A Mission Planning Method for Giant Remote Sensing Constellations Oriented to Regional Targets

Abstract

The present invention discloses a method for mission planning of a giant remote sensing constellation for regional targets, comprising the following steps: Step 1, construct a global regional reference system, determine the reference grid of the regional target and the corresponding observation grid, and obtain the observation grid information; Step 2, determine the observation priority, and calculate the comprehensive observation priority of each reference grid; Step 3, pre-allocate the constellation mission, generate the one-to-one correspondence between the observation grid and the imaging satellite within the observation demand period in the observation demand information, and obtain the constellation mission pre-allocation plan; Step 4, single-satellite mission planning, generate the satellite imaging and data transmission plans in the single-satellite mission planning stage based on the constellation mission pre-allocation plan, satellite special constraint conditions, satellite imaging characteristic parameters, satellite data transmission scheme and its optimization strategy. The present invention fully considers the constellation orbit heterogeneity, highly symmetric spatial structure and the law of global periodic motion, which helps to achieve the instant observation of the giant remote sensing constellation.

Description

Technical Field

[0001] The present invention relates to the technical field of mission planning for giant remote sensing constellations, and specifically to a mission planning method for giant remote sensing constellations targeting regional targets. Background Art

[0002] With the progress of space 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 with a scale of hundreds or even more than ten thousand satellites at a speed of "60 satellites per rocket and 4 launches per month". In the future, giant remote sensing constellations will exhibit characteristics such as heterogeneous networking, global distribution, multi-satellite collaboration, and multi-purpose use of a single satellite. Driven by this development trend, how to design a flexible and diverse mission planning framework for giant remote sensing constellations based on the existing on-orbit remote sensing satellite observation capabilities and taking into account subsequent development, and solve 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 focused on breaking through.

[0003] In order to complete the task of multi-satellite collaborative observation of large-area regional targets, most domestic and foreign research institutions decompose the problem of multi-satellite collaborative regional observation into two sub-problems: regional target segmentation and observation activity sequencing. For regional target segmentation, essentially, it is in the form of a single satellite with a fixed imaging swath, or a form of a fixed imaging swath and a deflection angle, and along the direction perpendicular to the satellite flight, through parallel segmentation, the on-off time of satellite imaging is determined. This method is only applicable to the single-satellite multiple observations of specific models of satellites and the repeated observations of multi-satellites in the same orbit, and it is difficult to meet the multi-satellite collaborative observation in the case of orbital heterogeneity, nor is it applicable to the regional observation of agile satellites.

[0004] For the sequencing of observation activities, domestic and foreign research institutions usually first use models such as integer linear programming models, graph models, and constraint satisfaction models to characterize the regional target observation scheduling problem, then introduce constraint information such as the single imaging duration of satellites and the daily imaging duration, as well as task objectives such as the largest cumulative coverage area, the smallest consumption of satellite resources, and the earliest observation time, and finally use optimization algorithms such as greedy algorithms, genetic algorithms, and ant colony algorithms to obtain the optimal solution. This problem belongs to the problem of combinatorial explosion and is an Np-hard problem. The optimization process requires combinatorial sorting and conflict resolution of a series of precise datasets of satellite imaging on-off times, satellite side-sway angles, imaging swaths, etc. After obtaining the optimal solution, if the observation requirements are adjusted temporarily, re-planning is required, and the re-calculation is time-consuming. At the same time, the above algorithms naturally introduce randomness, resulting in uncertainty in each planning result. At the same time, for problems such as multi-regional target collaborative observation and demand merging caused by overlapping regional targets, few studies give specific solutions. Summary of the Invention

[0005] Aiming at the problem of multi-satellite collaborative observation of regional targets in imaging requirements such as global-scale periodic observation, detailed investigation observation in key regions, and emergency observation in specific regions, the present invention provides a task planning method for a giant remote sensing constellation for regional targets.

[0006] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] A task planning method for a giant remote sensing constellation for regional targets, comprising the following steps:

[0008] Step 1, construct a global regional reference system, the process is as follows:

[0009] Load multiple large-scale observation regional targets, obtain the longitude and latitude coordinate data sets of the boundary inflection points of each large-scale observation regional target; generate the circumscribed rectangle of the corresponding regional target based on the longitude and latitude coordinate data sets of the boundary inflection points of each large-scale observation regional target; set a hexagonal reference grid in the corresponding large-scale observation regional target with any vertex of the circumscribed rectangle of each large-scale observation regional target as the starting point; obtain the intersection of each large-scale observation regional target and the corresponding hexagonal reference grid, thereby obtaining the observation grid corresponding to each large-scale observation regional target, and obtaining the observation grid information.

