A large-scale constellation-oriented autonomous calibration task cooperative planning method and device

Abstract

The application discloses a kind of large-scale constellation-oriented autonomous calibration task cooperation planning method and device.The method includes S1, obtains calibration resource information, satellite information and constellation resource information;The calibration resource information includes star calibration field, cold air calibration field, moon reference source, ground comprehensive field, ground uniform field and cross calibration field;The satellite information includes satellite state information and satellite task type information;The satellite state information includes the on-orbit state information of N satellites, N is positive integer;The on-orbit state information includes fast evaluation phase information, on-orbit test phase information or operation guarantee phase information;S2, based on the calibration resource information, the satellite information and the constellation resource information, determine task allocation information;S3, based on the task allocation information, determine the execution task sequence.It can be seen that the present application is beneficial to improve the on-orbit calibration efficiency under the current cluster giant optical constellation networking condition.

Description

Technical Field

[0001] The present invention relates to the field of high-resolution optical remote sensing satellite design and preprocessing, and in particular to a method and device for collaborative planning of autonomous calibration tasks for large-scale constellations. Background Art

[0002] Over the past 20 years, with the rapid development of aerospace and aviation remote sensing technologies, the spatial, spectral, and temporal resolutions of Earth observation satellites have continued to improve. Driven by this continuous improvement in satellite performance, Earth observation has shifted from the traditional single-satellite model to a constellation of lightweight, small satellites. These satellites meet data acquisition requirements for shorter revisit periods, wider observation coverage, and rapid response and continuous dynamic monitoring based on specific mission objectives. In 2018, DARPA launched the Blackjack low-Earth orbit constellation project, aiming to fully leverage low-cost commercial satellite platforms from the United States to construct a constellation of approximately 60-200 microsatellites at an orbital altitude of 500-130 km. The constellation will operate autonomously for 30 days, achieving continuous global coverage and collaborating with commercial constellations to enhance system resilience. The constellation era presents both opportunities and challenges. Domestic satellites have long been subject to restrictions on foreign core components, resulting in significant image noise, insufficient clarity, low calibration efficiency, and low accuracy. With the rapid increase in the scale of satellites, the traditional 2-3 months of single-satellite on-orbit calibration and 5-6 months of routine calibration processing are difficult to meet the on-orbit use requirements of "launch and use immediately, and rapid replenishment".

[0003] With the continuous evolution and intensification of domestic and international competition, and the explosive growth of downlinked remote sensing data from satellite clusters, how to maximize the comprehensive system efficiency, achieve intelligent and precise processing of high-frequency imagery on a global scale, and provide fast and accurate information services has become a major issue that urgently needs to be addressed for ground-based applications. Therefore, a method and device for collaborative planning of autonomous calibration tasks for large-scale constellations is provided to improve the efficiency of on-orbit calibration under the current conditions of clustered giant optical constellations. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method and device for collaborative planning of autonomous calibration tasks for large-scale constellations, so as to improve the on-orbit calibration efficiency under the current cluster giant optical constellation networking conditions.

[0005] To solve the above technical problems, a first aspect of an embodiment of the present invention discloses a collaborative planning method for autonomous calibration tasks for large-scale constellations, the method comprising:

[0006] S1, obtain calibration resource information, satellite information and constellation resource information;

[0007] The calibration resource information includes stellar calibration field, cold sky calibration field, lunar reference source, ground comprehensive field, ground uniform field and cross calibration field; the satellite information includes satellite status information and satellite mission type information;

[0008] The satellite status information includes on-orbit status information of N satellites, where N is a positive integer; the on-orbit status information includes quick assessment phase information, on-orbit test phase information, or operation guarantee phase information;

[0009] The satellite mission type information includes emergency missions, data transmission missions, inter-satellite collaborative missions, ground planning routine missions, orbit control missions and autonomous calibration missions;

[0010] S2, determining task allocation information based on the calibration resource information, the satellite information, and the constellation resource information;

[0011] S3: Determine an execution task sequence based on the task allocation information.

[0012] As an optional implementation manner, in the first aspect of the embodiment of the present invention, determining the task allocation information based on the calibration resource information, the satellite information, and the constellation resource information includes:

[0013] S21, determining calibration mode information based on the calibration resource information; the calibration mode information includes a cold sky observation mode in an illuminated shadow area, an autonomous radiation calibration mode for lunar observation, an autonomous geometric calibration mode for sky imaging, an autonomous geometric calibration mode based on a reference star intersection, an autonomous radiation calibration mode based on a cross-field, an autonomous geometric calibration mode based on a ground field, an autonomous geometric calibration mode based on a no-field intersection, an autonomous radiation calibration mode based on a synthetic field, and a relative radiation calibration mode based on a uniform field;

[0014] S22, determining autonomous calibration and maintenance information based on the calibration mode information and the on-orbit status information;

[0015] S23 : Determine task allocation information based on the calibration resource information, the autonomous calibration and maintenance information, the satellite information, and the constellation resource information.

[0016] As an optional implementation manner, in the first aspect of the embodiments of the present invention, determining the autonomous calibration and maintenance information based on the calibration mode information and the on-orbit status information includes:

[0017] S221, preset judgment times a=1;

[0018] S222, extracting the on-orbit status information of the a-th satellite to obtain extracted information;

[0019] When the extracted information is the quick review stage information, the autonomous calibration and maintenance information of the a-th satellite is set to the sky imaging autonomous geometric calibration mode and the illumination shadow area cold sky observation mode, or the reference star crossing-based autonomous geometric calibration mode and the crossing field-based autonomous radiation calibration mode;

[0020] When the extracted information is the on-orbit test phase information, setting the autonomous calibration and maintenance information of the a-th satellite to a non-field-crossing autonomous geometric calibration mode, a uniform field-based relative radiation calibration mode, a ground field-based autonomous geometric calibration mode and a comprehensive field-based autonomous radiation calibration mode, or a reference satellite-crossing autonomous geometric calibration mode and a cross-field-based autonomous radiation calibration mode, or a sky imaging autonomous geometric calibration mode and a ground field-based autonomous geometric calibration mode;

[0021] When the extracted information is the operation support phase information, setting the autonomous calibration and maintenance information of the a-th satellite to an autonomous geometric calibration mode for sky imaging, or an autonomous radiometric calibration mode for lunar observation, or an autonomous geometric calibration mode based on a reference star intersection and an autonomous radiometric calibration mode based on a cross-field;

[0022] S223, determining whether a is equal to N, and obtaining a number determination result;

[0023] When the result of the number of times judgment is no, the number of times a is increased by 1, and S222 is executed;

[0024] When the result of the number of times is yes, S23 is executed.

