Constraint verification method and system based on remote sensing satellite target area imaging task

Abstract

The invention provides a constraint verification method and system based on a remote sensing satellite target area imaging task, and the method comprises the steps: carrying out the task constraint verification or imaging constraint verification according to obtained pre-imaging related parameters; if the task constraint verification is satisfied, carrying out detection processing according to the satellite load space capability until a first constraint condition is satisfied; and if the imaging constraint verification is satisfied, carrying out detection processing according to the imaging equipment and the imaging environment condition until a second constraint condition is satisfied so as to complete the pre-imaging task. Intelligent full-process constraint verification is performed according to the preset imaging parameters, whether the occupied space of the imaging task exists or whether the imaging task meets the execution condition or not is detected in a centralized mode, and therefore constraint verification is performed through the intelligent full process. The requirements of different remote sensing satellites and imaging tasks are met, functions can be expanded according to user requirements, various imaging constraint conditions can be comprehensively considered, it is ensured that the imaging tasks meet preset requirements, and the imaging quality is improved.

Description

Technical Field

[0001] This application relates to the technical field of satellite on-orbit management, and specifically to a constraint verification method and system based on the imaging task of a remote sensing satellite in a target area. Background Art

[0002] In the imaging task planning of remote sensing satellites, constraint verification is a crucial link. Due to the complexity of imaging satellite resources, different satellites have differences in payload capabilities, maneuverability, energy and storage capacities, etc., so various constraint conditions need to be strictly verified to ensure the smooth progress of the imaging task.

[0003] However, the existing constraint verification is basically manual or verified by multiple software and multiple processes, which has problems such as being error-prone, slow emergency response speed, and difficult to track.

[0004] Therefore, a new constraint verification scheme based on the imaging task of a remote sensing satellite in a target area is needed. Summary of the Invention

[0005] In view of this, the embodiments of this specification provide a constraint verification method and system based on the imaging task of a remote sensing satellite in a target area.

[0006] The embodiments of this specification provide the following technical solutions:

[0007] The embodiments of this specification provide a constraint verification method based on the imaging task of a remote sensing satellite in a target area, including:

[0008] Performing task constraint verification or imaging constraint verification according to the obtained pre-imaging related parameters;

[0009] If the task constraint verification is satisfied, performing detection processing according to the satellite payload space capability until the first constraint condition is satisfied;

[0010] If the imaging constraint verification is satisfied, performing detection processing according to the imaging device and imaging environment conditions until the second constraint condition is satisfied to complete the pre-imaging task.

[0011] The embodiments of this specification further provide a constraint verification system based on the imaging task of a remote sensing satellite in a target area, including:

[0012] An acquisition module, configured to perform task constraint verification or imaging constraint verification according to the obtained pre-imaging related parameters;

[0013] A first detection module, configured to, if the task constraint verification is satisfied, perform detection processing according to the satellite payload space capability until the first constraint condition is satisfied;

[0014] A second detection module, configured to perform detection processing according to the imaging device and imaging environment conditions until the second constraint condition is met if the imaging constraint verification is satisfied, so as to complete the pre-imaging task.

[0015] An embodiment of this specification also provides an electronic device, including: a memory, a processor, and a computer program. The computer program is stored in the memory, and the processor runs the computer program to execute the constraint verification method for the imaging task of the target area based on the remote sensing satellite described in the above technical solution.

[0016] Compared with the prior art, the beneficial effects that can be achieved by at least one of the above technical solutions adopted in the embodiments of this specification at least include:

[0017] This application provides a new constraint verification solution for the imaging task of the target area based on the remote sensing satellite. It performs intelligent full-process constraint verification according to the preset imaging parameters, centrally detects whether there is an occupied space for the imaging task or whether the imaging task meets the execution conditions, etc., so as to perform constraint verification through the intelligent full process. It not only supports users to customize imaging constraint conditions to meet the needs of different remote sensing satellites and imaging tasks, but also expands functions according to user needs in the preset imaging parameters. It can comprehensively consider various imaging constraint conditions, ensure that the imaging task meets the predetermined requirements, and improve the imaging quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of this application, the drawings required to be used in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 It is a schematic diagram of a method for comprehensively considering various constraint verification conditions provided by an embodiment of this specification;