[0010] Step 2, determine the observation priority, the process is as follows:

[0011] Configure the priority P1 of each reference grid obtained in Step 1 ij , and the priority P2 of the observation requirement for each reference grid ij , the priority P3 of the satellite imaging payload for observing each reference grid ij , the priority P4 of the observation task for each reference grid ij , and calculate the comprehensive observation priority P of each reference grid based on the configured priorities.

[0012] Step 3, pre-allocate the constellation tasks, the process is as follows:

[0013] Load the satellite capability parameter information, the constellation task pre-allocation constraint conditions, obtain the observation requirement information, obtain the satellite instantaneous orbital elements, the observation grid information obtained in Step 1, and the comprehensive observation priority P of each reference grid obtained in Step 2, and perform orbital prediction calculation, circle number calculation, observation grid center point and satellite payload visibility analysis calculation, and penumbra prediction calculation in sequence, and formulate a constellation task pre-allocation strategy.

[0014] Set the constellation task pre-allocation optimization goal according to the visibility analysis results of several groups of observation grid center points and satellite payloads.

[0015] Based on the calculation results of the visibility analysis of the central points of the observation grids and the satellite payloads, combined with the constellation mission pre-allocation strategy and the constellation mission pre-allocation constraints, the data that does not meet the requirements is eliminated; then, according to the optimization objectives of the constellation mission pre-allocation, an optimization algorithm is used to generate the one-to-one correspondence between the observation grids and the imaging satellites within the observation demand period in the observation demand information, that is, the Pareto optimal solution of the multi-constraint multi-objective constellation mission pre-allocation scheme, thereby generating the one-to-one correspondence between the observation grids and the imaging satellites within the observation demand period to obtain the constellation mission pre-allocation scheme.

[0016] Step 4, single-satellite mission planning, the process is as follows:

[0017] Load the special constraints of the satellite, set the satellite imaging characteristic parameters, obtain the information of the ground receiving stations, generate the satellite data transmission scheme based on the satellite's instantaneous orbital elements and the information of the ground receiving stations, and formulate the optimization strategy for the satellite data transmission scheme. Then, based on the constellation mission pre-allocation scheme, the special constraints of the satellite, the satellite imaging characteristic parameters, the satellite data transmission scheme and its optimization strategy obtained in Step 3, generate the satellite imaging plan and the satellite data transmission plan in the single-satellite mission planning stage.

[0018] Furthermore, in Step 1, calculate the maximum and minimum values of the boundary inflection point longitude and latitude coordinate datasets of each regional target, obtain the longitude and latitude coordinates of the 4 vertices of the circumscribed rectangle, and thereby generate the circumscribed rectangle corresponding to the regional target.

[0019] Furthermore, in Step 1, starting from the upper left vertex of the circumscribed rectangle of each regional target, set hexagonal reference grids in the corresponding regional target from left to right and from top to bottom in a clockwise direction. 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.

[0020] Furthermore, in Step 2, according to the principle that the home country and its surrounding areas are superior to other areas, and cities with a large population are superior to areas with a sparse population, configure the priority P1 of each reference grid obtained in Step 1 ij 。

[0021] Furthermore, in Step 2, according to the global topographic and geomorphic data information, formulate the priority P2 of the observation requirements of different industry users for each reference grid ij 。

[0022] Furthermore, in Step 2, configure the priority P3 of the satellite imaging payload for observing each reference grid according to the time period ij 。

[0023] Furthermore, in Step 2, configure the priority P4 of the observation tasks of each reference grid according to the importance and urgency of a single observation task ij 。

[0024] Further, in step 2, the observed comprehensive priority P of each reference grid is the priority P1 ij , the priority P2 ij , the priority P3 ij , the priority P4 ij weighted sum of.

[0025] Further, in step 3, according to the payload type in the satellite capability parameter information, a constellation mission pre-allocation strategy is formulated. The constellation mission pre-allocation strategy is as follows: when the local time is daytime, imaging satellites are selected according to the principle of visible light payload > SAR payload > hyperspectral payload > electronic payload; when the local time is night, imaging satellites are selected according to the principle of infrared payload > SAR payload > electronic payload > visible light payload.