[0025] As another optional implementation manner, in the first aspect of the embodiment of the present invention, determining the task allocation information based on the calibration resource information, the autonomous calibration and maintenance information, the satellite information, and the constellation resource information includes:

[0026] S231, determining a task sequence set based on the constellation resource information, the calibration resource information, the autonomous calibration and maintenance information, and the satellite information; the task sequence set includes M task sequences, where M is a positive even number;

[0027] S232, using a calibration task calculation model, processing the M task sequences in the task sequence set respectively to obtain corresponding task sequence values;

[0028] The calibration task calculation model is:

[0029]

[0030] Wherein, F represents the task sequence value, the α, β, γ and ε represent the first weight coefficient, the second weight coefficient, the third weight coefficient and the fourth weight coefficient respectively, resCal, resSta, calMain and calInf represent the calibration resource information, the constellation resource information, the autonomous calibration and maintenance information and the satellite information respectively; the resCal i 、the resStta i , the calMain i and the calInf i represent the calibration resource information, the constellation resource information, the autonomous calibration and maintenance information, and the satellite information of the i-th satellite respectively, and N is the number of satellites.

[0031] S233, determining a first task sequence set based on the task sequence set and the task sequence values ​​corresponding to the task sequences in the task sequence set; the first task sequence set includes a plurality of the task sequences;

[0032] S234, using the calibration task calculation model, performing calculation processing on a plurality of the task sequences in the first task sequence set to obtain corresponding task sequence values;

[0033] S235, merging the task sequence set with the first task sequence set to obtain a second task sequence set;

[0034] S236, sorting the task sequence values ​​of the task sequences in the second task sequence set from small to large to obtain a target task sequence; the target task sequence is the task sequence with the smallest task sequence value in the second task sequence set;

[0035] S237, determining whether the task sequence value corresponding to the target task sequence is less than a first threshold, and obtaining a first determination result;

[0036] When the first judgment result is no, determining that the second task sequence set is the task sequence set, executing S233;

[0037] When the first judgment result is yes, it is determined that the satellite task type information in the satellite information in the target task sequence is task allocation information.

[0038] As an optional implementation manner, in the first aspect of the embodiment of the present invention, a task sequence set is determined based on the constellation resource information, the calibration resource information, the autonomous calibration and maintenance information, and the satellite information; the task sequence set includes M task sequences, where M is a positive even number, including:

[0039] S2311, determining preprocessing task information for each satellite based on the constellation resource information, the calibration resource information, the autonomous calibration and maintenance information, and the satellite information; the preprocessing task information includes a plurality of preprocessing tasks;

[0040] S2312, performing M random combinations on a plurality of the pre-processing tasks in the pre-processing task information of each satellite to obtain M task sequences;

[0041] S2313: Merge the M task sequences to obtain a task sequence set.

[0042] As another optional implementation, in the first aspect of the embodiment of the present invention, determining the first task sequence set based on the task sequence set and the task sequence values ​​corresponding to the task sequences in the task sequence set includes:

[0043] S2331, the preset task processing times b=1, the third task sequence set and the fourth task sequence set are both empty sets;

[0044] S2332, determining whether the task processing times b is greater than the length of the task sequence set, and obtaining a second determination result;

[0045] When the second judgment result is no, executing S2333;

[0046] When the second judgment result is yes, execute S2334;

[0047] S2333, determining whether the task sequence value corresponding to the bth task sequence in the task sequence set is less than a second threshold, and obtaining a third determination result;

[0048] When the third judgment result is yes, adding the bth task sequence to the third task sequence set;

[0049] When the third judgment result is no, adding the bth task sequence to the fourth task sequence set;

[0050] The task processing times b is increased by 1, and S2332 is executed;

[0051] S2334, exchanging elements in the task interval [R1, R2] of the task sequences in the third task sequence set to obtain a fifth task sequence set; R1 is a positive integer greater than or equal to 1 and less than or equal to R2; R2 is a positive integer greater than or equal to R1 and less than or equal to N;

[0052] S2335, transforming the task sequence in the fourth task sequence set to obtain a sixth task sequence set;

[0053] S2336: Merge the fifth task sequence set and the sixth task sequence set to obtain a first task sequence set.

[0054] A second aspect of an embodiment of the present invention discloses a collaborative planning device for autonomous calibration tasks for large-scale constellations, characterized in that the device includes:

[0055] An acquisition module is used to obtain calibration resource information, satellite information and constellation resource information;

[0056] The calibration resource information includes stellar calibration field, cold sky calibration field, lunar reference source, ground comprehensive field, ground uniform field and cross calibration field; the satellite information includes satellite status information and satellite mission type information;

[0057] The satellite status information includes on-orbit status information of N satellites, where N is a positive integer; the on-orbit status information includes quick assessment phase information, on-orbit test phase information, or operation guarantee phase information;

[0058] The satellite mission type information includes emergency missions, data transmission missions, inter-satellite collaborative missions, ground planning routine missions, orbit control missions and autonomous calibration missions;

[0059] A task allocation module, configured to determine task allocation information based on the calibration resource information, the satellite information, and the constellation resource information;

[0060] The task collaborative planning module is used to determine the execution task sequence based on the task allocation information.

[0061] A third aspect of an embodiment of the present invention discloses another device for collaborative planning of autonomous calibration tasks for large-scale constellations, characterized in that the device includes:

[0062] processor;

[0063] a memory coupled to the processor and storing executable program code;

[0064] The processor calls the executable program code stored in the memory to execute some or all steps of the method for collaborative planning of autonomous calibration tasks for large-scale constellations disclosed in the first aspect of the embodiment of the present invention.

