A method for rapid decomposition of autonomous tasks on satellite

Abstract

The present invention discloses a method for rapid decomposition of autonomous tasks on a satellite, including: obtaining the sub-satellite point position of the satellite when the target point is observed; constructing a model of the adjacent spatial distribution characteristics of the sun-synchronous regression orbit, and obtaining an orbit number distribution table; obtaining the observation orbit number of the target point to be observed by analytical calculation; solving the observation time window of the target point to obtain the time window of the four corner points of the region; for the regional target, according to the vertex grid information of the time window of the four corner points of the region and the orbit and wave position corresponding to the left and right end points of the horizontal boundary, the grid through which the horizontal boundary of the regional target passes is obtained by inference; then combined with the grids corresponding to the upper and lower horizontal boundaries of the known regional target, all grids corresponding to the region are further obtained to determine the start and end time of the observation strip. The present invention realizes the global inference solution capability of the point target time window through analytical calculation, and has the advantages of high calculation efficiency, high accuracy, and small amount of required data.

Description

Technical Field

[0001] The invention belongs to the field of aerospace remote sensing, and in particular relates to a method for quickly decomposing autonomous tasks on a satellite. Background Art

[0002] With the continuous development of aerospace technology, satellites use the equipment carried by their payloads to conduct high-resolution and high-precision observations of the earth's surface. They are widely used in agriculture, forestry, urban planning, ocean monitoring and other fields, and have become one of the most important means of observation. The visible window of a satellite to a ground target refers to the time range in which the field of view payload carried by the satellite can observe the target. The calculation of this visible window, also known as task decomposition, is the basis for satellites to perform observation tasks and is the prerequisite for many tasks such as regional target coverage calculation and observation task planning.

[0003] In the traditional satellite mission planning process, the satellite's observation plan is pre-made by the ground control center. This method is difficult to respond quickly to dynamic observation tasks or emergency observation needs, and it is difficult to adapt to new needs due to the inability to deploy ground stations globally and the lengthy mission planning information link. Therefore, it is of great significance to switch from the satellite-ground loop to autonomous mission planning on the satellite, and task decomposition is an important part of it. The computing resources and storage resources on the satellite are very limited. The traditional task decomposition method is difficult to use on the satellite, and it is difficult to fully utilize the satellite's observation resources. Summary of the invention

[0004] The purpose of the present invention is to provide a method for rapid decomposition of autonomous tasks on a satellite. The method makes full use of the characteristics of a sun-synchronous regression orbit satellite, studies the spatial distribution law of its trajectory, constructs a rapid matching processing method for satellite sub-satellite points and ground targets for space point targets, and approximates and quickly obtains the time window of the space point; on this basis, for regional targets, a boundary solution method based on slope adaptive fitting is further proposed, which quickly divides the regional observation strips, thereby accurately and efficiently decomposing the ground targets to be observed by the satellite to meet the needs of autonomous mission planning on the satellite.

[0005] To achieve the above object, the present invention provides a method for rapidly decomposing autonomous tasks on a satellite, comprising:

[0006] Based on the principle of satellite orbit motion and spatial distribution characteristics, the sub-satellite position of the satellite is obtained when the target point is observed;

[0007] According to the relative motion characteristics of the satellite and the earth in the revisit orbit, the orbit number in the satellite revisit period is used as a variable to build a model of the adjacent space distribution characteristics of the sun-synchronous regression orbit, and obtain the orbit number distribution table;

[0008] Select the reference orbit, and obtain the observation orbit number of the target point to be observed by analytical calculation based on the reference orbit data, the longitude and latitude information of the point target and the regional target to be observed using the satellite orbit distribution law;

[0009] For point targets, based on the reference orbit data, each orbit trajectory and the distribution law of the observation area, the observation time window of the target point is solved to obtain the time windows of the four corner points of the area;

[0010] For regional targets, based on the vertex grid information of the time window of the four corner points of the region and the orbits and wave positions corresponding to the left and right end points of the lateral boundary, combined with the geographical distribution law of the satellite trajectory, the grid through which the lateral boundary of the regional target passes is inferred; then, combined with the grids corresponding to the upper and lower lateral boundaries of the known regional targets, all grids corresponding to the region are further obtained to determine the start and end time of the observation strip.

