LEO satellite-oriented scheduling method, medium and equipment

Abstract

The invention discloses a scheduling method, medium and equipment for LEO satellites, and relates to the technical field of satellite scheduling, and the method comprises the steps: constructing a region-of-interest coverage system for cooperative observation of a plurality of LEO satellites; according to an orbit and a shooting visual field of an LEO satellite in the system, the region of interest is fragmented; on the premise of minimizing full coverage of RoI by image acquisition, the purpose of minimizing the rotation energy consumption of a satellite camera is taken as a target, and shooting tasks are allocated to satellites according to fragments. According to the invention, not only is the rotation energy consumption of the camera reduced, but also the size of the image is ensured, so that the minimum RoI comprehensive coverage is realized under the condition that the total energy consumption of the satellite camera is lowest. And the performance is excellent and the robustness is good.

Description

Technical Field

[0001] The present invention relates to the field of satellite scheduling technology, and in particular to a scheduling method, medium and equipment for LEO satellites. Background Art

[0002] In recent years, Low Earth Orbit (LEO) satellites have become a hot topic in academia and industry due to their high sensing accuracy, fast communication capabilities and low cost, which has promoted the successful launch of many LEO satellites. Equipped with high-resolution cameras, communication modules and advanced processors, LEO satellites provide technical support for earth observation missions and are widely used in fields such as carbon emission monitoring, disaster response and environmental analysis. In these missions, multiple satellites are usually required to coordinate observations to fully cover the region of interest (RoI).

[0003] However, as mission complexity increases, the energy problem of LEO satellites becomes increasingly severe. Due to the small size of satellites, the limited area of ​​solar panels, and the low battery capacity, energy shortages affect satellite performance and mission execution. Secondly, when multiple satellites are coordinated for observation, non-RoI image capture may be increased, further increasing energy consumption. Therefore, it is necessary to reasonably allocate satellite image capture tasks.

[0004] At present, academia and industry are mainly focused on reducing image size to optimize camera energy consumption for satellite remote sensing missions. Current research ignores the impact of satellite task allocation and camera rotation angle on camera energy consumption for remote sensing missions. Summary of the invention

[0005] The purpose of the present invention is to solve the problem that the existing satellite camera scheduling focuses on reducing the image size and fails to achieve effective energy optimization, and proposes a scheduling method for LEO satellites, comprising the following steps:

[0006] S1. Construct a coverage system of the area of ​​interest for collaborative observation by multiple LEO satellites;

[0007] S2, according to the orbit and shooting field of view of the LEO satellite in the system, the area of ​​interest is divided into slices;

[0008] S3. Under the premise of minimizing the full coverage of RoI by image acquisition, the goal is to minimize the rotation energy consumption of the satellite camera and schedule the shooting tasks of the satellite according to the slices.

[0009] Furthermore, when the number of satellites in the coverage system is 2, the intersection angle of the two satellite orbits is 80°-100°; when the number of satellites in the coverage system is greater than 2, all satellite orbits have two conditions: two are parallel to each other and the intersection angle is 80°-100°.

[0010] Furthermore, a LEO satellite forms a strip with a width equal to the shooting field of view when it orbits one circle. Each LEO satellite camera forms two observation strips by rotating the areas on both sides of the shooting track. The observation strips of all satellites form a series of grids, which divide the RoI into a series of slices, and all slices form a complete RoI area.

[0011] Furthermore, each satellite can only capture one of the slices on both sides of the orbit at the same time; two satellites in the ascending and descending orbit directions in the same space with an intersection angle of 80°-100° are grouped for analysis;

[0012] A satellite in an ascending orbit satisfies:

[0013]

[0014] in, Indicates whether the nth satellite captures the fragment with coordinates (i, j). If yes, then otherwise I represents the set of all rows in the shard, J represents the set of all columns in the shard, Indicates whether the nth satellite is in an ascending orbit. If yes, then otherwise

[0015] A satellite in a descending orbit satisfies:

[0016]

[0017] And satisfy:

[0018]

[0019] in, Indicates whether the nth satellite is in a descending orbit. If yes, then otherwise Indicates whether the nth satellite can capture the fragment with coordinates (i, j).

[0020] Furthermore, in order to achieve full coverage of the area of ​​interest, the following conditions must be met:

[0021]

[0022] Where N represents the set of LEO satellites.