[0020] Figure 2 It is a schematic diagram of meeting the priority constraint verification conditions provided by an embodiment of this specification;

[0021] Figure 3 It is a schematic diagram of full-process imaging constraint verification provided by an embodiment of this specification;

[0022] Figure 4 It is a schematic diagram of cloud amount verification provided by an embodiment of this specification;

[0023] Figure 5 It is a schematic diagram of imaging verification provided by an embodiment of this specification;

[0024] Figure 6It is a flowchart of a constraint verification method for a remote sensing satellite target area imaging task provided by an embodiment of this specification. Detailed implementation manners

[0025] The embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0026] The following uses specific specific examples to illustrate the implementation manners of the present application. Those skilled in the art can easily understand other advantages and effects of the present application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The present application can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without making creative efforts belong to the scope of protection of the present application.

[0027] It should be noted that the following describes various aspects of embodiments within the scope of the appended claims. It should be obvious that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is illustrative only. Based on the present application, those skilled in the art should understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number and aspects described herein can be used to implement the device and / or practice the method. In addition, this device and / or practice this method can be implemented using other structures and / or functions in addition to one or more of the aspects described herein.

[0028] It should also be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present application in a schematic manner. Only the components related to the present application are shown in the diagrams, rather than drawn according to the number, shape and size of the components in actual implementation. The type, quantity and proportion of each component in its actual implementation can be an arbitrary change, and the component layout type may also be more complex.

[0029] In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the examples can be practiced without these specific details.

[0030] In order to generate satellite control instructions for an imaging task, it is necessary to verify some constraints of the imaging task. However, the existing constraint verification is basically manual or multiple software and multiple process verifications, which have problems such as being error-prone, slow emergency response speed, and difficult to track.

[0031] In view of this, the inventors have found that the constraint conditions that need to be considered for remote sensing satellite imaging from complex satellite imaging resources mainly focus on the following aspects: time window constraint, payload capacity constraint, imaging performance constraint, energy and storage capacity constraint.

[0032] Among them, the time window constraint: It is related to the satellite orbit and the target position, and observations need to be carried out within a specific time window.

[0033] The payload capacity constraint: The payload capacity of the satellite is limited, and it is necessary to ensure that the imaging task does not exceed its maximum payload.

[0034] The imaging performance constraint: Visible light cameras cannot penetrate some obstacles, such as smoke, thick fog, etc. Therefore, it is necessary to check the weather conditions in the target area at the imaging moment, and whether the cloud cover is less than a certain specific value.

[0035] The energy and storage capacity constraint: The energy and storage capacity of the satellite are limited, and it is necessary to reasonably plan the imaging task and the data transmission strategy.

[0036] Based on this, the embodiments of this specification propose a new constraint verification scheme for the imaging task of the target area of a remote sensing satellite: performing intelligent full-process constraint verification according to preset imaging parameters, where the preset imaging parameters mainly focus on whether there is an occupied space for the imaging task or whether the imaging task meets the execution conditions, etc., so as to perform constraint verification through the intelligent full process. It not only supports users to customize imaging constraint conditions to meet the needs of different remote sensing satellites and imaging tasks, but also expands functions according to user needs in the preset imaging parameters, can comprehensively consider various imaging constraint conditions, ensure that the imaging task meets the predetermined requirements, and improve the imaging quality.

[0037] The following will describe the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.

[0038] The present application realizes the inspection of imaging constraint conditions by constructing a real satellite imaging task plan. Through the combination design of the pre-imaging task related parameters and each constraint condition, the constraint verification of the imaging task in the target area is realized, and it is confirmed whether the imaging task can be completed in the target area within the time period.

[0039] Such as Figure 6As shown in the figure, an embodiment of this specification provides a constraint verification method for the imaging task of a target area based on a remote sensing satellite, including steps S101 - S103. Among them, in step S101, according to the obtained pre - imaging related parameters, task constraint verification or imaging constraint verification is performed. In step S102, if the task constraint verification is satisfied, detection and processing are carried out according to the space capabilities of the satellite payload until the first constraint condition is met. In step S103, if the imaging constraint verification is satisfied, detection and processing are carried out according to the imaging device and imaging environment conditions until the second constraint condition is met to complete the pre - imaging task.