[0026] Further, in step 4, the optimized strategy for the satellite data transmission scheme is: emergency imaging tasks are preferentially downlinked, the combination of real-time shooting and real-time transmission is downlinked secondarily, and the combination of imaging playback and downlink is downlinked least preferably.

[0027] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0028] The present invention proposes a method for planning the tasks of a giant remote sensing constellation for regional targets. This method fully considers the constellation orbit heterogeneity, highly symmetric spatial structure, and the laws of global periodic motion, and combines the application scenarios of typical payloads such as satellite visible light, infrared, hyperspectral, SAR payload, and electronics, solving a series of systematic problems such as the lack of centralized overall planning, poor algorithm compatibility, low applicability, and poor timeliness in the commonly used regional target observation task planning methods, and contributing to the realization of the instant observation of the giant remote sensing constellation. Description of the Drawings

[0029] Figure 1 is the flowchart of the method in the embodiment of the present invention. Detailed Embodiment

[0030] In order to enable those skilled in the art to better understand the solution of the present invention, the following will describe in detail the implementation manner of the present invention in combination with the drawings and embodiments, so as to fully understand how the present invention uses technical means to solve technical problems and achieve the corresponding technical effects and implement them accordingly. Each feature in the embodiments of the present invention can be combined with each other without conflict, and the formed technical solutions are all within the protection scope of the present invention.

[0031] Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0032] It should be noted that the terms "comprising", "having" and any variations thereof in the description, claims and above-mentioned drawings of the present invention are intended to cover non-exclusive inclusion.

[0033] As Figure 1 shown, this embodiment discloses a method for mission planning of a giant remote sensing constellation for regional targets, which is divided into four stages: constructing a global regional reference system, determining observation priorities, pre-assigning constellation tasks, and single-satellite mission planning.

[0034] The stage of constructing a global regional reference system mainly realizes functions such as reference grid division, grid division representation, and mapping relationship generation. The stage of determining observation priorities comprehensively determines observation priorities mainly from aspects such as reference grids, observation requirements, satellite payloads, and observation tasks. The constellation task pre-assignment stage generates a one-to-one correspondence between the observation grids and imaging satellites within the observation requirement period through a certain pre-assignment strategy according to information such as satellite orbital elements, imaging swath and resolution, platform maneuverability (such as side-sway range), and observation grids. The single-satellite mission planning stage mainly dynamically adjusts the constellation task pre-assignment plan within the adjacent grid search space of the single-satellite observation plan, considering satellite special constraint conditions and combining ground receiving station information, to generate a satellite imaging plan and a satellite data transmission plan.

[0035] This embodiment includes the following steps:

[0036] Step 1: Construct 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 relationship between large-scale regional targets and reference grids. The process is as follows:

[0037] Load multiple large-scale observation regional targets in the forms of map linkage, importing specified type files, and selecting administrative regions.

[0038] Discretize the boundary information of the regional target, and obtain the boundary inflection point longitude and latitude coordinate dataset of each large-scale observation regional target according to the boundary information.

[0039] Based on the boundary inflection point longitude and latitude coordinate dataset of each large-scale observation regional target, calculate the maximum and minimum values of the boundary inflection point longitude and latitude coordinate dataset of each large-scale observation regional target, obtain the longitude and latitude coordinates of the 4 vertices of the circumscribed rectangle, and thus generate the circumscribed rectangle of the corresponding regional target.

[0040] 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. In this embodiment, taking the upper left 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 area target from left to right and top to bottom in a clockwise direction. 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, 1 km ≤ L ≤ 200 km and n ≥ 2.

[0041] Then, find 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. The information of the observation grid includes the longitude and latitude (log, lat) of the grid center point and the observation grid numbers (i, j).

[0042] Step 2: Comprehensively determine the observation priority from the dimensions of the reference grid, observation requirements, satellite payload, and observation mission. The process is as follows:

[0043] According to the principle that the home country and its surrounding areas are superior to other areas, and cities with a large population are superior to areas with a sparse population, combined with the global population data information, configure the priority P1 of each reference grid obtained in Step 1 ij 。

[0044] According to the global topographic and geomorphic data information (including plain, mountain, island, and desert data information), configure the priority P2 of the observation requirements of different industry users (including agriculture, forestry, water conservancy, earthquake, and ocean users) for each reference grid obtained in Step 1 ij 。