[0023] Furthermore, the camera rotation energy consumption of satellite n is expressed as:

[0024]

[0025] Among them, θn represents the rotation energy consumption of the nth satellite camera, M represents the slice set, suc((i,j)) represents the coordinates of the next slice taken after the nth satellite takes the slice (i,j), (i′,j′) represents a coordinate in suc((i,j)), Indicates whether the nth satellite captures the fragment with coordinates (i′, j′), E ro Represents the energy required for one rotation of the camera;

[0026] And the shooting energy satisfies the following constraints:

[0027]

[0028] in, It represents the energy required for the nth satellite to capture the slice (i, j), E thres Indicates the upper limit of shooting energy;

[0029] The scheduling target is expressed as min∑ n∈N θ n .

[0030] The present invention also proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned scheduling method for LEO satellites is implemented.

[0031] The present invention also proposes an electronic device, comprising a processor and a memory, wherein the processor and the memory are interconnected, wherein the memory is used to store a computer program, the computer program comprises computer-readable instructions, and the processor is configured to call the computer-readable instructions to execute the above-mentioned scheduling method for LEO satellites.

[0032] The beneficial effects brought by the technical solution provided by the present invention are:

[0033] The present invention first divides the RoI into slices according to the satellite observation strips, and by jointly considering the image size and camera rotation energy consumption obtained by the satellite camera shooting the RoI slices, the satellite photography tasks are allocated based on the premise of minimizing the full coverage of the RoI by image acquisition, with the purpose of minimizing the camera rotation energy consumption. The present invention not only reduces the rotation energy consumption of the camera, but also ensures the size of the image, so that the minimized RoI full coverage is achieved with the lowest overall energy consumption. The performance is excellent and the robustness is good. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is a flow chart of a scheduling method for LEO satellites according to an embodiment of the present invention;

[0035] Figure 2It is a schematic diagram of slices captured by a camera of a group of ascending orbit and descending orbit satellites according to an embodiment of the present invention;

[0036] Figure 3 These are three slicing scenarios of an embodiment of the present invention;

[0037] Figure 4 This is a schematic diagram of the results of photographing a slice of the RoI area using satellites in different orbital directions according to an embodiment of the present invention;

[0038] Figure 5 is a schematic diagram of a satellite camera rotating for shooting according to an embodiment of the present invention;

[0039] Figure 6 is a block diagram of an electronic device in an exemplary embodiment of the present invention;

[0040] Figure 7 It is the sum of the rotational energy consumption of the satellite camera using three algorithms (CPO, REO, EC) to shoot different maps and the content ratio of the picture. Figure 7 (a) shows the rotational energy consumption of satellite cameras using three algorithms to capture different maps. Figure 7 (b) is the sum of the content proportions of the images of different maps taken by the three algorithms;

[0041] Figure 8 It is the sum of the rotational energy consumption of satellite cameras and the content proportion of the images when using three algorithms (CPO, REO, EC) to capture the same area of ​​interest under different numbers of satellites. Figure 8 (a) shows the rotational energy consumption of satellite cameras using three algorithms to capture the same area of ​​interest under different numbers of satellites. Figure 8 (b) is the sum of the content proportions of the images of the same area of ​​interest taken using the three algorithms under different numbers of satellites;

[0042] Fig. 9 It is the sum of the rotational energy consumption of the satellite camera and the content proportion of the image when shooting the same area of ​​interest using three algorithms (CPO, REO, EC) at different shooting energies. Fig. 9 (a) shows the rotation energy consumption of the satellite camera using three algorithms to shoot the same area of ​​interest at different shooting energies. Fig. 9 (b) is the sum of the content proportions of images of the same area of ​​interest taken using three algorithms at different shooting energies. DETAILED DESCRIPTION

[0043] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0044] The flowchart of the scheduling method for LEO satellites according to an embodiment of the present invention is as follows: Figure 1 , specifically including the following steps:

[0045] S1. Construct a coverage system of the area of ​​interest for collaborative observation by multiple LEO satellites.

