Self-adaptive discretization decomposition method and device for observation planning of regional target by satellite

Abstract

The invention discloses a self-adaptive discretization decomposition method and device for observation planning of a satellite on a regional target, belongs to the technical field of spaceflight, and particularly relates to strip decomposition of the satellite on the regional target. The problems that according to an existing regional target decomposition method, the time for regional target visibility coverage condition and observation strip decomposition operation of a satellite is long, and the efficiency is low are solved. The method comprises the following steps: determining a discretization step length of a regional target according to an observation range of a satellite load; discretizing the regional target into a regional sub-node set based on the discretization step length and the shape of the earth; the regional sub-node set comprises a plurality of sub-nodes. The adaptive discretization decomposition method and device for observation planning of the satellite on the regional target are suitable for task planning calculation of observation of a single or multiple earth observation satellites on a single or multiple irregular-shaped regional targets.

Description

Technical Field

[0001] The invention relates to the field of aerospace technology, and in particular to strip decomposition of regional targets by satellites. Background Art

[0002] In recent years, with the development of space information technology, a multi-satellite joint earth observation planning system has been formed, which is composed of multiple earth observation satellites of different models, types and purposes. In order to improve the working efficiency of satellites and the utilization rate of satellite payloads, optimize the observation tasks of satellite systems and reduce operating costs, it is necessary to carry out satellite mission planning and scheduling to formulate efficient observation mission plans.

[0003] Since the satellite is operating at a certain orbital altitude, the field of view of the onboard remote sensor is limited, and the remote sensor can only observe a limited ground area at the same time. For larger regional targets on the ground, they cannot be covered by a single observation strip of the satellite. Before satellite observation, they must be decomposed into multiple observation strips, that is, the regional targets are decomposed into meta-tasks that the satellite can perform at a time. The regional decomposition method determines the satellite's observation efficiency of regional targets in a certain sense, and it is of great significance to study efficient regional target decomposition technology. Therefore, it is necessary to develop an efficient regional target decomposition method to improve the observation efficiency of multiple satellites.

[0004] At present, the regional target decomposition method mainly uses geometric algorithms to calculate the observation strips and collect relevant geometric data such as the area, intersection and position of the region to determine the observation decomposition and area coverage of the regional target. The existing regional target decomposition method has the problem of long calculation time when facing irregular polygonal areas.

[0005] In summary, with the increase in the number of satellites and targets involved in satellite mission planning and the diversification of regional targets, how to speed up the satellite's visibility calculation speed for regional targets and provide timely options for subsequent satellite mission planning is an urgent problem that needs to be solved. Summary of the invention

[0006] The present invention proposes an adaptive discretization decomposition method and device for satellite observation planning of regional targets, which solves the problems of long calculation time and low efficiency of satellite visibility coverage of regional targets and observation strip decomposition in existing regional target decomposition methods.

[0007] The adaptive discretization decomposition method for satellite observation planning of regional targets of the present invention comprises the following steps:

[0008] Determine the step size: Determine the discretization step size of the regional target according to the observation range of the satellite payload;

[0009] Discretization into sub-node set step: discretizing the regional target into a regional sub-node set based on the discretization step size and the shape of the earth; the regional sub-node set includes a plurality of sub-nodes;

[0010] Steps for calculating the minimum observation elevation angle: Calculate the minimum observation angle of the satellite to each sub-node in the regional target in each circle and the target sub-node for which the satellite has an observation opportunity in each circle;

[0011] Subnode grouping step: construct a strip interval and group all target subnodes according to the minimum observation angle and target subnode;

[0012] Steps for merging strips: According to the grouping of all target sub-nodes, the target sub-nodes are merged into strips, and the convex hull algorithm is used to calculate the vertex position of the strips and the time window for the satellite to observe each group of strips.

[0013] Further, a preferred embodiment is provided, wherein the step of determining the step size comprises the following steps:

[0014] Step 1.1: Determine the observation range of the satellite payload:

[0015] Earth observation satellites are classified according to the observation range of the payload, and are divided into payloads with conical field of view and rectangular field of view. Among them, the payloads with conical field of view have the same field of view angle in all directions, and the payloads with rectangular field of view have different field of view angles in two mutually perpendicular directions.

[0016] Assume that the minimum altitude of the satellite orbit is h, and the half angle of the payload of the conical field of view is α 1 , the half angle of the rectangular field of view payload perpendicular to the satellite's forward direction is α 2 , the half angle of the payload of the rectangular field of view parallel to the satellite's forward direction is β;

[0017] The radius of the circular projection of the load in the conical field of view on the ground is R, and the side length of the rectangular projection of the load in the rectangular field of view on the ground is 2L. 1 and 2L 2 ; Where R = h·tanα 1 , L 1 =h·tanα 2 , L 2 =h·tanβ;

[0018] Step 1.2: Calculate the discretization step size of the regional target:

[0019] Assume that the discretization step size of the regional target is d, which is determined by the minimum observation range of the satellite payload;

[0020] For a cone-shaped field of view load,

[0021] For a rectangular field of view load,

[0022] Further, a preferred embodiment is provided, wherein the step of discretizing into a sub-node set comprises the following steps:

[0023] Step 2.1: Determine the position of each vertex of the regional target:

[0024] Determine the n vertices of the target area to be observed. The vertex positions are expressed in longitude and latitude, denoted as Points = [lat, lon] n , where lat represents latitude and lon represents longitude;

[0025] Let the maximum latitude of the vertex be lat max , the minimum latitude of the vertex is lat min , the maximum longitude of the vertex is lon max , the minimum longitude of a vertex is lon min ;

[0026] Step 2.2: Override the region target using child nodes:

[0027] Step 2.2.1: Calculate the longitude set of the child node according to the longitude and latitude range of the vertices of the regional target described in step 2.1:

[0028] From the vertex corresponding to the minimum longitude and minimum latitude [lat min ,lon min ], add child nodes one by one in the direction of the same latitude and high longitude with a step size of d; in the process of adding child nodes each time:

[0029] Let the longitude of the starting point be lon 0 , latitude is lat 0 , the latitude corresponds to the radius of the earth's latitude circle

[0030]

[0031] Among them, a is the major semi-axis of the earth; b is the minor semi-axis of the earth (polar radius);

[0032] The longitude of the new child node obtained by moving in the same latitude and high longitude direction is lon 1 :

[0033]

[0034] Repeat adding child nodes until the longitude of the new child node is greater than or equal to lon max , get the longitude set of the child node;

[0035] Step 2.2.2: Based on the longitude and latitude range of the vertices of the regional target described in step 2.1, the longitude set of the child nodes obtained in step 2.2.1 is diffused toward the high latitude direction so that the child nodes cover the regional target:

[0036] Starting from each child node in the longitude set, add child nodes one by one in the direction of high latitude with the same longitude; in the process of adding child nodes each time:

[0037] Let the longitude of the starting point be lon 0 ', latitude is lat 0 ', move to the same longitude and high latitude direction to obtain the new child node with a latitude of lat 1 ;

[0038]

[0039] in, is the Earth's flattening;

