A multi-satellite coordinated intelligent mission execution method

Abstract

This specification discloses a multi-satellite collaborative intelligent task execution method, which acquires the satellite trajectory data of each satellite in advance, determines the rectangular area and timestamp corresponding to each trajectory point of each satellite, determines the imaging area and imaging time in response to the user's operation, and generates an imaging task, matches the imaging area and imaging time with the stored rectangular area and timestamp corresponding to each trajectory point, determines the target satellite, target imaging area and target imaging time for performing the imaging task, and performs the imaging task accordingly. It can be seen that pre-planning and designing tasks based on the trajectory data of multiple satellites greatly reduces the planning waiting time of the user's imaging tasks and improves the efficiency of task execution. In addition, by closely connecting user needs with satellite resources through digital means, the intelligence and automation of task planning are realized, which greatly improves the efficiency of satellite remote sensing data management and task execution.

Description

Technical Field

[0001] The present invention relates to the field of satellite remote sensing data management technology, and in particular to a multi-satellite coordinated intelligent task execution method. Background Art

[0002] As an important means of obtaining information on the earth's surface, satellite remote sensing technology has been widely used in many fields in recent years, such as environmental monitoring, resource management, weather forecasting, agricultural monitoring, and disaster warning. With the diversification and complexity of remote sensing needs, the observation capabilities of a single satellite are difficult to fully cover all user needs, and the task execution efficiency is low, and it is unable to respond quickly to user needs. In response to this challenge, multi-satellite collaborative observation technology has gradually become the focus of industry attention in recent years. Through the collaborative work of multiple satellites, multi-satellite systems can cover a wide area in a short period of time and obtain various types of data, thereby quickly and effectively providing more comprehensive and accurate remote sensing services. However, how to efficiently manage and utilize these widely distributed satellite resources to efficiently meet the ever-changing needs of users is one of the important technical challenges facing the current field of satellite remote sensing data management.

[0003] At present, traditional satellite mission planning systems usually adopt the method of summarizing and reporting user needs, processing user needs manually or semi-automatically, and then formulating observation tasks based on the satellite's orbit and resource conditions. This traditional mission planning method can work well in the early single or small number of satellite operating environments, but in multi-satellite systems, due to the large number of satellites and complex orbits, traditional mission planning methods face many challenges.

[0004] Based on this, this specification provides a multi-satellite collaborative intelligent task execution method. Summary of the invention

[0005] This specification provides a multi-satellite coordinated intelligent task execution method to partially solve the above-mentioned problems existing in the prior art.

[0006] This manual adopts the following technical solutions:

[0007] This specification provides a multi-satellite coordinated intelligent task execution method, including:

[0008] Acquire satellite trajectory data of each satellite in advance, determine the rectangular area corresponding to each trajectory point of each satellite and the timestamp corresponding to each trajectory point according to the satellite trajectory data, and store them; wherein the rectangular area corresponding to the trajectory point is used to represent the imaging area of ​​the trajectory point in the geographic space;

[0009] In response to the user's operation, an imaging area and an imaging time are determined, and an imaging task is generated;

[0010] Matching the imaging area and imaging time with the stored rectangular areas corresponding to the trajectory points of the satellites and the timestamps corresponding to the trajectory points, to determine the target satellite, target imaging area and target imaging time for performing the imaging task;

[0011] The imaging task is performed according to the target satellite, the target imaging area and the target imaging time.

[0012] Optionally, determining the rectangular areas corresponding to the trajectory points of the satellites according to the satellite trajectory data specifically includes:

[0013] Determine the timestamp and longitude and latitude corresponding to each sub-satellite point of each satellite from the satellite trajectory data;

[0014] Determine the satellite tracks to which the sub-satellite points belong according to the timestamps and longitudes and latitudes corresponding to the sub-satellite points;

[0015] For each satellite trajectory, interpolation processing is performed on the satellite trajectory according to the timestamps and longitudes and latitudes corresponding to the sub-satellite points contained in the satellite trajectory to obtain the trajectory points contained in the satellite trajectory;

[0016] For each trajectory point, a rectangular area with a specified size and taking the trajectory point as the center is determined as the rectangular area corresponding to the trajectory point.

[0017] Optionally, determining the satellite tracks to which the sub-satellite points belong respectively according to the timestamps and the longitudes and latitudes respectively corresponding to the sub-satellite points specifically includes:

[0018] Get the preset time interval;

[0019] Traversing the longitudes and latitudes corresponding to the sub-satellite points, respectively, and determining two sub-satellite points adjacent to each other as a sub-satellite point pair;

[0020] Determine the time difference between each sub-satellite point included in each sub-satellite point pair according to the timestamps corresponding to each sub-satellite point included in each sub-satellite point pair;

[0021] For each sub-satellite point pair, if the time difference between the sub-satellite points included in the sub-satellite point pair is different from the preset time interval, it is determined that the sub-satellite points included in the sub-satellite point pair belong to different satellite tracks;

[0022] If the time difference between the sub-satellite points included in the sub-satellite point pair is the same as the preset time interval, it is determined that the sub-satellite points included in the sub-satellite point pair belong to the same satellite trajectory.

[0023] Optionally, for each satellite trajectory, interpolation processing is performed on the satellite trajectory according to the timestamps and longitudes and latitudes corresponding to the sub-satellite points contained in the satellite trajectory to obtain the trajectory points contained in the satellite trajectory, specifically including:

[0024] For each satellite trajectory, sort the sub-satellite points contained in the satellite trajectory according to the timestamps corresponding to the sub-satellite points contained in the satellite trajectory to obtain a sub-satellite point sequence corresponding to the satellite trajectory;

[0025] For each sub-satellite point included in the sub-satellite point sequence corresponding to the satellite trajectory, determine the distance between the sub-satellite point and the sub-satellite point next to the sub-satellite point according to the longitude and latitude of the sub-satellite point and the longitude and latitude of the sub-satellite point next to the sub-satellite point in the sub-satellite point sequence;

[0026] Determine the number of interpolation points according to the distance between the sub-satellite point and the next sub-satellite point of the sub-satellite point and a preset length;

[0027] According to the longitude and latitude of the sub-satellite point and the longitude and latitude of the sub-satellite point next to the sub-satellite point, interpolating the number of interpolation points between the sub-satellite point and the adjacent sub-satellite point by linear interpolation method;

[0028] The sub-satellite points included in the satellite trajectory and the determined interpolation points are used as trajectory points included in the satellite trajectory.

[0029] Optionally, for each trajectory point, determining a rectangular area with a specified size and centered at the trajectory point as the rectangular area corresponding to the trajectory point specifically includes:

[0030] For each trajectory point, determine the forward direction of the satellite trajectory to which the trajectory point belongs at the trajectory point and the vertical direction corresponding to the forward direction;

[0031] Obtaining a specified size, and determining a plurality of vertices corresponding to the trajectory point based on the specified size, a forward direction of the satellite trajectory to which the trajectory point belongs at the trajectory point, and a vertical direction corresponding to the forward direction, with the trajectory point as the center;

[0032] A rectangular area formed by a plurality of vertices corresponding to the trajectory point is taken as the rectangular area corresponding to the trajectory point.

[0033] Optionally, according to the target satellite, the target imaging area and the target imaging time, before performing the imaging task, the method further includes:

[0034] Acquiring weather forecast data of the target imaging area at the target imaging time;

[0035] According to the acquired weather forecast data and the parameters of the imaging device carried by the target satellite, a suitability evaluation result of performing the imaging task of the target imaging area by the target satellite at the target imaging time under the weather indicated by the weather forecast data is determined by using a pre-constructed suitability model;

[0036] Prompt information is generated according to the suitability evaluation result, and the prompt information is used to prompt the user to adjust the target imaging time of the imaging task.

[0037] Optionally, according to the target satellite, the target imaging area and the target imaging time, before performing the imaging task, the method further includes:

[0038] Determining a regional importance evaluation index corresponding to the target imaging area;

[0039] Determine a specific event related to the target imaging area at the target imaging time, obtain attribute information of the specific event, and the distance between the occurrence position corresponding to the specific event and the center of the target imaging area, and determine a heat evaluation index of the specific event;

[0040] Obtaining the precipitation probability and cloud coverage percentage of the target imaging area at the target imaging time, and determining the weather suitability evaluation index corresponding to the target imaging area according to the obtained precipitation probability and cloud coverage percentage;

[0041] Determining the priority of the imaging task according to the regional importance evaluation index, the heat evaluation index and the weather suitability evaluation index;

[0042] Executing the imaging task according to the target satellite, the target imaging area and the target imaging time specifically includes:

[0043] According to the priority of the imaging task, the imaging task is executed according to the target satellite, the target imaging area and the target imaging time.