[0046] The LEO satellite camera remains stationary and takes pictures while flying around its orbit, forming an observation strip. During the flight of the satellite, each satellite camera can rotate to shoot one of the strips on both sides of the orbit. Therefore, each satellite corresponds to two observation strips. The strips formed by multiple satellites in ascending and descending orbits crisscross to complete the coverage of the area of ​​interest. The number of satellites is required to be able to complete full coverage of the RoI. Two satellites in the ascending and descending orbit directions in the same space with an intersection angle of 80°-100° are analyzed as a group (at the same time, satellites in the ascending and descending orbit directions do not necessarily appear in the ascending and descending orbits at the same time.), and the intersection angle of the satellite orbits of each group is required to be 80°-100°. According to the scope of the area of ​​interest, the system is required to have more than or equal to 2 satellites, and there must be at least one group of two satellites whose orbits intersect at an angle of 80°-100°. When the number of satellites in the coverage system is 2, the intersection angle of the two satellite orbits is 80°-100°; when the number of satellites in the coverage system is greater than 2, all satellite orbits have two conditions: parallel to each other and the intersection angle is 80°-100°. The observation strips of all satellites form a series of grids to completely cover the area of ​​interest.

[0047] S2. According to the orbit and field of view of the LEO satellite in the system, the region of interest is divided into slices. The observation strips of all satellites divide the RoI into a series of grids, called slices, and all slices form a complete RoI area.

[0048] S3. Under the premise of minimizing the full coverage of RoI by image acquisition, the goal is to minimize the rotation energy consumption of the satellite camera and schedule the shooting tasks of the satellite according to the slices.

[0049] refer to Figure 2 , Figure 2 1 is a schematic diagram of slices captured by a camera of a group of ascending orbit and descending orbit satellites according to an embodiment of the present invention, wherein: Figure 2 The multiple crisscross observation strips are formed by multiple satellite cameras. The figure only explains the satellite camera allocation for the slices in the figure. Figure 2The observation strips of the two satellites in the figure are two observation strips located on both sides of their respective running directions. The main axes of the orbits of the two LEO satellites are marked by arrows in the figure. The figure shows the fields of view of the cameras of the two LEO satellites before they each shoot a slice. The figure shows a quadrilateral region of interest (RoI) and a slice in the region of interest. Since the camera shooting width is fixed but the shooting length is variable, the satellite running in the ascending orbit can shoot the slice in a smaller size. When the satellite in the descending orbit shoots the slice, due to the fixed shooting width, an additional area needs to be shot on the shooting strip of the satellite in the descending orbit where the slice is located, and the size of the shot image is larger. Assigning the slice to the satellite in the ascending orbit can reduce the size of the image, but in order to achieve shooting, the satellite camera in the ascending orbit needs to rotate the camera to turn the field of view from the observation strip on the right side of the satellite orbit to the observation strip on the left side. The additional camera rotation will cause more energy consumption.

[0050] In order to minimize the camera energy consumption of satellite shooting RoI, the satellite image can fully cover the RoI area under the premise of minimum, and effectively reduce the energy consumption generated by the rotation of the satellite remote sensing camera. First of all, it is necessary to consider the task allocation of the target RoI slice. Since the shooting width of the high-precision camera is fixed, while the length is variable, different satellite orbits bring different shooting angles, which will cause differences in the size of the captured RoI image. Therefore, the system divides the slices into three types. In one slice scenario, the RoI area of ​​the ascending orbit satellite shooting perspective accounts for a larger proportion; in another slice scenario, the RoI area of ​​the descending orbit satellite shooting perspective accounts for a larger proportion; and the last is a scene where both orbital satellites are suitable for shooting. Figure 3 As shown, Figure 3 These are three slice scenes of an embodiment of the present invention. One side of slice 1 is the same width as the image taken by the ascending orbit satellite, so the image size taken by the ascending orbit satellite is small; one side of slice 2 is the same width as the image taken by the descending orbit satellite, so the image size taken by the descending orbit satellite is small; one side of slice 3 is the same width as the image taken by the ascending orbit satellite, and the other side is the same width as the image taken by the descending orbit satellite, so both orbit satellites are suitable for photographing slice 3.

[0051] like Figure 4 As shown, Figure 4This is a schematic diagram of the results of shooting a slice of the RoI area using satellites in different orbital directions in an embodiment of the present invention. It can be found that shooting a slice of the RoI area using a descending orbit satellite will result in shooting additional non-RoI areas (such as the blank area in the figure), increasing the amount of shooting tasks and increasing energy consumption; shooting using an ascending orbit satellite only covers the RoI area, and the non-target area is smaller and consumes less energy, so the slice shooting task should be assigned to the ascending orbit satellite. In summary, first of all, it is necessary to reduce the camera shooting energy consumption and image size by assigning the slice to the most suitable satellite.

