Large-scale constellation ultrahigh-precision phase adjustment method, system and device considering camera incoming light avoidance and eccentricity rate control, and storage medium

Abstract

The invention discloses a large constellation ultrahigh-precision phase adjustment method, system and device considering camera incoming light avoidance and eccentricity rate control and a storage medium, belongs to the technical field of constellation phase adjustment, and solves the problem that the prior art lacks a large constellation ultrahigh-precision phase adjustment method considering camera incoming light avoidance and eccentricity rate control. Sorting the plurality of satellites based on the average orbit initial height in the initial orbit information of the plurality of satellites in the large constellation, and taking the satellite with the highest average orbit initial height as a reference satellite; any satellite except the reference satellite in the large constellation is selected, and the orbit control day number and the orbit control circle number of the satellite are obtained respectively; respectively obtaining the optimal orbit control day number and the optimal orbit control circle number of the satellite; selecting the orbit control time within the optimal orbit control circle number of the satellite; and the operation is repeatedly executed until the orbit control time of all satellites in the large constellation is determined, and then phase adjustment of the large constellation is completed.

Description

Technical Field

[0001] The present invention relates to the technical field of constellation phase adjustment, and in particular to a method, system, device and storage medium for ultra-high precision phase adjustment of a large constellation that takes camera light avoidance and eccentricity control into consideration. Background Art

[0002] With the continuous development of the low-orbit satellite market, the number and scale of low-orbit remote sensing satellite constellations are increasing day by day. In the process of constellation construction and networking, the relative phase control accuracy of each satellite is an important indicator of constellation operation and one of the factors for optimizing constellation capabilities. For optical remote sensing satellite constellations, constellation control methods that can quickly, safely and efficiently complete constellation networking tasks are of great significance.

[0003] For the rapid and high-precision networking mission of a large constellation of low-orbit remote sensing satellites, the following three limitations need to be considered. First, the payload camera carried by it must avoid the sun during orbit control to prevent the camera from being irreversibly damaged by light entering the camera. Secondly, the current low-orbit satellite constellation is large in scale, and there are a large number of satellites in an orbit at an altitude of 500km. In order to avoid the risk of collision with each other, the eccentricity of the satellite must be controlled to limit the range of the satellite's perigee height to be as small as possible, thereby avoiding the risk of collision from satellites at other orbital altitudes as much as possible. Finally, for the orbit control accuracy to be controlled under the above two premises, and the orbit control capability is strictly limited by the satellite's propulsion system, and the orbit control mission needs to be completed in multiple times, it is necessary to propose a high-precision orbit control timing search algorithm to obtain the optimal orbit control time for high-precision phase adjustment.

[0004] In the prior art, Chinese patent CN117639896A discloses "a method for fast phase adjustment with small control amount for ultra-large-scale constellations", which solves the problem of the difficulty in quickly obtaining the phase distribution scheme of ultra-large constellations by introducing genetic algorithms, so that this phase adjustment method can be used for phase adjustment within any number of constellations on the same orbital plane, and has extremely wide compatibility. However, this prior art does not consider the task of fast and high-precision networking of large constellations of low-orbit remote sensing satellites, and therefore, it cannot achieve fast and high-precision phase adjustment of large constellations.

[0005] In summary, the prior art lacks an ultra-high precision phase adjustment method for large constellations that takes camera light avoidance and eccentricity control into consideration. Summary of the invention

[0006] The present invention solves the problem that the prior art lacks a large-scale constellation ultra-high precision phase adjustment method that takes into account camera light avoidance and eccentricity control.

[0007] The large-scale constellation ultra-high precision phase adjustment method considering camera light avoidance and eccentricity control of the present invention comprises the following steps:

[0008] Step S1, respectively inputting initial orbit information of multiple satellites in a large constellation;

[0009] Step S2, sorting the multiple satellites based on the average initial orbital heights in the initial orbital information of the multiple satellites in the large constellation, and taking the satellite with the highest average initial orbital height as the reference satellite;

[0010] Step S3, randomly selecting a satellite other than the reference satellite in the large constellation, and obtaining the orbital control days and orbital control circles of the satellite;

[0011] Step S4, after optimizing the orbit control days and orbit control circles of the satellite respectively, the optimal orbit control days and the optimal orbit control circles of the satellite are obtained respectively;

[0012] Step S5, selecting the orbital control time within the optimal orbital control circle number of the satellite based on the optimal orbital control days and the optimal orbital control circle number of the satellite;

[0013] Step S6, repeating the operations of steps S3 to S6, optionally selecting another satellite in the large constellation except the reference satellite, until the orbit control time of all satellites in the large constellation is determined, and the phase adjustment of the large constellation is completed.

[0014] Further, in one embodiment of the present invention, in step S4, the respectively optimizing the orbit control days and orbit control circles of the satellite is specifically:

[0015] Taking the deviation between the phase difference between the satellite and the target when completing orbit control as the optimization target, the orbit control days and orbit control circles of the satellite are optimized respectively.

