Agile optical satellite multi-target fast maneuvering autonomous task planning method and system

Abstract

The invention provides a multi-target fast maneuvering autonomous task planning method and system for an agile optical satellite. The method comprises the following steps: a visible window queue generation step: calculating and screening out a visible window queue meeting expectation according to priority; and a task allocation step: performing priority ranking on the generated visible window queue, selecting the optimal observation moment and the optimal observation attitude of the first target, sending the optimal observation moment and the optimal observation attitude into a new queue, and performing task allocation of the target window. According to the method, multiple targets can be primarily screened within limited startup time of an agile satellite in a multi-target scene, and a better working time window conforming to priority setting is generated by considering priority requirements; the method can be suitable for a multi-target detection scene, enables a satellite to have the capability of autonomously selecting a working window to achieve a better working effect, and provides a solution for the problem that target points are discrete and are difficult to cover within one startup duration.

Description

Technical Field

[0001] The present invention relates to the field of optical satellites, and in particular to a method and system for planning multi-target rapid maneuvering autonomous tasks for an agile optical satellite. Background Art

[0002] With the rapid development of space technology, optical satellites are increasingly used in many fields such as geography, military, and meteorology. Traditional optical satellite mission planning often relies on manual operations by ground control centers, which is not only inefficient, but also may not be able to make the best decision in time when faced with sudden multi-target tasks.

[0003] Agile optical satellites, with their high maneuverability and flexibility, can quickly change their observation posture, thereby completing continuous observation of multiple targets in a short period of time. However, how to design an efficient and autonomous mission planning method for agile optical satellites in multi-target scenarios to ensure the maximum utilization of satellite resources and meet observation needs is a current technical challenge.

[0004] Existing multi-objective tasks mainly rely on simple time order or priority order for execution, and adopt simple adjustment and cancellation strategies when tasks conflict, which cannot maximize the efficiency of satellite resource utilization. Therefore, it is urgent to develop a task planning method that can quickly carry out multi-objective task planning while meeting constraints such as attitude maneuvers, adaptively coordinate task sequences, and maximize satellite utilization efficiency. Summary of the invention

[0005] In view of the defects in the prior art, the object of the present invention is to provide a method and system for agile optical satellite multi-target rapid maneuvering autonomous mission planning.

[0006] A method for planning multi-target rapid maneuvering autonomous missions for an agile optical satellite provided by the present invention includes:

[0007] Visible window queue generation step: filter out the expected visible window queue based on priority calculation;

[0008] Task allocation step: prioritize the generated visible window queues, select the best observation time and best observation posture of the first target and send them to the new queue to allocate tasks to the target window.

[0009] Preferably, the visible window queue generating step comprises:

[0010] Enter the time window threshold and visible time window to form the first task queue;

[0011] Create a second task queue according to the order of the time windows, and store the time windows in the first task queue in the second task queue;

[0012] Among the multiple time windows, the length of the last time window is greater than the length of the first task queue;

[0013] Among multiple end times, if the length of the last end time is greater than the length of the second task queue, the second task queue and the minimum start time are output;

[0014] The minimum start time includes the difference between the last end time and the time window threshold.

[0015] Preferably, the task allocation step includes:

[0016] Based on the earliest visible time and the parameters of a single push-sweep duration, the maneuvering time is calculated according to the required attitude and the front and back attitudes, and each insertable position is inserted; if the insertion is successful, the next target window is allocated, otherwise the preset iterative search step is added to the earliest visible time as the start time of the work, and insertion is performed again until the insertion is successful or the window end time is exceeded.

[0017] Preferably, the visible window queue generation step includes solving the start and end time of the multi-target detection task; and the task allocation step includes solving the observation timing problem of each point in the satellite multi-target detection task.

[0018] Preferably, the input of the visible window queue generation step includes the priority of each target point and the visible window, and the output includes the load startup time and shutdown time; the input of the task allocation step includes the position information of each point, the observable window, the single working time, the single startup time, and the optimal iterative search step, and the output includes the observation timing of each point in the optimal multi-target detection task.

[0019] An agile optical satellite multi-target rapid maneuvering autonomous mission planning system provided by the present invention comprises:

[0020] Visible window queue generation module: Filters out the expected visible window queues based on priority calculation;

[0021] Task allocation module: prioritizes the generated visible window queues, selects the best observation time and best observation posture of the first target and sends them to the new queue to allocate tasks to the target window.

