Regional target-oriented giant remote sensing constellation task planning method

Abstract

The invention discloses a giant remote sensing constellation task planning method for a regional target, and the method comprises the following steps: 1, constructing a global regional reference system, determining a reference grid of the regional target and a corresponding observation grid, and obtaining the information of the observation grid; 2, determining observation priorities, and obtaining an observation comprehensive priority of each reference grid based on calculation; step 3, constellation task pre-allocation: generating a one-to-one correspondence relationship between observation grids and imaging satellites in an observation demand period in the observation demand information, and obtaining a constellation task pre-allocation scheme; and step 4, single-satellite task planning: generating a satellite imaging and data transmission plan in a single-satellite task planning stage based on a constellation task pre-allocation scheme, a satellite special constraint condition, a satellite imaging characteristic parameter, a satellite data transmission scheme and an optimization strategy thereof. According to the method, a constellation orbit isomerism, a highly symmetrical space structure and a global periodic motion rule are fully considered, and immediate observation of the giant remote sensing constellation can be realized.

Description

Technical Field

[0001] The invention relates to the technical field of giant remote sensing constellation mission planning, and in particular to a giant remote sensing constellation mission planning method oriented to regional targets. Background Art

[0002] With the advancement of aerospace technology, companies represented by SpaceX (Space Exploration Technologies Corporation) in the United States are promoting the networking of giant constellations such as StarLink and StarShield, which are hundreds or even tens of thousands of satellites at a speed of "60 satellites per rocket, 4 launches per month". In the future, giant remote sensing constellations will feature heterogeneous networking, global distribution, multi-satellite collaboration, and multiple uses of one satellite. Driven by this development trend, how to design a flexible and diverse giant remote sensing constellation mission planning framework based on the existing in-orbit remote sensing satellite observation capabilities, taking into account subsequent development, and solving the problem of multi-satellite and multi-payload collaborative observation for large-scale regional targets is one of the technical difficulties that need to be overcome.

[0003] In order to complete the task of multi-satellite coordinated observation of large-area regional targets, most research institutions at home and abroad have broken down the multi-satellite coordinated regional observation problem into two sub-problems: regional target segmentation and observation activity sequencing. For regional target segmentation, it is essentially to use a single satellite fixed imaging width, or a fixed imaging width and deflection angle, along the direction perpendicular to the satellite flight, through the method of parallel segmentation to determine the on and off time of satellite imaging. This method is only applicable to single-satellite multiple observations of specific models of satellites and repeated observations of multiple satellites on the same track. It is difficult to meet the requirements of multi-satellite coordinated observations in the case of orbital heterogeneity, and is not suitable for regional observations of agile satellites.

[0004] For the sequencing of observation activities, domestic and foreign research institutions usually first use integer linear programming models, graphical models, constraint satisfaction models and other models to characterize the regional target observation scheduling problem, and then introduce constraint information such as satellite single imaging duration, daily imaging duration, and mission objectives such as maximum cumulative coverage area, minimum satellite resource consumption, and earliest observation time. Finally, greedy algorithms, genetic algorithms, ant colony algorithms and other optimization algorithms are used to obtain the optimal solution. This problem belongs to the combinatorial explosion problem and is an Np-hard problem. The optimization process requires a series of accurate satellite imaging power-on and power-off time, satellite side swing angle, imaging width and other parameter data sets to be combined and sorted to eliminate conflicts. After obtaining the optimal solution, if the observation demand is temporarily adjusted and re-planning is required, the calculation is time-consuming, and the above-mentioned algorithm naturally introduces randomness, resulting in uncertainty in each planning result. At the same time, few studies have given specific solutions to problems such as collaborative observation of multiple regional targets and demand merging caused by overlapping regional targets. Summary of the invention