[0011] Preferably, the process of obtaining the observation orbit number of the target point to be observed by analytical calculation using the satellite orbit distribution law includes:

[0012] Through the matching processing method of the satellite sub-satellite point and the ground target, the sub-satellite point position of the satellite when the space point is observed is inferred from the input space point position information, and the longitude difference between this space point and the corresponding point in the reference orbit and the average longitude difference between the orbits are divided to obtain the number of orbits between the two, and the orbit number distribution table is searched to obtain the observation orbit number corresponding to this target point.

[0013] Preferably, the matching processing method of the satellite sub-satellite point and the ground target includes:

[0014] Assume that the number of regression circles is N, point T is the target point to be observed, M is the satellite sub-satellite point when the target T is observed obtained by T and satellite-to-ground mapping, M' is the sub-satellite point of the same latitude corresponding to M in the reference orbit; R' is the observation area of ​​the satellite at M', and M is the observation area when the satellite observes T;

[0015] For the space point T, through sub-satellite point mapping, the corresponding satellite sub-satellite point M when the vertex can be observed is obtained, and then the sub-satellite point M' at the same latitude of M in the reference orbit is obtained;

[0016] According to the longitude difference D of M-M' and the average longitude difference d between the orbits, where d = 360° / N, N is the number of regression circles, D is divided by d and rounded to get the number of orbits n between T and the reference orbit, that is,

[0017] Then, according to the track number distribution table, the observation track number corresponding to the target point can be obtained by looking up the table.

[0018] Preferably, the process of obtaining the grid through which the lateral boundary of the regional target is pushed includes:

[0019] For regular rectangular area targets, the four vertices of the area target are regarded as point targets and the grid information corresponding to the vertices is obtained; according to whether the tracks corresponding to the left and right endpoints of a horizontal boundary are the same, the grid through which the horizontal boundary of the area target passes is obtained.

[0020] Preferably, the process of obtaining the grid through which the lateral boundary of the regional target passes according to whether the tracks corresponding to the left and right endpoints of a lateral boundary are the same comprises:

[0021] For the case where the left and right vertices correspond to the same track, the time window where each wave position in the middle intersects with the lateral boundary is calculated according to the wave position number. After obtaining each wave position between the two vertices, the observation time when each wave position intersects with the grid is determined in turn to obtain the intersecting grid information;

[0022] For two vertices corresponding to adjacent tracks, the passage of the wave positions corresponding to the two tracks through the grid is determined respectively;

[0023] If the tracks corresponding to two vertices are not adjacent, and there is one or more tracks passing through the lateral boundary, the grids intersecting the lateral boundary are calculated for each track.

[0024] Preferably, the process of further acquiring all grids corresponding to the region in combination with the grids corresponding to the upper and lower lateral boundaries of the known regional target and determining the start and end times of the observation strip includes:

[0025] According to the overlapping of the strips corresponding to the lateral boundaries, the regional targets are classified to obtain the regional target classification results;

[0026] Different regions are extracted according to the regional target classification results, and the start and end times of the observation strips corresponding to the different regions are obtained through the regional slope adaptive fitting solution method.

[0027] Preferably, the process of classifying the regional targets according to the overlap of the strips corresponding to the lateral boundaries includes:

[0028] According to the overlap of the strips corresponding to the lateral boundaries, the regional targets are divided into: the strips corresponding to the upper boundary and the strips corresponding to the lower boundary have an intersection, that is, there is an overlap between the orbital wave position corresponding to the grid passed by the upper boundary and the orbital wave position corresponding to the lower boundary; the strips corresponding to the upper and lower boundaries of the regional target are adjacent; and the strips corresponding to the upper and lower boundaries have no intersection, and there is an unknown strip in between.