[0022] Preferably, the visible window queue generation module includes:

[0023] Enter the time window threshold and visible time window to form the first task queue;

[0024] Create a second task queue according to the order of the time windows, and store the time windows in the first task queue in the second task queue;

[0025] Among the multiple time windows, the length of the last time window is greater than the length of the first task queue;

[0026] Among multiple end times, if the length of the last end time is greater than the length of the second task queue, the second task queue and the minimum start time are output;

[0027] The minimum start time includes the difference between the last end time and the time window threshold.

[0028] Preferably, the task allocation module includes:

[0029] Based on the earliest visible time and the parameters of a single push-sweep duration, the maneuvering time is calculated according to the required attitude and the front and back attitudes, and each insertable position is inserted; if the insertion is successful, the next target window is allocated, otherwise the preset iterative search step is added to the earliest visible time as the start time of the work, and insertion is performed again until the insertion is successful or the window end time is exceeded.

[0030] Preferably, the visible window queue generation module includes solving the start and end time of the multi-target detection task; the task allocation module includes solving the observation timing problem of each point in the satellite multi-target detection task.

[0031] Preferably, the input of the visible window queue generation module includes the priority of each target point and the visible window, and the output includes the load startup time and shutdown time; the input of the task allocation module includes the position information of each point, the observable window, the single working time, the single startup time, and the optimal iterative search step size, and the output includes the observation timing of each point in the optimal multi-target detection task.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. The present invention can perform preliminary screening of multiple targets within a limited startup time for agile satellites in multi-target scenarios, consider priority requirements, and generate a better working time window that meets the priority settings; it can be applicable to multi-target detection scenarios, so that the satellite has the ability to autonomously select a working window to achieve a better working effect, and provides a solution to the problem that discrete target points are difficult to cover within one startup time.

[0034] 2. Aiming at the scenario where agile satellites perform mobile detection of a large number of target points under startup time, the present invention proposes a task allocation method that takes attitude maneuvering time into consideration and a task queue generation method that takes priority, visible window, and maneuvering duration into consideration when all target points are visible. This method can solve the problems of target point screening and detection timing decision-making faced by agile satellites in rapid mobile detection of multiple target points, and has good practicality.

[0035] Other beneficial effects of the present invention will be explained in the specific implementation manner through the introduction of specific technical features and technical solutions. Through the introduction of these technical features and technical solutions, those skilled in the art should be able to understand the beneficial technical effects brought about by the technical features and technical solutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0037] Figure 1 The figure is a flow chart of the method of the present invention.

[0038] Figure 2 The flowchart of the method for generating a visible window queue taking priority into consideration according to the present invention.

[0039] Figure 3 The present invention is a flow chart of the task allocation method considering the posture maneuvering time. DETAILED DESCRIPTION

[0040] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0041] In order to meet the real-time or near-real-time mission planning requirements of multiple constraints and multiple objectives in agile optical satellite mission planning, this paper proposes a new optical autonomous mission planning algorithm. Different from the traditional sequential observation method, this algorithm adopts a rule-based task adjustment and conflict resolution strategy, while considering multiple constraints such as single startup time and satellite maneuvering time, so as to ensure that the observation plan with the best solution is obtained under the premise of meeting the constraints.

[0042] Reference Figure 1 As shown in the figure, a method for planning multi-target rapid maneuvering autonomous missions for an agile optical satellite includes the following components:

[0043] 1. A method for generating a visible window queue taking priority into account;

[0044] 2. Task allocation method considering attitude maneuvering time;

[0045] In the visible window queue generation method considering priority, the visible window of each target is first calculated by observing target parameters such as target longitude and latitude, as well as task constraints such as mission start time, complaint events, minimum observation time of the target, single-star repeated observation interval, and satellite status, time, GNSS data, etc., and then each target window is screened on the basis of priority to eliminate target windows that do not meet the single power-on time.

[0046] In the task allocation method considering the attitude maneuvering time, based on the above implementation results, the generated window queues are prioritized, the first target best observation time and the best observation attitude are selected and sent to the new queue, and then the maneuvering time is calculated according to the required attitude and the front and back attitudes based on the earliest visible time, single push sweep duration and other parameters, and each insertable position is inserted. If the insertion is successful, the next target window is allocated, otherwise the earliest visible time plus the optimal iterative search step is used as the work start time, and the insertion is performed again until it succeeds or exceeds the window end time.

[0047] Among them, the visible window queue generation method taking priority into consideration is applicable to mission scenarios including but not limited to optical detection satellites, synthetic aperture radar imaging satellites, radar detection satellites, and other agile / non-agile satellites observing multiple target points on the ground, and is used to solve the start and end times of multi-target detection missions.