[0016] Furthermore, in one embodiment of the present invention, the deviation between the satellite and the target phase difference is:

[0017] dlt_w=W_hope i -(W i -W1);

[0018] Among them, dlt_w is the deviation between the satellite and the target phase difference, W_hope is the expected phase, 1 is the reference star, i is the satellite, and W is the initial latitude angle.

[0019] Further, in one embodiment of the present invention, in said step S4, after respectively optimizing the orbital control days and orbital control circles of the satellite, respectively obtaining the optimal orbital control days and the optimal orbital control circles of the satellite comprises the following steps:

[0020] Step S401, inputting the orbital control days and orbital control circles of the satellite, and determining the coding length based on the orbital control days of the satellite, respectively encoding the orbital control days and orbital control circles of the satellite, and recording the encoded orbital control days of the satellite as set A, and recording the encoded orbital control circles of the satellite as set B;

[0021] Step S402, respectively obtaining a population set A and a population set B, and respectively initializing the population set A and the population set B, and respectively obtaining a primary population set A and a primary population set B;

[0022] Step S403, respectively calculating the fitness of all individuals in the set A of the primary population and all individuals in the set B of the primary population, and outputting the fitness results of all individuals in the set A of the primary population and the fitness results of all individuals in the set B of the primary population;

[0023] Step S404, based on the fitness results of all individuals in the set A of the primary population and the fitness results of all individuals in the set B of the primary population, the set A of the primary population and the set B of the primary population are sorted respectively, and the local optimal individual and the global optimal individual in the set A of the primary population, and the local optimal individual and the global optimal individual in the set B of the primary population are selected respectively;

[0024] Step S405, based on the local optimal individual and the global optimal individual in the set A of the primary population, the set A of the primary population is updated, and based on the local optimal individual and the global optimal individual in the set B of the primary population and the global optimal individual in the set B of the primary population, the set B of the primary population is updated;

[0025] Step S406, repeatedly executing the operations of step S3 to step S6 until the set A of the initial population and the set B of the initial population obtain the optimal number of orbital control days and the optimal number of orbital control circles respectively.

[0026] Further, in one embodiment of the present invention, in step S404, the locally optimal individual and the globally optimal individual in the set A of the primary population, and the locally optimal individual and the globally optimal individual in the set B of the primary population are respectively selected, specifically:

[0027] Select a set A of the initial population and output the local optimal individual in the set A of the initial population;

[0028] The locally optimal individual in a set A of the selected initial population is selected as the global optimal individual in a set A of the initial population;

[0029] Compare the global best individual in a set A of the primary population selected subsequently with the global best individual in a set A of the primary population selected last time, and output the global best individual in the set A of the primary population, until all sets A of the primary population are compared, and the update of the global best individual in the set A of the primary population is completed;

[0030] The set B of the initial population adopts the same method as the set A of the initial population to select the local optimal individual and the global optimal individual in the set B of the initial population respectively.

[0031] Further, in one embodiment of the present invention, in step S405, the set A of the primary population is updated based on the local optimal individual and the global optimal individual in the set A of the primary population, and the set B of the primary population is updated based on the local optimal individual and the global optimal individual in the set B of the primary population and the global optimal individual in the set B of the primary population, specifically:

[0032] A i =a i +rand*c1*(a_a i -a i )+rand*c2*(a_p i -a i );

[0033] Among them, c1 and c2 are inertia coefficients, rand is a random number between 0 and 1, and a_p i is the local optimal individual in the set A of the initial population or the local optimal individual in the set B of the initial population, a_a i is the global optimal individual in the set A of the initial population or the global optimal individual in the set B of the initial population, a i is any element in the set A of the initial population or any element in the set B of the initial population, A i It is the updated set A of the initial population or the updated set B of the initial population.

[0034] Further, in one embodiment of the present invention, in the step S5, the orbital control time within the optimal number of orbital control circles of the satellite is selected as follows:

[0035] The satellite is in the earth's shadow, and the difference between the absolute value of the latitude argument and the perigee argument in the earth's shadow is closest to 180°.

[0036] The large-scale constellation ultra-high precision phase adjustment system considering camera light avoidance and eccentricity control described in the present invention includes the following modules:

[0037] Module S1, respectively inputs the initial orbit information of multiple satellites in a large constellation;

[0038] Module S2, sorting multiple satellites based on average orbital initial altitudes in initial orbital information of multiple satellites in a large constellation, and taking the satellite with the highest average orbital initial altitude as a reference satellite;

[0039] Module S3, selects a satellite other than the reference satellite in the large constellation, and obtains the orbital control days and orbital control circles of the satellite;

[0040] Module S4, after optimizing the orbit control days and orbit control circles of the satellite respectively, obtain the optimal orbit control days and optimal orbit control circles of the satellite respectively;

[0041] Module S5, based on the optimal orbit control circle number of the satellite, selecting the orbit control time within the optimal orbit control circle number of the satellite;

[0042] Module S6, repeatedly executes the operations of modules S3 to S6, and optionally selects another satellite in the large constellation except the reference satellite, until the orbit control time of all satellites in the large constellation is determined, and the phase adjustment of the large constellation is completed.