[0029] Preferably, the process of extracting different regions according to the regional target classification result includes:

[0030] According to the regional target classification result, the overlapping part where the start and end time of the strip observation is known is extracted; the lower triangular part corresponding to the lower boundary where the start time of the strip observation is known; the upper triangular part corresponding to the upper boundary where the end time of the strip observation is known; and the unknown boundary part where the start and end time of the strip observation are unknown.

[0031] Preferably, the process of obtaining the start and end times of the observation strips corresponding to different regions by the regional slope adaptive fitting solution method includes:

[0032] For the overlapping parts of the strip observations with known start and end times, strip matching is performed based on the overlapping parts of the strips corresponding to the upper and lower boundaries, as well as the start and end times of all strip observations in the known area;

[0033] For the lower triangular part corresponding to the lower boundary with known strip observation start time, the start time of all strip observations in the known area and the end time of the strip observation are known in the ascending orbit. The slope adaptive fitting method is used to fit the strip to be sought to a straight line according to the starting grid and the observation area of ​​several unit times before and after it, and the intersection with the left boundary is obtained, and then the grid number of the target area corresponding to the strip to be sought is obtained, and the strip observation end time is obtained.

[0034] For the upper triangular part corresponding to the upper boundary where the end time of strip observation is known, the end time of all strip observations in the area is known in the ascending orbit. According to the end grid and straight line fitting method, the intersection with the right boundary is calculated, and then the grid number and observation start time of the target area corresponding to the strip to be calculated are obtained;

[0035] For the unknown boundary part where the start and end times of the strip observation are unknown, the start and end times of all strip observations in the area are unknown. The observation center time of the nearest strip in the adjacent upper and lower triangular areas is referred to, which is approximated as the center time of the current strip observation. The data of several unit times before and after are combined to fit a point-slope straight line, and the intersection points of the point-slope straight line and the left and right boundaries of the regional target are obtained. The corresponding grid number is obtained according to the distance between the intersection points and the average grid width, and then the observation start and end times are obtained.

[0036] Compared with the prior art, the present invention has the following advantages and technical effects:

[0037] For ground point targets to be observed, the present invention establishes a satellite-to-ground inverse model based on the satellite orbit motion principle and spatial distribution characteristics, constructs a rapid mapping capability from point targets to satellite sub-satellite points, and provides support for the subsequent target observation orbit solution based on satellite sub-satellite points.

[0038] The present invention relies on a given single-orbit reference data and combines the orbital spatial distribution law of the satellite in the sun-synchronous regression orbit to achieve the global inference solution capability of the point target time window through analytical calculation. It has the advantages of high calculation efficiency, high accuracy and small amount of data required.

[0039] The present invention divides regional targets into three categories: co-track, adjacent track and cross-track according to the orbit conditions corresponding to the vertices of the horizontal boundaries, and then the observation grid corresponding to the horizontal boundary of the regional target is deduced by the satellite trajectory and the spatial distribution law of the observation area. Further, according to whether the strips corresponding to the grids of the upper and lower horizontal boundaries of the region are intersected, the regional targets to be observed are divided into three categories: there is an intersection between the strips corresponding to the region, the strips are adjacent, and the strips are separated by one or more unknown strips; then, according to whether the observation start and end times of these strips are known, four types of areas are extracted from the above three types of targets: the start and end times of the observation strips are known, only the start time is known, only the end time is known, and the start and end times are unknown. The intersection grids of the strips and the vertical boundaries are obtained by the known grid information and the slope adaptive fitting method, that is, the unknown strip observation start or end time is obtained, thereby realizing the rapid segmentation of the regional target observation strips, with a simple principle and high accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0041] Figure 1 A schematic diagram of a method flow chart of an embodiment of the present invention;