[0065] A fourth aspect of an embodiment of the present invention discloses another computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions, which, when called, are used to execute some or all steps of the method for collaborative planning of autonomous calibration tasks for large-scale constellations disclosed in the first aspect of the embodiment of the present invention.

[0066] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0067] In an embodiment of the present invention, calibration resource information, satellite information, and constellation resource information are obtained; the calibration resource information includes a stellar calibration field, a cold-air calibration field, a lunar reference source, a ground-based integrated field, a ground-based uniform field, and a cross-calibration field; the satellite information includes satellite status information and satellite mission type information; the satellite status information includes on-orbit status information of N satellites, where N is a positive integer; the on-orbit status information includes quick assessment phase information, on-orbit test phase information, or operation guarantee phase information; the satellite mission type information includes emergency tasks, data transmission tasks, inter-satellite collaborative tasks, ground-based planning routine tasks, orbit control tasks, and autonomous calibration tasks; based on the calibration resource information, the satellite information, and the constellation resource information, task allocation information is determined; based on the task allocation information, a task execution sequence is determined. It can be seen that this application is beneficial to improving the efficiency of on-orbit calibration under the current cluster giant optical constellation networking conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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.

[0069] Figure 1 This is a flow chart of a collaborative planning method for autonomous calibration tasks for large-scale constellations disclosed in an embodiment of the present invention;

[0070] Figure 2 This is a schematic diagram of the structure of a collaborative planning device for autonomous calibration tasks for large-scale constellations disclosed in an embodiment of the present invention;

[0071] Figure 3 This is a schematic diagram of the structure of another device for collaborative planning of autonomous calibration tasks for large-scale constellations disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0072] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0073] The terms "first," "second," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different objects, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or device comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or device.

[0074] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0075] This invention discloses a collaborative planning method and apparatus for autonomous calibration tasks for large-scale constellations, which is beneficial for improving the efficiency of on-orbit calibration under current clustered giant optical constellation networking conditions. These are described in detail below.

[0076] Example 1

[0077] See also Figure 1 , Figure 1 This is a flow chart of a collaborative planning method for autonomous calibration tasks for large-scale constellations disclosed in an embodiment of the present invention. Figure 1 The described collaborative planning method for autonomous calibration tasks for large-scale constellations is applied to a collaborative planning system for autonomous calibration tasks for large-scale constellations, such as a local server or cloud server for data processing and management of collaborative planning for autonomous calibration tasks for large-scale constellations, and the embodiments of the present invention do not limit this. Figure 1 As shown, the collaborative planning method for the autonomous calibration task of the large-scale constellation may include the following operations:

[0078] S1, obtain calibration resource information, satellite information and constellation resource information;

[0079] The calibration resource information includes stellar calibration field, cold sky calibration field, lunar reference source, ground comprehensive field, ground uniform field and cross calibration field; the satellite information includes satellite status information and satellite mission type information;

[0080] The satellite status information includes on-orbit status information of N satellites, where N is a positive integer; the on-orbit status information includes quick assessment phase information, on-orbit test phase information, or operation guarantee phase information;

[0081] The satellite mission type information includes emergency missions, data transmission missions, inter-satellite collaborative missions, ground planning routine missions, orbit control missions and autonomous calibration missions;

[0082] S2, determining task allocation information based on the calibration resource information, the satellite information, and the constellation resource information;

[0083] S3: Determine an execution task sequence based on the task allocation information.

[0084] It should be noted that the on-orbit status information includes quick assessment phase information, on-orbit test phase information or operation support phase information. Specifically, for each satellite, its on-orbit status information is quick assessment phase information, on-orbit test phase information or operation support phase information. The specific type of information is determined by the operating time after the satellite is launched.

[0085] It should be noted that the constellation resource information includes resource type information, resolution, satellite orbit information, satellite sway angle, satellite imaging range information, visible time window information and attitude maneuverability performance information;

[0086] It should be noted that the above-mentioned large-scale constellation uses large-scale, low-cost microsatellites, in accordance with a new aerospace system that is distributed, flexible, collaborative, and intelligent; it has the ability to conduct high-frequency observations and information support in any region of the world, forming a space-based earth observation network. Each satellite is regarded as a resource node in a large system, and information can be exchanged between resource nodes. Through the integrated space-ground earth observation system composed of inter-satellite and satellite-to-ground links, remote sensing observation information on the ground is obtained. The constellation has the ability to operate and manage independently, and has the ability to intelligently acquire, store and distribute information.

[0087] It should be noted that the camera payload indicators used in the large-scale constellation in this application are: panchromatic resolution of 0.5 meters at an orbital altitude of 500 kilometers, and multispectral resolution of 2 meters; the full color spectrum range is 0.45 microns-0.8 microns, and the multispectral spectrum range is B1 0.45 microns-0.52 microns, B2 0.52 microns-0.59 microns, B3 0.63 microns-0.69 microns, and B4 0.77 microns-0.89 microns.

[0088] It should be noted that the calibration resource information includes stellar calibration fields, cold-sky calibration fields, lunar reference sources, ground-based integrated fields, ground-based uniform fields, and cross-calibration fields. The stellar calibration fields are primarily based on the SAO star catalog, with the highest apparent magnitude detectable by the camera payload set to 9.0. The uniformity and coverage of the horizontal star distribution within the field of view are used as indicators to evaluate the suitability of the sky region, resulting in stellar fields with different sky region distributions for geometric calibration. The cold-sky calibration fields primarily refer to deep space, which contains no stars and has a relatively low temperature, making them the best resource for dark current statistics for optical payloads. The lunar reference source primarily refers to the Moon, Earth's natural satellite, whose properties make it an ideal reference source for on-orbit radiometric calibration. The ground-based integrated fields primarily refer to remote sensing integrated calibration fields for autonomous geometric and radiometric calibration. Representative examples include the Songshan, Baotou, Zhongwei, La Crua, France, Railroad Valley Playa, USA, and Gobabed, Namibia. These fields can automatically measure surface reflectance and atmospheric parameters at their locations. The ground uniform field primarily refers to a large-scale uniform site (natural uniform and stable radiation field resource) that meets the uniformity requirements, selected from existing global Earth observation imagery. This site serves as a radiation benchmark for relative radiation calibration. These sites are primarily distributed in North Africa, Central Asia, and the Arctic and Antarctic regions, including deserts, Gobi deserts, and ice caps. The cross-calibration field primarily involves selecting several calibration sites from around the world, downloading their corresponding MODIS data, analyzing their BRDFs (bidirectional reflectance distribution functions), and constructing a cross-calibration field BRDF resource library.