[0048] The priority of each target point, visible window, etc. are taken as key input conditions, and the optimal load startup and shutdown times are output to achieve better overall observation performance.

[0049] Reference Figure 2 As shown, in one embodiment, the specific steps are:

[0050] Step 1: Enter the time window threshold Time_max and Num target visible time windows to form queue A;

[0051] Step 2: Let i=1;

[0052] Step 3: Determine if i is not equal to 1, if so, proceed to step 3, otherwise proceed to step 10;

[0053] Step 4: Extract the i-th window Tin_i in queue A;

[0054] Step 5: Determine whether Tin_i is greater than the minimum start time Min_Tin in queue B. If so, proceed to step 6; otherwise, proceed to step 12.

[0055] Step 6: Determine whether Tin_i is less than the maximum start time Max_Tin in queue B. If so, execute step 7; otherwise, execute step 13.

[0056] Step 7: Store the i-th time window in queue A into queue B;

[0057] Step 8: Determine whether i is greater than or equal to the length of queue A. If so, go to step 14; otherwise, go to step 9.

[0058] Step 9: i++, return to step 3;

[0059] Step 10: Create task queue B and store the i-th time window in queue A into queue B;

[0060] Step 11: Let Min_Yin = Tin_i, Max_Yin = Tin_i, and return to step 8;

[0061] Step 12: Determine whether Max_Tin-Tin_i is less than Time_max. If so, set Min_Tin=Tin_i and return to step 7; otherwise, return to step 9;

[0062] Step 13: Determine whether Tin_i-Min_Tin is less than Time_max. If so, set Max_Tin=Tin_i and return to step 7; otherwise, return to step 9.

[0063] Step 14: let k=1;

[0064] Step 15: Determine whether k is less than the length of queue B. If so, execute step 16; otherwise, execute step 19.

[0065] Step 16: Determine the k-th time end time - queue B minimum start time Min_Tin, if yes, go to step 17, otherwise go to step 18;

[0066] Step 17: K++, return to step 15;

[0067] Step 18: Set the end time of the kth window in queue B = Min_Tin + Time_max, and return to step 17;

[0068] Step 19: Output queue B and the minimum start time Min_Tin.

[0069] The task allocation method considering attitude maneuvering time is used to solve the observation timing problem of each point in the satellite multi-target detection mission. The position information of each point, observable window, single working time, single power-on time, optimal iterative search step size, etc. are used as key input parameters to output the optimal observation timing of each point in the multi-target detection mission, so as to improve the overall observation performance.

[0070] Reference Figure 3As shown, the key operation steps require the application of the maneuvering duration calculation method and the step length / variable step length working time search method. In one embodiment, the specific steps are as follows:

[0071] Step 1: Let i_B = 0 and length_C = 0;

[0072] Step 2: Determine whether i <= the length of queue B. If so, proceed to Step 3; otherwise, go to Step 31;

[0073] Step 3: Determine whether length_C = 0. If so, proceed to Step 4; otherwise, go to Step 6;

[0074] Step 4: Record the best observation time and the best observation attitude of the i_B-th target in queue B and send them to queue C;

[0075] Step 5: Increment i_B by 1, increment length_C by 1, and return to Step 2;

[0076] Step 6: Let j = 0 and k = 0;

[0077] Step 7: Let T_worktemp = Tin_i + 0.5 * t_work + k * dt_sch, where Tin_i is the visible start time of the i-th target in queue B, t_work is the single push sweep duration, and dt_sch is the optimal iterative search step length;

[0078] Step 8: Determine whether T_worktemp < Tout_i, where Tout_i is the visible end time of the i-th target in queue B. If so, execute Step 9; otherwise, execute Step 14;

[0079] Step 9: Calculate the attitude Pos_i of the satellite towards the i-th target in queue B at the time of T_worktemp;

[0080] Step 10: Calculate the time T_turn2 required for Pos_i to reach the push sweep attitude of the (j + 1)-th task in queue C;

[0081] Step 11: Determine whether Tin_i + 0.5 * t_work + T_turn2 < the start time T_start of the (j + 1)-th task in queue B. If so, execute Step 12; otherwise, execute Step 11;

[0082] Step 12: Increment k by 1 and go to Step 7;

[0083] Step 13: Select T_worktemp as the working time and Pos_i of the i_B-th target in queue B and send them to queue C at the (j + 1)-th position, and return to Step 5;

[0084] Step 14: Increment j by 1;

[0085] Step 15: Judge whether 1 < j <= Length_C. If so, execute Step 16; otherwise, execute Step 24;