[0042] Figure 2 A relative position diagram of a target point, a target point sub-satellite point, a satellite trajectory, etc. according to an embodiment of the present invention;

[0043] Figure 3 A schematic diagram of track overlap and relative positions of point targets according to an embodiment of the present invention;

[0044] Figure 4 These are three situations corresponding to the upper and lower boundaries of the regional target in the embodiment of the present invention;

[0045] Figure 5 Schematic diagram of four types of regions in an embodiment of the present invention;

[0046] Figure 6 Schematic diagram of four regional slope adaptive fitting solution methods according to an embodiment of the present invention. DETAILED DESCRIPTION

[0047] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0048] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0049] like Figure 1 As shown, this embodiment provides a method for quickly decomposing autonomous tasks on a satellite, including:

[0050] Based on the principle of satellite orbit motion and spatial distribution characteristics, the sub-satellite position of the satellite is obtained when the target point is observed;

[0051] According to the relative motion characteristics of the satellite and the earth in the revisit orbit, the orbit number in the satellite revisit period is used as a variable to build a model of the adjacent space distribution characteristics of the sun-synchronous regression orbit, and obtain the orbit number distribution table;

[0052] Select the reference orbit, and obtain the observation orbit number of the target point to be observed by analytical calculation based on the reference orbit data, the longitude and latitude information of the point target and the regional target to be observed using the satellite orbit distribution law;

[0053] Based on the reference orbit data, each orbit trajectory and the distribution law of the observation area, the observation time window of the target point is solved to obtain the time windows of the four corner points of the area;

[0054] For regional targets, the grids through which the lateral boundaries of regional targets pass are deduced based on the vertex grid information of the time window of the four corner points of the region and the orbits and wave positions corresponding to the left and right end points of the lateral boundaries, combined with the geographical distribution law of satellite tracks. Then, combined with the grids corresponding to the upper and lower lateral boundaries of the known regional targets, all grids corresponding to the region are further obtained to determine the start and end times of the observation strips.

[0055] Furthermore, the specific steps of this method include:

[0056] Step 1: Based on the principle of satellite orbital motion and spatial distribution characteristics, calculate the sub-satellite position of the satellite when the target point is observed, and build a fast matching capability between the satellite and the ground.

[0057] Step 2: Through in-depth exploration of the satellite-to-earth relative motion characteristics of the revisit orbit, taking the orbit number within the satellite revisit period as a variable, a model for the adjacent spatial distribution characteristics of the sun-synchronous regression orbit is established to obtain the orbit number distribution table.

[0058] Step 3: The user selects the reference orbit and inputs the reference orbit data, the longitude and latitude information of the point target and regional target to be observed into the target point observation orbit rough allocation module.

[0059] Step 4: In the rough allocation module of the target point observation orbit, the orbit number for observing this target point is solved by analytical calculation using the satellite orbit distribution law.

[0060] Specifically, in the spatial point time window fast solution module, a set of reference orbit data is first given by the target point observation orbit rough allocation module, and then a distribution model based on the sun-synchronous orbit is established, and a fast matching processing method for satellite sub-satellite points and ground targets is constructed. The sub-satellite point position of the satellite when this spatial point is observed is inferred from the input spatial point position information, and the longitude difference between this point and the corresponding point in the reference orbit and the average longitude difference between the orbits are divided to obtain the number of orbits between the two, and the observation orbit number corresponding to this target point is obtained by looking up the table.