[0040] Based on the above, the inventors found that for the imaging task of a target area based on a remote sensing satellite, imaging task parameters can be obtained according to the input imaging task parameters, that is, users can customize pre - imaging related parameters. The system can classify the pre - imaging related parameters in a similar way by setting, such as classifying by defining different preset parameters, such as performing task constraint verification or imaging constraint verification, and considering imaging constraint conditions from different directions according to the types and ranges of predefined parameters, achieving good scalability to adapt to the needs of different remote sensing satellites and imaging tasks. It can not only complete the imaging constraint inspection task quickly and accurately, improve the efficiency of task planning, but also comprehensively consider various imaging constraint conditions to ensure that the imaging task meets the specified requirements and improve the imaging quality.

[0041] Specifically, in step S101, pre - imaging related parameters such as priority, time, and location are obtained according to the input; and then task constraint verification or imaging constraint verification is performed according to the pre - imaging related parameters.

[0042] The pre - imaging related parameters can be specifically increased, decreased, or otherwise set according to the actual situation. The embodiments of this specification are only examples. Regardless of what the pre - imaging related parameters are specifically set to, they can be classified according to the preset types or ranges, so as to perform task constraint verification or imaging constraint verification.

[0043] Task constraint verification mainly performs constraint verification from the perspective of whether there is an imaging task occupying space, and imaging constraint verification mainly performs constraint verification from the perspective of whether the imaging task meets the execution conditions.

[0044] In step S102, if the task constraint verification is satisfied, detection and processing are carried out according to the space capabilities of the satellite payload until the first constraint condition is met. Among them, the space capabilities of the satellite payload include payload capacity constraints, energy and storage capacity constraints. The first constraint condition mainly aims at the imaging task occupying space meeting the constraint verification conditions, such as the task occupying space in the satellite payload space capabilities meeting the current imaging constraints.

[0045] If the imaging constraint check is satisfied in step S103, detection and processing are performed according to the imaging device and imaging environment conditions until the second constraint condition is satisfied to complete the pre-imaging task. The imaging device and imaging environment conditions include time window constraints, imaging performance constraints, etc., which can be obtained by direct input, or by direct reading or through calls. The second constraint condition mainly performs constraint check on the angle that satisfies the execution condition for the imaging task execution.

[0046] In the embodiments of this specification, the detailed description is made with the first constraint condition being satisfied. However, the detection of the first constraint condition and the second constraint condition can be limited in a specific order according to the actual situation, or the two constraint conditions can also be detected alternately in a changed order.

[0047] In some embodiments, the pre-imaging related parameters include priority, and the priority is used to indicate the priority for task constraint check to ensure the completion of the task.

[0048] For example, the priority is set to 1, which represents the highest. As Figure 1 shown, if the priority is 1, the task constraint check is directly performed according to the priority in the pre-imaging related parameters. If the priority is not 1, the imaging constraint check of the weight process is performed.

[0049] In some other embodiments, the priority can be interspersed in the imaging constraint check process to represent a certain degree of priority for execution, etc.

[0050] In some embodiments, the detection and processing are performed according to the satellite payload space capacity until the first constraint condition is satisfied, including: if there is a task conflict, the added imaging tasks are sequentially deleted according to the priority in the pre-imaging related parameters until the satellite payload space capacity meets the current imaging capacity.

[0051] For example Figure 2 shown, during the task constraint check process, if it is detected that there is a task conflict, the added imaging tasks are sequentially deleted according to the priority until the current imaging constraint is satisfied. If there are multiple imaging tasks with priorities among the added imaging tasks, the tasks corresponding to the priorities ranked later are sequentially deleted according to the sequence of task time until the satellite payload space capacity meets the current imaging capacity. Another example is that different numerical values can be set for the priority corresponding to different priority levels. If there are multiple imaging tasks with priorities among the added imaging tasks, after sorting according to the priority level, the tasks corresponding to the priorities ranked later are sequentially deleted until the satellite payload space capacity meets the current imaging capacity.

[0052] In some embodiments, it further includes: according to the location in the pre-imaging related parameters, at least one weather application interface is called to obtain the weather conditions and cloud cover of the target area, and it is judged whether the imaging conditions are satisfied within the time of the target area.

[0053] As Figure 3 shown, at least one weather API interface is called according to the location in the pre-imaging related parameters input, and the weather parameters returned by the weather API interface are compared with the specific cloud amount value Cloud to determine whether the imaging condition is satisfied within the target area time.