[0086] Step 16: k = 0;

[0087] Step 17: Let T_worktemp = Tin_i + 0.5 * t_work + k * dt_sch;

[0088] Step 18: Judge whether T_worktemp < Tout_i, where Tout_i is the visible end time of the i-th target in queue B. If so, execute Step 19; otherwise, execute Step 14;

[0089] Step 19: Calculate the attitude Pos_i of the satellite towards the i-th target in queue B at time T_worktemp;

[0090] Step 20: Calculate the time T_turn1 required for the push-sweeping attitude of the j-th task in queue C to reach Pos_i

[0091] Step 21: Calculate the time T_turn2 required for Pos_i to reach the push-sweeping attitude of the (j + 1)-th task in queue C;

[0092] Step 22: Judge whether Tin_i - 0.5 * t_work - T_turn2 > the end time T_over of the j-th task in queue B. If so, execute Step 23; otherwise, execute Step 17;

[0093] Step 23: Judge whether Tin_i + 0.5 * t_work + T_turn2 < the start time T_start of the (j + 1)-th task in queue B. If so, execute Step 13; otherwise, execute Step 17;

[0094] Step 24: Judge whether j > Length_C. If so, execute Step 25; otherwise, execute Step 30

[0095] Step 25: k = 0;

[0096] Step 26: Let T_worktemp = Tin_i + 0.5 * t_work + k * dt_sch;

[0097] Step 27: Judge whether T_worktemp < Tout_i, where Tout_i is the visible end time of the i-th target in queue B. If so, execute Step 28; otherwise, execute Step 30;

[0098] Step 28: Calculate the time T_turn1 required for the push-sweeping attitude of the j-th task in queue C to reach Pos_i

[0099] Step 29: Determine whether Tin_i-0.5*t_work-T_turn2> the end time T_over of the j-th task in queue B. If so, execute step 13; otherwise, execute step 26.

[0100] Step 30: i_B++, return to step 2;

[0101] Step 31: Output queue C.

[0102] The present invention can perform preliminary screening of multiple targets within a limited startup time for agile satellites in multi-target scenarios, consider priority requirements, and generate a better working time window that meets the priority settings; it can be applicable to multi-target detection scenarios, so that the satellite has the ability to autonomously select a working window to achieve a better working effect, and provides a solution to the problem that discrete target points are difficult to cover within one startup time.

[0103] Aiming at the scenario where agile satellites perform mobile detection of a large number of target points under the condition of startup time, when all target points are visible, a task queue generation method that takes into account attitude maneuvering time and design priorities, visible windows, and maneuvering duration is proposed. This method can solve the problems of target point screening and detection timing decision-making when agile satellites face rapid mobile detection of multiple target points, and has good practicality.

[0104] The present invention also provides an agile optical satellite multi-target rapid maneuvering autonomous task planning system, which can be implemented by executing the process steps of the agile optical satellite multi-target rapid maneuvering autonomous task planning method, that is, those skilled in the art can understand the agile optical satellite multi-target rapid maneuvering autonomous task planning method as a preferred implementation of the agile optical satellite multi-target rapid maneuvering autonomous task planning system.

[0105] Specifically, an agile optical satellite multi-target rapid maneuvering autonomous mission planning system includes:

[0106] Visible window queue generation module: Filters out the expected visible window queues based on priority calculation;

[0107] Task allocation module: prioritizes the generated visible window queues, selects the best observation time and best observation posture of the first target and sends them to the new queue to allocate tasks to the target window.

[0108] The visible window queue generation module comprises:

[0109] Enter the time window threshold and visible time window to form the first task queue;

[0110] Create a second task queue according to the order of the time windows, and store the time windows in the first task queue in the second task queue;

[0111] Among the multiple time windows, the length of the last time window is greater than the length of the first task queue;

[0112] Among multiple end times, if the length of the last end time is greater than the length of the second task queue, the second task queue and the minimum start time are output;

[0113] The minimum start time includes the difference between the last end time and the time window threshold.

[0114] The task allocation module includes:

[0115] Based on the earliest visible time and the parameters of a single push-sweep duration, the maneuvering time is calculated according to the required attitude and the front and back attitudes, and each insertable position is inserted; if the insertion is successful, the next target window is allocated, otherwise the preset iterative search step is added to the earliest visible time as the start time of the work, and insertion is performed again until the insertion is successful or the window end time is exceeded.

[0116] The visible window queue generation module includes solving the start and end time of the multi-target detection task; the task allocation module includes solving the observation timing problem of each point in the satellite multi-target detection task.