[0040] Repeat adding child nodes until the latitude of the new child node is greater than or equal to lat max , get the longitude and latitude set of the child node;

[0041] Step 2.3: Remove the child nodes outside the region target and obtain the region child node set:

[0042] Step 2.3.1: According to the longitude and latitude set of the child node obtained in step 2.2, traverse each child node in the longitude and latitude set of the child node to obtain the longitude and latitude position of each child node;

[0043] Set any child node in the longitude and latitude set of child nodes as node k ;

[0044] Step 2.3.2: Get the number of intersections between the rightward ray of the child node and the boundary line of the target region:

[0045] For each boundary line of the regional target, the two vertices of the boundary line are recorded as point i and point j ;

[0046] For a child node whose latitude is between the latitudes of two vertices of the boundary line, if the child node is on the left side of the boundary line formed by the two vertices, it is considered that the rightward ray of the child node has an intersection with the boundary line; where:

[0047] If the conditions are met Then the child node is considered k The latitude is between the latitudes of the two vertices of the boundary line;

[0048] If the conditions are met Then the child node is consideredk On the left side of the boundary line, it is considered as the child node k The rightward ray and the two vertices point i and point j The constituent boundary lines have a point of intersection;

[0049] Step 2.3.3: According to the number of intersection points obtained in step 2.3.2, determine whether the child node is within the area target;

[0050] Traverse each child node in the latitude and longitude set of the child node:

[0051] If any child node k If the number of intersections between the rightward ray and the target boundary line of the region is even, then the child node k Outside the regional target;

[0052] All child nodes outside the regional target are deleted from the longitude and latitude set of the child nodes to obtain the regional child node set, which is recorded as Nodes.

[0053] Further, a preferred embodiment is provided, wherein the step of calculating the minimum observation elevation angle comprises the following steps:

[0054] Step 3.1: Set the start and end time of the observation mission scenario for the regional target;

[0055] Step 3.2: Use the orbit recursion algorithm to calculate the latitude and longitude data of the satellite's orbit every second in the observation mission scenario;

[0056] Assume that the latitude and longitude data of the satellite orbit per second is LLA = {lla 0 ,lla 1 ,…,lla j , ...}; among them, lla j is the latitude and longitude data sample of the satellite in the jth second of orbit;

[0057] lla j = {lat′ j ,lon′ j ,alt′ j};

[0058] Among them, lat j ' means lla j The latitude value, lon j ' means lla j The longitude value of alt j ' means lla j The height value of

[0059] Step 3.3: Circle division:

[0060] Traversing the satellite's orbit every second, the longitude and latitude data LLA:

[0061] When (lat j ′-lat 0 ′)·(lat j ' +1 -lat 0 ′)<0, lla j The indicated position is recorded as the end of the current lap, lla j+1 The indicated position is recorded as the beginning of the next orbit, and the longitude and latitude data of each orbit of the satellite are obtained;

[0062] Step 3.4: Calculate the overall geometric visibility time window of the satellite to all sub-nodes in the regional target in each orbit:

[0063] Step 3.4.1: Assume that in each orbit, the satellite's altitude is alt and the radius of the earth is R. e , then the distance from the satellite to the center of the earth is R Sat =R e +alt;

[0064] Step 3.4.2: Calculate the maximum range of the satellite's geometric visibility of any sub-node within the regional target on the earth's surface as η:

[0065]

[0066] Then the angle between the satellite and the geocentric angle of any sub-node in the regional target is

[0067] Step 3.4.3: Use binary search to calculate the overall geometric visibility time window of the satellite to all sub-nodes within the regional target:

[0068] Traverse each circle and divide each circle into the initial step length Perform binary search calculations to determine whether the satellite is within the geometrically visible time window based on the angle η, and obtain the time data of the start and end positions of the geometrically visible time window of the satellite for any subnode in the regional target; wherein, Indicates rounding up;

[0069] In each round, the time data of the start and end positions of the satellite's geometric visibility time window for each sub-node in the regional target are combined, and the earliest start time and the latest end time are selected to obtain the overall geometric visibility time window of the satellite for all sub-nodes in the regional target, which is called the overall geometric visibility time window;

[0070] Step 3.5: Based on the overall geometric visibility time window of the satellite to all sub-nodes in the regional target, calculate the minimum observation angle of the satellite to each sub-node in the regional target in each circle:

[0071] Step 3.5.1: Calculate the expression of the star lower line;

[0072] In each orbit of the satellite, the longitude and latitude of two sub-satellite points at the start and end positions in the overall geometric visible time window are obtained;

[0073] According to the longitude and latitude of the two sub-satellite points, the expression of the sub-satellite line is:

[0074]

[0075] in, The longitude of the sub-satellite point of the starting position in the overall geometric visibility time window; is the latitude of the sub-satellite point at the start position of the overall geometric visibility time window; The longitude of the sub-satellite point at the end of the overall geometric visibility time window; is the latitude of the sub-satellite point at the end of the overall geometric visible time window;

[0076] Step 3.5.2: Calculate the foot position of the perpendicular line from each sub-node in the regional sub-node set to the star line:

[0077] Combine the following two equations:

[0078]

[0079] According to the result of the joint operation, get any child node k The foot position of the perpendicular line to the lower line of the star:

[0080]

[0081] The subsatellite point position corresponding to the vertical foot position is any child node k The corresponding nearest sub-satellite point position is obtained, and then the satellite orbit position 11a corresponding to the vertical foot position is obtained. s ;

[0082] Step 3.5.3: Obtain the minimum observation angle for each sub-node in the regional target:

[0083] The satellite orbit position 11a corresponding to the vertical foot position s Converted to Earth-centered Earth-fixed coordinate system: ecef(lla s );

[0084] Any child node kConverted to the Earth-centered Earth-fixed coordinate system: ecef(node k );

[0085] The satellite targets any child node in the regional target k The minimum observation angle is ξ k :

[0086]

[0087] Step 3.6: Based on the overall geometric visibility time window of all subnodes in the regional target, calculate the target subnodes for which the satellite has observation opportunities in each orbit, as well as the payload visibility time window of the satellite to the regional target:

[0088] Step 3.6.1: Get the time period between the earliest start time and the latest end time of the overall geometric visible time window, and obtain the latitude and longitude data of the satellite orbit every second during this time period based on the orbit extrapolation data.

[0089] Step 3.6.2: Traverse the satellite and in each circle, perform a search on any child node in the target area. k The minimum observation angle ξ k :

[0090] If k ≤α+ω, then any corresponding child node k is the target subnode; the satellite has an observation opportunity for the target subnode;

[0091] Where ω is the maximum maneuvering side swing angle of the satellite; α is the half angle. For the load of the conical field of view, α = α 1 , for a rectangular field of view load, α = α 2 ;

[0092] Step 3.6.3: Get the satellite orbit position lla corresponding to the target subnode s '; Reference longitude and latitude data By satellite orbital position lla s 'Determine the scene time when the satellite has an observation opportunity for the target subnode;

[0093] Step 3.6.4: Select the earliest time and the latest time from the scene time when the satellite has observation opportunities for all target sub-nodes in each circle. The time window between the two is the payload visibility time window of the satellite for regional targets in each circle.