[0005] In order to solve the problem of multi-satellite collaborative observation of regional targets in imaging requirements such as global-scale periodic observations, detailed observations in key areas, and emergency observations in specific areas, the present invention provides a giant remote sensing constellation mission planning method for regional targets.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is: A method for planning a regional target-oriented giant remote sensing constellation mission includes the following steps: Step 1: Build a global regional reference system. The process is as follows: Load multiple large-scale observation area targets, obtain the longitude and latitude coordinate data set of the boundary inflection points of each large-scale observation area target; generate the circumscribed rectangle of the corresponding area target based on the longitude and latitude coordinate data set of the boundary inflection points of each large-scale observation area target; set a hexagonal reference grid in the corresponding large-scale observation area target with any vertex of the circumscribed rectangle of each large-scale observation area target as the starting point; obtain the intersection of each large-scale observation area target and the corresponding hexagonal reference grid, thereby obtaining the observation grid corresponding to each large-scale observation area target, and obtaining the observation grid information; Step 2: Determine the observation priority. The process is as follows: Configure the priority P1 of each reference grid obtained in step 1 ij , and the priority P2 of each reference grid observation requirement ij , the priority of satellite imaging payload for each reference grid observation P3 ij , the priority of the observation task of each reference grid P4 ij , and calculate the observation comprehensive priority P of each reference grid based on the configured priorities; Step 3: Pre-allocation of constellation tasks. The process is as follows: Load satellite capability parameter information and constellation task pre-allocation constraints, obtain observation demand information, obtain the satellite instantaneous orbit elements, observation grid information obtained in step 1, and the observation comprehensive priority P of each reference grid obtained in step 2, and perform orbit prediction calculation, circle number calculation, observation grid center point and satellite payload visibility analysis calculation, and earth shadow prediction calculation in sequence, and formulate constellation task pre-allocation strategy; According to the results of visibility analysis of several groups of observation grid center points and satellite payloads, the optimization target of constellation task pre-allocation is set; Based on the results of the visibility analysis of the observation grid center point and the satellite payload, combined with the constellation task pre-allocation strategy and the constellation task pre-allocation constraints, the data that does not meet the requirements is eliminated; then, according to the constellation task pre-allocation optimization goal, an optimization algorithm is used to generate a one-to-one correspondence between the observation grid and the imaging satellite in the observation demand period in the observation demand information, that is, the Pareto optimal solution of the multi-constraint and multi-objective constellation task pre-allocation scheme, thereby generating a one-to-one correspondence between the observation grid and the imaging satellite in the observation demand period, and obtaining the constellation task pre-allocation scheme; Step 4: Single-star mission planning. The process is as follows: Load satellite-specific constraints, set satellite imaging characteristic parameters, obtain ground receiving station information, generate a satellite data transmission plan based on the satellite instantaneous orbit elements and ground receiving station information, and formulate a satellite data transmission plan optimization strategy. Then, based on the constellation task pre-allocation plan, satellite-specific constraints, satellite imaging characteristic parameters, the satellite data transmission plan and its optimization strategy obtained in step 3, generate a satellite imaging plan and a satellite data transmission plan for the single-satellite mission planning stage.

[0007] Furthermore, in step 1, the maximum and minimum values ​​of the longitude and latitude coordinate data set of the boundary inflection points of each regional target are calculated to obtain the longitude and latitude coordinates of the four vertices of the circumscribed rectangle, thereby generating the circumscribed rectangle of the corresponding regional target.

[0008] Furthermore, in step 1, starting from the upper left corner vertex of the circumscribed rectangle of each regional target, a hexagonal reference grid is set in the corresponding regional target in a clockwise direction from left to right and from top to bottom. The side length of each hexagonal reference grid is L / n, where L is the typical imaging width of the giant remote sensing constellation and n is an empirical parameter.

[0009] Furthermore, in step 2, according to the principle that China and periodic regions are better than other regions, and cities with large populations are better than regions with sparse populations, the priority P1 of each reference grid obtained in step 1 is configured. ij .

[0010] Furthermore, in step 2, based on the global topographic data information, the priority P2 of different industry users for each reference grid observation demand is formulated. ij .

[0011] Furthermore, in step 2, the priority P3 of the satellite imaging payload for each reference grid observation is configured according to the time period ij .

[0012] Furthermore, in step 2, the priority P4 of the observation task of each reference grid is configured according to the importance and urgency of the single observation task. ij .

[0013] Furthermore, in step 2, the observation comprehensive priority P of each reference grid is priority P1 ij , Priority P2 ij , Priority P3 ij , Priority P4 ij The weighted sum of .

[0014] Furthermore, in step 3, a constellation task pre-allocation strategy is formulated according to the payload type in the satellite capability parameter information. The constellation task pre-allocation strategy is: when the local time is daytime, the imaging satellite is selected according to the principle of visible light payload > SAR payload > hyperspectral payload > electronic payload; when the local time is night, the imaging satellite is selected according to the principle of infrared payload > SAR payload > electronic payload > visible light payload.