[0052] Secondly, the turning strategy of the satellite camera needs to be considered. During the flight of the satellite, the LEO satellite camera can rotate within a limited range, that is, at time t1, it points to any strip on the left or right side of the satellite's orbit. At time t2, t2>t1, if the satellite's mission target slice is in another strip, the satellite must rotate the camera to point to another strip to complete the shooting of the slice. Therefore, it is necessary to assign the shooting task to the satellite that best matches the orbital direction and camera rotation angle based on the slice position, so as to further reduce energy consumption. When necessary, certain slices can be assigned to satellites with mismatched orbital directions for shooting, reducing the camera rotation energy consumption. Although the non-RoI image size is increased, energy is allocated between the image size and the camera rotation energy consumption, thereby minimizing the total energy consumption of the shooting task. For example Figure 5 As shown, Figure 5 is a schematic diagram of a satellite camera rotating for shooting according to an embodiment of the present invention, Figure 5 In the figure, the satellite flies from left to right. At time t1, the satellite camera captures the slice on the right side of the flight track (i.e., the slice below in the figure). At time t2, the satellite camera needs to rotate by an angle α to point to the strip on the left side of the track and capture the slice on the left side of the flight track (i.e., the slice below in the figure).

[0053] The above strategy is expressed using a formula. The area of ​​interest coverage system consists of a group of LEO satellites, denoted as N = {1, 2, ..., N}, where N represents the LEO satellite set. and Indicates whether the nth satellite is in an ascending orbit or a descending orbit, 1 for yes, 0 otherwise. Indicates that the nth satellite is in an ascending orbit, Indicates that the nth satellite is not in an ascending orbit, Indicates that the nth satellite is in a descending orbit, Indicates that the nth satellite is not in a descending orbit. hour hour so, and The following constraints are met:

[0054] The two-dimensional coordinate information of the RoI slice can be expressed as a set M = {(i, j)}. Each satellite can only observe the slices on the left and right sides of its orbit at any time, and the slices outside the orbit range cannot be observed. Indicates whether the nth satellite can observe the fragment (i, j), where

[0055] Since the shooting width of the satellite camera is fixed and the length is adjustable, shooting the same slice from different directions will result in different image sizes. Therefore, the camera's shooting energy will also be different. represents the energy required for satellite n to capture slice (i, j).

[0056] For each slice, there may be multiple satellites to choose from. In order to clearly indicate which satellite took the slice, a new variable is introduced M represents the fragment set, indicating whether the nth satellite captures fragment (i, j). The prerequisite is Right now And satisfy: I represents the set of all rows in the shard, and J represents the set of all columns in the shard. In order to ensure full coverage of the RoI, it must be satisfied In order to achieve this, we can sacrifice a little bit of photo size to reduce the total energy consumption of the camera (camera energy composition: shooting energy + rotation energy) so that the shooting energy meets the following constraints:

[0057]

[0058] in, It represents the energy required for the nth satellite to capture the slice (i, j), E thres Indicates the upper limit of the shooting energy.

[0059] The goal of the present invention is to minimize the energy consumption caused by the rotation of the satellite camera. For the nth satellite, its rotation energy consumption is expressed as:

[0060]

[0061] Among them, θ n represents the camera rotation energy consumption of the nth satellite, suc((i,j)) represents the coordinates of the next slice after the nth satellite takes slice (i,j), (i′,j′) represents a coordinate in suc((i,j)), Indicates whether the nth satellite captures the fragment with coordinates (i′, j′), E roRepresents the energy required for the camera to rotate once.

[0062] The final scheduling goal of the problem can be expressed as min∑ n∈N θ n .

[0063] Using the slicing algorithm proposed in the present invention, the slicing is assigned to the corresponding satellite, and then the slicing assignment result is uploaded to the corresponding satellite along with the uploading of the remote sensing task; in the process of assigning the RoI slicing shooting task, considering the rotational energy consumption of the satellite camera and the content ratio of the image, the satellite with the lowest energy consumption is selected for each RoI slicing shooting task for shooting; when the assigned satellite is a satellite that has flown by, the algorithm will go back to the moment when the satellite just arrived and clear the assignment result of the RoI slicing shooting task after that moment, and assign the slicing shooting task to the optimal satellite, and continue to assign all the remaining RoI slicing shooting tasks to ensure that the energy consumption of the entire shooting task is minimized. Subsequently, the satellite executes the shooting task and performs the corresponding on-board processing on the image, and then transmits the subsequent data to the ground, and finally performs data processing and result aggregation on the ground.