[0044] Optionally, the target satellite belongs to a target constellation including a plurality of satellites, and each satellite included in the target constellation images a target imaging area at a different time;

[0045] Executing the imaging task according to the target satellite, the target imaging area and the target imaging time specifically includes:

[0046] By using the imaging device carried by the target satellite, the target imaging area is imaged at the target imaging time to obtain a target image of the target imaging area;

[0047] Detecting the target image to obtain a detection result of the target imaging area;

[0048] When the detection result of the target imaging area indicates that an abnormal event exists in the target imaging area, an abnormal monitoring message is determined according to the position information of the target imaging area, the event information of the abnormal event existing in the target imaging area and the abnormal monitoring time window, and the abnormal monitoring message is sent to each other satellite except the target satellite among the multiple satellites included in the target constellation, so that each other satellite responds to the abnormal monitoring message, collects images of the target imaging area through the imaging equipment carried by itself within the abnormal monitoring time window, and monitors abnormal events occurring in the target imaging area with the collected images.

[0049] Optionally, the method further comprises:

[0050] Determine the task completion time and status update period of the imaging task;

[0051] When the status update cycle is reached, the current task status of the imaging task is determined according to the task completion time and the execution status of the imaging task, and the current task status of the imaging task is sent to the user through a message queue;

[0052] The current task status includes one of unfinished, failed and completed; wherein, when the task completion time is not reached, the current task status of the imaging task is unfinished; when the task completion time is reached and the target image sent by the target satellite is not received, the task status of the imaging task is failed; when the task completion time is reached and the target image sent by the target satellite is received, the task status of the imaging task is completed;

[0053] The target image is obtained by collecting images of the target imaging area at the target imaging time through an imaging device carried by the target satellite when the target satellite performs the imaging mission.

[0054] This specification provides a multi-satellite coordinated intelligent task execution device, including:

[0055] An acquisition module, used to pre-acquire satellite trajectory data of each satellite, determine the rectangular area corresponding to each trajectory point of each satellite and the timestamp corresponding to each trajectory point according to the satellite trajectory data, and store them; wherein the rectangular area corresponding to the trajectory point is used to represent the imaging area of ​​the trajectory point in the geographic space;

[0056] A task generation module, used to determine the imaging area and imaging time in response to the user's operation, and generate an imaging task;

[0057] A matching module, used to match the imaging area and imaging time with the stored rectangular areas corresponding to the trajectory points of the satellites and the timestamps corresponding to the trajectory points, to determine the target satellite, target imaging area and target imaging time for performing the imaging task;

[0058] An execution module is used to execute the imaging task according to the target satellite, the target imaging area and the target imaging time.

[0059] This specification provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned multi-satellite collaborative intelligent task execution method is implemented.

[0060] This specification provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned multi-satellite collaborative intelligent task execution method when executing the program.

[0061] At least one of the above technical solutions adopted in this specification can achieve the following beneficial effects:

[0062] In the multi-satellite collaborative intelligent task execution method provided in this specification, the satellite trajectory data of each satellite is acquired in advance, the rectangular area and timestamp corresponding to each trajectory point of each satellite are determined, the imaging area and imaging time are determined in response to the user's operation, and the imaging task is generated. The imaging area and imaging time are matched with the rectangular area and timestamp corresponding to each stored trajectory point, and the target satellite, target imaging area and target imaging time for performing the imaging task are determined, and the imaging task is performed accordingly. It can be seen that through the above scheme, based on the trajectory data of multiple satellites, the planning and design of tasks are carried out in advance, which greatly reduces the planning waiting time of the user's imaging tasks and improves the efficiency of task execution. In addition, through digital means, user needs and satellite resources are closely connected, the intelligence and automation of task planning are realized, and the efficiency of satellite remote sensing data management and task execution is greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The drawings described herein are used to provide a further understanding of this specification and constitute a part of this specification. The illustrative embodiments and descriptions of this specification are used to explain this specification and do not constitute an improper limitation on this specification. In the drawings:

[0064] Figure 1 This is a schematic diagram of the architecture of a multi-satellite coordinated intelligent task execution system in this specification;

[0065] Figure 2 A flowchart of a multi-satellite coordinated intelligent task execution method in this specification;

[0066] Figure 3 A schematic diagram of a trajectory point and a rectangular area in this specification;

[0067] Figure 4 A flowchart of a multi-satellite coordinated intelligent task execution method in this specification;

[0068] Figure 5 A schematic diagram of a multi-satellite coordinated intelligent task execution device provided in this specification;

[0069] Figure 6 The corresponding Figure 2 Schematic diagram of electronic equipment. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solutions and advantages of this specification more clear, the technical solutions of this specification will be clearly and completely described below in combination with the specific embodiments of this specification and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this specification.

[0071] In addition, it should be noted that all actions of acquiring signals, information or data in this manual are performed in compliance with the relevant local data protection laws and policies and with the authorization given by the owner of the corresponding device.

[0072] It should be noted that, in the absence of conflict, the features in the following embodiments and implementations may be combined with each other.

[0073] As mentioned above, in multi-satellite collaborative scenarios, traditional mission planning methods have many defects, resulting in low mission execution efficiency and inability to effectively respond to user needs. Traditional mission planning methods have the following problems:

[0074] 1. The diversity and complexity of user needs have increased significantly: In the scenario of multi-satellite collaboration, the dynamic changes and complexity of user needs have increased significantly, greatly increasing the difficulty of mission planning. Traditional methods are difficult to effectively handle all user needs in a short period of time.

[0075] 2. Requirements for real-time and flexibility: Since traditional planning systems lack the ability to adjust and optimize in real time, satellite resource utilization is often low and the matching degree between observation tasks and user needs is not high.

[0076] Based on this, this specification provides a multi-satellite collaborative intelligent task execution method and a pre-planned task system design method based on multi-satellite sub-satellite point data, which aims to plan satellite observation tasks in advance through accurate calculation and prediction of satellite sub-satellite point data, reduce user waiting time, and improve the timeliness of data acquisition. This method closely connects user needs with satellite resources through digital means, realizes the intelligence and automation of task planning, and greatly improves the efficiency of satellite remote sensing data management and user experience.

[0077] Figure 1 The figure shows an optional architecture diagram of an intelligent task planning and execution system for executing the multi-satellite collaborative intelligent task execution method provided in this specification. Among them, the management personnel are personnel who maintain the system and pre-process satellite data, and the users are personnel who have actual satellite imaging needs. The pre-planning management system is used to plan satellite trajectories and possible observation imaging tasks in advance based on pre-acquired satellite data to meet the user's needs for real-time and accuracy of remote sensing data. The demand management system is used to receive the task requirements input by the user, extract task information using an automated method and generate corresponding user demand sheets to improve the timeliness of establishing imaging tasks and reduce the complexity of demand management. The satellite task planning system is used to perform actual task planning for the imaging tasks corresponding to the user's needs based on the user's needs and the satellite data pre-extracted by the pre-planning management system. The planning content includes information such as the target satellite for executing the imaging task, the area and time of actually executing the imaging task. The task planning subsystem can dynamically manage the order and timing of issuing each imaging task based on the execution time and priority of different imaging tasks. The imaging task is transferred to the measurement and control center and the measurement and control station network through the task planning subsystem, so as to assign the imaging task to the corresponding target satellite for execution. The image data obtained by the target satellite when performing the imaging mission can be transmitted back to the measurement and control station network, and then sent to the application service system via the measurement and operation control center and the mission planning subsystem. Therefore, the task execution results and execution status of the imaging mission can be synchronized to the demand management system so that users can view or execute the subsequent tasks required by the users.

[0078] The technical solutions provided by the embodiments of this specification are described in detail below in conjunction with the accompanying drawings.

[0079] Figure 2 This is a flowchart of a multi-satellite collaborative intelligent task execution method provided in this specification.

[0080] S100: Pre-acquire satellite trajectory data of each satellite, determine the rectangular area corresponding to each trajectory point of each satellite and the timestamp corresponding to each trajectory point according to the satellite trajectory data, and store them; wherein the rectangular area corresponding to the trajectory point is used to represent the imaging area of ​​the trajectory point in the geographic space.

[0081] In the embodiments of this specification, a method for executing a multi-satellite coordinated intelligent task is provided. The execution process of this method can be performed by an electronic device such as a server for satellite remote sensing imaging task planning. The server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. Figure 1 The server cluster of the intelligent task planning and execution system shown is taken as an example as the execution subject of the method provided in this specification to illustrate the specific technical solution.

[0082] Multi-satellite collaboration refers to a way in which multiple satellites coordinate and cooperate to complete specific tasks. These satellites may belong to the same constellation (a group of satellites designed to work together) or to different constellations. In the field of remote sensing, the collaboration of multiple satellites can increase the number of data collection times for a specific area and improve the frequency of data acquisition. In addition, multi-satellite collaboration can also enhance space coverage by reasonably arranging satellites on different orbits. Moreover, in this specification, the types of imaging devices and sensors carried by different satellites can be the same or different, so that ground information can be obtained from multiple angles and bands, improving data quality and diversity, and helping to improve the accuracy and richness of the final product (such as remote sensing images).

[0083] Based on this, in this manual, satellite trajectory data of multiple satellites are pre-acquired, and optional imaging areas are constructed through the satellite trajectory data of multiple satellites, so that when the user inputs the imaging requirements, the imaging area to be imaged can be directly determined by box selection, thereby reducing the complexity of the user's selection of the imaging area and improving the construction efficiency of the imaging task.