[0015] Furthermore, in step 4, the satellite data transmission optimization strategy is formulated as follows: emergency imaging tasks are first transmitted, the real shooting and real transmission combination is second, and the imaging playback and transmission combination is the least transmitted.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention proposes a giant remote sensing constellation mission planning method for regional targets. The method fully considers the heterogeneous and highly symmetrical spatial structure of the constellation orbits and the laws of global periodic motion, and combines the application scenarios of typical payloads such as satellite visible light, infrared, hyperspectral, SAR payloads, and electronics. The method solves a package of systematic problems in the commonly used regional target observation mission planning methods, such as the failure to achieve centralized overall planning, poor algorithm compatibility, low applicability, and poor timeliness, which is helpful to realize real-time observation of giant remote sensing constellations. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of a method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will describe the implementation methods of the present invention in detail in conjunction with the accompanying drawings and embodiments, so that the implementation process of how the present invention applies technical means to solve technical problems and achieve corresponding technical effects can be fully understood and implemented accordingly. The embodiments of the present invention and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the protection scope of the present invention.

[0019] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0020] It should be noted that the terms "include" and "have" in the specification and claims of the present invention and the above drawings and any modifications thereof are intended to cover non-exclusive inclusions.

[0021] like Figure 1 As shown, this embodiment discloses a giant remote sensing constellation mission planning method for regional targets, which is divided into four stages: building a global regional reference system, determining observation priorities, constellation mission pre-allocation, and single-satellite mission planning.

[0022] The stage of building a global regional reference system mainly realizes the functions of reference grid division, grid division representation, and mapping relationship generation. The stage of determining observation priorities mainly comprehensively determines the observation priorities from the aspects of reference grids, observation requirements, satellite payloads, and observation tasks. The constellation task pre-allocation stage generates a one-to-one correspondence between observation grids and imaging satellites within the observation demand cycle through a certain pre-allocation strategy based on information such as the number of satellite orbital elements, imaging width and resolution, platform maneuverability (such as side swing range), and observation grids. The single-satellite task planning stage mainly considers the special constraints of the satellite in the adjacent grid search space of the single-satellite observation plan, combines the information of the ground receiving station, and dynamically adjusts the constellation task pre-allocation plan to generate satellite imaging plans and satellite data transmission plans.

[0023] This embodiment includes the following steps: Step 1: Build a global regional reference system, clarify the grid division method, grid division granularity, grid representation method and grid mapping relationship, and establish a long-term association between large-scale regional targets and reference grids. The process is as follows: Load multiple large-scale observation area targets by linking maps, importing files of specified types, and selecting administrative areas.

[0024] The boundary information of the discretized regional targets is used to obtain the longitude and latitude coordinates dataset of the boundary inflection points of each large-scale observation regional target based on the boundary information.

[0025] Based on the longitude and latitude coordinate data set of the boundary inflection points of each large-scale observation area target, the maximum and minimum values ​​of the longitude and latitude coordinate data set of the boundary inflection points of each large-scale observation area target are calculated, and the longitude and latitude coordinates of the four vertices of the circumscribed rectangle are obtained, thereby generating the circumscribed rectangle of the corresponding area target.

[0026] Taking any vertex of the bounding rectangle of each large-scale observation area target as the starting point, a hexagonal reference grid is set in the corresponding large-scale observation area target. In this embodiment, taking the upper left corner vertex of the bounding rectangle of each large-scale observation area target as the starting point, a hexagonal reference grid is set in the corresponding area target from left to right and from top to bottom in a clockwise direction, and the side length of each hexagonal reference grid is L / n, where L is the typical imaging width of the giant remote sensing constellation, and n is an empirical parameter. In this embodiment, 1km≤L≤200km, and n≥2.

[0027] Then, the intersection of each large-scale observation area target and the corresponding hexagonal reference grid is obtained, thereby obtaining the observation grid corresponding to each large-scale observation area target and the observation grid information. The observation grid information includes the longitude and latitude of the grid center point (log, lat) and the observation grid number (i, j).