[0094] Further, a preferred implementation is provided, wherein the sub-node grouping step comprises the following steps:

[0095] Step 4.1: The minimum observation angle ξ corresponding to the target sub-node where the satellite has an observation opportunity in each orbit k 'Processing:

[0096] Determine the position relationship between the target subnode and the satellite line. If the target subnode is on the left side of the satellite line, the minimum observation angle ξ k 'Take a negative value, otherwise the value remains unchanged:

[0097]

[0098] In all target child nodes, let ξ k The minimum value of ' is ξ min , k The maximum value of ' is ξ max ;

[0099] Step 4.2: Take ξ min The corresponding target child node is the starting point, 2α is the step size, and ξ max The corresponding target sub-node is the end point, and the strip interval is constructed. All target sub-nodes are divided into Groups:

[0100] [ξ min ,ξ min +2α],[ξ min +2α,ξ min +4α],......,[...,ξ max ];

[0101] The average value of the minimum observation angle of each set of two end points is the side swing angle of each set of satellite imaging.

[0102] Further, a preferred embodiment is provided, wherein the step of merging stripes comprises the following steps:

[0103] Step 5.1: Merge each group of target sub-nodes using the convex hull algorithm to obtain the vertex positions of the strips corresponding to each group of target sub-nodes;

[0104] Step 5.2: The visible time window of the payload of each group of target sub-nodes is used as the time window for satellite observation of each group of strips;

[0105] Step 5.3: The ratio of the number of target sub-nodes included in each group of stripes to the number of all sub-nodes of the regional target is taken as the target coverage rate of each group of stripes.

[0106] The present invention also proposes an adaptive discretization decomposition device for satellite observation planning of regional targets, and the device includes the following modules:

[0107] Determine step size module: Determine the discretization step size of regional targets according to the observation range of satellite payload;

[0108] Discretization into sub-node set module: discretizes the regional target into a regional sub-node set based on the discretization step size and the shape of the earth; the regional sub-node set includes multiple sub-nodes;

[0109] Module for calculating the minimum observation elevation angle: Calculates the minimum observation angle of the satellite to each sub-node in the regional target in each circle and the target sub-node that the satellite has the opportunity to observe in each circle;

[0110] Subnode grouping module: constructs strip intervals and groups all target subnodes according to the minimum observation angle and target subnodes;

[0111] Strip merging module: According to the grouping of all target sub-nodes, the target sub-nodes are merged into strips, and the convex hull algorithm is used to calculate the vertex position of the strips and the time window for the satellite to observe each group of strips.

[0112] The present invention also proposes a computer system, comprising: a processor and a memory, wherein the memory is used to store executable instructions of the processor, and the processor is configured to execute any one of the above-mentioned adaptive discretization decomposition methods for satellite observation planning of regional targets by executing the executable instructions.

[0113] The present invention also proposes a computer storage medium, in which a computer program is stored. When the computer program is run, the adaptive discretization decomposition method for satellite observation planning of regional targets described in any one of the above items is executed.

[0114] The present invention also proposes a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the adaptive discretization decomposition method for satellite observation planning of regional targets as described in any one of the above.

[0115] The present invention has the following beneficial effects:

[0116] 1. The adaptive discretization decomposition method and device for satellite observation planning of regional targets of the present invention adopt an adaptive discretization method based on the satellite payload observation range to discretize the regional targets to be observed into regional sub-nodes; the minimum observation angle of the satellite to the regional sub-nodes is used to represent the observation situation of the satellite to the target; the regional sub-nodes are merged into strips according to the minimum observation angle required by the regional sub-nodes, and the time window of the satellite strip observation is determined for reference in subsequent mission planning.

[0117] 2. The adaptive discretization decomposition method and device for satellite observation planning of regional targets described in the present invention determine the step size of regional target discretization according to the detection range of the satellite payload to adapt to different observation payloads of different satellites; discretize continuous regional targets into sub-nodes for separate calculation of observation conditions to reduce the complexity of calculation, and the position of the sub-nodes will be determined based on the original regional range and the discretization step size with reference to the shape of the earth; through discretization processing, the use of complex geometric algorithms to calculate coverage is avoided, thereby speeding up the solution efficiency.

[0118] The adaptive discretization decomposition method and device for satellite observation planning of regional targets described in the present invention are suitable for mission planning calculation of single or multiple earth observation satellites observing single or multiple irregularly shaped regional targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0119] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0120] Figure 1 A schematic diagram of the field load observation effect in one embodiment of the present invention;

[0121] Figure 2 A schematic diagram of a regional target discretization process in one embodiment of the present invention;

[0122] Figure 3 A schematic diagram of a geometric visible time window of a satellite to any sub-node within a regional target in one embodiment of the present invention;

[0123] Figure 4 A schematic diagram of the minimum observation angle of a satellite to any sub-node within a regional target in one embodiment of the present invention;

[0124] Figure 5 This is a schematic diagram of a target sub-node synthesis strip in one embodiment of the present invention. DETAILED DESCRIPTION

[0125] In order to make the technical solutions and advantages of the present invention more clearly described, the specific implementation methods of the present invention will be further described in detail and completely in conjunction with the accompanying drawings. The various implementation methods described below are only part of the preferred solutions of the present invention, rather than all implementation methods; the various implementation methods described below are intended to explain the present invention and cannot be understood as limitations on the present invention; the reasonable combination of technical features defined in the various implementation methods of the present invention, and all other implementation methods obtained by ordinary technicians in the field without creative work based on the implementation methods of the present invention, are within the scope of protection of the present invention.

[0126] In one embodiment, an adaptive discretization decomposition method for satellite observation planning of regional targets is provided, the method comprising the following steps:

[0127] Determine the step size: Determine the discretization step size of the regional target according to the observation range of the satellite payload;

[0128] Discretization into sub-node set step: discretizing the regional target into a regional sub-node set based on the discretization step size and the shape of the earth; the regional sub-node set includes a plurality of sub-nodes;

[0129] Steps for calculating the minimum observation elevation angle: Calculate the minimum observation angle of the satellite to each sub-node in the regional target in each circle and the target sub-node for which the satellite has an observation opportunity in each circle;

[0130] Subnode grouping step: construct a strip interval and group all target subnodes according to the minimum observation angle and target subnode;

[0131] Steps for merging strips: According to the grouping of all target sub-nodes, the target sub-nodes are merged into strips, and the convex hull algorithm is used to calculate the vertex position of the strips and the time window for the satellite to observe each group of strips.

[0132] In addition, in one embodiment, the step of determining the step size, determining the discretization step size of the regional target according to the observation range of the satellite payload, includes the following steps:

[0133] Step 1.1: Determine the observation range of the satellite payload:

[0134] Earth observation satellites are classified according to the observation range of the payload, and are divided into payloads with conical field of view and rectangular field of view. Among them, the payloads with conical field of view have the same field of view angle in all directions, and the payloads with rectangular field of view have different field of view angles in two mutually perpendicular directions.