[0084] Satellite trajectory data can be a collection of information describing the path of a satellite moving around the earth. The satellite trajectory data can include at least orbital parameters, orbital period, orbital type, position and velocity information. Based on the satellite trajectory data, each sub-satellite point corresponding to each satellite can be obtained. The sub-satellite point is the intersection of the line connecting the center of the earth and the satellite on the earth's surface. By analyzing the satellite trajectory data, the timestamp and longitude and latitude of each sub-satellite point can be obtained.

[0085] Afterwards, based on the information of each satellite's sub-satellite point, the trajectory points of each satellite can be analyzed. The trajectory points are also the trajectories projected onto the earth's surface during the satellite's operation. In general, the sub-satellite point of each satellite can be directly used as the trajectory point corresponding to the satellite. However, in practical applications, the time interval between points is relatively long, and the sub-satellite point data may be too sparse. To this end, an interpolation method can be used to interpolate between every two sub-satellite points, and both the interpolation points and the sub-satellite points are used as trajectory points projected by the satellite on the ground, so that the rectangular area corresponding to the satellite's trajectory points can cover the imaging area selected by the user that needs to be imaged. Among them, the interpolation method can be any existing type of interpolation method such as polynomial interpolation, segmented interpolation, spline interpolation, linear interpolation, etc., and this manual does not limit this.

[0086] It should be noted that each trajectory point of a satellite can constitute a satellite trajectory, and the trajectory points of different satellites generally belong to different satellite trajectories, and different trajectory points of the same satellite can belong to the same satellite trajectory or to different satellite trajectories. In the above-mentioned scheme of using interpolation to obtain interpolation points by interpolating between every two sub-satellite points, interpolation is generally performed between two sub-satellite points belonging to the same satellite trajectory. Therefore, before interpolation, the satellite trajectories to which each sub-satellite point of each satellite belongs can be determined first.

[0087] After determining each track point of each satellite, a rectangular area corresponding to each track point can be formed by extending a specified size outward with each track point as the center. In this specification, the specific length of the specified size is not limited, but in order to avoid omission of the imaging area, the rectangular areas corresponding to two adjacent track points can usually be geographically adjacent to each other, such as Figure 3 Assume that track point A and track point B are two adjacent track points, then in terms of geographical location, the rectangular area corresponding to track point A is adjacent to the rectangular area of ​​track point B, and there is no gap between the two. Of course, according to the actual application scenario, the rectangular areas corresponding to different track points may also partially overlap, and this specification does not limit this.

[0088] In addition, the timestamps corresponding to the trajectory points can be determined based on the timestamps corresponding to the sub-satellite points. Afterwards, the geometric information of the rectangular area corresponding to each trajectory point, the timestamps corresponding to each trajectory point, the longitude and latitude, the satellite identification and other information can be stored in the data to facilitate the planning and execution of subsequent imaging tasks.

[0089] In this specification, the rectangular area corresponding to each trajectory point of each satellite determined based on the satellite trajectory data of each satellite can represent the imaging area of ​​each satellite in the geographic space where remote sensing imaging can be performed. That is, the rectangular area corresponding to the trajectory point is used to represent the imaging area of ​​the trajectory point in the geographic space. When the satellite moves to the position corresponding to the trajectory point according to the predetermined orbit, the rectangular area corresponding to the trajectory point can be imaged by calling the imaging device carried by the satellite itself to obtain remote sensing image data of the picture containing the rectangular area. The collected remote sensing image data can be applied to climate and environmental monitoring, urban planning and management, disaster warning, geological exploration, ecological protection, weather forecasting and other fields to complete tasks in corresponding fields.

[0090] It can be seen that through step S100, based on the pre-acquired satellite trajectory data of each satellite, the rectangular area and timestamp corresponding to each trajectory point are determined. In fact, the rectangular area corresponding to each trajectory point is a pre-planned imaging area of ​​the imaging task that can be executed at the trajectory point. Similarly, the timestamp corresponding to each trajectory point is actually a pre-planned imaging time of the imaging task that can be executed at the trajectory point. Through such pre-planning, when the user's imaging needs are received, there is no need to obtain satellite trajectory data or satellite resources again. It is possible to directly determine the target satellite for executing the imaging task required by the user based on the pre-planned imaging area and imaging time of the executable imaging task, thereby reducing the time consumed in the construction of the imaging task in the multi-satellite collaborative mission planning scenario and improving the efficiency of mission planning and execution.

[0091] S102: In response to the user's operation, an imaging area and an imaging time are determined, and an imaging task is generated.

[0092] Specifically, the user logs in to the demand management system through the client, and can select the required imaging area and imaging time by inputting different operations. He can also select a specific satellite to execute the user's imaging needs by screening the satellite identifier. Among them, the user's client can display an area of ​​a certain range, and the user can use the input device connected to the client used by him to select one or more areas of a certain size as imaging areas within the displayed area, and select the imaging time corresponding to the imaging area. Then, the imaging task corresponding to the user is generated based on the imaging area and the imaging area. This specification does not limit the specific number of imaging areas corresponding to an imaging task, and the location of the imaging area. Generally, an imaging area corresponds to an imaging time, which can be an imaging moment or an imaging period. The imaging times corresponding to different imaging areas can be the same or different, and this specification does not limit this.

[0093] Additionally, the user may enter / select a satellite ID to limit the imaging mission to a specific satellite.

[0094] S104: Match the imaging area and imaging time with the stored rectangular areas corresponding to the trajectory points of the satellites and the timestamps corresponding to the trajectory points to determine the target satellite, target imaging area and target imaging time for performing the imaging task.

[0095] Furthermore, the imaging area and imaging time in the imaging task determined in step S102 are matched with the rectangular areas corresponding to the trajectory points of each satellite and the timestamps of each trajectory point predetermined in step S100, and a user imaging requirement list is formed through intersection search analysis to determine the target satellite actually used to execute the user's imaging task, the target imaging area actually imaged, and the imaging time of the actual remote sensing image.

[0096] Among them, the intersection search analysis can be performed by using the imaging area in the imaging task as an index to search for one or more rectangular areas that can cover the imaging area in the rectangular areas of each stored trajectory point. Similarly, the imaging time in the imaging task can be used to search for one or more timestamps that can cover the imaging time in the timestamps of each stored trajectory point. Thus, one or more trajectory points whose rectangular area can cover the imaging area and whose timestamp can cover the imaging time are used as matched trajectory points, and then based on the rectangular area and timestamp corresponding to the matched trajectory point, as well as the satellite to which the trajectory point belongs, the target satellite, target imaging area and target imaging time for performing the imaging task are determined.

[0097] Optionally, since the quality of remote sensing imaging may be affected by internal factors (the technical characteristics of the imaging device itself) and external factors (environmental conditions during imaging), and since the technical characteristics of the imaging device carried by the satellite are generally fixed, the target satellite for performing the imaging task can be determined in step S104 by considering the internal factor of the technical characteristics of the imaging device itself, so as to select a target satellite suitable for performing the imaging task. The environmental conditions during imaging, especially the meteorological conditions, change at any time, and there may even be sudden meteorological changes that cannot be known in advance by the meteorological forecast data when approaching the target imaging time. Therefore, before performing the imaging task, it is also possible to introduce meteorological forecast data, based on the weather forecast data of the target imaging time period and the technical parameters of the imaging device, to determine whether the imaging task can be completed, that is, whether the weather conditions at the target imaging time are suitable for the target satellite to perform remote sensing imaging, and to promptly remind the user when it is not suitable, and provide the opportunity to adjust the information of the imaging task (such as the target imaging time).

[0098] S106: Execute the imaging task according to the target satellite, the target imaging area and the target imaging time.

[0099] Afterwards, the target imaging area and the target imaging time are sent to the target satellite that performs the imaging task, so that the target satellite calls the imaging equipment it carries to collect remote sensing images of the target imaging area at the target imaging time, and returns the collected remote sensing images to the ground for users to view and download, thereby completing the imaging task.

[0100] In the multi-satellite collaborative intelligent task execution method provided in this specification, the satellite trajectory data of each satellite is acquired in advance, the rectangular area and time stamp corresponding to each trajectory point of each satellite are determined, the imaging area and imaging time are determined in response to the user's operation, and the imaging task is generated. The imaging area and imaging time are matched with the rectangular area and time stamp corresponding to each stored trajectory point, the target satellite, target imaging area and target imaging time for executing the imaging task are determined, and the imaging task is executed accordingly.

[0101] It can be seen that through the above solution, based on the trajectory data of multiple satellites, the mission is planned and designed in advance, which greatly reduces the waiting time for the user's imaging mission planning and improves the efficiency of mission execution. In addition, through digital means, user needs are closely connected with satellite resources, which realizes the intelligence and automation of mission planning and greatly improves the efficiency of satellite remote sensing data management and mission execution.