[0089] It should be noted that the information in the quick assessment phase refers to the on-orbit status information of the satellite 5-7 days after launch, the information in the on-orbit test phase refers to the on-orbit status information of the satellite 1-3 months after launch, and the information in the operation guarantee phase refers to the on-orbit status information of the satellite for long-term operation and maintenance. The information in the quick assessment phase mainly refers to the ability to quickly complete the on-orbit calibration of the geometric external parameters and relative radiation parameters of the optical camera payload within 5-7 days of the satellite entering orbit to initially meet the mission observation requirements; the information in the on-orbit test phase mainly refers to the fine calibration and analysis of the geometric parameters and radiation parameters of the optical camera payload within 1-3 months of the satellite entering orbit to meet the requirements of high-quality observation information support; the information in the operation guarantee phase mainly refers to the satellite completing the on-orbit test and entering the long-term operation and maintenance state, monitoring and maintaining the satellite's geometric and radiation parameters to achieve stable and consistent quality of observation products.

[0090] It can be seen that implementing the collaborative planning method for autonomous calibration tasks for large-scale constellations described in the embodiments of the present invention is conducive to improving the on-orbit calibration efficiency under the current cluster giant optical constellation networking conditions.

[0091] In another optional embodiment, determining task allocation information based on the calibration resource information, the satellite information, and the constellation resource information includes:

[0092] S21, determining calibration mode information based on the calibration resource information; the calibration mode information includes a cold sky observation mode in an illuminated shadow area, an autonomous radiation calibration mode for lunar observation, an autonomous geometric calibration mode for sky imaging, an autonomous geometric calibration mode based on a reference star intersection, an autonomous radiation calibration mode based on a cross-field, an autonomous geometric calibration mode based on a ground field, an autonomous geometric calibration mode based on a no-field intersection, an autonomous radiation calibration mode based on a synthetic field, and a relative radiation calibration mode based on a uniform field;

[0093] S22, determining autonomous calibration and maintenance information based on the calibration mode information and the on-orbit status information;

[0094] S23 : Determine task allocation information based on the calibration resource information, the autonomous calibration and maintenance information, the satellite information, and the constellation resource information.

[0095] It should be noted that the calibration mode information determined based on the calibration resource information may be manually set or obtained based on analysis of historical statistical data, which is not specifically limited in the embodiment of the present invention.

[0096] It should be noted that each mode in the calibration mode information has on-orbit boundary conditions, and its on-orbit boundary conditions are as follows: the cold sky observation mode in the illuminated shadow area is mainly used for the statistics of dark current of optical payloads, and requires that the imaging area has no stars and is in the shadow area; the autonomous radiation calibration mode for lunar observation requires that the moon be observed at a specific lunar phase angle to obtain time series observation data; the autonomous geometric calibration mode for sky imaging requires that the satellite has the ability to "image the sky" and obtain observation images of the specified star field, with the stars distributed as much as possible throughout the imaging field of view; the autonomous geometric calibration mode based on the reference star cross requires cross observations of the same area, and the imaging side swing angle is controlled within 5 degrees; the autonomous radiation calibration mode based on the cross field It is required to conduct cross-observation of existing cross-fields, with the time interval controlled within 30 minutes and the imaging angle difference controlled within 20 degrees; the ground field autonomous geometric calibration mode requires the satellite to observe the existing comprehensive field, and the side swing angle is controlled within 5 degrees; the field-free cross-autonomous geometric calibration mode requires the satellite's maneuverable imaging capability to obtain multi-scene "cross images" in orbit, with an overlap of 55% to 60%; the comprehensive field-based autonomous radiation calibration mode requires the satellite to observe and image the comprehensive field, with the side swing angle controlled within 5 degrees, and the ground observation equipment is carried out synchronously; the uniform field-based relative radiation calibration mode requires the satellite to image the existing uniform field library, with the side swing angle controlled within 5 degrees and the solar altitude angle above 30 degrees.

[0097] It should be noted that the on-orbit usage boundary conditions of each mode in the above calibration mode information can be set by the user or determined by statistical analysis based on historical data, and the embodiment of the present invention does not impose any limitation thereto.

[0098] It should be noted that the autonomous calibration and maintenance information is determined based on the calibration mode information and the on-orbit status information. The specific determination may be set by the user or determined by the system based on historical data, which is not limited in the embodiment of the present invention.

[0099] It should be noted that the autonomous calibration and maintenance information includes satellite information in the quick assessment phase, satellite information in the on-orbit test phase, and satellite information in the operation support phase.

[0100] It can be seen that implementing the collaborative planning method for autonomous calibration tasks for large-scale constellations described in the embodiments of the present invention is conducive to improving the on-orbit calibration efficiency under the current cluster giant optical constellation networking conditions.

[0101] In yet another optional embodiment, determining autonomous calibration and maintenance information based on the calibration mode information and the on-orbit status information includes:

[0102] S221, preset judgment times a=1;

[0103] S222, extracting the on-orbit status information of the a-th satellite to obtain extracted information;

[0104] When the extracted information is the quick review stage information, the autonomous calibration and maintenance information of the a-th satellite is set to the sky imaging autonomous geometric calibration mode and the illumination shadow area cold sky observation mode, or the reference star crossing-based autonomous geometric calibration mode and the crossing field-based autonomous radiation calibration mode;

[0105] It should be noted that the autonomous calibration and maintenance information of the above-mentioned a-th satellite is: (1) the autonomous geometric calibration mode for sky imaging and the cold sky observation mode for the illuminated shadow area, or (2) the autonomous geometric calibration mode based on the reference star crossing and the autonomous radiation calibration mode based on the crossing field; whether (1) or (2) is selected as the autonomous calibration and maintenance information of the above-mentioned a-th satellite is specified by the user or obtained based on historical data, and the embodiment of the present invention does not make any specific limitation.