[0135] Assume that the minimum altitude of the satellite orbit is h, and the half angle of the payload of the conical field of view is α 1 , the half angle of the rectangular field of view payload perpendicular to the satellite's forward direction is α 2, the half angle of the payload of the rectangular field of view parallel to the satellite's forward direction is β;

[0136] The radius of the circular projection of the load in the conical field of view on the ground is R, and the side length of the rectangular projection of the load in the rectangular field of view on the ground is 2L. 1 and 2L 2 ; Where R = h·tanα 1 , L 1 =h·tanα 2 , L 2 =h·tanβ;

[0137] Step 1.2: Calculate the discretization step size of the regional target:

[0138] Assume that the discretization step size of the regional target is d, which is determined by the minimum observation range of the satellite payload;

[0139] For a cone-shaped field of view load,

[0140] For a rectangular field of view load,

[0141] In this embodiment, if Figure 1 The figure shows the schematic diagram of the observation effect of the field of view load. From the figure, it can be seen that the observation range of different types of loads; among them, the circular radius of the load of the conical field of view projected on the ground is R; the rectangular side length of the load of the rectangular field of view projected on the ground is 2L 1 and 2L 2 .

[0142] In addition, in one embodiment, in the step of discretizing into a sub-node set, the regional target is discretized into a regional sub-node set based on the discretization step size and the shape of the earth; the regional sub-node set includes a plurality of sub-nodes, and includes the following steps:

[0143] Step 2.1: Determine the position of each vertex of the regional target:

[0144] Determine the n vertices of the target area to be observed. The vertex positions are expressed in longitude and latitude, denoted as Points = [lat, lon] n , where lat represents latitude and lon represents longitude;

[0145] Let the maximum latitude of the vertex be lat max , the minimum latitude of the vertex is lat min , the maximum longitude of the vertex is lon max , the minimum longitude of a vertex is lon min ;

[0146] Step 2.2: Override the region target using child nodes:

[0147] Step 2.2.1: Calculate the longitude set of the child node according to the longitude and latitude range of the vertices of the regional target described in step 2.1:

[0148] From the vertex corresponding to the minimum longitude and minimum latitude [lat min ,lon min ], add child nodes one by one in the direction of the same latitude and high longitude with a step size of d; in the process of adding child nodes each time:

[0149] Let the longitude of the starting point be lon 0 , latitude is lat 0 , the latitude corresponds to the radius of the earth's latitude circle R lat0 :

[0150]

[0151] Among them, a is the major semi-axis of the earth; b is the minor semi-axis of the earth (polar radius);

[0152] The longitude of the new child node obtained by moving in the same latitude and high longitude direction is lon 1 :

[0153]

[0154] Repeat adding child nodes until the longitude of the new child node is greater than or equal to lon max , get the longitude set of the child node;

[0155] Step 2.2.2: Based on the longitude and latitude range of the vertices of the regional target described in step 2.1, the longitude set of the child nodes obtained in step 2.2.1 is diffused toward the high latitude direction so that the child nodes cover the regional target:

[0156] Starting from each child node in the longitude set, add child nodes one by one in the direction of high latitude with the same longitude; in the process of adding child nodes each time:

[0157] Let the longitude of the starting point be lon 0 ', latitude is lat 0 ', move to the same longitude and high latitude direction to obtain the new child node with a latitude of lat 1 ;

[0158]

[0159] in, is the Earth's flattening;

[0160] Repeat adding child nodes until the latitude of the new child node is greater than or equal to lat max , get the longitude and latitude set of the child node;

[0161] Step 2.3: Remove the child nodes outside the region target and obtain the region child node set:

[0162] Step 2.3.1: According to the longitude and latitude set of the child node obtained in step 2.2, traverse each child node in the longitude and latitude set of the child node to obtain the longitude and latitude position of each child node;

[0163] Set any child node in the longitude and latitude set of child nodes as node k ;

[0164] Step 2.3.2: Get the number of intersections between the rightward ray of the child node and the boundary line of the target region:

[0165] For each boundary line of the regional target, the two vertices of the boundary line are recorded as point i and point j ;

[0166] For a child node whose latitude is between the latitudes of two vertices of the boundary line, if the child node is on the left side of the boundary line formed by the two vertices, it is considered that the rightward ray of the child node has an intersection with the boundary line; where:

[0167] If the conditions are met Then the child node is considered k The latitude is between the latitudes of the two vertices of the boundary line;

[0168] If the conditions are met Then the child node is considered k On the left side of the boundary line, it is considered as the child node k The rightward ray and the two vertices point i and point j The constituent boundary lines have a point of intersection;

[0169] Step 2.3.3: According to the number of intersection points obtained in step 2.3.2, determine whether the child node is within the area target;

[0170] Traverse each child node in the latitude and longitude set of the child node:

[0171] If any child node k If the number of intersections between the rightward ray and the target boundary line of the region is even, then the child node k Outside the regional target;

[0172] All child nodes outside the regional target are deleted from the longitude and latitude set of the child nodes to obtain the regional child node set, which is recorded as Nodes.

[0173] In this embodiment, the semi-major axis of the earth is the equatorial radius, and the semi-minor axis of the earth is the polar radius.

[0174] In this implementation, the longitude set of the subnode includes multiple subnodes; the multiple subnodes are at the same latitude, and the latitude value is the minimum latitude; the longitude values ​​of the multiple subnodes are between the minimum longitude and the maximum longitude (including the minimum longitude and the maximum longitude).

[0175] In this implementation, the effect of using discretized sub-nodes to cover the regional target is as follows: Figure 2 As shown. Figure 2 It can be seen that the regional target is an irregular polygon. First, sub-nodes are added in the longitude and latitude directions to cover the entire regional target, and then the sub-nodes outside the regional target are deleted, and finally a set of regional sub-nodes that matches the shape of the regional target is obtained.

[0176] In this implementation, the child node k The latitude is between the latitudes of the two vertices of the boundary line, including the child node k The situation on the borderline.

[0177] In this implementation, based on the characteristics of the satellite earth observation payload, the reference payload field of view and the shape of the regional target are integrated to adaptively discretize the target in the observed area. A region is dispersed into multiple regional sub-nodes that can be completed by a single observation of the satellite observation payload, reducing the complexity of regional visibility and coverage calculations.