[0102] In one or more embodiments of this specification, Figure 2 The step S100 shown in FIG. 1 determines the rectangular areas corresponding to the trajectory points of the satellites according to the satellite trajectory data, which can be specifically implemented by the following implementation methods: Figure 4 As shown:

[0103] S200: Determine the timestamp and longitude and latitude corresponding to each sub-satellite point of each satellite from the satellite trajectory data.

[0104] This step is similar to the aforementioned step S100 and will not be described again here.

[0105] S202: Determine the satellite tracks to which the sub-satellite points belong, according to the timestamps and longitudes and latitudes corresponding to the sub-satellite points.

[0106] As mentioned above, the track points of different satellites generally belong to different satellite tracks, and different track points of the same satellite may belong to the same satellite track or to different satellite tracks. In the scheme of interpolating between every two sub-satellite points to obtain interpolation points, interpolation is generally performed between two sub-satellite points belonging to the same satellite track. Therefore, before interpolation, the satellite tracks to which each sub-satellite point of each satellite belongs may be determined.

[0107] In practical applications, no matter whether the sub-satellite points are obtained by sampling or by calculation based on satellite parameters, there are certain rules between the timestamps of the sub-satellite points belonging to the same satellite track of the same satellite. Specifically, two sub-satellite points that are close in geographical location can be determined based on the longitude and latitude of the sub-satellite points, and then the timestamps of the two sub-satellite points are compared. If the time difference between the two sub-satellite points is very large, then they may not belong to the same satellite track of the same satellite. If the time difference between the two sub-satellite points is within a reasonable time range, then they may belong to the same satellite track of the same satellite.

[0108] In an optional embodiment of this specification, Figure 4 The step S202 shown can be specifically implemented by the following implementations:

[0109] Step 1: Get the preset time interval.

[0110] Specifically, the time stamps corresponding to two geographically adjacent sub-satellite points belonging to the same satellite track of the same satellite respectively conform to the rule that the time difference between the time stamps is the preset time interval. Based on this, the preset time interval for determining whether the sub-satellite points belong to the same satellite track can be first obtained. The preset time interval can be a fixed value manually set based on prior experience, or can be flexibly adjusted, and this specification does not limit this.

[0111] Step 2: traverse the longitudes and latitudes corresponding to the sub-satellite points, and determine two adjacent sub-satellite points as a sub-satellite point pair.

[0112] As mentioned above, in acquiring the satellite trajectory data of each satellite, the sub-satellite points corresponding to each satellite can be analyzed, and the sub-satellite points are discretely distributed within a certain geographical range. Therefore, based on the longitude and latitude of each sub-satellite point, the sub-satellite points that are geographically adjacent to each other can be determined, so that in subsequent steps, the timestamps corresponding to the two adjacent sub-satellite points can be compared.

[0113] Specifically, for each sub-satellite point, according to the longitude and latitude of the sub-satellite point and the longitude and latitude of each other sub-satellite point, the longitude and latitude differences between the sub-satellite point and each other sub-satellite point are determined, and several other sub-satellite points with smaller longitude and latitude differences are taken as other sub-satellite points adjacent to the sub-satellite point. Since there may be a situation where the positions are adjacent but the time difference does not meet the conditions, each sub-satellite point can correspond to one or more adjacent sub-satellite points, and the number of adjacent sub-satellite points corresponding to each sub-satellite point can be the same or different. This specification does not limit the number of adjacent sub-satellite points corresponding to different sub-satellite points and their longitude and latitude differences.

[0114] Afterwards, for each sub-satellite point, the sub-satellite point and other sub-satellite points adjacent to the sub-satellite point are placed in the same sub-satellite point pair. Generally, the number of other sub-satellite points adjacent to the sub-satellite point is the same as the number of the sub-satellite point pair to which the sub-satellite point belongs.

[0115] For example, other subsatellite points adjacent to the subsatellite point X include subsatellite point Y and subsatellite point Z. Then the subsatellite point pairs to which the subsatellite point belongs are (X, Y) and (X, Z).

[0116] Step 3: Determine the time difference between each sub-satellite point included in each sub-satellite point pair according to the timestamps corresponding to each sub-satellite point included in each sub-satellite point pair.

[0117] For each sub-satellite point pair, the time difference is determined according to the timestamps corresponding to the two sub-satellite points included in the sub-satellite point pair. Taking the sub-satellite point pair (X, Y) as an example, an optional implementation is as follows:

[0118]

[0119] Where Δt is the time difference, t X is the timestamp of subsatellite point X, t Y The timestamp of the subsatellite point Y.

[0120] Step 4: for each sub-satellite point pair, if the time difference between the sub-satellite points included in the sub-satellite point pair is different from the preset time interval, it is determined that the sub-satellite points included in the sub-satellite point pair belong to different satellite tracks.

[0121] Step 5: If the time difference between the sub-satellite points included in the sub-satellite point pair is the same as the preset time interval, it is determined that the sub-satellite points included in the sub-satellite point pair belong to the same satellite track.

[0122] The time difference between each sub-satellite point included in the sub-satellite point pair obtained in the above step is compared with the preset time interval obtained. If the two are the same, it is determined that the sub-satellite points included in the sub-satellite point pair belong to the same satellite track. If the two are different, it is determined that the sub-satellite points included in the sub-satellite point pair belong to different satellite tracks.

[0123] At this time, each satellite trajectory can be considered as a point set containing multiple sub-satellite points, which are sorted based on the timestamps corresponding to each sub-satellite point contained in the satellite trajectory. In this way, two sub-satellite points adjacent to each other in the satellite trajectory are actually two sub-satellite points adjacent in both geographical location and time.

[0124] S204: For each satellite trajectory, interpolation processing is performed on the satellite trajectory according to the timestamps and longitudes and latitudes corresponding to the sub-satellite points included in the satellite trajectory to obtain the trajectory points included in the satellite trajectory.

[0125] Afterwards, for each satellite track, interpolation is performed between any two adjacent sub-satellite points in each sub-satellite point included in the satellite track by any existing difference method to obtain an interpolation point between any two adjacent sub-satellite points, thereby improving the continuity of the track and the map.

[0126] In an optional embodiment of this specification, Figure 4 The step S204 shown can be specifically implemented by the following implementations:

[0127] Step 1: For each satellite trajectory, sort the sub-satellite points contained in the satellite trajectory according to the timestamps corresponding to the sub-satellite points contained in the satellite trajectory to obtain the sub-satellite point sequence corresponding to the satellite trajectory.

[0128] In practical applications, the data may be sorted in the order from the beginning to the end or in the order from the end to the beginning, and this specification does not limit this.

[0129] Step 2: For each sub-satellite point included in the sub-satellite point sequence corresponding to the satellite trajectory, determine the distance between the sub-satellite point and the next sub-satellite point in the sub-satellite point sequence according to the longitude and latitude of the sub-satellite point and the longitude and latitude of the next sub-satellite point in the sub-satellite point sequence.

[0130] It should be noted that since the sub-satellite point is the intersection of the line connecting the center of the earth and the satellite on the earth's surface, the latitude and longitude of the sub-satellite point actually indicate the position on the ground. Therefore, the determined distance difference between the sub-satellite point and the next sub-satellite point is actually the distance between the sub-satellite point and the next sub-satellite point on the ground.

[0131] Step 3: Determine the number of interpolation points according to the distance between the sub-satellite point and the next sub-satellite point of the sub-satellite point and the preset length.

[0132] In this manual, since the sub-satellite points are relatively sparse, a rectangular area is generated based only on the sub-satellite points as track points. The size and area of ​​the rectangular area are large, and the imaging area selected by the user for imaging is likely to occupy only a part of the rectangular area of ​​the sub-satellite points, resulting in low imaging accuracy and reduced quality of remote sensing image data. To this end, track points can be added by interpolation, which can not only improve the continuity of the satellite track on the map, but also effectively reduce the size and area of ​​the rectangular area, so that the imaging area required by the user can be matched to a more accurate rectangular area, which is conducive to handing over the user's performance task to a satellite that is more suitable for performing the task, so as to improve the imaging quality.

[0133] Before the actual interpolation, the number of interpolation points may be determined. In this specification, the interpolation process may be performed by average linear interpolation, so the number of interpolation points may be determined according to the distance between the sub-satellite point and the next sub-satellite point of the sub-satellite point and the preset length.

[0134] For example, the sub-satellite points are interpolated by uniform interpolation to obtain interpolation points, so as to fill the points between the sub-satellite points. Assuming that the distance between two sub-satellite points is 40 km and the preset length is 10 km, the number of interpolation points can be determined to be 3.

[0135] Step 4: according to the longitude and latitude of the sub-satellite point and the longitude and latitude of the sub-satellite point next to the sub-satellite point, interpolate the number of interpolation points between the sub-satellite point and the adjacent sub-satellite point by linear interpolation method.

[0136] A formula for linear interpolation of longitude and latitude is as follows:

[0137]

[0138]

[0139] Among them, φ i is the latitude of subsatellite point i, λ i is the longitude of subsatellite point i, t i i is the timestamp of subsatellite point i. i+1 is the latitude of the next subsatellite point i+1 of subsatellite point i, λ i+1 is the longitude of subsatellite point i+1, t i+1 i is the timestamp of the subsatellite point i+1. φ(t) is the latitude of the interpolation point, λ(t) is the longitude of the interpolation point, and t is the timestamp of the interpolation point.