[0054] In some embodiments, it further includes: calling a first weather query interface to obtain weather parameters within the local time and defining a first cloud amount; calling a second weather query interface to obtain weather parameters within the local time and defining a second cloud amount; comparing the first cloud amount and the second cloud amount with the configured specific cloud amount value respectively. When one of the first cloud amount and the second cloud amount is not greater than the specific cloud amount value, the imaging requirement is satisfied; if both the first cloud amount and the second cloud amount are greater than their respective corresponding specific cloud amount values, the imaging requirement is not satisfied and the verification process is aborted.

[0055] As Figure 4 shown, the openWeather weather query interface is called to obtain weather parameters within the local time and the cloud amount is defined as oCloud; the qWeather weather query interface is called to obtain weather parameters within the local time and the cloud amount is defined as qCloud; oCloud and qCloud are compared with the configured specific cloud amount value Cloud respectively. When one is not greater than the specific cloud amount value Cloud, it is considered that the visibility is high within the imaging time of the target area, the imaging requirement is satisfied, and the next-stage constraint verification can be carried out; if both are greater than the specific cloud amount value Cloud, it is considered that the visibility is low within the imaging time of the target area, the imaging requirement is not satisfied, and the verification process is aborted.

[0056] In some embodiments, it further includes: verifying whether the first constraint condition is satisfied or verifying whether the second constraint condition is satisfied according to the start time and end time in the pre-imaging related parameters.

[0057] As Figure 1 、 Figure 4 and Figure 5 shown, during the constraint verification process of the remote sensing satellite target area imaging task, it is verified whether the first constraint condition is satisfied according to the start time, end time and satellite payload space capability of the pre-imaging related parameters, or it is verified whether the second constraint condition is satisfied according to the start time, end time and imaging device and imaging environment conditions of the pre-imaging related parameters.

[0058] In some embodiments, it further includes: respectively expanding the first m minutes according to the start time and end time of the input pre-imaging related parameters, querying the data transmission task table, and determining whether there is a data transmission task conflict; if the imaging time is full within the data transmission time period, the imaging tasks with lower priority are deleted in turn until the current imaging task is satisfied;

[0059] Or, expand the start time and end time of the input pre-imaging related parameters by the second m minutes respectively, query the data transmission task table, and determine whether there is a data transmission task conflict; or, expand the start time and end time of the input pre-imaging related parameters by n minutes respectively, query the laser task table, and determine whether there is a laser task conflict; or, query the imaging task table according to the start time and end time of the input pre-imaging related parameters to check whether there is an imaging task conflict; if there is a conflict, return a failure result, and report the failure reason as: there is an imaging task conflict during this time period; if there is no conflict, calculate whether the imaging time of all imaging tasks on a single track plus the current imaging time is less than the imaging specific value t. If it is satisfied, perform imaging time verification, current imaging time length verification or laser task verification. If it is not satisfied, return a failure status and report the failure reason as: the remaining imaging time in this time period is s seconds. Please modify the imaging time and retry.

[0060] As Figure 2 shown, according to the priority of 1 and combining the input imaging task parameters, let the input start time be startTime and the end time be endTime. The data transmission task expansion time is the first m, then define the start time of the data transmission comparison time as stAdd = startTime - m, and the end time as edAdd = endTime + m. The longest imaging time on a single track is t.

[0061] Query the data transmission task table according to stAdd and edAdd, and define the data transmission task table time field as rst, satisfying the condition rst ≤ edAdd && rst ≥ stAdd; then it means there is a data transmission task conflict, return a failure status, and report the failure reason as: the current imaging time conflicts with the data transmission task.

[0062] Query the data transmission plan table according to startTime. If there is a record, take out the time field of the data transmission task in the record and define it as the start time scStartTime within the data transmission task interval; query the data transmission plan table according to endTime. If there is a record, take out the time field of the data transmission task in the record and define it as the end time scEndTime within the data transmission task interval. If there is no record, it means there is no data transmission cycle for the current imaging time, return a failure status and report the failure reason as: there is no data transmission cycle after the current imaging task.