[0043] An electronic device described in the present invention comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0044] Memory, used to store computer programs;

[0045] The processor is used to implement any of the method steps described in the above method when executing the program stored in the memory.

[0046] The computer-readable storage medium described in the present invention stores a computer program, and when the computer program is executed by a processor, the method steps of any of the above methods are implemented.

[0047] The present invention solves the problem that the prior art lacks a large-scale constellation ultra-high precision phase adjustment method that takes into account camera light avoidance and eccentricity control. Specific beneficial effects include:

[0048] 1. The ultra-high precision phase adjustment method for large constellations that takes into account camera light avoidance and eccentricity control described in the present invention. The prior art lacks an ultra-high precision phase adjustment method for large constellations that takes into account camera light avoidance and eccentricity control. To solve the above technical problems, the present invention uses the basic principle of satellite orbit operation and combines an improved optimization search algorithm under the condition of satisfying multiple constraints to provide the best phase adjustment scheme for large constellations, including the specific control time of each satellite and the corresponding orbital control amount. This solves the problem that the prior art lacks an ultra-high precision phase adjustment method for large constellations that takes into account camera light avoidance and eccentricity control;

[0049] 2. The large-scale constellation ultra-high precision phase adjustment method considering camera light avoidance and eccentricity control of the present invention solves the problem of camera light risk during the orbit control process of low-orbit optical remote sensing satellites by limiting the orbit control time to the earth's shadow area to avoid the sun;

[0050] 3. The ultra-high precision phase adjustment method for large constellations taking into account camera light avoidance and eccentricity control of the present invention obtains orbit control time by screening the relationship between the argument of perigee and the argument of latitude corresponding to the shadow area time, thereby reducing the eccentricity, thereby solving the problem of increased collision risk caused by increased eccentricity during the continuous orbit control of low-orbit optical remote sensing satellites with large control amounts;

[0051] The large-scale constellation ultra-high precision phase adjustment method considering camera light avoidance and eccentricity control described in the present invention is applied to the constellation phase adjustment problem, especially the problem of high-precision phase adjustment networking of optical remote sensing satellites considering camera light avoidance, and has significant effect and wide adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0053] Figure 1 It is a flow chart of the ultra-high precision phase adjustment method for a large constellation considering camera light avoidance and eccentricity control as described in Implementation Method 1;

[0054] Figure 2 It is a flow chart of the improved intelligent optimization method for multi-operator fusion described in Implementation Mode 1;

[0055] Figure 3 is a graph showing the phase deviation result changing with the number of iterations during the cycle described in the first embodiment;

[0056] Figure 4 is a semi-major axis variation diagram corresponding to the 10 control processes described in the first embodiment;

[0057] Figure 5 is a diagram showing changes in eccentricity described in the first embodiment;

[0058] Figure 6 This is a phase result diagram at the end of the last orbit control, taking the fourth satellite and the fifth satellite as an example in the first implementation mode;

[0059] Figure 7 is the large constellation input data graph described in Implementation Mode 1;

[0060] Figure 8 This is a partial forecast result diagram described in Implementation Method 1. DETAILED DESCRIPTION

[0061] The following will clearly and completely describe various embodiments of the present invention in conjunction with the accompanying drawings. The embodiments described with reference to the accompanying drawings are exemplary and intended to be used to explain the present invention, but should not be understood as limiting the present invention.

[0062] Implementation method 1: The large-scale constellation ultra-high precision phase adjustment method considering camera light avoidance and eccentricity control described in this implementation method includes the following steps:

[0063] Step S1, respectively inputting initial orbit information of multiple satellites in a large constellation;

[0064] Step S2, sorting the multiple satellites based on the average initial orbital heights in the initial orbital information of the multiple satellites in the large constellation, and taking the satellite with the highest average initial orbital height as the reference satellite;

[0065] Step S3, randomly selecting a satellite other than the reference satellite in the large constellation, and obtaining the orbital control days and orbital control circles of the satellite;

[0066] Step S4, after optimizing the orbit control days and orbit control circles of the satellite respectively, the optimal orbit control days and the optimal orbit control circles of the satellite are obtained respectively;

[0067] Step S5, selecting the orbital control time within the optimal orbital control circle number of the satellite based on the optimal orbital control days and the optimal orbital control circle number of the satellite;

[0068] Step S6, repeating the operations of steps S3 to S6, optionally selecting another satellite in the large constellation except the reference satellite, until the orbit control time of all satellites in the large constellation is determined, and the phase adjustment of the large constellation is completed.