[0117] The input of the visible window queue generation module includes the priority of each target point and the visible window, and the output includes the load startup time and shutdown time; the input of the task allocation module includes the position information of each point, the observable window, the single working time, the single startup time, and the optimal iterative search step size, and the output includes the observation timing of each point in the optimal multi-target detection task.

[0118] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0119] In the description of the present application, it should be understood that the terms "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0120] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for planning multi-target rapid maneuvering autonomous missions for an agile optical satellite, characterized in that: include: Visible window queue generation step: filter out the expected visible window queue based on priority calculation; Task allocation step: prioritize the generated visible window queues, select the best observation time and best observation posture of the first target and send them to the new queue to allocate tasks to the target window.

2. The method for planning multi-target rapid maneuvering autonomous missions of an agile optical satellite according to claim 1, characterized in that: The visible window queue generation step comprises: Enter the time window threshold and visible time window to form the first task queue; Create a second task queue according to the order of the time windows, and store the time windows in the first task queue in the second task queue; Among the multiple time windows, the length of the last time window is greater than the length of the first task queue; Among multiple end times, if the length of the last end time is greater than the length of the second task queue, the second task queue and the minimum start time are output; The minimum start time includes the difference between the last end time and the time window threshold.

3. The method for planning multi-target rapid maneuvering autonomous missions of an agile optical satellite according to claim 1, characterized in that: The task allocation step comprises: Based on the earliest visible time and the parameters of a single push-sweep duration, the maneuvering time is calculated according to the required attitude and the front and back attitudes, and each insertable position is inserted; if the insertion is successful, the next target window is allocated, otherwise the preset iterative search step is added to the earliest visible time as the start time of the work, and insertion is performed again until the insertion is successful or the window end time is exceeded.

4. The method for planning multi-target rapid maneuvering autonomous missions of an agile optical satellite according to claim 1, characterized in that: The visible window queue generation step includes solving the start and end time of the multi-target detection task; the task allocation step includes solving the observation timing problem of each point in the satellite multi-target detection task.

5. The method for planning multi-target rapid maneuvering autonomous missions of an agile optical satellite according to claim 1, characterized in that: The input of the visible window queue generation step includes the priority of each target point and the visible window, and the output includes the load startup time and shutdown time; the input of the task allocation step includes the position information of each point, the observable window, the single working time, the single startup time, and the optimal iterative search step, and the output includes the observation timing of each point in the optimal multi-target detection task.

6. An agile optical satellite multi-target rapid maneuvering autonomous mission planning system, characterized in that: include: Visible window queue generation module: Filters out the expected visible window queues based on priority calculation; Task allocation module: prioritizes the generated visible window queues, selects the best observation time and best observation posture of the first target and sends them to the new queue to allocate tasks to the target window.

7. The agile optical satellite multi-target rapid maneuvering autonomous mission planning system according to claim 6 is characterized in that: The visible window queue generation module comprises: Enter the time window threshold and visible time window to form the first task queue; Create a second task queue according to the order of the time windows, and store the time windows in the first task queue in the second task queue; Among the multiple time windows, the length of the last time window is greater than the length of the first task queue; Among multiple end times, if the length of the last end time is greater than the length of the second task queue, the second task queue and the minimum start time are output; The minimum start time includes the difference between the last end time and the time window threshold.

8. The agile optical satellite multi-target rapid maneuvering autonomous mission planning system according to claim 6 is characterized in that: The task allocation module includes: Based on the earliest visible time and the parameters of a single push-sweep duration, the maneuvering time is calculated according to the required attitude and the front and back attitudes, and each insertable position is inserted; if the insertion is successful, the next target window is allocated, otherwise the preset iterative search step is added to the earliest visible time as the start time of the work, and insertion is performed again until the insertion is successful or the window end time is exceeded.

9. The agile optical satellite multi-target rapid maneuvering autonomous mission planning system according to claim 6, characterized in that: The visible window queue generation module includes solving the start and end time of the multi-target detection task; the task allocation module includes solving the observation timing problem of each point in the satellite multi-target detection task.

10. The agile optical satellite multi-target rapid maneuvering autonomous mission planning system according to claim 6, characterized in that: The input of the visible window queue generation module includes the priority of each target point and the visible window, and the output includes the load startup time and shutdown time; the input of the task allocation module includes the position information of each point, the observable window, the single working time, the single startup time, and the optimal iterative search step size, and the output includes the observation timing of each point in the optimal multi-target detection task.

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