[0063] Query the camera task table according to scStartTime and scEndTime to check if there is an imaging task. If there is an imaging task, it is necessary to calculate the imaging time of all current imaging tasks and check if the sum of the current input imaging time exceeds the maximum single-track imaging time t. If the imaging time t is exceeded, delete the imaging tasks with low priority according to the imaging priority until the current imaging requirements are met. That is, complete the imaging time verification and the verification of the length of the current imaging time.

[0064] In some embodiments, query the TT&C task table according to startTime, and calculate the TT&C circle number near the startTime. This circle number is the TT&C circle number for the injectable imaging task, and return the success status and the TT&C circle number.

[0065] Or, as Figures 3 - 5 shown, if the priority level is not 1, according to the input imaging task parameters, set the input location as location, the start time as startTime, and the end time as endTime. The extended time for the data transmission task is the second m, and the extended time for the laser task is n. Then define the start time of the data transmission comparison time as stAdd = startTime - m, the end time as edAdd = endTime + m, the start time of the laser comparison time as laserStAdd = startTime - n, and the end time as laserEdAdd = endTime + n. Set the maximum single-track imaging time as t.

[0066] According to location, startTime, and endTime, call the openWeatherapi and qWeatherapi, call the openWeather weather query interface to obtain the weather parameters within the local time, and define the cloud amount as oCloud; call the qWeather weather query interface to obtain the weather parameters within the local time, and define the cloud amount as qCloud; compare oCloud and qCloud with the configured specific cloud amount value Cloud respectively.

[0067] When there is one that is not greater than the specific cloud amount value Cloud, it is considered that the visibility is high during the imaging time of the target area, meeting the imaging requirements, and the next-stage constraint verification can be carried out; if both are greater than the specific cloud amount value Cloud, it is considered that the visibility is low during the imaging time of the target area, not meeting the imaging requirements, and the verification process is aborted.

[0068] Among them, according to location, startTime, and endTime, call the openWeatherapi and qWeatherapi, call the openWeather weather query interface to obtain weather parameters within the local time, and define the cloud amount as oCloud; call the qWeather weather query interface to obtain weather parameters within the local time, and define the cloud amount as qCloud; compare oCloud and qCloud with the configured specific cloud amount value Cloud respectively. When one of them is not greater than the specific cloud amount value Cloud, it is considered that the visibility is high during the imaging time of the target area, meeting the imaging requirements, and the next stage of constraint verification can be carried out; if both are greater than the specific cloud amount value Cloud, it is considered that the visibility is low during the imaging time of the target area, not meeting the imaging requirements, and the verification process is aborted.

[0069] Query the data transmission schedule table according to startTime. If there is a record, take out the time field of the data transmission task in the record and define it as the start time scStartTime within the data transmission task interval; query the data transmission schedule table according to endTime. If there is a record, take out the time field of the data transmission task in the record and define it as the end time scEndTime within the data transmission task interval. If there is no record, it means that there is no data transmission cycle at the current imaging time, and return the failure status and report the failure reason as: there is no data transmission cycle after the current imaging task.

[0070] Query the camera task table according to scStartTime and scEndTime to check if there is an imaging task. If there is an imaging task, it is necessary to calculate the imaging time of all current imaging tasks and check if adding the currently input imaging time exceeds the maximum single-track imaging time t. If it does not exceed, proceed to the next verification; if it exceeds, return the failure status and report the failure reason as: the imaging time is full and a new imaging task cannot be added. That is, complete the imaging time verification and the verification of the length of the current imaging time.

[0071] Query the laser task table according to laserStAdd and laserEdAdd to check if there is a conflict with the laser task. If there is a conflict, return the failure result and report the failure reason as: conflict with the laser task; if the conditions are met, proceed to the next verification. That is, complete the laser task verification.

[0072] Query the TT&C task table according to startTime, calculate the TT&C cycle near the startTime, and this cycle is the TT&C cycle number for uploading the imaging task, and return the success status and the TT&C cycle number.

[0073] In some embodiments, it further includes: for the imaging tasks that pass the constraint verification, query the TT&C task table according to the start time of the pre-imaging related parameters, return a successful result, and report the TT&C loop number for injecting the satellite control instruction to complete the imaging task.

[0074] For example, according to startTime, query the TT&C task table, calculate the TT&C loop close to the startTime, and this loop is the TT&C loop number for uploading the imaging task, and return the successful status and the TT&C loop number.