[0061] like Figure 2 As shown in , assuming that the number of regression circles is N, point T is the target point to be observed, M is the satellite sub-satellite point when the target T is observed obtained by mapping T and the satellite to the ground, the yellow track is the given reference orbit, M' is the sub-satellite point of the same latitude corresponding to M in the reference orbit; R' is the observation area where the satellite is located at M', and M is the observation area when the satellite observes T; the green track is the roughly allocated observation orbit calculated in this section, and the purple track is the left and right adjacent orbits of the observation orbit. For the spatial point T, through the sub-satellite point mapping in the first step, the corresponding satellite sub-satellite point M when the vertex can be observed is obtained. Then calculate the sub-satellite point M' at the same latitude of M in the reference orbit. According to the longitude difference D of M-M' and the average longitude difference d between orbits, where d=360° / N, and N is the number of regression circles, divide D by d and round up to get the number of orbits n between T and the reference orbit, that is, Then, the observation orbit number of the target point can be obtained by looking up the orbit number distribution table obtained in the second step.

[0062] Step 5: In the rough allocation module of observation wave position and time, the observation time window of the target point is quickly solved based on the reference orbit data, the orbital trajectories and the distribution law of the observation area.

[0063] The orbital height of a near-circular orbit satellite is approximately unchanged during its operation. Therefore, the latitude and longitude span and inclination of the observation area at the same latitude during the satellite operation can be considered the same, and the relative positions of each wave position in the observation area can also be considered the same. Based on this, first find the relative time m in the orbit of the corresponding sub-satellite point at the same latitude in the reference orbit data, as well as the satellite observation area R' at this time. Using the longitude difference D between M-M' obtained in the fourth step, R' is translated by a distance of D to the observation orbit, which is approximately used as the observation area R of this orbit at the time m in the orbit. Then determine the wave position and observation time of the vertex in R.

[0064] In actual satellite orbit design, there is usually overlap between adjacent orbits and between wave positions within an orbit. The higher the latitude, the greater the overlap ratio. Figure 3 As shown in , a target point may correspond to multiple time windows. Therefore, it is also necessary to determine the left and right adjacent tracks of the obtained track, that is, Figure 2 The purple track in the figure is used to determine whether the target point is visible. The method is the same as the principle described in the previous part of this section. So far, the solution of the point target time window has been completed.

[0065] Step 6: For regional targets, the four vertex grid information obtained in the previous five steps is input into the regional lateral boundary grid deduction and solution module. According to the orbit and wave position corresponding to the left and right end points of the lateral boundary, combined with the geographical distribution law of the satellite trajectory, the grid through which the lateral boundary of the regional target passes is deduced.

[0066] For regular rectangular area targets, the four vertices of the area target are regarded as point targets. According to the methods in the first five steps, the grid information corresponding to the vertices is obtained by analytical methods. According to whether the tracks corresponding to the left and right endpoints of a horizontal boundary are the same, three cases are discussed: the left and right vertices correspond to the same track (same track), adjacent tracks (adjacent tracks), and non-adjacent tracks (cross tracks):

[0067] (1) For the same track, the two vertices correspond to the same track. The time window where each intermediate wave position intersects with the lateral boundary is calculated according to the wave position number. That is, for each wave position between the two vertices, the observation time when they intersect with the grid is determined in turn to obtain the intersecting grid information.

[0068] (2) For adjacent tracks, the two vertices correspond to adjacent tracks, and the passage of the corresponding wave positions of the two tracks through the grid is determined respectively.

[0069] (3) For cross-track, the tracks corresponding to the two vertices are not adjacent, and there is one or more tracks passing through this lateral boundary. Similarly, the grids intersecting with the lateral boundary are calculated for these tracks respectively.

[0070] Step 7: In the regional boundary solution module based on slope adaptive fitting, all grids corresponding to the upper and lower lateral boundaries of the known regional target are further calculated to determine the start and end time of the observation strip.

[0071] According to the overlap of the corresponding strips of the lateral boundaries, regional targets are divided into three types:

[0072] (a) The strip corresponding to the upper boundary and the strip corresponding to the lower boundary have an intersection, that is, there is an overlap between the orbital wave position corresponding to the grid through which the upper boundary passes and the orbital wave position corresponding to the lower boundary.