[0045] Judge whether the local time at the satellite sub-satellite point is day or night, and configure the priority P3 of the satellite imaging payload for observing each reference grid according to the time period ij 。If it is day, configure the observation priority of the satellite imaging payload according to the principle of visible light payload > SAR payload > hyperspectral payload > electronic payload; if it is night, configure the observation priority of the satellite imaging payload according to the principle of SAR payload > infrared payload > electronic payload > hyperspectral payload. Thus, configure the priority P3 of the satellite imaging payload for observing each reference grid obtained in Step 1 ij 。

[0046] According to the importance and urgency of a single observation mission, configure the priority P4 of the observation mission of each reference grid obtained in Step 1 ij 。For example, the priority of the emergency imaging mission in a specific area > the priority of the precise imaging mission of the area target > the priority of the detailed imaging mission in the key area > the priority of the global basic imaging mission.

[0047] Finally, based on the various priorities configured, the observed comprehensive priority P of each reference grid is calculated, and the calculation formula is as follows:

[0048] P = a1 * P1 ij + a2 * P2 ij + a3 * P3 ij + a4 * P4 ij

[0049] Where: a1, a2, a3, and a4 are the permission factors of the corresponding priorities respectively, a1 + a2 + a3 + a4 = 1, and 0 < a1, a2, a3, a4 < 1.

[0050] Step 3: Pre-allocation of constellation tasks.

[0051] In the pre-allocation stage of constellation tasks, based on information such as satellite orbital elements, imaging swath and resolution, platform maneuverability (such as side-sway range), observation grids, and the observed comprehensive priority P, a one-to-one correspondence between observation grids and imaging satellites within the observation demand period is generated through a certain pre-allocation strategy. The process of constellation task pre-allocation is as follows:

[0052] Load satellite capability parameter information, which includes satellite code, imaging swath and resolution, satellite field of view, platform maneuverability (such as side-sway range), and payload type. For the case where the same satellite has multiple payloads and the imaging swath, resolution, satellite field of view, etc. are completely different under various payload modes, it participates in the process of constellation task pre-allocation in the form of constructing virtual satellites.

[0053] Load the constellation task pre-allocation constraint conditions, which include the maximum satellite on-time, satellite health status, and cloud amount of the weather forecast grid.

[0054] Obtain the observation demand information, which includes the time period of the observation demand cycle, the minimum resolution requirement, and the minimum multiplicity of regional target coverage.

[0055] Obtain the satellite's instantaneous orbital elements, the observation grid information obtained in Step 1, and the observed comprehensive priority P of each reference grid obtained in Step 2, and perform orbit prediction calculation, loop number calculation, visibility analysis calculation of the observation grid center point and the satellite payload, and earth shadow prediction calculation in sequence.

[0056] According to the payload type in the satellite capability parameter information, formulate the pre-allocation strategy for constellation missions. The pre-allocation strategy for constellation missions is as follows: When the local time is daytime, select imaging satellites according to the principle that the visible light payload priority > SAR payload priority > hyperspectral payload priority > electronic payload priority; when the local time is night, select imaging satellites according to the principle that the infrared payload priority > SAR payload priority > electronic payload priority > visible light payload priority.

[0057] According to the analysis results of the central points of several groups of observation grids and the visibility of satellite payloads, set the optimization objectives for constellation mission pre-allocation. The optimization objectives for constellation mission pre-allocation include the largest number of covered grids, the largest multiplicity of covered grids, the largest cumulative sum of comprehensive observation priorities, the smallest number of imaging satellites, the smallest sum of satellite maneuvering angles (such as the side-sway angle), and the smallest sum of observation start times.

[0058] Based on the analysis and calculation results of the central points of observation grids and the visibility of satellite payloads, combined with the constellation mission pre-allocation strategy and the constellation mission pre-allocation constraint conditions, eliminate the data that do not meet the requirements. Then, according to the optimization objectives of constellation mission pre-allocation, use the optimization algorithm to generate the one-to-one correspondence between the observation grids and imaging satellites within the observation demand period in the observation demand information, that is, the Pareto optimal solution of the multi-constraint multi-objective constellation mission pre-allocation scheme. The Pareto optimal solution includes satellite code, observation grid, orbit number, planned imaging start time, planned imaging end time, planned imaging duration, and side-sway angle. Thus, generate the one-to-one correspondence between the observation grids and imaging satellites within the observation demand period to obtain the constellation mission pre-allocation scheme.

[0059] Step 4: Single-satellite mission planning.