[0106] When the extracted information is the on-orbit test phase information, setting the autonomous calibration and maintenance information of the a-th satellite to a non-field-crossing autonomous geometric calibration mode, a uniform field-based relative radiation calibration mode, a ground field-based autonomous geometric calibration mode and a comprehensive field-based autonomous radiation calibration mode, or a reference satellite-crossing autonomous geometric calibration mode and a cross-field-based autonomous radiation calibration mode, or a sky imaging autonomous geometric calibration mode and a ground field-based autonomous geometric calibration mode;

[0107] It should be noted that the autonomous calibration and maintenance information of the above-mentioned a-th satellite is: (1) based on the autonomous geometric calibration mode without field crossing, the relative radiation calibration mode based on the uniform field, the autonomous geometric calibration mode based on the ground field and the autonomous radiation calibration mode based on the integrated field, or (2) based on the autonomous geometric calibration mode based on the reference star crossing and the autonomous radiation calibration mode based on the cross-field, or (3) the autonomous geometric calibration mode for sky imaging and the autonomous geometric calibration mode based on the ground field; specifically, the selection of (1), (2) or (3) as the autonomous calibration and maintenance information of the above-mentioned a-th satellite is specified by the user or obtained based on historical data, and the embodiment of the present invention does not make any specific limitation.

[0108] When the extracted information is the operation support phase information, setting the autonomous calibration and maintenance information of the a-th satellite to an autonomous geometric calibration mode for sky imaging, or an autonomous radiometric calibration mode for lunar observation, or an autonomous geometric calibration mode based on a reference star intersection and an autonomous radiometric calibration mode based on a cross-field;

[0109] It should be noted that the autonomous calibration and maintenance information of the above-mentioned a-th satellite is: (1) autonomous geometric calibration mode for sky imaging, or (2) autonomous radiation calibration mode for lunar observation, or (3) autonomous geometric calibration mode based on reference star crossing and autonomous radiation calibration mode based on crossing field; specifically, the selection of (1), (2) or (3) as the autonomous calibration and maintenance information of the above-mentioned a-th satellite is specified by the user or obtained based on historical data, and the embodiment of the present invention does not make any specific limitation.

[0110] S223, determining whether a is equal to N, and obtaining a number determination result;

[0111] When the result of the number of times judgment is no, the number of times a is increased by 1, and S222 is executed;

[0112] When the result of the number of times is yes, S23 is executed.

[0113] In yet another optional embodiment, determining task allocation information based on the calibration resource information, the autonomous calibration and maintenance information, the satellite information, and the constellation resource information includes:

[0114] S231, determining a task sequence set based on the constellation resource information, the calibration resource information, the autonomous calibration and maintenance information, and the satellite information; the task sequence set includes M task sequences, where M is a positive even number;

[0115] S232, using a calibration task calculation model, processing the M task sequences in the task sequence set respectively to obtain corresponding task sequence values;

[0116] The calibration task calculation model is:

[0117]

[0118] Wherein, F represents the task sequence value, the α, β, γ and ε represent the first weight coefficient, the second weight coefficient, the third weight coefficient and the fourth weight coefficient respectively, resCal, resSta, calMain and calInf represent the calibration resource information, the constellation resource information, the autonomous calibration and maintenance information and the satellite information respectively; the resCal i 、the reSta i , the calMain i and the callnfi i represent the calibration resource information, the constellation resource information, the autonomous calibration and maintenance information, and the satellite information of the i-th satellite respectively, and N is the number of satellites.

[0119] It should be noted that the use of the above model is to obtain the task sequence value by performing different permutations and combinations on the calibration resource information, the constellation resource information, the autonomous calibration and maintenance information, and the satellite information in the task sequence, and defining different weight coefficients by using α, β, γ, and ε. For example, the task sequence<a,b> The mission sequence for two satellites includes the calibration resource information, the constellation resource information, the autonomous calibration and maintenance information, and the satellite information of each satellite. For example, the calibration resource information, the constellation resource information, the autonomous calibration and maintenance information, and the satellite information included in satellite a are:

[0120] The calibration resource information is the star calibration field; the constellation resource information includes resource type and resolution, satellite orbit information, satellite sway angle, satellite imaging range, and visible time window information for each task; the autonomous calibration maintenance information is the autonomous geometric calibration mode for sky imaging and the cold sky observation mode in the illuminated shadow area; the on-orbit status information in the satellite information is the quick assessment stage information, and the satellite mission type information is emergency mission, data transmission mission, and inter-satellite collaborative mission.

[0121] For example, the calibration resource information, the constellation resource information, the autonomous calibration and maintenance information, and the satellite information included in satellite b are:

[0122] The calibration resource information is the ground uniform field; the constellation resource information includes resource type and resolution, satellite orbit information, satellite sway angle, satellite imaging range, and visible time window information for each task; the autonomous calibration maintenance information is the autonomous geometric calibration mode based on the ground field and the autonomous radiation calibration mode based on the integrated field; the on-orbit status information in the satellite information is the on-orbit test phase information, and the satellite mission type information is the inter-satellite collaborative mission, ground planning routine mission, and orbit control mission.

[0123] S233, determining a first task sequence set based on the task sequence set and the task sequence values ​​corresponding to the task sequences in the task sequence set; the first task sequence set includes a plurality of the task sequences;

[0124] S234, using the calibration task calculation model, performing calculation processing on a plurality of the task sequences in the first task sequence set to obtain corresponding task sequence values;

[0125] S235, merging the task sequence set with the first task sequence set to obtain a second task sequence set;

[0126] S236, sorting the task sequence values ​​of the task sequences in the second task sequence set from small to large to obtain a target task sequence; the target task sequence is the task sequence with the smallest task sequence value in the second task sequence set;

[0127] S237, determining whether the task sequence value corresponding to the target task sequence is less than a first threshold, and obtaining a first determination result;

[0128] When the first judgment result is no, determining that the second task sequence set is the task sequence set, executing S233;

[0129] When the first judgment result is yes, it is determined that the satellite task type information in the satellite information in the target task sequence is task allocation information.