[0064] In an exemplary embodiment, a computer-readable storage medium is included, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned scheduling method for LEO satellites is implemented.

[0065] See also Figure 6 In an exemplary embodiment, an electronic device is also included, including at least one processor, at least one memory, and at least one communication bus.

[0066] A computer program is stored in the memory, and the computer program includes computer-readable instructions. The processor calls the computer-readable instructions stored in the memory through a communication bus to execute the above-mentioned scheduling method for LEO satellites.

[0067] In order to evaluate the performance of the algorithm proposed in the present invention, the performance improvement of the method of the present invention in actual application scenarios was verified by using real-world maps and simulation environments. Specifically, the present invention first simulated a constellation consisting of 200 satellites, which are evenly distributed in 20 orbits. Each satellite is evenly arranged in its orbit, and multiple satellites are used to conduct comprehensive coverage scanning of the area of ​​interest and the artificially generated maps based on the area of ​​interest from different directions. The present invention sets the satellite camera to be able to rotate within a range of 15° on both sides of the orbit, and the satellite camera consumes approximately 100 joules of energy each rotation. Detailed parameters are set for the satellites in this system: the satellite orbit altitude is set to 550 kilometers, and the inclination of the satellite orbit is set to approximately 53 degrees. This design ensures that the satellite can cover the earth's surface from the poles to most longitude regions.

[0068] Algorithm that only considers content ratio (content ratio refers to the ratio of the RoI area to the area of ​​the image of each slice in the image taken. The larger the value, the smaller the photo size) (also named CPO): This scheme only considers maximizing the content ratio, without considering the energy consumption caused by the rotation of the satellite camera, while ensuring full coverage of the RoI.

[0069] Consider only rotational energy (also named REO): This scheme only considers minimizing the rotational energy consumption of the satellite camera without considering the content ratio of the satellite image while ensuring full coverage of the RoI.

[0070] The algorithms (EC), CPO and REO proposed in this invention are evaluated from three different perspectives, namely different maps, different numbers of satellites and different shooting energy restrictions.

[0071] Evaluation reference of algorithms EC, CPO, REO from different map perspectives Figure 7 , Figure 7 It is the sum of the rotational energy consumption of the satellite camera using three algorithms (CPO, REO, EC) to shoot different maps and the content ratio of the picture. Figure 7 (a) shows the rotational energy consumption of satellite cameras using three algorithms to capture different maps. Figure 7 (b) is the sum of the content proportions of images of different maps taken by the three algorithms.

[0072] Depend on Figure 7 It can be seen that the EC algorithm reduces the rotation energy consumption of the camera while ensuring full coverage of the RoI. At the same time, it also ensures the size of the image, which minimizes the energy consumption of the RoI shooting task. Moreover, through the test of multiple maps, the EC algorithm not only has excellent performance, but also shows strong robustness.

[0073] Evaluation reference of algorithms EC, CPO, REO from the perspective of different numbers of satellites Figure 8 , Figure 8 It is the sum of the rotational energy consumption of satellite cameras and the content proportion of the images when using three algorithms (CPO, REO, EC) to capture the same area of ​​interest under different numbers of satellites. Figure 8 (a) shows the rotational energy consumption of satellite cameras using three algorithms to capture the same area of ​​interest under different numbers of satellites. Figure 8 (b) is the sum of the content proportions of images of the same area of ​​interest taken using three algorithms with different numbers of satellites.

[0074] By comparison Figure 8 (a) and Figure 8 In (b), it can be seen that when the number of satellites is 3, due to the limitation of the satellite camera’s field of view, it is impossible to fully cover the RoI, resulting in a very low content ratio. When the number of satellites increases to 4, the RoI can be fully covered. In this case, the EC algorithm not only significantly improves the content ratio of the image, but also minimizes the rotation energy consumption of the camera. However, since some slices were not taken by the satellite in the correct direction, the content ratio did not reach the maximum value.

[0075] As the number of satellites further increases, when the number of satellites increases to 6, the camera rotation energy consumption of algorithm REO and algorithm EC is reduced to 0, and the content proportion of algorithm EC and algorithm CPO reaches the maximum value. At this time, the overall performance of algorithm EC is the best. In general, regardless of the number of satellites, algorithm EC always maintains excellent performance.