[0140] By using the interpolation algorithm to insert multiple interpolation points between two adjacent sub-satellite points, the satellite trajectory is made smoother and more accurate, and the size and area of ​​the rectangular region of the trajectory point are more reasonable, thereby improving the planning and execution efficiency of the imaging task.

[0141] Step 5: The sub-satellite points included in the satellite trajectory and the determined interpolation points are used as the trajectory points included in the satellite trajectory.

[0142] Afterwards, the timestamps, longitude and latitude of each track point belonging to the same satellite track are stored in a table as the basic data for subsequent mission planning. Standard coordinate information ST_GeogFromText of each track point can also be generated, which indicates the position of each track point in the geographic coordinate system.

[0143] S206: For each trajectory point, determine a rectangular area with a specified size and with the trajectory point as the center as the rectangular area corresponding to the trajectory point.

[0144] Since the track point represents the position of the satellite in orbit projected onto the ground when the satellite moves along the satellite orbit, the imaging device carried by the satellite can collect remote sensing images within a certain range centered on the track point. In this specification, the rectangular area centered on the track point is generated to match the imaging area in the imaging requirement input by the user to determine which satellite can perform the user's imaging requirement at which time point.

[0145] The specified size may be information such as the length and width of the rectangular area determined based on the device parameters of the imaging device carried by the satellite, and the specified size may also be determined based on the distance between each track point, or may be determined based on prior experience, which is not limited in this specification. In this specification, the specified sizes of the rectangular areas of different track points may be the same or different, but usually, in order to avoid omission of the imaging area, the rectangular areas corresponding to two adjacent track points may be geographically adjacent to each other, or may partially overlap, so the specified size is not less than the distance between two adjacent track points.

[0146] In an optional embodiment of this specification, Figure 4 Step S206 can be implemented in the following manner:

[0147] Firstly, for each trajectory point, the forward direction of the satellite trajectory to which the trajectory point belongs at the trajectory point and the vertical direction corresponding to the forward direction are determined.

[0148] The forward direction corresponding to the trajectory point can be the tangent direction of the trajectory point on the satellite trajectory to which it belongs, and correspondingly, the vertical direction of the trajectory point can be the normal direction of the trajectory point on the satellite trajectory to which it belongs. In addition, the positive direction of the forward direction can be defined as the direction from the previous trajectory point in time to the next trajectory point in time, and correspondingly, the negative direction of the forward direction can be defined as the direction from the next trajectory point in time to the previous trajectory point in time. The following is a formula for determining the forward direction at a trajectory point:

[0149]

[0150] Among them, v represents the forward direction at the trajectory point.

[0151] The unit vector in the forward direction is:

[0152]

[0153] The formula for determining the vertical direction based on the heading direction can be shown as follows:

[0154]

[0155] The unit vector in the vertical direction is:

[0156]

[0157] Secondly, a designated size is obtained, and based on the designated size, the heading direction of the satellite track to which the track point belongs at the track point, and the vertical direction corresponding to the heading direction, the track point is taken as the center to determine multiple vertices corresponding to the track point. The designated size is the size of the rectangular area corresponding to the track. In this specification, the specific length of the designated size is not limited, but in order to avoid omission of the imaging area, the designated size can be determined based on the distance between two adjacent track points.

[0158] Afterwards, use the Geodetic Calculator tool to calculate the coordinates of the four vertices starting from the trajectory point in four directions (i.e. the forward direction of the trajectory point and its perpendicular direction).

[0159] The following is to determine the four vertices corresponding to the trajectory point in four directions with the trajectory point as the center. Among them, P1 is the vertex obtained by extending along the positive direction of the forward direction, P2 is the vertex obtained by extending along the negative direction of the forward direction, P3 is the vertex obtained by extending along the positive direction of the vertical direction, and P4 is the vertex obtained by extending along the negative direction of the vertical direction.

[0160]

[0161]

[0162]

[0163]

[0164] Then, a rectangular area formed by a plurality of vertices corresponding to the trajectory point is used as the rectangular area corresponding to the trajectory point.

[0165] based on Figure 4 The scheme shown predetermines the rectangular area corresponding to each trajectory point of each satellite. Through technologies such as big data and cloud computing, it realizes dynamic management and real-time optimization of satellite resources, improves the automation and intelligence of task planning, and effectively improves the utilization efficiency of satellite resources. In addition, by using the sub-satellite point data of multi-satellite collaborative observation, the observation task is planned in advance, which significantly improves the timeliness of data acquisition, reduces the waiting time of users, and meets the user's demand for real-time and accuracy of remote sensing data.

[0166] In an optional embodiment of this specification, Figure 2 After step S104 and before step S106, weather forecast data may be introduced to evaluate whether the imaging task is suitable for execution at the target imaging time. The specific implementation is as follows:

[0167] The first step: obtaining weather forecast data of the target imaging area at the target imaging time.

[0168] Specifically, high-precision weather forecast data for the target imaging area can be obtained by calling multiple meteorological data sources. These data sources can provide weather conditions at different time granularities (e.g., hourly and daily). Weather forecast data may include information such as temperature, humidity, air pressure, precipitation, visibility, and cloud cover, which is used to describe and predict the weather conditions at the target imaging time (or time period).

[0169] Step 2: Based on the acquired weather forecast data and the parameters of the imaging equipment carried by the target satellite, a suitability evaluation result of performing the imaging task of the target imaging area with the target satellite at the target imaging time under the weather indicated by the weather forecast data is determined through a pre-constructed suitability model.

[0170] Afterwards, based on the pre-built suitability model, the suitability for imaging is determined according to the weather forecast data and the parameters of the imaging equipment carried by the target satellite. The suitability model can be constructed using machine learning or statistical methods, such as Ju Ce tree model, random forest model, support vector machine, neural network model, rule model, etc.

[0171] The input of the suitability model is the weather forecast data and the parameters of the imaging equipment carried by the target satellite, where the parameters of the imaging equipment may include spatial resolution, observation angle, equipment type, sensitivity, etc. The input of the suitability model may also include other information of the imaging task, such as the target imaging time and the target imaging area.

[0172] The suitability evaluation result output by the suitability model can be a binary classification result, that is, suitable imaging / unsuitable imaging, or a probability result, such as a probability value indicating the suitability of imaging.

[0173] Step 3: Generate prompt information according to the suitability evaluation result, wherein the prompt information is used to prompt the user to adjust the target imaging time of the imaging task.

[0174] If the suitability evaluation result is a binary classification result, then when the suitability evaluation result is suitable for imaging, no prompt information may be generated, and the imaging task may be directly assigned to the corresponding target satellite for execution. If the suitability evaluation result is unsuitable for imaging, a prompt information may be generated to prompt the user to adjust the target imaging time to avoid the impact of unsuitable weather conditions on the imaging task.

[0175] If the suitability evaluation result is a probability result, the probability threshold can be obtained in advance. If the probability value used to indicate the suitability of imaging is greater than the probability threshold, it means that it is suitable for imaging, and no prompt information may be generated. The imaging task is directly assigned to the corresponding target satellite for execution. If the probability value used to indicate the suitability of imaging is not greater than the probability threshold, it means that it is not suitable for imaging. A prompt message can be generated to prompt the user to adjust the target imaging time to avoid the impact of inappropriate weather conditions on the imaging task. The probability threshold can be determined in advance based on prior experience, and this manual does not limit the specific value of the probability threshold.

[0176] In addition, based on the implementation of the above embodiment, the weather conditions in the target imaging area can also be monitored in real time by subscribing to the real-time meteorological data of the target imaging area before executing step S106. If the weather conditions in the target imaging area are determined to have suddenly changed (such as temporary increase in cloud cover or rainfall) when approaching the target imaging time according to the real-time meteorological data, prompt information for prompting the user to adjust the target imaging time of the imaging task can be generated again, so as to provide a second adjustment opportunity and avoid failure in the execution of the imaging task.

[0177] In an optional embodiment of the present specification, when there are many imaging tasks to be performed within a certain period of time, the target satellite that actually performs the imaging task may not be able to complete the imaging task simultaneously and efficiently in a short period of time. At this time, in order to improve the execution efficiency of the task and ensure that the more important and urgent imaging tasks are completed first, Figure 2 Before the imaging task is executed in step S106, the priority of each imaging task is determined, and the imaging task is executed according to the priority of the imaging task when the step S106 is specifically implemented. The specific implementation method is as follows:

[0178] The first step: determining the regional importance evaluation index corresponding to the target imaging area.

[0179] The regional importance evaluation index may be a fixed value set for the target imaging area, and may be calculated based on user needs and task data of historical imaging tasks related to the target imaging area. The regional importance evaluation index is used to indicate the importance of the imaging task of the target imaging area. The regional importance evaluation indexes of different imaging areas may be the same or different, and this specification does not limit this.