[0130] It should be noted that the α, β, γ, and ε represent the first weight coefficient, the second weight coefficient, the third weight coefficient, and the fourth weight coefficient, respectively, which can be set manually or obtained based on historical data analysis. In the embodiments of the present invention, no specific limitation is made.

[0131] It should be noted that the task allocation information is determined based on the calibration resource information, the autonomous calibration and maintenance information, the satellite information and the constellation resource information. The task allocation information can also be determined using a greedy algorithm, a reinforcement learning algorithm or other algorithms. This embodiment does not impose any limitations.

[0132] It should be noted that the first threshold is used to determine whether the obtained target task sequence is the optimal task sequence. The first threshold can be set manually or obtained based on historical data information, and this embodiment does not impose any limitation.

[0133] It can be seen that implementing the collaborative planning method for autonomous calibration tasks for large-scale constellations described in the embodiments of the present invention is conducive to improving the on-orbit calibration efficiency under the current cluster giant optical constellation networking conditions.

[0134] In yet another optional embodiment, a task sequence set is determined based on the constellation resource information, the calibration resource information, the autonomous calibration and maintenance information, and the satellite information; the task sequence set includes M task sequences, where M is a positive even number, including:

[0135] S2311, determining preprocessing task information for each satellite based on the constellation resource information, the calibration resource information, the autonomous calibration and maintenance information, and the satellite information; the preprocessing task information includes a plurality of preprocessing tasks;

[0136] S2312, performing M random combinations on a plurality of the pre-processing tasks in the pre-processing task information of each satellite to obtain M task sequences;

[0137] S2313: Merge the M task sequences to obtain a task sequence set.

[0138] It should be noted that based on the constellation resource information, the calibration resource information, the autonomous calibration and maintenance information and the satellite information, the preprocessing task information of each satellite is determined; the preprocessing task information includes several preprocessing tasks, including merging the constellation resource information, the calibration resource information, the autonomous calibration and maintenance information and the satellite information of each satellite to obtain the constellation resource information, the calibration resource information, the autonomous calibration and maintenance information and the satellite information containing all satellites.

[0139] It should be noted that several pre-processing tasks in the pre-processing task information of each satellite are randomly combined M times to obtain M task sequences, including randomly combining elements in the satellite task type in the satellite information in the pre-processing task information, wherein the elements included in the satellite task type include emergency tasks, data transmission tasks, inter-satellite collaborative tasks, ground planning routine tasks, orbit control tasks, and autonomous calibration tasks.

[0140] It can be seen that implementing the collaborative planning method for autonomous calibration tasks for large-scale constellations described in the embodiments of the present invention is conducive to improving the on-orbit calibration efficiency under the current cluster giant optical constellation networking conditions.

[0141] In an optional embodiment, determining the first task sequence set based on the task sequence set and the task sequence values ​​corresponding to the task sequences in the task sequence set includes:

[0142] S2331, the preset task processing times b=1, the third task sequence set and the fourth task sequence set are both empty sets;

[0143] S2332, determining whether the task processing times b is greater than the length of the task sequence set, and obtaining a second determination result;

[0144] When the second judgment result is no, executing S2333;

[0145] When the second judgment result is yes, execute S2334;

[0146] S2333, determining whether the task sequence value corresponding to the bth task sequence in the task sequence set is less than a second threshold, and obtaining a third determination result;

[0147] When the third judgment result is yes, adding the bth task sequence to the third task sequence set;

[0148] When the third judgment result is no, adding the bth task sequence to the fourth task sequence set;

[0149] The task processing times b is increased by 1, and S2332 is executed;

[0150] S2334, exchanging elements in the task interval [R1, R2] of the task sequences in the third task sequence set to obtain a fifth task sequence set; R1 is a positive integer greater than or equal to 1 and less than or equal to R2; R2 is a positive integer greater than or equal to R1 and less than or equal to N;

[0151] S2335, transforming the task sequence in the fourth task sequence set to obtain a sixth task sequence set;

[0152] S2336: Merge the fifth task sequence set and the sixth task sequence set to obtain a first task sequence set.

[0153] It should be noted that the second threshold is greater than 0 and less than 1. The specific value can be randomly generated, manually set, or obtained based on historical data records. This embodiment does not impose any limitation.

[0154] It should be noted that the task interval [R1, R2] may be randomly generated, manually set, or obtained based on historical data records, and this embodiment does not impose any limitation.

[0155] It should be noted that, the elements of the task sequence in the third task sequence set in the task interval [R1, R2] are exchanged to obtain a fifth task sequence set, including:

[0156] Step 1-1, preset the number of cycles p=2, and the exchange task sequence set is an empty set;

[0157] Step 1-2, determining whether p is greater than the length of the third task sequence set, and obtaining an exchange determination result;

[0158] When the judgment result is no, execute steps 1-3;

[0159] When the judgment result is yes, execute steps 1-4;

[0160] Step 1-3, replacing the elements on the task interval [R1, R2] of the p-th sequence of the third task sequence with the p-1-th sequence of the third task sequence, and adding the replaced task sequence to the exchange task sequence set, the p is increased by 1, and step 1-2 is executed;

[0161] Step 1-4, replacing the p-1th sequence of the third task sequence with the elements on the task interval [R1, R2] of the first sequence of the third task sequence, and adding the replaced task sequence to the exchange task sequence set;

[0162] Step 1-5: Determine that the exchange task sequence set is the fifth task sequence set.

[0163] It should be noted that the task sequence in the fourth task sequence set is transformed to obtain the sixth task sequence set, including: randomly increasing or decreasing a number of calibration tasks in all the task sequences in the fourth task sequence set according to the transformation probability model to obtain a transformed sequence set, and determining the transformed sequence set as the sixth task sequence set.