[0069] In this implementation manner, in step S4, the optimization of the orbital control days and orbital control circles of the satellite is specifically as follows:

[0070] Taking the deviation between the phase difference between the satellite and the target when completing orbit control as the optimization target, the orbit control days and orbit control circles of the satellite are optimized respectively.

[0071] In this implementation, the deviation between the satellite and the target phase difference is:

[0072] dlt_w=W_hope i -(W i -W1);

[0073] Among them, dlt_w is the deviation between the satellite and the target phase difference, W_hope is the expected phase, 1 is the reference star, i is the satellite, and W is the initial latitude angle.

[0074] In this embodiment, in step S4, after respectively optimizing the orbital control days and orbital control circles of the satellite, respectively obtaining the optimal orbital control days and optimal orbital control circles of the satellite includes the following steps:

[0075] Step S401, inputting the orbital control days and orbital control circles of the satellite, and determining the coding length based on the orbital control days of the satellite, respectively encoding the orbital control days and orbital control circles of the satellite, and recording the encoded orbital control days of the satellite as set A, and recording the encoded orbital control circles of the satellite as set B;

[0076] Step S402, respectively obtaining a population set A and a population set B, and respectively initializing the population set A and the population set B, and respectively obtaining a primary population set A and a primary population set B;

[0077] Step S403, respectively calculating the fitness of all individuals in the set A of the primary population and all individuals in the set B of the primary population, and outputting the fitness results of all individuals in the set A of the primary population and the fitness results of all individuals in the set B of the primary population;

[0078] Step S404, based on the fitness results of all individuals in the set A of the primary population and the fitness results of all individuals in the set B of the primary population, the set A of the primary population and the set B of the primary population are sorted respectively, and the local optimal individual and the global optimal individual in the set A of the primary population, and the local optimal individual and the global optimal individual in the set B of the primary population are selected respectively;

[0079] Step S405, based on the local optimal individual and the global optimal individual in the set A of the primary population, the set A of the primary population is updated, and based on the local optimal individual and the global optimal individual in the set B of the primary population and the global optimal individual in the set B of the primary population, the set B of the primary population is updated;

[0080] Step S406, repeatedly executing the operations of step S3 to step S6 until the set A of the initial population and the set B of the initial population obtain the optimal number of orbital control days and the optimal number of orbital control circles respectively.

[0081] In this implementation, in step S404, the local optimal individuals and the global optimal individuals in the set A of the primary population, and the local optimal individuals and the global optimal individuals in the set B of the primary population are selected respectively, specifically:

[0082] Select a set A of the initial population and output the local optimal individual in the set A of the initial population;

[0083] The locally optimal individual in a set A of the selected initial population is selected as the global optimal individual in a set A of the initial population;

[0084] Compare the global best individual in a set A of the primary population selected subsequently with the global best individual in a set A of the primary population selected last time, and output the global best individual in the set A of the primary population, until all sets A of the primary population are compared, and the update of the global best individual in the set A of the primary population is completed;

[0085] The set B of the initial population adopts the same method as the set A of the initial population to select the local optimal individual and the global optimal individual in the set B of the initial population respectively.

[0086] In this implementation, in step S405, the set A of the primary population is updated based on the local optimal individual and the global optimal individual in the set A of the primary population, and the set B of the primary population is updated based on the local optimal individual and the global optimal individual in the set B of the primary population and the global optimal individual in the set B of the primary population, specifically as follows:

[0087] A i =a i +rand*c1*(a_a i -a i )+rand*c2*(a_p i -a i );

[0088] Among them, c1 and c2 are inertia coefficients, rand is a random number between 0 and 1, and a_p i is the local optimal individual in the set A of the initial population or the local optimal individual in the set B of the initial population, a_a i is the global optimal individual in the set A of the initial population or the global optimal individual in the set B of the initial population, a iis any element in the set A of the initial population or any element in the set B of the initial population, A i It is the updated set A of the initial population or the updated set B of the initial population.

[0089] In this embodiment, in step S5, the orbital control time within the optimal number of orbital control circles of the satellite is selected as follows:

[0090] The satellite is in the earth's shadow, and the difference between the absolute value of the latitude argument and the perigee argument in the earth's shadow is closest to 180°.

[0091] In the prior art, there is a lack of ultra-high precision phase adjustment methods for large constellations that take camera light avoidance and eccentricity control into consideration.

[0092] To solve the above technical problems, Figure 1 As shown, this embodiment designs a large constellation ultra-high precision phase adjustment method considering camera light avoidance and eccentricity control, including the following steps:

[0093] Step S1, input the initial orbit information of the large constellation S, the initial orbit information includes the initial average orbit semi-major axis length H of multiple satellites, the initial latitude argument W, the expected phase W_hope, the propulsion system capabilities of multiple satellites, that is, the maximum distance L of single control, the maximum number of controls per day N, and the expected maximum time T to complete the orbit control task.

[0094] Step S2, sorting the multiple satellites according to their average initial orbital height H', and selecting the satellite with the highest height as the reference star S1, that is, decomposing the phase adjustment problem of multiple satellites in the entire large constellation into the relative phase adjustment problem of multiple satellites to the reference star.