[0180] Step 2: Determine a specific event related to the target imaging area at the target imaging time, obtain attribute information of the specific event, and the distance between the occurrence location corresponding to the specific event and the center of the target imaging area, and determine a thermal evaluation index of the specific event.

[0181] Specifically, emergencies or activities related to the imaging task may occur in the target imaging area, such as natural events (such as typhoons, floods, earthquakes, etc.) and man-made events (such as wars, environmental issues, nature conservation projects, etc.). The system can determine a specific event related to the imaging task based on the target imaging area and target imaging time of the imaging task, and the specific event is the natural event or man-made event mentioned above. The determined specific event can be sent to the user to prompt the user about the current hotspot information related to the imaging task. Of course, the user can also set different current hotspot push types according to their needs, such as focusing only on natural disasters, environmental protection events, or only on man-made events. This will help users obtain the most relevant current affairs information and improve the pertinence of imaging tasks.

[0182] Afterwards, the attribute information of the specific event and the location where the specific event occurred are obtained to determine the heat evaluation index of the specific event. An optional formula for determining the heat evaluation index of the specific event is as follows:

[0183]

[0184] Among them, M e Indicates the scale of a specific event, I e It represents the degree and scope of influence of a specific event, and d represents the distance between the sound location of the specific event and the center of the imaging area.

[0185] Step 3: Obtain the precipitation probability and cloud coverage percentage of the target imaging area at the target imaging time, and determine the weather suitability evaluation index corresponding to the target imaging area based on the obtained precipitation probability and cloud coverage percentage.

[0186] An optional weather adaptability evaluation index formula is as follows:

[0187]

[0188] Among them, C t Indicates the cloud cover percentage, M t It indicates the probability of precipitation. It can be seen that the weather adaptability evaluation index is inversely proportional to the cloud coverage percentage and inversely proportional to the probability of precipitation.

[0189] Step 4: Determine the priority of the imaging task according to the regional importance evaluation index, the heat evaluation index and the weather suitability evaluation index.

[0190] Determine the weight corresponding to the regional importance evaluation index, the weight of the heat evaluation index, and the weight of the weather suitability evaluation index, and perform weighted summation to obtain the priority of the imaging task. An optional priority determination formula is as follows:

[0191]

[0192] Among them, P t Indicates priority, R i represents the regional importance evaluation index, H t represents the heat evaluation index, W t represents the weather suitability evaluation index. α represents the weight corresponding to the regional importance evaluation index, β represents the weight of the heat evaluation index, and γ represents the weight of the weather suitability evaluation index.

[0193] Thus, according to the priority of the generated task, the imaging task is executed according to the target satellite, the target imaging area and the target imaging time.

[0194] In an optional embodiment of the present specification, since the multi-satellite coordinated intelligent task execution method provided in the present specification is executed in a multi-satellite coordinated scenario, although one target satellite is generally used to actually execute one imaging task, in actual application scenarios, multiple satellites may be used to dynamically monitor the same target imaging area within a certain time window to improve the detection efficiency of the target imaging area, obtain feedback data of the target imaging area, and thus quickly detect abnormal events that may occur in the target imaging area. The specific implementation methods are as follows:

[0195] In this specification, the system will assign imaging tasks to satellites for execution. The target satellite responds to the assigned imaging tasks and, based on the target imaging time and target imaging area in the imaging tasks, uses the imaging equipment carried by the target satellite to collect images of the target imaging area at the target imaging time to obtain a target image of the target imaging area.

[0196] Afterwards, the target image may be detected to obtain a detection result of the target imaging area.

[0197] Specifically, the target image reflects the actual situation of the target imaging area at the target imaging time. The target image can be detected through a machine learning model or an image processing model to determine whether there are abnormal events in the target imaging area and record them in the detection results. Abnormal events may be surface deformation, abnormal weather, sudden natural disasters (such as fire, flood, etc.), or other significant surface changes in the target imaging area.

[0198] It should be noted that in this specification, the subject for detecting the target image can be Figure 1 The server of the satellite mission planning system in the system shown. That is, when the target satellite acquires the target image, it will return the target image to the measurement and control station network, and then transmit it back to the satellite mission planning system through the measurement and control center and the mission planning subsystem, so as to detect the target image.

[0199] Optionally, detection of the target image can also be completed on the target satellite. Under this condition, detection tools for image detection, such as machine learning models, can be pre-deployed on the target satellite. After the target image is detected based on the detection tools pre-deployed on the target satellite and the corresponding detection results are obtained, the detection results can be transmitted back to the ground, or the target satellite can execute subsequent steps.

[0200] Afterwards, when the detection result of the target imaging area indicates that an abnormal event exists in the target imaging area, an abnormal monitoring message is determined according to the position information of the target imaging area, the event information of the abnormal event existing in the target imaging area and the abnormal monitoring time window, and the abnormal monitoring message is sent to each other satellite except the target satellite among the multiple satellites included in the target constellation, so that each other satellite responds to the abnormal monitoring message, collects images of the target imaging area through the imaging equipment carried by itself within the abnormal monitoring time window, and monitors abnormal events occurring in the target imaging area with the collected images.

[0201] In a multi-satellite collaboration scenario, the target satellite may belong to a target constellation including multiple satellites, and each of the multiple satellites included in the target constellation may image the target imaging area at different times. Based on this condition, when the detection result of the target image collected by the target satellite indicates that an abnormal event does exist in the target imaging area, other satellites included in the constellation to which the target satellite belongs may be triggered to continuously monitor the target imaging area to pay attention to the abnormal event occurring in the target imaging area.

[0202] Specifically, the abnormal monitoring message can be determined based on the location information of the target imaging area, the event information of the abnormal event existing in the target imaging area, and the abnormal monitoring time window. The abnormal monitoring time window refers to the image acquisition of the target imaging area within a time period so as to detect the implementation of the abnormal event based on the acquired image. In other words, when the satellite that receives the abnormal monitoring message reaches the position where the image of the target imaging area can be acquired, it is also necessary to determine whether the current moment is within the abnormal monitoring time window. If so, the image of the target imaging area is acquired and analyzed. If not, the abnormal monitoring message may not be responded to.

[0203] Thus, the abnormal monitoring message is sent to all other satellites in the target constellation except the target satellite. When other satellites move to a position where they can collect images of the target imaging area, they can collect images of the target imaging area based on their own imaging devices. The images collected by other satellites can be returned to the ground, that is, Figure 1 The system shown in the figure detects the target imaging area again to identify the abnormal event. If the abnormal event disappears, it means that the abnormality in the target imaging area has been resolved, and the monitoring and attention to the target imaging area can be ended. If the abnormal event still exists or even worsens, it is necessary to call other satellites in the target constellation to continue monitoring the target imaging area, or call satellites in other constellations for monitoring until the abnormality is resolved or the event ends.

[0204] In one or more embodiments of this specification, Figure 1 The system architecture shown also includes an application service system for managing user needs and monitoring task execution. Users can access the application service system through the control client, and can view the user's imaging needs, imaging needs information, and imaging tasks corresponding to the imaging needs, especially the task status of the imaging task. And when the imaging task is completed, the user can also view the execution result of the imaging task, that is, the target image of the target imaging area collected by the target satellite at the target imaging time. The information that the user can view also includes the thumbnail of the target image, the actual imaging time and other information. In addition, the user can collect and download the target image to complete the closed loop of user needs.

[0205] The execution status of the imaging task can be updated and fed back through the following implementations:

[0206] First, the task completion time and status update period of the imaging task are determined.

[0207] Specifically, the task completion time of the imaging task can be set. The task completion time can indicate how long after the target imaging time the target image needs to be transmitted back by the person executing the imaging task, so as to monitor the completion of the imaging task within a certain time limit. The task completion time of the imaging task can be determined by the user or based on prior experience, and this specification does not limit this.

[0208] In addition, a status update cycle can also be set, that is, each time a status update cycle is reached, the execution status of the task will be determined based on the task completion time and whether the target image transmitted by the target satellite is received. Similarly, the status update cycle can also be determined by the user or based on prior experience.

[0209] Thus, when the status update cycle is reached, the current task status of the imaging task is determined according to the task completion time and the execution status of the imaging task, and the current task status of the imaging task is sent to the user through the message queue. The current task status can be prompted to the user through the kafka message queue.

[0210] The current task status includes one of unfinished, failed, and completed. When the task completion time is not reached, the current task status of the imaging task is unfinished. When the task completion time is reached and the target image sent by the target satellite is not received, the task status of the imaging task is failed. When the task completion time is reached and the target image sent by the target satellite is received, the task status of the imaging task is completed.

[0211] The target image mentioned in the above scheme is actually image data obtained by collecting images of the target imaging area at the target imaging time through the imaging equipment carried by the target satellite when the target satellite performs the imaging mission.

[0212] The above is a multi-satellite collaborative intelligent task execution method provided by one or more embodiments of this specification. Based on the same idea, this specification also provides a corresponding multi-satellite collaborative intelligent task execution device, such as Figure 5 shown.