[0178] In addition, in one embodiment, the step of calculating the minimum observation elevation angle, calculating the minimum observation angle of the satellite to each sub-node in the regional target in each circle and the target sub-node for which the satellite has an observation opportunity in each circle, includes the following steps:

[0179] Step 3.1: Set the start and end time of the observation mission scenario for the regional target;

[0180] Step 3.2: Use the orbit recursion algorithm to calculate the latitude and longitude data of the satellite's orbit every second in the observation mission scenario;

[0181] Assume that the latitude and longitude data of the satellite orbit per second is LLA = {lla 0 ,lla 1 ,…,lla j , ...}; among them, lla j is the latitude and longitude data sample of the satellite in the jth second of orbit;

[0182] lla j = {lat j ′,lonj ′,alt j '};

[0183] Among them, lat j ' means lla j The latitude value, lon j ' means lla j The longitude value of alt j ' means lla j The height value of

[0184] Step 3.3: Circle division:

[0185] Traversing the satellite's orbit every second, the longitude and latitude data LLA:

[0186] When (lat′ j -lat′ 0 )·(lat′ j+1 -lat′ 0 )<0, lla j The indicated position is recorded as the end of the current lap, lla j+1 The indicated position is recorded as the beginning of the next orbit, and the longitude and latitude data of each orbit of the satellite are obtained;

[0187] Step 3.4: Calculate the overall geometric visibility time window of the satellite to all sub-nodes in the regional target in each orbit:

[0188] Step 3.4.1: Assume that in each orbit, the satellite's altitude is alt and the radius of the earth is R. e , then the distance from the satellite to the center of the earth is R Sat =R e +alt;

[0189] Step 3.4.2: Calculate the maximum range of the satellite's geometric visibility of any sub-node within the regional target on the earth's surface as η:

[0190]

[0191] Then the angle between the satellite and the geocentric angle of any sub-node in the regional target is

[0192] Step 3.4.3: Use binary search to calculate the overall geometric visibility time window of the satellite to all sub-nodes within the regional target:

[0193] Traverse each circle and divide each circle into the initial step length Perform binary search calculations to determine whether the satellite is within the geometrically visible time window based on the angle η, and obtain the time data of the start and end positions of the geometrically visible time window of the satellite for any subnode in the regional target; wherein, Indicates rounding up;

[0194] In each round, the time data of the start and end positions of the satellite's geometric visibility time window for each sub-node in the regional target are combined, and the earliest start time and the latest end time are selected to obtain the overall geometric visibility time window of the satellite for all sub-nodes in the regional target, which is called the overall geometric visibility time window;

[0195] Step 3.5: Based on the overall geometric visibility time window of the satellite to all sub-nodes in the regional target, calculate the minimum observation angle of the satellite to each sub-node in the regional target in each circle:

[0196] Step 3.5.1: Calculate the expression of the star lower line;

[0197] In each orbit of the satellite, the longitude and latitude of two sub-satellite points at the start and end positions in the overall geometric visible time window are obtained;

[0198] According to the longitude and latitude of the two sub-satellite points, the expression of the sub-satellite line is:

[0199]

[0200] in, The longitude of the sub-satellite point of the starting position in the overall geometric visibility time window; is the latitude of the sub-satellite point at the start position of the overall geometric visibility time window; The longitude of the sub-satellite point at the end of the overall geometric visibility time window; is the latitude of the sub-satellite point at the end of the overall geometric visible time window;

[0201] Step 3.5.2: Calculate the foot position of the perpendicular line from each sub-node in the regional sub-node set to the star line:

[0202] Combine the following two equations:

[0203]

[0204] According to the result of the joint operation, get any child node k The foot position of the perpendicular line to the lower line of the star:

[0205]

[0206] The subsatellite point position corresponding to the vertical foot position is any child node kThe corresponding nearest sub-satellite point position is obtained, and then the satellite orbit position 11a corresponding to the vertical foot position is obtained. s ;

[0207] Step 3.5.3: Obtain the minimum observation angle for each sub-node in the regional target:

[0208] The satellite orbit position 11a corresponding to the vertical foot position s Converted to Earth-centered Earth-fixed coordinate system: ecef(lla s );

[0209] Any child node k Converted to the Earth-centered Earth-fixed coordinate system: ecef(node k );

[0210] The satellite targets any child node in the regional target k The minimum observation angle is ξ k :

[0211]

[0212] Step 3.6: Based on the overall geometric visibility time window of all subnodes in the regional target, calculate the target subnodes for which the satellite has observation opportunities in each orbit, as well as the payload visibility time window of the satellite to the regional target:

[0213] Step 3.6.1: Get the time period between the earliest start time and the latest end time of the overall geometric visible time window, and obtain the latitude and longitude data of the satellite orbit every second during this time period based on the orbit extrapolation data.

[0214] Step 3.6.2: Traverse the satellite and in each circle, perform a search on any child node in the target area. k The minimum observation angle ξ k :

[0215] If k ≤α+ω, then any corresponding child node k is the target subnode; the satellite has an observation opportunity for the target subnode;

[0216] Where ω is the maximum maneuvering side swing angle of the satellite; α is the half angle. For the load of the conical field of view, α = α 1 , for a rectangular field of view load, α = α 2 ;

[0217] Step 3.6.3: Get the satellite orbit position lla corresponding to the target subnode s '; Reference longitude and latitude data By satellite orbital position lla s 'Determine the scene time when the satellite has an observation opportunity for the target subnode;

[0218] Step 3.6.4: Select the earliest time and the latest time from the scene time when the satellite has observation opportunities for all target sub-nodes in each circle. The time window between the two is the payload visibility time window of the satellite for regional targets in each circle.

[0219] In this implementation, for a multi-satellite joint earth observation system formed by a joint network of multiple earth observation satellites, each satellite must calculate the corresponding minimum observation angle and payload visible time window.

[0220] In this implementation, the latitude, longitude and altitude data is location data, including information such as latitude value, longitude value and altitude value.

[0221] In this implementation, the geometric visibility time window of the satellite to any sub-node within the regional target is as follows: Figure 3 As shown, whether the satellite is within the geometric visible time window corresponding to any child node is determined based on the opening angle η.

[0222] In this implementation, regarding the geometric visible time window, refer to the following documents:

[0223] E Zhibo and Li Junfeng, "A fast calculation method for the visibility of regional targets by remote sensing satellites", Journal of Tsinghua University (Science and Technology), Vol.59, No.9, doi:10.16511 / j.cnki.qhdxxb.2019.26.020.

[0224] In this implementation, regarding the binary search method, refer to the following documents:

[0225] L. Rabiner, "Combinatorial optimization: Algorithms and complexity," in IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.32, no.6, pp.1258-1259, December 1984, doi:10.1109 / TASSP.1984.1164450.

[0226] In this implementation manner, the satellite provides time data of the start position and end position of the geometrically visible time window of each sub-node in the regional target, that is, the start time node and end time node of the geometrically visible time window.

[0227] In this implementation manner, the satellite calculates the time data of the start position and the end position of the geometric visible time window of each sub-node in the regional target with an accuracy of 1 second.

[0228] In this implementation, the time data of the start position and end position of the geometric visible time window of each sub-node in the regional target by the satellite are combined to select the earliest start time and the latest end time:

[0229] The time data of the starting position and the ending position of the geometric visible time window of each sub-node in the regional target by the satellite, that is, the starting time node and the ending time node of the geometric visible time window corresponding to each sub-node;

[0230] By combining these start time nodes and end time nodes, the earliest start time and the latest end time of the overall geometric visible time window corresponding to all child nodes can be selected.

[0231] The earliest start time of the overall geometric visible time window corresponds to the starting position of the overall geometric visible time window;

[0232] The latest end time of the overall geometrically visible time window corresponds to the end position of the overall geometrically visible time window.