[0028] Step 2: Determine the observation priority comprehensively from the dimensions of reference grid, observation requirements, satellite payload, and observation mission. The process is as follows: Based on the principle that China and periodic regions are better than other regions, and cities with large populations are better than regions with small populations, combined with global population data information, the priority P1 of each reference grid obtained in step 1 is configured. ij .

[0029] According to the global topographic data information (including plains, mountains, islands, and desert data information), configure the priority P2 of different industry users (including agriculture, forestry, water conservancy, earthquake, and marine users) for each reference grid observation demand obtained in step 1 ij .

[0030] Determine whether the local time of the satellite subsatellite point is day or night, and configure the priority of the satellite imaging payload for each reference grid observation according to the time period P3 ij If it is daytime, the observation priority of satellite imaging payload is configured according to the principle of visible light payload > SAR payload > hyperspectral payload > electronic payload; if it is night, the observation priority of satellite imaging payload is configured according to the principle of SAR payload > infrared payload > electronic payload > hyperspectral payload. Thus, the priority P3 of satellite imaging payload observed for each reference grid obtained in step 1 is configured. ij .

[0031] According to the importance and urgency of a single observation task, configure the priority P4 of the observation task of each reference grid obtained in step 1 ij For example, the priority of emergency imaging tasks in specific areas > the priority of precise imaging tasks for regional targets > the priority of detailed investigation imaging tasks in key areas > the priority of global basic imaging tasks.

[0032] Finally, the observation comprehensive priority P of each reference grid is calculated based on the configured priorities. The calculation formula is as follows: P=a1* P1 ij + a2* P2 ij + a3* P3 ij + a4* P4 ij Among them: a1, a2, a3, a4 are the permission factors of the corresponding priorities respectively, a1+a2+a3+a4=1, 0<a1,a2,a3,a4<1.

[0033] Step 3: Pre-allocation of constellation tasks.

[0034] In the constellation task pre-allocation phase, based on the number of satellite orbit elements, imaging width and resolution, platform maneuverability (such as side swing range), observation grid, and observation comprehensive priority P, a one-to-one correspondence between observation grids and imaging satellites within the observation demand cycle is generated through a certain pre-allocation strategy. The constellation task pre-allocation process is as follows: Load satellite capability parameter information, including satellite code, imaging width and resolution, satellite field of view, platform maneuverability (such as side swing range), and payload type. For the same satellite with multiple payloads, where the imaging width, resolution, satellite field of view and other information are completely different under various payload modes, the constellation mission pre-allocation process is participated in by constructing virtual satellites.

[0035] Load constellation task pre-allocation constraints, which include the maximum satellite power-on time, satellite health status, and weather forecast grid cloud cover.

[0036] Obtain observation demand information, which includes observation demand cycle period, minimum resolution requirement, and minimum coverage of regional targets.

[0037] Obtain the satellite's instantaneous orbital elements, the observation grid information obtained in step 1, and the observation comprehensive priority P of each reference grid obtained in step 2, and perform orbit prediction calculation, circle number calculation, visibility analysis calculation of the observation grid center point and satellite payload, and ground shadow prediction calculation in sequence.

[0038] According to the payload type in the satellite capability parameter information, the constellation mission pre-allocation strategy is formulated. The constellation mission pre-allocation strategy is: when the local time is daytime, the imaging satellite is selected according to the principle of visible light payload priority > SAR payload priority > hyperspectral payload priority > electronic payload priority; when the local time is night, the imaging satellite is selected according to the principle of infrared payload priority > SAR payload priority > electronic payload priority > visible light payload priority.

[0039] According to the visibility analysis results of several groups of observation grid center points and satellite payloads, the constellation task pre-allocation optimization objectives are set. The constellation task pre-allocation optimization objectives include the maximum number of covered grids, the maximum number of covered grids, the maximum cumulative sum of comprehensive observation priorities, the minimum number of imaging satellites, the minimum sum of satellite maneuvering angles (such as side swing angle), and the minimum sum of observation start times.

[0040] Based on the results of the visibility analysis and calculation of the observation grid center point and satellite payload, combined with the constellation task pre-allocation strategy and constellation task pre-allocation constraints, the data that does not meet the requirements are eliminated. Then, according to the constellation task pre-allocation optimization goal, the optimization algorithm is used to generate the one-to-one correspondence between the observation grid and the imaging satellite in the observation demand period in the observation demand information, that is, the Pareto optimal solution of the multi-constraint and multi-objective constellation task pre-allocation scheme. The Parteo optimal solution includes satellite code, observation grid, circle number, planned imaging start time, planned imaging end time, planned imaging duration, and side swing angle, thereby generating a one-to-one correspondence between the observation grid and the imaging satellite in the observation demand period, and obtaining the constellation task pre-allocation scheme.