[0073] (b) The strips corresponding to the upper and lower boundaries of the regional target are adjacent.

[0074] (c) The strips corresponding to the upper and lower boundaries have no intersection, and there is an unknown strip in between.

[0075] like Figure 4 As shown, the red strips are the strips corresponding to the upper boundary of the regional target, the blue strips are the strips corresponding to the lower boundary of the regional target, and the green grid is the grid through which the lateral boundary obtained in the sixth step passes. Their orbit number, wave position number and observation time are known.

[0076] From these three cases, we can extract Figure 5 Four areas:

[0077] (I) The overlapping part where the start and end times of the band observation are known.

[0078] (II) The lower triangular part corresponding to the lower boundary where the start time of the strip observation is known.

[0079] (III) The upper triangular part corresponding to the upper boundary where the end time of the strip observation is known.

[0080] (IV) The unknown boundary portion where the start and end times of the strip observation are unknown.

[0081] for Figure 4 The objectives in (a) are discussed in the first, second and third category areas respectively; Figure 4 The objectives in (b) are discussed in the second and third category areas respectively; Figure 4 The objectives in (c) are discussed in the second, third and fourth category areas respectively. Figure 6 In the figure, the red grid represents the grid obtained in the sixth step with known information, the green grid is the grid to be determined, where the strip intersects with the left and right boundaries, the black dots are the "points" in the point-slope fitting line, and are the vertices of the known red grid. The orange line is fitted based on the red grid several seconds before and after, and the red dots are the intersections of the fitting line and the boundary.

[0082] For the first type of area, it is the overlapping part of the strips corresponding to the upper and lower boundaries. The start and end times of all strip observations in the area are known, and strip matching can be performed;

[0083] For the second type of area, the start time of all strip observations in the area is known under the condition of orbit raising, and the end time of observation of the strip to be found is known. Using the slope adaptive fitting method, for the strip to be found, according to the observation area of ​​the starting grid and several unit times before and after it, this strip is approximately fitted as a straight line, and its intersection with the left boundary is calculated, and then the grid number of the target area corresponding to this strip is obtained, and the end time of strip observation can be obtained;

[0084] For the third type of area, the end time of all strip observations in the area is known in the case of orbit raising. Similar to the second type of area, according to the end grid and straight line fitting method, the intersection with the right boundary is calculated, and then the grid number and observation start time of the target area corresponding to this strip are obtained.

[0085] For the Category IV area, the start and end times of all strip observations in the area are unknown. Therefore, the observation center time of the nearest strip in the adjacent upper and lower triangular areas is referred to, which is approximated as the center time of the strip observation. The data of several unit times before and after it are fitted into a point-slope straight line, and the intersection of this straight line with the left and right boundaries of the regional target is calculated. The corresponding grid number is calculated from the distance between the two points and the average grid width, and then the observation start and end times are obtained.

[0086] Step 8: Complete task decomposition, organize and store the decomposed strip information to be observed.

[0087] For ground point targets to be observed, the present invention establishes a satellite-to-ground inverse model based on the satellite orbit motion principle and spatial distribution characteristics, constructs a rapid mapping capability from point targets to satellite sub-satellite points, and provides support for the subsequent target observation orbit solution based on satellite sub-satellite points.

[0088] The present invention relies on a given single-orbit reference data and combines the orbital spatial distribution law of the satellite in the sun-synchronous regression orbit to achieve the global inference solution capability of the point target time window through analytical calculation. It has the advantages of high calculation efficiency, high accuracy and small amount of data required.