[0164] The randomly adding or reducing a plurality of elements of the satellite mission type information in the satellite information in all the task sequences in the fourth task sequence set includes:

[0165] When randomly increasing a plurality of elements of the satellite mission type information in the satellite information in all task sequences in the fourth task sequence set, the number of tasks in the plurality of elements of the satellite mission type information in the satellite information in the task sequence is increased, but the increased elements are all the total amount of the satellite mission type information, and the increased elements of the satellite mission type information in the satellite information are all tasks in the satellite mission type information;

[0166] When randomly reducing the number of element tasks of the satellite task type information in the satellite information in all task sequences in the fourth task sequence set, the number of tasks of the elements of the satellite task type information in the satellite information in the task sequence is reduced, and the reduced elements are all tasks in the satellite task type information;

[0167] It should be noted that the above-mentioned transformation probability model can be set manually or obtained based on historical data, and this embodiment does not make any specific limitation.

[0168] It can be seen that implementing the collaborative planning method for autonomous calibration tasks for large-scale constellations described in the embodiments of the present invention is conducive to improving the on-orbit calibration efficiency under the current cluster giant optical constellation networking conditions.

[0169] In another optional embodiment, determining the execution task sequence based on the task allocation information includes:

[0170] S31, based on the task allocation information, prioritize the resource type information in the constellation resource information of each satellite to determine first task allocation information;

[0171] S32, using an orbit calculation and extrapolation model, processing the satellite orbit information in the constellation resource information of each satellite and the first task allocation information to obtain second task allocation information;

[0172] S33, processing the second task allocation information using a satellite resource usage constraint model to obtain the execution task sequence;

[0173] It should be noted that the resource type information has been assigned a priority order in advance according to the urgency of the resource type;

[0174] It should be noted that the orbit calculation and extrapolation model and the satellite resource utilization constraint model are both existing models.

[0175] It can be seen that implementing the collaborative planning method for autonomous calibration tasks for large-scale constellations described in the embodiments of the present invention is conducive to improving the on-orbit calibration efficiency under the current cluster giant optical constellation networking conditions.

[0176] Example 2

[0177] See also Figure 2 , Figure 2 This is a schematic diagram of the structure of a collaborative planning device for autonomous calibration tasks for large-scale constellations disclosed in an embodiment of the present invention. Figure 2 The described large-scale constellation-oriented autonomous calibration task collaborative planning device is applied to a large-scale constellation autonomous calibration task collaborative planning system, such as a local server or cloud server for data processing and management of large-scale constellation autonomous calibration task collaborative planning, and the embodiments of the present invention do not limit this. Figure 2 As shown, the large-scale constellation autonomous calibration task collaborative planning device includes:

[0178] Acquisition module 201, used to acquire calibration resource information, satellite information and constellation resource information;

[0179] The calibration resource information includes stellar calibration field, cold sky calibration field, lunar reference source, ground comprehensive field, ground uniform field and cross calibration field; the satellite information includes satellite status information and satellite mission type information;

[0180] The satellite status information includes on-orbit status information of N satellites, where N is a positive integer; the on-orbit status information includes quick assessment phase information, on-orbit test phase information, or operation guarantee phase information;

[0181] The satellite mission type information includes emergency missions, data transmission missions, inter-satellite collaborative missions, ground planning routine missions, orbit control missions and autonomous calibration missions;

[0182] It should be noted that the constellation resource information includes resource type information, resolution, satellite orbit information, satellite sway angle, satellite imaging range information, and visible time window information;

[0183] A task allocation module 202 is configured to determine task allocation information based on the calibration resource information, the satellite information, and the constellation resource information;

[0184] The task collaborative planning module 203 is used to determine a task execution sequence based on the task allocation information.

[0185] It can be seen that the implementation of the large-scale constellation-oriented autonomous calibration task collaborative planning device described in the embodiment of the present invention is conducive to improving the on-orbit calibration efficiency under the current cluster giant optical constellation networking conditions.

[0186] Example 3

[0187] See also Figure 3 , Figure 3 This is a schematic diagram of the structure of another collaborative planning device for autonomous calibration tasks for large-scale constellations disclosed in an embodiment of the present invention. Figure 3 The described large-scale constellation-oriented autonomous calibration task collaborative planning device is applied to a large-scale constellation autonomous calibration task collaborative planning system, such as a local server or cloud server for data processing and management of large-scale constellation autonomous calibration task collaborative planning, and the embodiments of the present invention do not limit this. Figure 3 As shown, the large-scale constellation autonomous calibration task collaborative planning device includes:

[0188] Processor 301;

[0189] A memory 302 coupled to the processor 301 and storing executable program code;

[0190] The processor 301 calls the executable program code stored in the memory 302 to execute the collaborative planning method for autonomous calibration tasks for large-scale constellations.

[0191] It can be seen that the implementation of the large-scale constellation-oriented autonomous calibration task collaborative planning device described in the embodiment of the present invention is conducive to improving the on-orbit calibration efficiency under the current cluster giant optical constellation networking conditions.

[0192] Example 4

[0193] An embodiment of the present invention discloses a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program enables a computer to execute the steps of the collaborative planning method for autonomous calibration tasks for large-scale constellations described in the first embodiment.

[0194] Example 5

[0195] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program. The computer program is operable to cause a computer to execute the steps of the collaborative planning method for autonomous calibration tasks for large-scale constellations described in the first embodiment.