[0233] In this implementation, taking the cth circle as an example, let the time data of the start position and end position of the (geometric) geometric visible time window of the i-th subnode (or target subnode i) in the regional target be access c i , then the overall geometric visibility time window of the satellite to all sub-nodes in the regional target is recorded as Access c .

[0234] In this embodiment, the process of obtaining the minimum observation angle is as follows: Figure 4 shown.

[0235] In this embodiment, the present invention realizes a rough calculation of the visible arc segment of the satellite to the regional target based on the characteristics of the satellite orbit and the earth shape; abandons the traditional traversal judgment method, accurately judges the starting position of the visible time window based on the binary search method, and realizes the rapid calculation of the accurate visible time window of each satellite to the regional sub-node; based on the visibility of the regional sub-node, the visible time window result of each satellite to the regional target is obtained.

[0236] In addition, in one embodiment, the sub-node grouping step, based on the minimum observation angle and the target sub-node, constructs a stripe interval and groups all the target sub-nodes, comprises the following steps:

[0237] Step 4.1: The minimum observation angle ξ corresponding to the target sub-node where the satellite has an observation opportunity in each orbit k 'Processing:

[0238] Determine the position relationship between the target subnode and the satellite line. If the target subnode is on the left side of the satellite line, the minimum observation angle ξ k 'Take a negative value, otherwise the value remains unchanged:

[0239]

[0240] In all target child nodes, let ξ k The minimum value of ' is ξ min , k The maximum value of ' is ξ max ;

[0241] Step 4.2: Take ξ min The corresponding target child node is the starting point, 2α is the step size, and ξ max The corresponding target sub-node is the end point, and the strip interval is constructed. All target sub-nodes are divided into Groups:

[0242] [ξ min ,ξ min +2α],[ξ min +2α,ξ min +4α],......,[...,ξ max ];

[0243] The average value of the minimum observation angle of each set of two end points is the side swing angle of each set of satellite imaging.

[0244] In this implementation, the average value of the minimum observation angle of each set of two end points is the side swing angle of each set of satellite imaging, for example:

[0245] [ξ min ,ξ min +2α], the minimum observation angles of the two end points are ξ min and min +2α, then ξ min and min The average value of +2α is the side swing angle of the satellite imaging of this group;

[0246] [ξ min +2α,ξ min +4α], the minimum observation angles of the two end points are ξ min +2α and ξ min +4α, then ξ min +2α and ξ min The average value of +4α is the side swing angle of this group of satellite imaging.

[0247] In addition, in one embodiment, the step of merging strips, according to the grouping of all target sub-nodes, merges the target sub-nodes into strips, and uses a convex hull algorithm to calculate the vertex position of the strips and the time window for satellite observation of each group of strips, includes the following steps:

[0248] Step 5.1: Merge each group of target sub-nodes using the convex hull algorithm to obtain the vertex positions of the strips corresponding to each group of target sub-nodes;

[0249] Step 5.2: The visible time window of the payload of each group of target sub-nodes is used as the time window for satellite observation of each group of strips;

[0250] Step 5.3: The ratio of the number of target sub-nodes included in each group of stripes to the number of all sub-nodes of the regional target is taken as the target coverage rate of each group of stripes.

[0251] In this implementation, each group of target sub-nodes is merged using a convex hull algorithm to obtain the vertex positions of the strips, such as Figure 5 shown.

[0252] In this implementation, the vertex positions of the strips are obtained, that is, the strips corresponding to each group of target sub-nodes are determined.

[0253] In this implementation, the convex hull algorithm is a classic problem in computational geometry, and its goal is to find a minimum convex polygon of a geometric shape that can surround all original points (i.e., for each group of target subnodes, find a minimum convex polygon as a strip that surrounds all target subnodes).

[0254] For the convex hull algorithm, please refer to the following literature:

[0255] Kang Baosheng, "Computer construction of convex hull of finite point sets in space", Journal of Northwest University (Natural Science Edition), Vol.3, 1985.20-26+19.

[0256] In this implementation, the minimum observation angle required for the satellite to observe the sub-node is used to represent the observation situation. The angle is used to represent the relative position relationship of the payload observation target. The satellite's off-line and sub-node position relationship are used to obtain the minimum observation angle based on the satellite-ground geometry to represent the satellite's observation attitude of the target at the minimum maneuvering angle, thereby quickly calculating the target's payload visibility to the satellite.

[0257] In this implementation, the method for merging regional sub-nodes into strips and determining the working time window of the satellite payload is to group and aggregate the observation conditions of each node, recombining each sub-node according to the minimum observation angle and other conditions to form the strip information required for mission planning, and directly determine the observation time window of the strip based on the earliest and latest values ​​of the satellite's overpass time for each node.

[0258] In one embodiment, an adaptive discretization decomposition device for satellite observation planning of regional targets is provided, and the device includes the following modules:

[0259] Determine step size module: Determine the discretization step size of regional targets according to the observation range of satellite payload;

[0260] Discretization into sub-node set module: discretizes the regional target into a regional sub-node set based on the discretization step size and the shape of the earth; the regional sub-node set includes multiple sub-nodes;

[0261] Module for calculating the minimum observation elevation angle: Calculates the minimum observation angle of the satellite to each sub-node in the regional target in each circle and the target sub-node that the satellite has the opportunity to observe in each circle;

[0262] Subnode grouping module: constructs strip intervals and groups all target subnodes according to the minimum observation angle and target subnodes;

[0263] Strip merging module: According to the grouping of all target sub-nodes, the target sub-nodes are merged into strips, and the convex hull algorithm is used to calculate the vertex position of the strips and the time window for the satellite to observe each group of strips.

[0264] It should be noted that it is original to the present invention to determine the discrete step size of the region according to the shape of the earth and the payload observation range, and to determine the payload visible time window and strip division using the minimum observation angle of the target sub-node to the satellite.

[0265] It should be noted that the existing related regional target decomposition (or simplification) algorithms simply discretize the region into point targets for processing, such as the method recorded in the Chinese patent document with the publication number "CN 111695237 A" and the name "Regional Decomposition Method and System for Satellite-Based Regional Coverage Detection Simulation", which processes a region into multiple point targets at equal distances for calculation. Although this method is simple, it does not consider the impact of discretization on the accuracy of observation calculation: if the interval between target points is too large, the accuracy will be significantly reduced, and if the interval is too small, it will occupy more computing memory. In addition, due to the influence of the earth's flattening and satellite-ground geometry, the point targets divided at equal distances may not be evenly distributed from the satellite observation angle, which will also cause certain errors. On the other hand, considering the changes in the observation width under different attitudes of agile satellites, there are errors in strip decomposition of the region using a fixed length, which is particularly obvious when the satellite side swing angle is large.

[0266] The adaptive discretization (regional strip) decomposition method in this embodiment adopts an adaptive discretization method based on the satellite payload observation range, comprehensively considers the satellite payload observation range and the shape of the earth, discretizes the regional target to be observed into a set of regional sub-nodes, and uses a vector to represent the satellite visibility of each sub-node. The observation angle is used to represent the satellite's observation of the regional sub-node, which includes the satellite's observation attitude information while avoiding the process of accurately calculating the visible window for each sub-node, making the related calculations simpler. Instead of using the fixed width of the traditional method, the regional sub-node set is integrated according to the satellite's observation range and maneuverability to obtain the satellite's observation time window for each group of strips for selection and reference in subsequent mission planning.