[0041] Step 4: Single-star mission planning.

[0042] The single-satellite mission planning stage mainly considers the satellite's special constraints within the adjacent grid search space of the single-satellite observation plan, combines the ground receiving station information, dynamically adjusts the constellation task pre-allocation plan, and generates satellite imaging plans and satellite data transmission plans. The single-satellite mission planning process is as follows: Load satellite-specific constraints, which include satellite maneuver switching time, payload startup warm-up time, multiple imaging times at one startup, and the shortest imaging time.

[0043] Set satellite imaging characteristic parameters, including the polarization mode (HH, HV, VH, VV, HH+HV, VH+VV, AHV) required for SAR payload imaging, and the maximum cloud cover constraint required for visible light payload and infrared payload imaging.

[0044] Get the ground receiving station information, including the ground receiving station site coordinates, antenna type, and shielding angle.

[0045] Based on the satellite instantaneous orbit elements obtained in step 3 and the ground receiving station information, perform data transmission visibility analysis and calculation, and eliminate unreasonable results in which data transmission is earlier than imaging, and generate a satellite data transmission plan.

[0046] Develop an optimization strategy for satellite data transmission solutions. The optimization strategy for satellite data transmission solutions is: emergency imaging tasks are given priority for downlinking, real-shot and real-transmission combinations are given priority for downlinking, and imaging and playback downlink combinations are given the lowest priority for downlinking.

[0047] Then, based on the constellation task pre-allocation plan obtained in step 3, the satellite special constraints loaded in step 4, satellite imaging characteristic parameters, satellite data transmission plan, and satellite data transmission plan optimization strategy, the satellite imaging plan and satellite data transmission plan for the single-satellite mission planning stage are generated. Therefore, satellite command processing and reverse compilation verification are performed according to the satellite imaging plan to generate the corresponding satellite measurement and control plan.

[0048] The preferred embodiments of the present invention are described in detail above in conjunction with the accompanying drawings. The embodiments described in the present invention are merely descriptions of the preferred embodiments of the present invention, and do not limit the concept and scope of the present invention. The various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction, and such combinations should also be regarded as the contents disclosed in the present disclosure as long as they do not violate the concept of the present invention. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0049] The present invention is not limited to the specific details of the above-mentioned embodiments. Within the technical concept of the present invention and without departing from the design concept of the present invention, various modifications and improvements made to the technical solution of the present invention by technical personnel in this field should fall within the protection scope of the present invention. The technical contents for which protection is sought in the present invention have been fully recorded in the claims.

