DtWin registered by the user i , according to the task period agreed in the window, plan and generate the digital transmission playback task DTTask, and perform digital transmission playback on the ground for the recorded data of the observation task; 3) Intersatellite guidance task input: Enter the intersatellite collaborative task window period described in step 2) and receive guidance tasks from the intersatellite link in real time, which are defined as intersatellite situation tasks; 4) Task preprocessing: 41) Perform visibility judgment on the inter-satellite situation tasks received in the inter-satellite collaborative tasks, and store the tasks that are visible and whose visible arc segments are within the collaborative period into the valid task set, which is recorded as TaskVaild; 42) Pre-sorting the tasks in the valid task pool TaskVaild described in step 41) according to the hierarchical priority sorting strategy, and the sorting result is defined as IMTask; 5) Determine the task insertion position: Use a greedy algorithm to determine the position of the task to be inserted into the existing task execution sequence IMTask, and generate a new detection task sequence IMTask_New; 6) Task conflict resolution: First, determine whether the newly inserted task conflicts with the tasks in the original sequence. If there is a conflict, use the greedy strategy described in step 5) to resolve the conflicting task and update IMTask_New; 7) Data transmission task insertion: According to the data transmission task window DtWin described in step 2) i , when it is determined that the digital transmission task window period overlaps with the inter-satellite coordination task window period, the playback task is defined as a real transmission task, and the digital transmission subsystem is set to perform a recording and playback working mode; 8) Generation of tasks to be executed: 81) Perform constraint check on IMTask_New and DTTask in combination with the constraint condition S in step 1), delete tasks that fail the constraint check, and update IMTask_New and DTTask; 82) Combine IMTask_New, DTWin and the target attitude calculated by the target task visibility determination method, calculate the target attitude maneuvering time, and generate the attitude maneuvering task ATTTask; 83) Task merging to produce tasks to be executed; 9) Task rolling planning: Determine whether there is a new task entering the queue to be planned. If so, return to step 3), perform rolling planning on the tasks in the queue to be planned according to the rolling planning frequency f, and update IMTask_New in real time.

2. According to claim 1, a progressive local rolling optimization intersatellite collaborative task autonomous planning method is characterized by: Step 1) The satellite constraint model is specifically: S={IMTask_t,Vad,SEA,Mvk,SWATH,SDC,FILE}; Among them, IMTask_t represents the imaging duration of the detection mission, Vad represents the payload field of view angle, SEA represents the solar altitude angle, Mvk represents the attitude maneuverability, SWATH represents the payload camera width, SDC represents the storage capacity, and FILE represents the record file number.

3. The method for autonomous planning of intersatellite collaborative tasks by progressive local rolling optimization according to claim 1 is characterized in that: Step 2) The intersatellite collaborative task window and the data transmission task window are specifically: Interplanetary collaborative task window CorpWin i = {Co_ts i ,Co_te i ,f}; Data transmission task window DtWin i ={Dt_ts i ,Dt_te i ,ST i }; Among them, Co_ts i Indicates the start time of the intersatellite collaborative mission, Co_te i represents the end time of the intersatellite collaborative mission, f represents the rolling planning frequency of the intersatellite collaborative mission; Dt_ts i Indicates the start time of the data transmission task, Dt_te i Indicates the end time of the data transmission task, ST i Indicates the ground station code for the ground data transmission mission.

4. The method for autonomous planning of intersatellite collaborative tasks by progressive local rolling optimization according to claim 1 is characterized in that: Step 2) the intersatellite collaborative task window, Its specific features are: In the global planning, a local space is obtained, namely, the intersatellite collaborative task window, and it is agreed that the rolling planning process is only carried out in the local interval and does not affect the tasks outside the collaborative interval; first, it is determined whether there are tasks that have been planned and are to be executed in the collaborative interval. If so, the priority of such tasks is defined as the lowest, and such tasks are inserted into the sequence according to the planning strategy in the subsequent intersatellite situation task planning process.

5. The method for autonomous planning of intersatellite collaborative tasks with progressive local rolling optimization according to claim 1 is characterized in that: The intersatellite situation task in step 3) has the characteristics of uncertainty, high dynamics and high timeliness, specifically: Intersatellite situational task definition, T = {ID, δ, λ, h, t c ,v,PRI,CONF,Type}; Where, ID represents the mission number; (δ, λ, h) represents the geographical longitude, latitude, and altitude of the ground-fixed target point; t c represents the target observation transient time, PRI represents the target priority, and CONF represents the target confidence; v represents the target motion velocity vector, which describes the dynamic properties of the input task; Type is used as an index to match the target features in the situation task database, the user-defined detection target attributes, including the detection target type feature information.

6. The method for autonomous planning of intersatellite collaborative tasks by progressive local rolling optimization according to claim 1 is characterized in that: Step 41) The effective task set is defined as: TaskVaild = {T1,T2,T3...T i }, where T1~T i It indicates that the intersatellite situation tasks that have passed the visibility judgment are stored in order according to the time when the tasks are received.

7. The method for autonomous planning of intersatellite collaborative tasks with progressive local rolling optimization according to claim 1 is characterized in that: Step 42) The hierarchical priority sorting strategy is specifically: First, sort from high to low according to the target confidence CONF, then sort from high to low according to the priority of the user-defined situation task type Type, and then sort from high to low according to the target priority PRI.

8. The method for autonomous planning of intersatellite collaborative tasks with progressive local rolling optimization according to claim 1 is characterized in that: Step 5) The greedy algorithm defines a greedy strategy, specifically: Prioritize tasks with a high CONF, then tasks with a high Type priority, and finally tasks with a high PRI.

9. A processing device, characterized in that: include: Memory for storing computer programs; A processor, configured to call and run the computer program from the memory to execute the method according to any one of claims 1 to 8.

10. A computer program product, characterized in that The computer program product comprises instructions, which, when the computer program product is run on a computer, cause the computer to perform the method according to any one of claims 1 to 8.

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