[0213] Figure 5 A schematic diagram of a multi-satellite coordinated intelligent task execution device provided in this specification specifically includes:

[0214] The acquisition module 300 is used to pre-acquire the satellite trajectory data of each satellite, determine the rectangular area corresponding to each trajectory point of each satellite and the timestamp corresponding to each trajectory point according to the satellite trajectory data, and store them; wherein the rectangular area corresponding to the trajectory point is used to represent the imaging area of ​​the trajectory point in the geographic space;

[0215] The task generation module 302 is used to determine the imaging area and imaging time in response to the user's operation and generate an imaging task;

[0216] A matching module 304 is used to match the imaging area and the imaging time with the stored rectangular areas corresponding to the trajectory points of the satellites and the timestamps corresponding to the trajectory points, so as to determine the target satellite, target imaging area and target imaging time for performing the imaging task;

[0217] The execution module 306 is used to execute the imaging task according to the target satellite, the target imaging area and the target imaging time.

[0218] Optionally, the acquisition module 300 is specifically used to determine the timestamp and longitude and latitude corresponding to each sub-satellite point of each satellite from the satellite trajectory data; determine the satellite trajectory to which each sub-satellite point belongs according to the timestamp and longitude and latitude corresponding to each sub-satellite point; for each satellite trajectory, interpolate the satellite trajectory according to the timestamp and longitude and latitude corresponding to each sub-satellite point contained in the satellite trajectory to obtain the trajectory points contained in the satellite trajectory; for each trajectory point, determine a rectangular area of ​​a specified size with the trajectory point as the center as the rectangular area corresponding to the trajectory point.

[0219] Optionally, the acquisition module 300 is specifically used to obtain a preset time interval; traverse the longitude and latitude corresponding to each sub-satellite point, and determine two adjacent sub-satellite points as a sub-satellite point pair; determine the time difference between each sub-satellite point included in each sub-satellite point pair according to the timestamps corresponding to each sub-satellite point included in each sub-satellite point pair; for each sub-satellite point pair, if the time difference between each sub-satellite point included in the sub-satellite point pair is different from the preset time interval, then it is determined that each sub-satellite point included in the sub-satellite point pair belongs to different satellite tracks; if the time difference between each sub-satellite point included in the sub-satellite point pair is the same as the preset time interval, then it is determined that each sub-satellite point included in the sub-satellite point pair belongs to the same satellite track.

[0220] Optionally, the acquisition module 300 is specifically used to, for each satellite trajectory, sort the sub-satellite points included in the satellite trajectory according to the timestamps corresponding to the sub-satellite points in the satellite trajectory to obtain a sub-satellite point sequence corresponding to the satellite trajectory; determine, for each sub-satellite point included in the sub-satellite point sequence corresponding to the satellite trajectory, the distance between the sub-satellite point and the next sub-satellite point of the sub-satellite point according to the longitude and latitude of the sub-satellite point and the longitude and latitude of the next sub-satellite point of the sub-satellite point in the sub-satellite point sequence; determine the number of interpolation points according to the distance between the sub-satellite point and the next sub-satellite point of the sub-satellite point and a preset length; insert the number of interpolation points between the sub-satellite point and the adjacent sub-satellite point according to the longitude and latitude of the sub-satellite point and the longitude and latitude of the next sub-satellite point of the sub-satellite point by linear interpolation method; and use the sub-satellite points included in the satellite trajectory and the determined interpolation points as the trajectory points included in the satellite trajectory.

[0221] Optionally, the acquisition module 300 is specifically used to, for each trajectory point, determine the forward direction of the satellite trajectory to which the trajectory point belongs at the trajectory point and the vertical direction corresponding to the forward direction; obtain a specified size, and based on the specified size, the forward direction of the satellite trajectory to which the trajectory point belongs at the trajectory point and the vertical direction corresponding to the forward direction, determine multiple vertices corresponding to the trajectory point with the trajectory point as the center; and use a rectangular area formed by the multiple vertices corresponding to the trajectory point as the rectangular area corresponding to the trajectory point.

[0222] Optionally, the device further comprises:

[0223] The evaluation module 308 is specifically used to obtain the weather forecast data of the target imaging area at the target imaging time; determine the suitability evaluation result of performing the imaging task of the target imaging area at the target imaging time with the target satellite under the weather indicated by the weather forecast data, based on the acquired weather forecast data and the parameters of the imaging device carried by the target satellite, through a pre-constructed suitability model; and generate prompt information based on the suitability evaluation result, wherein the prompt information is used to prompt the user to adjust the target imaging time of the imaging task.

[0224] Optionally, the device further comprises:

[0225] The priority determination module 310 is specifically used to determine the regional importance evaluation index corresponding to the target imaging area; determine the specific event related to the target imaging area at the target imaging time, obtain the attribute information of the specific event, and the distance between the occurrence location corresponding to the specific event and the center of the target imaging area, and determine the heat evaluation index of the specific event; obtain the precipitation probability and cloud coverage percentage of the target imaging area at the target imaging time, and determine the weather suitability evaluation index corresponding to the target imaging area according to the obtained precipitation probability and cloud coverage percentage; determine the priority of the imaging task according to the regional importance evaluation index, the heat evaluation index and the weather suitability evaluation index;

[0226] Optionally, the execution module 306 is specifically configured to execute the imaging task according to the priority of the imaging task, the target satellite, the target imaging area and the target imaging time.

[0227] Optionally, the target satellite belongs to a target constellation including a plurality of satellites, and each satellite included in the target constellation images a target imaging area at a different time;

[0228] Optionally, the execution module 306 is specifically used to, through the imaging device carried by the target satellite, perform image acquisition on the target imaging area at the target imaging time to obtain a target image of the target imaging area; detect the target image to obtain a detection result of the target imaging area; when the detection result of the target imaging area indicates that there is an abnormal event in the target imaging area, determine an abnormal monitoring message according to the position information of the target imaging area, the event information of the abnormal event existing in the target imaging area and the abnormal monitoring time window, and send the abnormal monitoring message to each other satellite except the target satellite among the multiple satellites included in the target constellation, so that each other satellite responds to the abnormal monitoring message, acquires an image of the target imaging area through the imaging device carried by itself within the abnormal monitoring time window, and monitors abnormal events occurring in the target imaging area with the acquired image.

[0229] Optionally, the device further comprises:

[0230] The status monitoring module 312 is specifically used to determine the task completion time and status update cycle of the imaging task; when the status update cycle is reached, the current task status of the imaging task is determined according to the task completion time and the execution status of the imaging task, and the current task status of the imaging task is sent to the user through the message queue; the current task status includes one of unfinished, failed and completed; wherein, when the task completion time is not reached, the current task status of the imaging task is unfinished; when the task completion time is reached and the target image sent by the target satellite is not received, the task status of the imaging task is failed; when the task completion time is reached and the target image sent by the target satellite is received, the task status of the imaging task is completed; wherein, the target image is obtained by collecting the image of the target imaging area at the target imaging time through the imaging device carried by the target satellite when the target satellite performs the imaging task.

[0231] This specification also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the above Figure 2 The multi-satellite collaborative intelligent task execution method shown.

[0232] This manual also provides Figure 6 The schematic structure diagram of the electronic device shown in FIG. Figure 6 As mentioned above, at the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 2 Of course, in addition to the software implementation, this specification does not exclude other implementations, such as logic devices or a combination of software and hardware, etc., that is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0233] In the 1990s, it was very clear whether the improvement of a technology was hardware improvement (for example, improvement of the circuit structure of diodes, transistors, switches, etc.) or software improvement (improvement of the method flow). However, with the development of technology, many improvements of the method flow today can be regarded as direct improvements of the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be implemented with hardware entity modules. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask chip manufacturers to design and make dedicated integrated circuit chips. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one kind of HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0234] The controller may be implemented in any suitable manner, for example, the controller may take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (e.g., software or firmware) executable by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, and the memory controller may also be implemented as part of the control logic of the memory. It is also known to those skilled in the art that, in addition to implementing the controller in a purely computer-readable program code manner, the controller may be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, such a controller may be considered as a hardware component, and the devices for implementing various functions included therein may also be considered as structures within the hardware component. Or even, the devices for implementing various functions may be considered as both software modules for implementing the method and structures within the hardware component.

[0235] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0236] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0237] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0238] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0239] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0240] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0241] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0242] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0243] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0244] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0245] It should be understood by those skilled in the art that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, this specification may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0246] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0247] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0248] The above description is only an embodiment of the present specification and is not intended to limit the present specification. For those skilled in the art, the present specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification shall be included in the scope of the claims of the present specification.