[0267] The technical solution provided by the present invention is further described in detail above through several specific implementation modes in order to highlight the advantages and benefits of the technical solution provided by the present invention. However, the several specific implementation modes described above are not intended to be used as limitations on the present invention. Any reasonable changes and improvements to the present invention, reasonable combinations of implementation modes and equivalent substitutions based on the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An adaptive discretization decomposition method for satellite observation planning of regional targets, characterized in that: The method comprises the following steps: Determine the step size: Determine the discretization step size of the regional target according to the observation range of the satellite payload; Discretization into sub-node set step: discretizing the regional target into a regional sub-node set based on the discretization step size and the shape of the earth; the regional sub-node set includes a plurality of sub-nodes; Steps for calculating the minimum observation elevation angle: Calculate the minimum observation angle of the satellite to each sub-node in the regional target in each circle and the target sub-node for which the satellite has an observation opportunity in each circle; Subnode grouping step: construct a strip interval and group all target subnodes according to the minimum observation angle and target subnode; Steps for merging strips: According to the grouping of all target sub-nodes, the target sub-nodes are merged into strips, and the convex hull algorithm is used to calculate the vertex position of the strips and the time window for the satellite to observe each group of strips.

2. The adaptive discretization decomposition method for satellite observation planning of regional targets according to claim 1, characterized in that: The step of determining the step size comprises the following steps: Step 1.1: Determine the observation range of the satellite payload: Earth observation satellites are classified according to the observation range of the payload, and are divided into payloads with conical field of view and rectangular field of view. Among them, the payloads with conical field of view have the same field of view angle in all directions, and the payloads with rectangular field of view have different field of view angles in two mutually perpendicular directions. Assume that the lowest altitude of the satellite orbit is h, the half angle of the payload of the conical field of view is α1, the half angle of the payload of the rectangular field of view perpendicular to the satellite's forward direction is α2, and the half angle of the payload of the rectangular field of view parallel to the satellite's forward direction is β; Then the radius of the circle projected on the ground by the load of the conical field of view is R, and the length of the rectangle projected on the ground by the load of the rectangular field of view is 2L1 and 2L2; where R = h·tanα1, L1 = h·tanα2, L2 = h·tanβ; Step 1.2: Calculate the discretization step size of the regional target: Assume that the discretization step size of the regional target is d, which is determined by the minimum observation range of the satellite payload; For a cone-shaped field of view load, For a rectangular field of view load, 3. The adaptive discretization decomposition method for satellite observation planning of regional targets according to claim 2 is characterized in that: The step of discretizing into a sub-node set comprises the following steps: Step 2.1: Determine the position of each vertex of the regional target: Determine the n vertices of the target area to be observed. The vertex positions are expressed in longitude and latitude, denoted as Points = [lat, lon] n , where lat represents latitude and lon represents longitude; Let the maximum latitude of the vertex be lat max , the minimum latitude of the vertex is lat min , the maximum longitude of the vertex is lon max , the minimum longitude of a vertex is lon min ; Step 2.2: Override the region target using child nodes: Step 2.2.1: Calculate the longitude set of the child node according to the longitude and latitude range of the vertices of the regional target described in step 2.1: From the vertex corresponding to the minimum longitude and minimum latitude [lat min ,lon min ], add child nodes one by one in the direction of the same latitude and high longitude with a step size of d; in the process of adding child nodes each time: Assume the longitude of the starting point is lon0, the latitude is lat0, and the radius of the earth's latitude circle corresponding to this latitude is R lat0 : Among them, a is the major axis of the earth; b is the minor axis of the earth; The longitude of the new child node obtained by moving in the same latitude and high longitude direction is lon1: Repeat adding child nodes until the longitude of the new child node is greater than or equal to lon max , get the longitude set of the child node; Step 2.2.2: Based on the longitude and latitude range of the vertices of the regional target described in step 2.1, the longitude set of the child nodes obtained in step 2.2.1 is diffused toward the high latitude direction so that the child nodes cover the regional target: Starting from each child node in the longitude set, add child nodes one by one in the direction of high latitude with the same longitude; in the process of adding child nodes each time: Assume the longitude of the starting point is lon0', the latitude is lat0', and the latitude of the new child node obtained by moving in the same longitude and high latitude direction is lat1; in, is the Earth's flattening; Repeat adding child nodes until the latitude of the new child node is greater than or equal to lat max , get the longitude and latitude set of the child node; Step 2.3: Remove the child nodes outside the region target and obtain the region child node set: Step 2.3.1: According to the longitude and latitude set of the child node obtained in step 2.2, traverse each child node in the longitude and latitude set of the child node to obtain the longitude and latitude position of each child node; Set any child node in the longitude and latitude set of child nodes as node k ; Step 2.3.2: Get the number of intersections between the rightward ray of the child node and the boundary line of the target region: For each boundary line of the regional target, the two vertices of the boundary line are recorded as point i and point j ; For a child node whose latitude is between the latitudes of two vertices of the boundary line, if the child node is on the left side of the boundary line formed by the two vertices, it is considered that the rightward ray of the child node has an intersection with the boundary line; where: If the conditions are met Then the child node is considered k The latitude is between the latitudes of the two vertices of the boundary line; If the conditions are met Then the child node is considered k On the left side of the boundary line, it is considered as the child node k The rightward ray and the two vertices point i and point j The constituent boundary lines have a point of intersection; Step 2.3.3: According to the number of intersection points obtained in step 2.3.2, determine whether the child node is within the area target; Traverse each child node in the latitude and longitude set of the child node: If any child node k If the number of intersections between the rightward ray and the target boundary line of the region is even, then the child node k Outside the regional target; All child nodes outside the regional target are deleted from the longitude and latitude set of the child nodes to obtain the regional child node set, which is recorded as Nodes.