[0089] The present invention divides regional targets into three categories: co-track, adjacent track and cross-track according to the orbit conditions corresponding to the vertices of the horizontal boundaries, and then the observation grid corresponding to the horizontal boundary of the regional target is deduced by the satellite trajectory and the spatial distribution law of the observation area. Further, according to whether the strips corresponding to the grids of the upper and lower horizontal boundaries of the region are intersected, the regional targets to be observed are divided into three categories: there is an intersection between the strips corresponding to the region, the strips are adjacent, and the strips are separated by one or more unknown strips; then, according to whether the observation start and end times of these strips are known, four types of areas are extracted from the above three types of targets: the start and end times of the observation strips are known, only the start time is known, only the end time is known, and the start and end times are unknown. The intersection grids of the strips and the vertical boundaries are obtained by the known grid information and the slope adaptive fitting method, that is, the unknown strip observation start or end time is obtained, thereby realizing the rapid segmentation of the regional target observation strips, with a simple principle and high accuracy.

[0090] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for rapid decomposition of autonomous tasks on a satellite, characterized in that: include: Based on the principle of satellite orbit motion and spatial distribution characteristics, the sub-satellite position of the satellite is obtained when the target point is observed; According to the relative motion characteristics of the satellite and the earth in the revisit orbit, the orbit number in the satellite revisit period is used as a variable to build a model of the adjacent space distribution characteristics of the sun-synchronous regression orbit, and obtain the orbit number distribution table; Select the reference orbit, and obtain the observation orbit number of the target point to be observed by analytical calculation based on the reference orbit data, the longitude and latitude information of the point target and the regional target to be observed using the satellite orbit distribution law; For point targets, based on the reference orbit data, each orbit trajectory and the distribution law of the observation area, the observation time window of the target point is solved to obtain the time windows of the four corner points of the area; For regional targets, according to the vertex grid information of the time window of the four corner points of the region and the orbits and wave positions corresponding to the left and right end points of the lateral boundary, combined with the geographical distribution law of the satellite trajectory, the grid through which the lateral boundary of the regional target passes is deduced; then combined with the grids corresponding to the upper and lower lateral boundaries of the known regional targets, all grids corresponding to the region are further obtained to determine the start and end time of the observation strip; Combining the grids corresponding to the upper and lower lateral boundaries of the known regional target, further obtaining all grids corresponding to the region, and determining the start and end time of the observation strip include: According to the overlapping of the strips corresponding to the lateral boundaries, the regional targets are classified to obtain the regional target classification results; Extract different regions according to the regional target classification results, and obtain the start and end times of the observation strips corresponding to the different regions through the regional slope adaptive fitting solution method; The process of obtaining the start and end times of observation strips corresponding to different regions through the regional slope adaptive fitting solution method includes: For the overlapping parts of the strip observations with known start and end times, strip matching is performed based on the overlapping parts of the strips corresponding to the upper and lower boundaries, as well as the start and end times of all strip observations in the known area; For the lower triangular part corresponding to the lower boundary with known strip observation start time, the start time of all strip observations in the known area and the end time of the strip observation are known in the ascending orbit. The slope adaptive fitting method is used to fit the strip to be sought to a straight line according to the starting grid and the observation area of ​​several unit times before and after it, and the intersection with the left boundary is obtained, and then the grid number of the target area corresponding to the strip to be sought is obtained, and the strip observation end time is obtained. For the upper triangular part corresponding to the upper boundary where the end time of strip observation is known, the end time of all strip observations in the area is known in the ascending orbit. According to the end grid and straight line fitting method, the intersection with the right boundary is calculated, and then the grid number and observation start time of the target area corresponding to the strip to be calculated are obtained; For the unknown boundary part where the start and end times of the strip observation are unknown, the start and end times of all strip observations in the area are unknown. The observation center time of the nearest strip in the adjacent upper and lower triangular areas is referred to, which is approximated as the center time of the current strip observation. The data of several unit times before and after are combined to fit a point-slope straight line, and the intersection points of the point-slope straight line and the left and right boundaries of the regional target are obtained. The corresponding grid number is obtained according to the distance between the intersection points and the average grid width, and then the observation start and end times are obtained.