[0095] Step S3, select a satellite S other than the reference satellite in the large constellation i , calculate the satellite's current orbit height deviation dlt_h to be adjusted, and the deviation dlt_w between the satellite and the target phase difference, that is:

[0096] dlt_h=H1-H i ;

[0097] dlt_w=W_hope i -(W i -W1);

[0098] Among them, 1 is the reference star and i is the satellite.

[0099] Then the minimum orbital control number of the satellite is dlt_h / L, and the minimum orbital control days is dlt_h / L / N.

[0100] Step S4, using the satellite days and orbit control circles as optimization variables, and the deviation dlt_w between the satellite and the target phase difference when orbit control is completed as the optimization target, an improved intelligent optimization method of multi-operator fusion is used to search for the optimal days and optimal circles of orbit control in the shadow area. Figure 2 As shown, the following steps are included:

[0101] Step S401, coding: set variable set A = [a1...a i ] is the set of orbital control days of the star starting from the epoch time, and the set B = [b1...b i ] is the number of circles corresponding to the first circle of the corresponding day, and the length of the set is the number of control days. The two sets A and B are obtained by decimal coding. The control performed within a day should be performed in consecutive circles, so only the number of the first circle of the day is determined to obtain all the orbit control circles of the day. The first circle of the i-th day corresponds to the circle number of the current epoch time order i =a i *15+b i +1 (for orbits around 500 kilometers, approximately 15 orbits a day).

[0102] Step S402, initialization: set a certain population set A and set B, randomly initialize set A and set B, and obtain set A of the primary population and set B of the primary population.

[0103] Step S403, fitness calculation: the fitness function is set to dlt_w = W_hope i -(W i -W1). At this time W i -W1 is the phase difference between the two satellites at the end of each orbit control, recorded as theta_final. l =theta0+(v i -v1)*dlt_t

[0104] Theta0 is the initial phase deviation, which is obtained by taking the difference between the two initial phases input. In subsequent orbit control, theta0 is the previous theta_final, v i and v1 are the drift angular velocities of the current star and the reference star respectively, and dlt_t is the drift time.

[0105] The orbital angular velocity v is calculated as:

[0106]

[0107] Among them, u is the earth constant, which is 3.986004418*10^14, H iis the length of the semi-major axis of the current star.

[0108] dlt_t=(order i -order i-1 )*2п / v;

[0109] Theta_final can be solved. The fitness of all individuals in the set A of the initial population and all individuals in the set B of the initial population is calculated, and the fitness results of all individuals in the set A of the initial population and the fitness results of all individuals in the set B of the initial population are output.

[0110] Step S404, fitness sorting and screening: based on the fitness results of all individuals in the set A of the primary population and the fitness results of all individuals in the set B of the primary population, sort the set A of the primary population and the set B of the primary population respectively. Taking the set A of the primary population as an example, a set A of the primary population is randomly selected in a roulette wheel manner, and the local optimal individual in the set A of the primary population is output. The local optimal individual in the set A of the primary population randomly selected in the roulette wheel manner is used as the global optimal individual in the set A of the primary population. The global optimal individual in the set A of the primary population selected subsequently is compared with the global optimal individual in the set A of the primary population selected last time, and the global optimal individual in the set A of the primary population is output, until all the sets A of the primary population are compared, and the update of the global optimal individual in the set A of the primary population is completed;

[0111] The set B of the initial population adopts the same method as the set A of the initial population to select the local optimal individual and the global optimal individual in the set B of the initial population respectively.

[0112] Step S405, new population generation: firstly, the optimization operator in the particle swarm algorithm is used to find the local optimal individual and the global optimal individual in the set A of the primary population, and the local optimal individual and the global optimal individual in the set B of the primary population and the global optimal individual in the set B of the primary population, and the local optimal individual and the global optimal individual in the set B of the primary population for the current population. That is, for any element a in the set A of the primary population and the set B of the primary population, i , assuming that the corresponding local optimal individual a_p i , the global optimal individual a_a i Then the new population a i Updated to:

[0113] a i =a i +rand*c1*(a_a i -a i )+rand*c2*(a_p i-a i )

[0114] Among them, c1 and c2 are inertia coefficients, which are 0.2, and rand is a random number between 0 and 1.

[0115] After traversing the set A of the first generation population and the set B of the first generation population to obtain the new population, in order to enhance the global search capability, the mutation operator is introduced to set the mutation probability to 0.4. Once triggered, a i =a i +(rand-0.5)*c3*a i , continue to traverse the population to get the latest population.

[0116] Step S406, iteration: Repeat the operations of steps S3 to S6, and continue to iterate and search until the initial population set A and the initial population set B obtain the optimal orbital control days and the optimal orbital control circles respectively. Decode according to the encoding method in step S401, and output the optimal orbital control circle number of the satellite.