4. The adaptive discretization decomposition method for satellite observation planning of regional targets according to claim 3 is characterized in that: The step of calculating the minimum observation elevation angle comprises the following steps: Step 3.1: Set the start and end time of the observation mission scenario for the regional target; Step 3.2: Use the orbit recursion algorithm to calculate the latitude and longitude data of the satellite's orbit every second in the observation mission scenario; Assume that the latitude and longitude data of the satellite orbit per second is LLA = {lla0, lla1, ..., lla j , ...}; among them, lla j is the latitude and longitude data sample of the satellite in the jth second of orbit; lla j ={lat′ j ,lon′ j ,alt′ j }; Among them, lat′ j Indicates lla j The latitude value, lon′ j Indicates lla j The longitude value, alt′ j Indicates lla j The height value of Step 3.3: Circle division: Traversing the satellite's orbit every second, the longitude and latitude data LLA: When (lat′ j -lat′0)·(lat′ j+1 -lat′0)<0, lla j The indicated position is recorded as the end of the current lap, lla j+1 The indicated position is recorded as the beginning of the next orbit, and the longitude and latitude data of each orbit of the satellite are obtained; Step 3.4: Calculate the overall geometric visibility time window of the satellite to all sub-nodes in the regional target in each orbit: Step 3.4.1: Assume that in each orbit, the satellite's altitude is alt and the radius of the earth is R. e , then the distance from the satellite to the center of the earth is R Sat =R e +alt; Step 3.4.2: Calculate the maximum range of the satellite's geometric visibility of any sub-node within the regional target on the earth's surface as η: Then the angle between the satellite and the geocentric angle of any sub-node in the regional target is Step 3.4.3: Use binary search to calculate the overall geometric visibility time window of the satellite to all subnodes within the regional target: Traverse each circle and divide each circle into the initial step length Perform binary search calculations to determine whether the satellite is within the geometrically visible time window based on the angle η, and obtain the time data of the start and end positions of the geometrically visible time window of the satellite for any subnode in the regional target; wherein, Indicates rounding up; In each round, the time data of the start and end positions of the satellite's geometric visibility time window for each sub-node in the regional target are combined, and the earliest start time and the latest end time are selected to obtain the overall geometric visibility time window of the satellite for all sub-nodes in the regional target, which is called the overall geometric visibility time window; Step 3.5: Based on the overall geometric visibility time window of the satellite to all sub-nodes in the regional target, calculate the minimum observation angle of the satellite to each sub-node in the regional target in each circle: Step 3.5.1: Calculate the expression of the star lower line; In each orbit of the satellite, the longitude and latitude of two sub-satellite points at the start and end positions in the overall geometric visible time window are obtained; According to the longitude and latitude of the two sub-satellite points, the expression of the sub-satellite line is: in, The longitude of the sub-satellite point of the starting position in the overall geometric visibility time window; is the latitude of the sub-satellite point at the start position of the overall geometric visibility time window; The longitude of the sub-satellite point at the end of the overall geometric visibility time window; is the latitude of the sub-satellite point at the end of the overall geometric visible time window; Step 3.5.2: Calculate the foot position of the perpendicular line from each sub-node in the regional sub-node set to the star line: Combine the following two equations: According to the result of the joint operation, get any child node k The foot position of the perpendicular line to the lower line of the star: The subsatellite point position corresponding to the vertical foot position is any child node k The corresponding nearest sub-satellite point position is obtained, and then the satellite orbit position 11a corresponding to the vertical foot position is obtained. s ; Step 3.5.3: Obtain the minimum observation angle for each sub-node in the regional target: The satellite orbit position 11a corresponding to the vertical foot position s Converted to Earth-centered Earth-fixed coordinate system: ecef(lla s ); Any child node k Converted to the Earth-centered Earth-fixed coordinate system: ecef(node k ); The satellite targets any child node in the regional target k The minimum observation angle is ξ k : Step 3.6: Based on the overall geometric visibility time window of all subnodes in the regional target, calculate the target subnodes for which the satellite has observation opportunities in each orbit, as well as the payload visibility time window of the satellite to the regional target: Step 3.6.1: Get the time period between the earliest start time and the latest end time of the overall geometric visible time window, and obtain the latitude and longitude data of the satellite orbit every second during this time period based on the orbit extrapolation data. Step 3.6.2: Traverse the satellite and in each circle, perform a search on any child node in the target area. k The minimum observation angle ξ k : If k ≤α+ω, then any corresponding child node k is the target subnode; the satellite has an observation opportunity for the target subnode; Wherein, ω is the maximum maneuvering side swing angle of the satellite; α is the half angle, for the load of the conical field of view, α=α1, for the load of the rectangular field of view, α=α2; Step 3.6.3: Get the satellite orbit position lla corresponding to the target subnode s '; Reference longitude and latitude data By satellite orbital position lla s 'Determine the scene time when the satellite has an observation opportunity for the target subnode; Step 3.6.4: Select the earliest time and the latest time from the scene time when the satellite has observation opportunities for all target sub-nodes in each circle. The time window between the two is the payload visibility time window of the satellite for regional targets in each circle.

5. The adaptive discretization decomposition method for satellite observation planning of regional targets according to claim 4, characterized in that: The sub-node grouping step comprises the following steps: Step 4.1: The minimum observation angle ξ corresponding to the target sub-node where the satellite has an observation opportunity in each orbit k 'Processing: Determine the position relationship between the target subnode and the satellite line. If the target subnode is on the left side of the satellite line, the minimum observation angle ξ k 'Take a negative value, otherwise the value remains unchanged: In all target child nodes, let ξ k The minimum value of ' is ξ min , k The maximum value of ' is ξ max ; Step 4.2: Take ξ min The corresponding target child node is the starting point, 2α is the step size, and ξ max The corresponding target sub-node is the end point, and the strip interval is constructed. All target sub-nodes are divided into Groups: [x] min ,x min +2a],[ξ min +2a,x min +4a],......,[...,ξ max ]; The average value of the minimum observation angle of each set of two end points is the side swing angle of each set of satellite imaging.

6. The adaptive discretization decomposition method for satellite observation planning of regional targets according to claim 5, characterized in that: The step of merging stripes comprises the following steps: Step 5.1: Merge each group of target sub-nodes using the convex hull algorithm to obtain the vertex positions of the strips corresponding to each group of target sub-nodes; Step 5.2: The visible time window of the payload of each group of target sub-nodes is used as the time window for satellite observation of each group of strips; Step 5.3: The ratio of the number of target sub-nodes included in each group of stripes to the number of all sub-nodes of the regional target is taken as the target coverage rate of each group of stripes.

7. An adaptive discretization decomposition device for satellite observation of regional targets, characterized in that: The device comprises the following modules: Determine step size module: Determine the discretization step size of regional targets according to the observation range of satellite payload; Discretization into sub-node set module: discretizes the regional target into a regional sub-node set based on the discretization step size and the shape of the earth; the regional sub-node set includes multiple sub-nodes; Module for calculating the minimum observation elevation angle: Calculates the minimum observation angle of the satellite to each sub-node in the regional target in each circle and the target sub-node that the satellite has the opportunity to observe in each circle; Subnode grouping module: constructs strip intervals and groups all target subnodes according to the minimum observation angle and target subnodes; Strip merging module: According to the grouping of all target sub-nodes, the target sub-nodes are merged into strips, and the convex hull algorithm is used to calculate the vertex position of the strips and the time window for the satellite to observe each group of strips.

8. A computer system comprising: A processor and a memory, characterized in that the memory is used to store executable instructions of the processor, and the processor is configured to execute the adaptive discretization decomposition method for satellite observation planning of regional targets as described in any one of claims 1 to 6 by executing the executable instructions.

9. A computer storage medium, characterized in that The storage medium stores a computer program, and when the computer program is run, the adaptive discretization decomposition method for satellite observation planning of regional targets according to any one of claims 1 to 6 is executed.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the steps of the adaptive discretization decomposition method for satellite observation planning of regional targets as described in any one of claims 1 to 6 are implemented.

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