Claims

1. A multi-satellite coordinated intelligent task execution method, characterized in that: include: Acquire satellite trajectory data of each satellite in advance, determine the rectangular area corresponding to each trajectory point of each satellite and the timestamp corresponding to each trajectory point according to the satellite trajectory data, and store them; wherein the rectangular area corresponding to the trajectory point is used to represent the imaging area of ​​the trajectory point in the geographic space; In response to the user's operation, an imaging area and an imaging time are determined, and an imaging task is generated; Matching the imaging area and imaging time with the stored rectangular areas corresponding to the trajectory points of the satellites and the timestamps corresponding to the trajectory points, to determine the target satellite, target imaging area and target imaging time for performing the imaging task; Execute the imaging task according to the target satellite, the target imaging area and the target imaging time; Wherein, determining the rectangular areas corresponding to the trajectory points of the satellites according to the satellite trajectory data specifically includes: Determine the timestamp and longitude and latitude corresponding to each sub-satellite point of each satellite from the satellite trajectory data; Determine the satellite tracks to which the sub-satellite points belong according to the timestamps and longitudes and latitudes corresponding to the sub-satellite points; For each satellite trajectory, interpolation processing is performed on the satellite trajectory according to the timestamps and longitudes and latitudes corresponding to the sub-satellite points contained in the satellite trajectory to obtain the trajectory points contained in the satellite trajectory; For each trajectory point, determine a rectangular area with a specified size and centered at the trajectory point as the rectangular area corresponding to the trajectory point; Determining the satellite tracks to which the sub-satellite points belong according to the timestamps and longitudes and latitudes corresponding to the sub-satellite points, specifically includes: Get the preset time interval; Traversing the longitudes and latitudes corresponding to the sub-satellite points, respectively, and determining two sub-satellite points adjacent to each other as a sub-satellite point pair; Determine the time difference between each sub-satellite point included in each sub-satellite point pair according to the timestamps corresponding to each sub-satellite point included in each sub-satellite point pair; For each sub-satellite point pair, if the time difference between the sub-satellite points included in the sub-satellite point pair is different from the preset time interval, it is determined that the sub-satellite points included in the sub-satellite point pair belong to different satellite tracks; If the time difference between the sub-satellite points included in the sub-satellite point pair is the same as the preset time interval, it is determined that the sub-satellite points included in the sub-satellite point pair belong to the same satellite trajectory.

2. The method according to claim 1, characterized in that For each satellite trajectory, the satellite trajectory is interpolated according to the timestamps and longitudes and latitudes of each sub-satellite point contained in the satellite trajectory to obtain each trajectory point contained in the satellite trajectory, specifically including: For each satellite trajectory, sort the sub-satellite points contained in the satellite trajectory according to the timestamps corresponding to the sub-satellite points contained in the satellite trajectory to obtain a sub-satellite point sequence corresponding to the satellite trajectory; For each sub-satellite point included in the sub-satellite point sequence corresponding to the satellite trajectory, determine the distance between the sub-satellite point and the sub-satellite point next to the sub-satellite point according to the longitude and latitude of the sub-satellite point and the longitude and latitude of the sub-satellite point next to the sub-satellite point in the sub-satellite point sequence; Determine the number of interpolation points according to the distance between the sub-satellite point and the next sub-satellite point of the sub-satellite point and a preset length; According to the longitude and latitude of the sub-satellite point and the longitude and latitude of the sub-satellite point next to the sub-satellite point, interpolating the number of interpolation points between the sub-satellite point and the adjacent sub-satellite point by linear interpolation method; The sub-satellite points included in the satellite trajectory and the determined interpolation points are used as trajectory points included in the satellite trajectory.

3. The method according to claim 1, characterized in that For each track point, a rectangular area with a specified size and centered at the track point is determined as the rectangular area corresponding to the track point, specifically including: For each trajectory point, determine the forward direction of the satellite trajectory to which the trajectory point belongs at the trajectory point and the vertical direction corresponding to the forward direction; Obtaining a specified size, and determining a plurality of vertices corresponding to the trajectory point based on the specified size, a forward direction of the satellite trajectory to which the trajectory point belongs at the trajectory point, and a vertical direction corresponding to the forward direction, with the trajectory point as the center; A rectangular area formed by a plurality of vertices corresponding to the trajectory point is taken as the rectangular area corresponding to the trajectory point.

4. The method according to claim 1, characterized in that Before performing the imaging task according to the target satellite, the target imaging area and the target imaging time, the method further includes: Acquiring weather forecast data of the target imaging area at the target imaging time; According to the acquired weather forecast data and the parameters of the imaging device carried by the target satellite, a suitability evaluation result of performing the imaging task of the target imaging area by the target satellite at the target imaging time under the weather indicated by the weather forecast data is determined by using a pre-constructed suitability model; Prompt information is generated according to the suitability evaluation result, and the prompt information is used to prompt the user to adjust the target imaging time of the imaging task.

5. The method according to claim 1, characterized in that Before performing the imaging task according to the target satellite, the target imaging area and the target imaging time, the method further includes: Determining a regional importance evaluation index corresponding to the target imaging area; Determine a specific event related to the target imaging area at the target imaging time, obtain attribute information of the specific event, and the distance between the occurrence position corresponding to the specific event and the center of the target imaging area, and determine a heat evaluation index of the specific event; Obtaining the precipitation probability and cloud coverage percentage of the target imaging area at the target imaging time, and determining the weather suitability evaluation index corresponding to the target imaging area according to the obtained precipitation probability and cloud coverage percentage; Determining the priority of the imaging task according to the regional importance evaluation index, the heat evaluation index and the weather suitability evaluation index; Executing the imaging task according to the target satellite, the target imaging area and the target imaging time specifically includes: According to the priority of the imaging task, the imaging task is executed according to the target satellite, the target imaging area and the target imaging time.

6. The method according to claim 1, characterized in that The target satellite belongs to a target constellation including a plurality of satellites, and each satellite included in the target constellation images a target imaging area at a different time; Executing the imaging task according to the target satellite, the target imaging area and the target imaging time specifically includes: By using the imaging device carried by the target satellite, the target imaging area is imaged at the target imaging time to obtain a target image of the target imaging area; Detecting the target image to obtain a detection result of the target imaging area; When the detection result of the target imaging area indicates that an abnormal event exists in the target imaging area, an abnormal monitoring message is determined according to the position information of the target imaging area, the event information of the abnormal event existing in the target imaging area and the abnormal monitoring time window, and the abnormal monitoring message is sent to each other satellite except the target satellite among the multiple satellites included in the target constellation, so that each other satellite responds to the abnormal monitoring message, collects images of the target imaging area through the imaging equipment carried by itself within the abnormal monitoring time window, and monitors abnormal events occurring in the target imaging area with the collected images.

7. The method according to claim 1, characterized in that The method further comprises: Determine the task completion time and status update period of the imaging task; When the status update cycle is reached, the current task status of the imaging task is determined according to the task completion time and the execution status of the imaging task, and the current task status of the imaging task is sent to the user through a message queue; The current task status includes one of unfinished, failed and completed; wherein, when the task completion time is not reached, the current task status of the imaging task is unfinished; when the task completion time is reached and the target image sent by the target satellite is not received, the task status of the imaging task is failed; when the task completion time is reached and the target image sent by the target satellite is received, the task status of the imaging task is completed; The target image is obtained by collecting images of the target imaging area at the target imaging time through an imaging device carried by the target satellite when the target satellite performs the imaging mission.

8. A multi-satellite coordinated intelligent task execution device, characterized in that: include: An acquisition module, used to pre-acquire satellite trajectory data of each satellite, determine the rectangular area corresponding to each trajectory point of each satellite and the timestamp corresponding to each trajectory point according to the satellite trajectory data, and store them; wherein the rectangular area corresponding to the trajectory point is used to represent the imaging area of ​​the trajectory point in the geographic space; A task generation module, used to determine the imaging area and imaging time in response to the user's operation, and generate an imaging task; A matching module, used to match the imaging area and imaging time with the stored rectangular areas corresponding to the trajectory points of the satellites and the timestamps corresponding to the trajectory points, to determine the target satellite, target imaging area and target imaging time for performing the imaging task; An execution module, used for executing the imaging task according to the target satellite, the target imaging area and the target imaging time; The acquisition module is specifically used to determine the timestamp and longitude and latitude corresponding to each sub-satellite point of each satellite from the satellite trajectory data; determine the satellite trajectories to which each sub-satellite point belongs according to the timestamp and longitude and latitude corresponding to each sub-satellite point; for each satellite trajectory, interpolate the satellite trajectory according to the timestamp and longitude and latitude corresponding to each sub-satellite point included in the satellite trajectory to obtain each trajectory point included in the satellite trajectory; for each trajectory point, determine a rectangular area with a specified size centered on the trajectory point as the rectangular area corresponding to the trajectory point; The acquisition module is specifically used to obtain a preset time interval; traverse the longitudes and latitudes corresponding to each sub-satellite point, and determine two adjacent sub-satellite points as a sub-satellite point pair; determine the time difference between each sub-satellite point included in each sub-satellite point pair according to the timestamps corresponding to each sub-satellite point included in each sub-satellite point pair; for each sub-satellite point pair, if the time difference between each sub-satellite point included in the sub-satellite point pair is different from the preset time interval, then determine that each sub-satellite point included in the sub-satellite point pair belongs to different satellite tracks; if the time difference between each sub-satellite point included in the sub-satellite point pair is the same as the preset time interval, then determine that each sub-satellite point included in the sub-satellite point pair belongs to the same satellite track.

9. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of claims 1 to 7 is implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method described in any one of claims 1 to 7 is implemented.

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