[0075] Embodiments of this specification determine the visibility of the target area through the time, location, and priority of the input parameters. For example, according to the input imaging task parameters, call the weather api interface to comprehensively judge the visibility of the target area and check whether the target area is suitable for the imaging task; or according to the input imaging task parameters, check whether there is a conflict with other tasks, and then check whether the camera switch time is satisfied and whether the imaging conditions are met; finally, add the tasks that meet the imaging conditions to the imaging task plan.

[0076] Specifically, according to the input pre-imaging related parameters (time, location, priority), when the priority is 1, query the data transmission task table to determine whether there is a data transmission task conflict. If there is a conflict, the verification fails; query whether there is an imaging task conflict during the time period of the pre-imaging related parameters. If there is a conflict, delete the imaging tasks with lower priority one by one until the current imaging constraints are met.

[0077] When the priority is not 1, after calling at least one weather api interface to obtain the weather conditions and cloud amount of the target area, verify with the specific value Cloud of the cloud amount to determine whether the target area meets the imaging conditions. If the cloud amount requirement is not met, the result is verification failure and the imaging conditions are not met. If the cloud amount requirement is met, perform data transmission task verification, laser task verification, imaging time verification, and verification of the imaging time length of this time, etc.

[0078] Embodiments of this specification implement the constraint verification of the imaging tasks in the target area to confirm whether the imaging tasks can be completed in the target area within a time period. The system has the following characteristics:

[0079] High efficiency: The system adopts advanced algorithms and technologies, can quickly and accurately complete the imaging constraint check task, and improve the efficiency of task planning.

[0080] Accuracy: The system can comprehensively consider various imaging constraint conditions, ensure that the imaging tasks meet the predetermined requirements, and improve the imaging quality.

[0081] Flexibility: The system supports users to customize imaging constraint conditions and can adapt to the needs of different remote sensing satellites and imaging tasks.

[0082] Scalability: The system has good scalability and can be functionally extended and optimized according to user requirements.

[0083] An embodiment of this specification also provides a constraint verification system for a remote sensing satellite target area imaging task. The system includes:

[0084] An acquisition module, configured to perform task constraint verification or imaging constraint verification according to the acquired pre-imaging related parameters;

[0085] A first detection module, configured to, if the task constraint verification is satisfied, perform detection processing according to the satellite payload space capability until the first constraint condition is satisfied;

[0086] A second detection module, configured to, if the imaging constraint verification is satisfied, perform detection processing according to the imaging device and imaging environment conditions until the second constraint condition is satisfied to complete the pre-imaging task.

[0087] This system can correspondingly be used to execute Figure 6 the steps in the method embodiment shown. The implementation principle and technical effects are similar and will not be elaborated here.

[0088] An electronic device provided by an embodiment of this specification, the electronic device includes: a processor, a memory, and a computer program; where

[0089] The memory is used to store the computer program, and the memory can also be a flash memory. The computer program is, for example, an application program, a functional module, etc. that implements the above method.

[0090] The processor is configured to execute the computer program stored in the memory to implement each step executed by the device in the above method. Specifically, reference can be made to the relevant descriptions in the previous method embodiment.

[0091] Optionally, the memory can be either independent or integrated with the processor.

[0092] When the memory is a device independent of the processor, the device may further include:

[0093] A bus, configured to connect the memory and the processor.

[0094] This application also provides a readable storage medium, in which a computer program is stored, and when the computer program is executed by a processor, it is used to implement the methods provided by the above various embodiments.

[0095] Among them, the readable storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The computer storage medium can be any available medium accessible by a general-purpose or special-purpose computer. For example, the readable storage medium is coupled to the processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Additionally, the ASIC can be located in a user device. Of course, the processor and the readable storage medium can also exist as discrete components in a communication device. The readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0096] For the various embodiments in this specification, the same or similar parts can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the product embodiments described later, since they correspond to the methods, the descriptions are relatively simple, and the relevant parts can be referred to the descriptions in the system embodiments.

[0097] As described above, the above are only the specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present application should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A constraint verification method based on remote sensing satellite target area imaging task, characterized in that: include: Perform task constraint verification or imaging constraint verification based on the acquired pre-imaging related parameters; If the mission constraint check is satisfied, detection processing is performed according to the satellite payload space capability until the first constraint condition is satisfied; If the imaging constraint check is satisfied, detection processing is performed according to the imaging device and imaging environment conditions until the second constraint condition is satisfied to complete the pre-imaging task.