2. The method for rapid decomposition of autonomous tasks on a satellite according to claim 1, characterized in that: The process of obtaining the observation orbit number of the target point to be observed by analytical calculation using the satellite orbit distribution law includes: Through the matching processing method of the satellite sub-satellite point and the ground target, the sub-satellite point position of the satellite when the space point is observed is inferred from the input space point position information, and the longitude difference between this space point and the corresponding point in the reference orbit and the average longitude difference between the orbits are divided to obtain the number of orbits between the two, and the orbit number distribution table is searched to obtain the observation orbit number corresponding to this target point.

3. The method for rapid decomposition of autonomous tasks on a satellite according to claim 2, characterized in that: The matching processing method of the satellite sub-satellite point and the ground target includes: Assume that the number of regression circles is N, point T is the target point to be observed, M is the satellite sub-satellite point when the target T is observed obtained by T and satellite-to-ground mapping, M' is the sub-satellite point of the same latitude corresponding to M in the reference orbit; R' is the observation area of ​​the satellite at M', and M is the observation area when the satellite observes T; For the space point T, through sub-satellite point mapping, the corresponding satellite sub-satellite point M when the vertex can be observed is obtained, and then the sub-satellite point M' at the same latitude of M in the reference orbit is obtained; According to the longitude difference D of M-M' and the average longitude difference d between the orbits, where d = 360° / N, N is the number of regression circles, D is divided by d and rounded to get the number of orbits n between T and the reference orbit, that is, Then, according to the track number distribution table, the observation track number corresponding to the target point can be obtained by looking up the table.

4. The method for rapid decomposition of autonomous tasks on a satellite according to claim 1, characterized in that: The process of obtaining the grid through which the lateral boundary of the regional target is derived includes: For regular rectangular area targets, the four vertices of the area target are regarded as point targets and the grid information corresponding to the vertices is obtained; according to whether the tracks corresponding to the left and right endpoints of a horizontal boundary are the same, the grid through which the horizontal boundary of the area target passes is obtained.

5. The method for rapid decomposition of autonomous tasks on a satellite according to claim 4, characterized in that: The process of obtaining the grid through which the lateral boundary of the regional target passes according to whether the tracks corresponding to the left and right endpoints of a lateral boundary are the same includes: For the case where the left and right vertices correspond to the same track, the time window where each wave position in the middle intersects with the lateral boundary is calculated according to the wave position number. After obtaining each wave position between the two vertices, the observation time when each wave position intersects with the grid is determined in turn to obtain the intersecting grid information; For two vertices corresponding to adjacent tracks, the passage of the wave positions corresponding to the two tracks through the grid is determined respectively; If the tracks corresponding to two vertices are not adjacent, and there is one or more tracks passing through the lateral boundary, the grids intersecting the lateral boundary are calculated for each track.

6. The method for rapid decomposition of autonomous tasks on a satellite according to claim 1, characterized in that: The process of classifying regional targets according to the overlap of the corresponding strips of the lateral boundaries includes: According to the overlap of the strips corresponding to the lateral boundaries, the regional targets are divided into: the strips corresponding to the upper boundary and the strips corresponding to the lower boundary have an intersection, that is, there is an overlap between the orbital wave position corresponding to the grid passed by the upper boundary and the orbital wave position corresponding to the lower boundary; the strips corresponding to the upper and lower boundaries of the regional target are adjacent; and the strips corresponding to the upper and lower boundaries have no intersection, and there is an unknown strip in between.

7. The method for rapid decomposition of autonomous tasks on a satellite according to claim 1, characterized in that: The process of extracting different regions according to the regional target classification results includes: According to the regional target classification result, the overlapping part where the start and end time of the strip observation is known is extracted; the lower triangular part corresponding to the lower boundary where the start time of the strip observation is known; the upper triangular part corresponding to the upper boundary where the end time of the strip observation is known; and the unknown boundary part where the start and end time of the strip observation are unknown.

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