[0117] Step S5, for the optimal orbital control days and optimal orbital control circles of the satellite output in step S4, orbital control time selection is performed within the orbital control circle number, and the selection criteria include two parts:

[0118] Selection criterion 1: The satellite must be in the earth's shadow at the orbital control moment, that is, the current solar vector is blocked by the earth.

[0119] Selection criterion 2: The difference between the absolute value of the latitude argument and the perigee argument in the shadow area is closest to 180°.

[0120] Traverse each control circle time output in the previous step, and combine the two selection criteria to complete the determination of the entire orbital control time of the satellite.

[0121] Step S6, repeating the operations of steps S3 to S6 until the orbit control times of all remaining satellites in the large constellation are determined and completed, and then the phase adjustment of the large constellation is completed.

[0122] Therefore, in view of the requirements of the prior art, the present embodiment considers the design of the ultra-high precision phase adjustment method for large constellations in consideration of camera light avoidance and eccentricity control as follows:

[0123] (1) Camera light avoidance strategy

[0124] The orbit raising and lowering operations performed during the orbit control process require the satellite's body coordinate system to be maneuvered to the orbit control attitude, that is, the direction of the satellite's propulsion device must be along the specific direction of the orbit coordinate system. This attitude is different from the conventional solar attitude. Therefore, when the camera is installed to a specific position, there will be a risk of light entering. In order to completely avoid the risk of light entering, all orbit control opportunities are selected to be carried out in the earth's shadow area, completely avoiding sunlight and completely avoiding the risk of light entering the camera.

[0125] (2) Eccentricity control strategy

[0126] Continuous orbit control with large control amounts near the same orbit point will cause the satellite's eccentricity to increase significantly. Orbit control is all carried out in the shadow area, resulting in a relatively concentrated orbit control time. To solve this problem, a method for searching for orbit control opportunities in the shadow area is used for orbit control. For the determined orbit control loops and orbit control shadow area time, the relationship between the satellite's latitude argument and the true anomaly angle at all times in the shadow area is searched to find the extreme position of the apogee in the shadow area, which is used as the orbit control opportunity.

[0127] (3) High-precision phase adjustment orbit control timing search algorithm

[0128] In addition to the above two restrictions, the optimal search for orbit control timing also needs to consider the single control amount of the propulsion system and complete orbit control in the fewest possible days. Therefore, in the search process, the number of days and orbits are used as search variables, the final phase adjustment accuracy is used as the optimization target, and an intelligent optimization method with multiple operator fusion is used to search for the best orbit control timing. According to the orbit control days and orbit control circles obtained by the search, combined with the shadow area constraints and eccentricity control constraints, the final orbit control time is determined.

[0129] Therefore, the ultra-high precision phase adjustment method for a large constellation taking into account camera light avoidance and eccentricity control described in this embodiment realizes efficient ultra-high precision phase adjustment of a large constellation under multiple constraints, and provides a new solution for fast, efficient and secure networking of large constellations.

[0130] In order to better illustrate the large-scale constellation ultra-high precision phase adjustment method considering camera light avoidance and eccentricity control described in this embodiment, the following examples are described in detail:

[0131] Step S1, such as Figure 7 The input data of a large constellation is shown. The large constellation adjusts the target 6 satellites, which are evenly distributed in the same orbital plane. The input file contains the length of the semi-major axis, latitude argument and the corresponding epoch time of the 6 satellites. The 6 satellites of this large constellation are of the same model and batch, with the same orbit control capability constraints. The maximum single orbit control can be one kilometer, and the maximum number of continuous control is three times.

[0132] Step S2, sorting by the length of the semi-major axis, selecting the 4th satellite as the reference satellite, and simplifying the phase adjustment problem of the large constellation into five relative phase adjustments of the 1st, 2nd, 3rd, 5th and 6th satellites relative to the 4th satellite. Here, the phase adjustment process of the 5th satellite relative to the 4th satellite is taken as an example to introduce the whole process of high-precision phase adjustment in detail.

[0133] Step S3, take 12:20 on October 8, 2024 as the epoch starting point. At this moment, the initial latitude argument set W of the 4th and 5th satellites is [274.718, 74.564], the initial orbit semi-major axis length set H is [6915.71, 6906.2], and the expected phase difference of the 5th satellite is 300°. Therefore, dlt_w = 74.564-274.718 = -200.154°, dlt_H = 6915.71-6906.2 = 9.51km. Therefore, at least 10 controls should be performed in at least 4 days.

[0134] Step S4, starting to search for control opportunities, includes the following steps:

[0135] Step S401, since it is carried out in 4 days, the length of set A and set B are both 4, the elements are integers, the elements in set A are less than 21, and the elements in set B are less than 16. For example, A = [1, 2, 3, 4], B = [1, 2, 3, 4].

[0136] Step S402, using decimal coding to initialize the 100*4 set A and set.