[0196] The device embodiments described above are merely illustrative. Modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, i.e., they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0197] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus the necessary general hardware platform, or of course, by means of hardware. Based on this understanding, the above technical solution, in essence, or the portion that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0198] Finally, it should be noted that the method and apparatus for collaborative planning of autonomous calibration tasks for large-scale constellations disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are intended to illustrate the technical solutions of the present invention, not to limit them. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will appreciate that the technical solutions described in the aforementioned embodiments may be modified, or some of the technical features thereof may be replaced by equivalents. However, such modifications or replacements do not deviate from the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A collaborative planning method for autonomous calibration tasks for large-scale constellations, characterized by: The method comprises: S1, obtain calibration resource information, satellite information and constellation resource information; The satellite information includes satellite status information and satellite mission type information; The satellite status information includes on-orbit status information of N satellites, where N is a positive integer; the on-orbit status information includes quick assessment phase information, on-orbit test phase information, or operation guarantee phase information; S2, determining task allocation information based on the calibration resource information, the satellite information, and the constellation resource information; S3, determining the execution task sequence based on the task allocation information; Among them, S2 includes: S21, determining calibration mode information based on the calibration resource information; S22, determining autonomous calibration and maintenance information based on the calibration mode information and the on-orbit status information; S23, determining task allocation information based on the calibration resource information, the autonomous calibration and maintenance information, the satellite information, and the constellation resource information, including: S231, determining a task sequence set based on the constellation resource information, the calibration resource information, the autonomous calibration and maintenance information, and the satellite information; the task sequence set includes M task sequences, where M is a positive even number; S232, using the calibration task calculation model, processing the M task sequences in the task sequence set respectively to obtain corresponding task sequence values; The calibration task calculation model is: Where F represents the task sequence value, α, β, γ and ε represent the first weight coefficient, the second weight coefficient, the third weight coefficient and the fourth weight coefficient respectively, and resCal i 、resSta i 、calMain i and calInf i They represent the calibration resource information, constellation resource information, autonomous calibration and maintenance information, and satellite information of the i-th satellite, respectively. N is the number of satellites. S233, determining a first task sequence set based on the task sequence set and the task sequence values ​​corresponding to the task sequences in the task sequence set; the first task sequence set includes a plurality of the task sequences; S234, using the calibration task calculation model, performing calculation processing on a plurality of the task sequences in the first task sequence set to obtain corresponding task sequence values; S235, merging the task sequence set with the first task sequence set to obtain a second task sequence set; S236, sorting the task sequence values ​​of the task sequences in the second task sequence set from small to large to obtain a target task sequence; the target task sequence is the task sequence with the smallest task sequence value in the second task sequence set; S237, determining whether the task sequence value corresponding to the target task sequence is less than a first threshold, and obtaining a first determination result; When the first judgment result is no, determining that the second task sequence set is the task sequence set, executing S233; When the first judgment result is yes, it is determined that the satellite task type information in the satellite information in the target task sequence is task allocation information.

2. The collaborative planning method for autonomous calibration tasks for large-scale constellations according to claim 1, characterized in that: The determining of autonomous calibration and maintenance information based on the calibration mode information and the on-orbit state information includes: S221, preset judgment times a=1; S222, extracting the on-orbit status information of the a-th satellite to obtain extracted information; When the extracted information is the quick review stage information, the autonomous calibration and maintenance information of the a-th satellite is set to the sky imaging autonomous geometric calibration mode and the illumination shadow area cold sky observation mode, or the reference star crossing-based autonomous geometric calibration mode and the crossing field-based autonomous radiation calibration mode; When the extracted information is the on-orbit test phase information, setting the autonomous calibration and maintenance information of the a-th satellite to a non-field-crossing autonomous geometric calibration mode, a uniform field-based relative radiation calibration mode, a ground field-based autonomous geometric calibration mode and a comprehensive field-based autonomous radiation calibration mode, or a reference satellite-crossing autonomous geometric calibration mode and a cross-field-based autonomous radiation calibration mode, or a sky imaging autonomous geometric calibration mode and a ground field-based autonomous geometric calibration mode; When the extracted information is the operation support phase information, setting the autonomous calibration and maintenance information of the a-th satellite to an autonomous geometric calibration mode for sky imaging, or an autonomous radiometric calibration mode for lunar observation, or an autonomous geometric calibration mode based on a reference star intersection and an autonomous radiometric calibration mode based on a cross-field; S223, determining whether a is equal to N, and obtaining a number determination result; When the result of the number of times judgment is no, the number of times a is increased by 1, and S222 is executed; When the result of the number of times is yes, S23 is executed.

3. The collaborative planning method for autonomous calibration tasks for large-scale constellations according to claim 1, characterized in that: The step of determining a task sequence set based on the constellation resource information, the calibration resource information, the autonomous calibration and maintenance information, and the satellite information; wherein the task sequence set includes M task sequences, where M is a positive even number, including: S2311, determining preprocessing task information for each satellite based on the constellation resource information, the calibration resource information, the autonomous calibration and maintenance information, and the satellite information; the preprocessing task information includes a plurality of preprocessing tasks; S2312, performing M random combinations on a plurality of the pre-processing tasks in the pre-processing task information of each satellite to obtain M task sequences; S2313: Merge the M task sequences to obtain a task sequence set.

4. The collaborative planning method for autonomous calibration tasks for large-scale constellations according to claim 1, characterized in that: The determining of a first task sequence set based on the task sequence set and the task sequence values ​​corresponding to the task sequences in the task sequence set includes: S2331, the preset task processing times b=1, the third task sequence set and the fourth task sequence set are both empty sets; S2332, determining whether the task processing times b is greater than the length of the task sequence set, and obtaining a second determination result; When the second judgment result is no, executing S2333; When the second judgment result is yes, execute S2334; S2333, determining whether the task sequence value corresponding to the bth task sequence in the task sequence set is less than a second threshold, and obtaining a third determination result; When the third judgment result is yes, adding the bth task sequence to the third task sequence set; When the third judgment result is no, adding the bth task sequence to the fourth task sequence set; The task processing times b is increased by 1, and S2332 is executed; S2334, exchanging elements in the task interval [R1, R2] of the task sequences in the third task sequence set to obtain a fifth task sequence set; R1 is a positive integer greater than or equal to 1 and less than or equal to R2; R2 is a positive integer greater than or equal to R1 and less than or equal to N; S2335, transforming the task sequence in the fourth task sequence set to obtain a sixth task sequence set; S2336: Merge the fifth task sequence set and the sixth task sequence set to obtain a first task sequence set.

5. A collaborative planning device for autonomous calibration tasks for large-scale constellations, characterized by: The device comprises: processor; a memory coupled to the processor and storing executable program code; The processor calls the executable program code stored in the memory to execute the collaborative planning method for autonomous calibration tasks for large-scale constellations according to any one of claims 1 to 4.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, which, when called, are used to execute the collaborative planning method for autonomous calibration tasks for large-scale constellations according to any one of claims 1 to 4.

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