2. The constraint verification method based on remote sensing satellite target area imaging task according to claim 1 is characterized in that: The pre-imaging related parameters include a priority, which is used to indicate that the task constraint check should be performed first to ensure the completion of the task.

3. The constraint verification method based on remote sensing satellite target area imaging task according to claim 1 is characterized in that: Perform detection processing according to the satellite payload space capability until the first constraint condition is met, including: If there is a task conflict, the added imaging tasks will be deleted in sequence according to the priority in the pre-imaging related parameters until the satellite payload space capability meets the imaging capacity of this time.

4. The constraint verification method based on remote sensing satellite target area imaging task according to claim 1 is characterized in that: Also includes: According to the location in the pre-imaging related parameters, at least one weather application interface is called to obtain the weather conditions and cloud cover of the target area, and determine whether the imaging conditions are met within the target area within the time.

5. The constraint verification method based on remote sensing satellite target area imaging task according to claim 4 is characterized in that: Also includes: Call the first weather query interface to obtain the weather parameters in the local time and define the first cloud cover; Call the second weather query interface to obtain the weather parameters in the local time and define the second cloud cover; Compare the first cloud amount and the second cloud amount with the configured specific cloud amount value respectively, and when one of the first cloud amount and the second cloud amount is not greater than the specific cloud amount value, the imaging requirement is met; If both the first cloud amount and the second cloud amount are greater than their corresponding specific cloud amount values, the imaging requirements are not met and the verification process is terminated.

6. The constraint verification method based on remote sensing satellite target area imaging task according to claim 1 is characterized in that: Also includes: According to the start time and the end time in the pre-imaging related parameters, it is checked whether the first constraint condition is satisfied or whether the second constraint condition is satisfied.

7. The constraint verification method based on remote sensing satellite target area imaging task according to claim 6 is characterized in that: Also includes: According to the start time and end time of the input pre-imaging related parameters, the first m minutes of expansion are performed respectively, and the data transmission task table is queried to determine whether there is a data transmission task conflict; If the imaging time within the data transmission time period is full, the imaging tasks with lower priorities will be deleted in turn until the current imaging task is satisfied; Or, according to the start time and end time of the input pre-imaging related parameters, expand the second m minutes respectively, query the data transmission task table, and determine whether there is a data transmission task conflict; or, according to the start time and end time of the input pre-imaging related parameters, expand the second m minutes respectively, query the laser task table, and determine whether there is a laser task conflict; or, according to the start time and end time of the input pre-imaging related parameters, query the imaging task table to check whether there is an imaging task conflict; If there is a conflict, a failure result is returned, and the reason for the failure is reported as: there is an imaging task conflict within this time period; If there is no conflict, calculate whether the imaging time of all imaging tasks on the single track plus the current imaging time is less than the specific imaging value t. If it is satisfied, perform imaging time verification, current imaging time length verification or laser task verification. If it is not satisfied, return to failure status and report the reason for failure: the remaining imaging time in this time period is s seconds, please modify the imaging time and try again.

8. The constraint verification method based on remote sensing satellite target area imaging task according to claim 1 is characterized in that: Also includes: For imaging tasks that pass constraint verification, the measurement and control task table is queried according to the start time of the pre-imaging related parameters, and a successful result is returned, and the measurement and control circle number of the injected satellite control command is reported to complete the imaging task.

9. A constraint verification system based on remote sensing satellite target area imaging mission, characterized in that: include: An acquisition module, used for performing task constraint verification or imaging constraint verification according to the acquired pre-imaging related parameters; A first detection module is used for, if the mission constraint check is satisfied, performing detection processing according to the satellite payload space capability until the first constraint condition is satisfied; The second detection module is used to perform detection processing according to the imaging device and imaging environment conditions until the second constraint condition is met if the imaging constraint check is met, so as to complete the pre-imaging task.

10. An electronic device, characterized in that: include: A memory, a processor and a computer program, wherein the computer program is stored in the memory, and the processor runs the computer program to execute the constraint verification method based on the remote sensing satellite target area imaging task according to any one of claims 1 to 8.

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