[0137] Step S403, calculate the initial population, assuming A = [1, 2, 3, 4], B = [1, 2, 3, 4]. Then according to the solution formula, the control loop number is [17, 18, 19, 33, 34, 35, 49, 50, 51, 64]. Theta_final is calculated in 10 iterations. The initial theta0 = dlt_w = -200.154° (positive) = 159.846°.

[0138] According to the v calculation formula, the orbital angular velocities of the 4th and 5th satellites are calculated respectively:

[0139] v4=0.001097775989358° / s; v5=0.001100076520566° / s.

[0140] The first orbit control circle is 17, so order = 17 in the formula. i-1 = 0. According to the dlt_t calculation formula, dlt_t = 98048.95001099912s.

[0141] Theta_final = 172.770855° at the end of the first orbit control.

[0142] Let theta0 = theta_final. Repeat the above calculation process ten times to get theta_final = 187.6268° after the last orbital control of the current solution. The phase deviation, i.e., the fitness, is 300-187.6268 = 11.23732°. The fitness of the first individual in the first generation population is 11.23732°. Traverse the entire population and calculate the population fitness.

[0143] Step S404, sort the individual fitness obtained in the previous step, find the individual with the smallest fitness, update it to the local optimum, compare it with the historical optimum, determine whether to update, and directly update the first generation.

[0144] Step S405: Assume that the best individuals are still set A and set B. Calculate a for each element in the set according to the formula i =a i +rand*c1*(a_a i -a i )+rand*c2*(a_p i -a i ). Randomly generate a number greater than the predetermined mutation probability 0.4, then output a i , otherwise a i =a i +(rand-0.5)*c3*a i , continue to update a i . Until all individuals are updated, the new population is output.

[0145] Step S406: Return to step S403 to perform fitness calculation and iterate continuously. After one hundred generations, output the current optimal individual and fitness value.

[0146] A=[12,13,15,9]; B=[5,12,15,11];

[0147] The phase deviation results change with the number of iterations during the cycle as follows: Figure 3 As shown. Convergence is completed within 50 generations, and the phase deviation is less than 10 -4 .

[0148] Step S5, select the specific orbit control time according to the two standards. According to the initial orbit data of the satellite, the HPOP prediction model is used. The satellite mass is 235kg, the surface mass ratio is 0.0194, and the gravity field order is 20*20. The shadow area corresponding to the orbit control circle in step S4 is predicted. The perigee argument and latitude argument of each prediction point in the shadow area are collected at intervals of 60s, that is, the moment farthest from the perigee. Some prediction results are as follows: Figure 8 As shown, the specific control time of the five stars is (Beijing time):

[0149] ['2024-10-18 05:14:39"2024-10-18 06:49:57"2024-10-18 08:25:15'

[0150] '2024-10-20 19:10:58"2024-10-20 20:46:15"2024-10-20 22:21:32'

[0151] '2024-10-22 06:07:12' 2024-10-22 07:42:29' 2024-10-22 09:17:46'

[0152] '2024-10-24 08:56:05']

[0153] The corresponding semi-major axis changes during the 10 control processes are as follows: Figure 4 The corresponding eccentricity changes are shown in Figure 5 After 10 orbital controls, the eccentricity did not increase and each orbital control significantly reduced the eccentricity.

[0154] Step S6, return to step S3 and repeat the calculation for the other four stars in the same way. After the iteration is completed, all phase adjustment work is completed.

[0155] Taking the 4th satellite and the 5th satellite as an example (Satellite 1 is 4 stars and Satellite 2 is 5 stars), the phase results at the end of the last orbit control are as follows: Figure 6 As shown, the actual phase difference is 300.038°, which is 0.038° away from the expected phase difference of 300°, and the control accuracy is better than 0.05°.

[0156] In summary, the ultra-high precision phase adjustment method for a large constellation considering camera light avoidance and eccentricity control described in this embodiment has high phase adjustment precision, which can ensure that the satellite can efficiently and safely complete the orbit raising phase adjustment task at a very small time cost. Not limited to this, the phase adjustment of a larger satellite constellation with higher precision can also quickly complete the phase adjustment task according to the method described in this embodiment.

[0157] Implementation method 2: The large-scale constellation ultra-high precision phase adjustment system considering camera light avoidance and eccentricity control described in this implementation method includes the following modules:

[0158] Module S1, respectively inputs the initial orbit information of multiple satellites in a large constellation;

[0159] Module S2, sorting multiple satellites based on average orbital initial altitudes in initial orbital information of multiple satellites in a large constellation, and taking the satellite with the highest average orbital initial altitude as a reference satellite;

[0160] Module S3, selects a satellite other than the reference satellite in the large constellation, and obtains the orbital control days and orbital control circles of the satellite;

[0161] Module S4, after optimizing the orbit control days and orbit control circles of the satellite respectively, obtain the optimal orbit control days and optimal orbit control circles of the satellite respectively;

[0162] Module S5, based on the optimal orbit control circle number of the satellite, selecting the orbit control time within the optimal orbit control circle number of the satellite;

[0163] Module S6, repeatedly executes the operations of modules S3 to S6, and optionally selects another satellite in the large constellation except the reference satellite, until the orbit control time of all satellites in the large constellation is determined, and the phase adjustment of the large constellation is completed.