[0076] Evaluation reference of algorithms EC, CPO, REO from different shooting energy perspectives Fig. 9 , Fig. 9 It is the sum of the rotational energy consumption of the satellite camera and the content proportion of the image when shooting the same area of ​​interest using three algorithms (CPO, REO, EC) at different shooting energies. Fig. 9 (a) shows the rotation energy consumption of the satellite camera using three algorithms to shoot the same area of ​​interest at different shooting energies. Fig. 9 (b) is the sum of the content proportions of images of the same area of ​​interest taken using three algorithms at different shooting energies.

[0077] pass Fig. 9 (a) and Fig. 9As can be seen in (b), when the shooting energy is 180J, the shooting energy is very small, the content ratio of the three algorithms is not high, and the camera rotation energy consumption is relatively low. The three algorithms cannot complete the full coverage of the RoI. When the shooting energy is 195J, the algorithm CPO can complete the full coverage of the RoI. Although the content ratio of the algorithm EC is not the largest at this time, the total energy consumption of the camera is reduced to the minimum. As the upper limit of the shooting energy continues to increase, the EC algorithm maintains the image size at an optimal value and reduces the camera rotation energy consumption to the minimum, so that the energy consumption of the RoI shooting task is minimized. Secondly, the upper limit of the required shooting energy is not high. Overall, regardless of the amount of satellite shooting energy, the EC algorithm always maintains excellent performance.

[0078] In summary, the algorithm proposed in the present invention not only has excellent performance, but also has good robustness and is not affected by the map, the number of satellites and the shooting energy.

[0079] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A scheduling method for LEO satellites, characterized in that: The following steps are involved: S1. Construct a coverage system of the area of ​​interest for collaborative observation by multiple LEO satellites; S2, according to the orbit and shooting field of view of the LEO satellite in the system, the area of ​​interest is divided into slices; S3. Under the premise of minimizing the full coverage of RoI by image acquisition, the goal is to minimize the rotation energy consumption of the satellite camera and schedule the shooting tasks of the satellite according to the slices.

2. A scheduling method for LEO satellites according to claim 1, characterized in that: When there are two satellites in the coverage system, the intersection angle of the two satellite orbits is 80°-100°; when the number of satellites in the coverage system is greater than two, all satellite orbits have two situations: two are parallel to each other and the intersection angle is 80°-100°.

3. A scheduling method for LEO satellites according to claim 2, characterized in that: A LEO satellite forms a strip with a width equal to the shooting field of view when it orbits one circle. Each LEO satellite camera forms two observation strips by rotating the areas on both sides of the shooting orbit. The observation strips of all satellites form a series of grids, which divide the RoI into a series of slices. All slices form a complete RoI area.

4. The scheduling method for LEO satellites according to claim 1, characterized in that: Each satellite can only capture one of the slices on both sides of the orbit at the same time; two satellites in the ascending and descending orbit directions in the same space with an intersection angle of 80°-100° are grouped for analysis; A satellite in an ascending orbit satisfies: in, Indicates whether the nth satellite captures the fragment with coordinates (i, j). If yes, then otherwise I represents the set of all rows in the shard, J represents the set of all columns in the shard, Indicates whether the nth satellite is in an ascending orbit. If yes, then otherwise A satellite in a descending orbit satisfies: And satisfy: in, Indicates whether the nth satellite is in a descending orbit. If yes, then otherwise Indicates whether the nth satellite can capture the fragment with coordinates (i, j).

5. A scheduling method for LEO satellites according to claim 4, characterized in that: In order to achieve complete coverage of the area of ​​interest, the following conditions must be met: Where N represents the set of LEO satellites.

6. A scheduling method for LEO satellites according to claim 5, characterized in that: The camera rotation energy consumption of satellite n is expressed as: Among them, θ n represents the rotation energy consumption of the nth satellite camera, M represents the slice set, suc((i,j)) represents the coordinates of the next slice taken after the nth satellite takes the slice (i,j), (i′,j′) represents a coordinate in suc((i,j)), Indicates whether the nth satellite captures the fragment with coordinates (i′, j′), E r0 Represents the energy required for one rotation of the camera; And the shooting energy satisfies the following constraints: in, It represents the energy required for the nth satellite to capture the slice (i, j), E thres Indicates the upper limit of shooting energy; The scheduling target is expressed as min∑ n∈N θ n .

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

8. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the processor and the memory are interconnected, wherein the memory is used to store a computer program, the computer program comprises computer-readable instructions, and the processor is configured to call the computer-readable instructions to execute the method according to any one of claims 1 to 6.

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