[0060] In the single-satellite mission planning stage, mainly within the adjacent grid search space of the single-satellite observation plan, considering the special constraints of the satellite and combining the information of the ground receiving station, dynamically adjust the constellation mission pre-allocation scheme to generate the satellite imaging plan and the satellite data transmission plan. The process of single-satellite mission planning is as follows:

[0061] Load the special constraints of the satellite. The special constraints of the satellite include the satellite maneuvering switching time, the payload power-on warm-up time, the number of multiple imaging times in one power-on, and the shortest imaging duration.

[0062] Set the satellite imaging characteristic parameters, including the polarization mode (HH, HV, VH, VV, HH+HV, VH+VV, AHV) that needs to be set when the SAR payload is imaging, and the maximum cloud cover constraint that needs to be set when the visible light payload and the infrared payload are imaging.

[0063] Obtain the information of the ground receiving station, including the site coordinates of the ground receiving station, the antenna type, and the shielding angle.

[0064] Based on the satellite's instantaneous orbital elements obtained in step 3 and the information of the ground receiving station, perform data transmission visibility analysis and calculation, and eliminate the unreasonable results in which data transmission is earlier than imaging in the results to generate a satellite data transmission plan.

[0065] Formulate an optimization strategy for the satellite data transmission plan. The optimization strategy for the satellite data transmission plan is as follows: prioritize the downlink of emergency imaging tasks, followed by the downlink of the combination of real shooting and real transmission, and the least priority is given to the downlink of the combination of imaging playback and downlink.

[0066] Then, based on the constellation mission pre-allocation plan obtained in step 3, the satellite special constraint conditions loaded in step 4, the satellite imaging characteristic parameters, the satellite data transmission plan, and the satellite data transmission plan optimization strategy, generate the satellite imaging plan and satellite data transmission plan in the single-satellite mission planning stage. Then, according to the satellite imaging plan, perform satellite command processing and inverse encoding verification to generate the corresponding satellite TT&C plan.

[0067] The preferred embodiments of the present invention have been described in detail above in conjunction with the accompanying drawings. The embodiments described in the present invention are only descriptions of the preferred embodiments of the present invention, and do not limit the concept and scope of the present invention. Among the various specific technical features described in the above specific embodiments, they can be combined in any suitable manner without contradiction. As long as such a combination does not violate the idea of the present invention, it should also be regarded as the content disclosed in this disclosure. To avoid unnecessary repetition, the present invention will not separately describe various possible combination methods.

[0068] The present invention is not limited to the specific details in the above embodiments. Without departing from the technical concept of the present invention and within the scope of the design idea of the present invention, various variations and improvements made by those skilled in the art to the technical solution of the present invention should fall within the protection scope of the present invention. The technical content claimed by the present invention has 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 and the priority P4 of the observation task of each reference grid 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, the observation grid information obtained in step 1, and the observation comprehensive priority P of each reference grid obtained in step 2, 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 the visibility analysis of several groups of observation grid center points and satellite payloads, the optimization objectives of constellation task pre-allocation are set. The optimization objectives of constellation task pre-allocation include the largest number of covered grids, the largest number of covered grids, the largest cumulative sum of comprehensive observation priorities, the smallest number of imaging satellites, the smallest sum of satellite maneuvering angles, and the smallest sum of observation start times. 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, the optimization algorithm is used to generate the Pareto optimal solution of the constellation task pre-allocation scheme. The Pareto optimal solution includes the satellite code, observation grid, circle number, planned imaging start time, planned imaging end time, planned imaging duration and sway angle, thereby generating a one-to-one correspondence between the observation grid and the imaging satellite within the observation demand cycle, and thus obtaining the constellation task pre-allocation scheme; Step 4: Single-star mission planning. The process is as follows: Load satellite-specific constraints, including satellite maneuver switching time, payload startup warm-up time, multiple imaging times per startup, and the shortest imaging duration; 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 special constraints, satellite imaging characteristic parameters and the satellite data transmission plan and its optimization strategy obtained in step 3, generate a satellite imaging plan and satellite data transmission plan for the single-star 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 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 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, the priority of each reference grid obtained in step 1 is configured based on the fact that the country and its surrounding areas have higher priority than other areas and that cities with large populations have higher priority than sparsely populated areas, combined with global population data information. 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, based on 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 and 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 given priority, the real-shot and real-transmission combination is given the second priority, and the imaging playback and downlink combination is given the lowest priority.

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