Claims

1. A method for planning a giant remote sensing constellation mission for regional targets, characterized in that: The following steps are involved: Step 1: Build a global regional reference system. The process is as follows: Load multiple large-scale observation area targets, obtain the longitude and latitude coordinate data set of the boundary inflection points of each large-scale observation area target; generate the circumscribed rectangle of the corresponding area target based on the longitude and latitude coordinate data set of the boundary inflection points of each large-scale observation area target; Taking any vertex of the circumscribed rectangle of each large-scale observation area target as the starting point, a hexagonal reference grid is set in the corresponding large-scale observation area target; the intersection of each large-scale observation area target and the corresponding hexagonal reference grid is obtained, thereby obtaining the observation grid corresponding to each large-scale observation area target and obtaining the observation grid information; Step 2: Determine the observation priority. The process is as follows: Configure the priority P1 of each reference grid obtained in step 1 ij , and the priority P2 of each reference grid observation requirement ij , the priority of satellite imaging payload for each reference grid observation P3 ij , the priority of the observation task of each reference grid P4 ij , and calculate the observation comprehensive priority P of each reference grid based on the configured priorities; Step 3: Pre-allocation of constellation tasks. The process is as follows: Load satellite capability parameter information and constellation task pre-allocation constraints, obtain observation demand information, obtain the satellite instantaneous orbit elements, observation grid information obtained in step 1, and the observation comprehensive priority P of each reference grid obtained in step 2, and perform orbit prediction calculation, circle number calculation, observation grid center point and satellite payload visibility analysis calculation, and earth shadow prediction calculation in sequence, and formulate constellation task pre-allocation strategy; According to the results of visibility analysis of several groups of observation grid center points and satellite payloads, the optimization target of constellation task pre-allocation is set; Based on the results of the visibility analysis of the observation grid center point and the satellite payload, combined with the constellation task pre-allocation strategy and the constellation task pre-allocation constraints, the data that does not meet the requirements is eliminated; then, according to the constellation task pre-allocation optimization goal, an optimization algorithm is used to generate a one-to-one correspondence between the observation grid and the imaging satellite in the observation demand period in the observation demand information, that is, the Pareto optimal solution of the multi-constraint and multi-objective constellation task pre-allocation scheme, thereby generating a one-to-one correspondence between the observation grid and the imaging satellite in the observation demand period, and obtaining the constellation task pre-allocation scheme; Step 4: Single-star mission planning. The process is as follows: Load satellite-specific constraints, set satellite imaging characteristic parameters, obtain ground receiving station information, generate a satellite data transmission plan based on the satellite instantaneous orbit elements and ground receiving station information, and formulate a satellite data transmission plan optimization strategy. Then, based on the constellation task pre-allocation plan, satellite-specific constraints, satellite imaging characteristic parameters, the satellite data transmission plan and its optimization strategy obtained in step 3, generate a satellite imaging plan and a satellite data transmission plan for the single-satellite mission planning stage.

2. The method for planning a regional target-oriented giant remote sensing constellation mission according to claim 1, characterized in that: In step 1, the maximum and minimum values ​​of the longitude and latitude coordinate data set of the boundary inflection points of each regional target are calculated to obtain the longitude and latitude coordinates of the four vertices of the circumscribed rectangle, thereby generating the circumscribed rectangle of the corresponding regional target.

3. The method for planning a regional target-oriented giant remote sensing constellation mission according to claim 1, characterized in that: In step 1, starting from the upper left corner vertex of the circumscribed rectangle of each regional target, a hexagonal reference grid is set in the corresponding regional target in a clockwise direction from left to right and from top to bottom. The side length of each hexagonal reference grid is L / n, where L is the typical imaging width of the giant remote sensing constellation and n is an empirical parameter.

4. The method for planning a regional target-oriented giant remote sensing constellation mission according to claim 1, characterized in that: In step 2, according to the principle that China and periodic regions are better than other regions, and cities with large populations are better than regions with sparse populations, the priority P1 of each reference grid obtained in step 1 is configured. ij .

5. The method for planning a regional target-oriented giant remote sensing constellation mission according to claim 1, characterized in that: In step 2, according to the global topographic data information, the priority P2 of different industry users for each reference grid observation demand is formulated. ij .

6. The method for planning a regional target-oriented giant remote sensing constellation mission according to claim 1, characterized in that: In step 2, the priority P3 of the satellite imaging payload for each reference grid observation is configured by time period ij .

7. The method for planning a regional target-oriented giant remote sensing constellation mission according to claim 1, characterized in that: In step 2, according to the importance and urgency of a single observation task, the priority P4 of the observation task of each reference grid is configured. ij .

8. The method for planning a regional target-oriented giant remote sensing constellation mission according to claim 1, characterized in that: In step 2, the observation integrated priority P of each reference grid is priority P1 ij , Priority P2 ij , Priority P3 ij , Priority P4 ij The weighted sum of .

9. The method for planning a regional target-oriented giant remote sensing constellation mission according to claim 1, characterized in that: In step 3, a constellation task pre-allocation strategy is formulated according to the payload type in the satellite capability parameter information. The constellation task pre-allocation strategy is: when the local time is daytime, the imaging satellite is selected according to the principle of visible light payload > SAR payload > hyperspectral payload > electronic payload; when the local time is night, the imaging satellite is selected according to the principle of infrared payload > SAR payload > electronic payload > visible light payload.

10. The method for planning a regional target-oriented giant remote sensing constellation mission according to claim 1, characterized in that: In step 4, the optimization strategy for the satellite data transmission scheme is formulated as follows: emergency imaging tasks are transmitted first, the real-shot and real-transmission combination is transmitted second, and the imaging playback and transmission combination is transmitted last.

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