[0164] Embodiment 3: An electronic device described in this embodiment includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus;

[0165] Memory, used to store computer programs;

[0166] The processor is used to implement the method steps described in the first embodiment when executing the program stored in the memory.

[0167] Embodiment 4: A computer-readable storage medium described in this embodiment stores a computer program, and when the computer program is executed by a processor, the method steps described in embodiment 1 are implemented.

[0168] The above is a detailed introduction to the ultra-high precision phase adjustment method, system, device and storage medium for a large constellation that considers camera light avoidance and eccentricity control proposed in the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A large-scale constellation ultra-high precision phase adjustment method considering camera light avoidance and eccentricity control, characterized in that: The following steps are involved: Step S1, respectively inputting initial orbit information of multiple satellites in a large constellation; Step S2, sorting the multiple satellites based on the average initial orbital heights in the initial orbital information of the multiple satellites in the large constellation, and taking the satellite with the highest average initial orbital height as the reference satellite; Step S3, randomly selecting a satellite other than the reference satellite in the large constellation, and obtaining the orbital control days and orbital control circles of the satellite; Step S4, after optimizing the orbit control days and orbit control circles of the satellite respectively, the optimal orbit control days and the optimal orbit control circles of the satellite are obtained respectively; Step S5, selecting the orbital control time within the optimal orbital control circle number of the satellite based on the optimal orbital control days and the optimal orbital control circle number of the satellite; Step S6, repeating the operations of steps S3 to S6, optionally selecting another satellite in the large constellation except the reference satellite, until the orbit control time of all satellites in the large constellation is determined, and the phase adjustment of the large constellation is completed.

2. The large-scale constellation ultra-high precision phase adjustment method considering camera light avoidance and eccentricity control according to claim 1, characterized in that: In step S4, the respectively optimizing of the orbit control days and orbit control circles of the satellite is specifically: Taking the deviation between the phase difference between the satellite and the target when completing orbit control as the optimization target, the orbit control days and orbit control circles of the satellite are optimized respectively.

3. The large-scale constellation ultra-high precision phase adjustment method considering camera light avoidance and eccentricity control according to claim 2, characterized in that: The deviation between the satellite and the target phase difference is: dlt_w=W_hope i -(W i -W1); Among them, dlt_w is the deviation between the satellite and the target phase difference, W_hope is the expected phase, 1 is the reference star, i is the satellite, and W is the initial latitude angle.

4. The large-scale constellation ultra-high precision phase adjustment method considering camera light avoidance and eccentricity control according to claim 1, characterized in that: In step S4, after respectively optimizing the orbital control days and orbital control circles of the satellite, obtaining the optimal orbital control days and the optimal orbital control circles of the satellite respectively comprises the following steps: Step S401, inputting the orbital control days and orbital control circles of the satellite, and determining the coding length based on the orbital control days of the satellite, respectively encoding the orbital control days and orbital control circles of the satellite, and recording the encoded orbital control days of the satellite as set A, and recording the encoded orbital control circles of the satellite as set B; Step S402, respectively obtaining a population set A and a population set B, and respectively initializing the population set A and the population set B, and respectively obtaining a primary population set A and a primary population set B; Step S403, respectively calculating the fitness of all individuals in the set A of the primary population and all individuals in the set B of the primary population, and outputting the fitness results of all individuals in the set A of the primary population and the fitness results of all individuals in the set B of the primary population; Step S404, based on the fitness results of all individuals in the set A of the primary population and the fitness results of all individuals in the set B of the primary population, the set A of the primary population and the set B of the primary population are sorted respectively, and the local optimal individual and the global optimal individual in the set A of the primary population, and the local optimal individual and the global optimal individual in the set B of the primary population are selected respectively; Step S405, based on the local optimal individual and the global optimal individual in the set A of the primary population, the set A of the primary population is updated, and based on the local optimal individual and the global optimal individual in the set B of the primary population and the global optimal individual in the set B of the primary population, the set B of the primary population is updated; Step S406, repeatedly executing the operations of step S3 to step S6 until the set A of the initial population and the set B of the initial population obtain the optimal number of orbital control days and the optimal number of orbital control circles respectively.

5. The large-scale constellation ultra-high precision phase adjustment method considering camera light avoidance and eccentricity control according to claim 4 is characterized in that: In step S404, the locally optimal individual and the globally optimal individual in the set A of the primary population, and the locally optimal individual and the globally optimal individual in the set B of the primary population are respectively selected as follows: Select a set A of the initial population and output the local optimal individual in the set A of the initial population; The locally optimal individual in a set A of the selected initial population is selected as the global optimal individual in a set A of the initial population; Compare the global best individual in a set A of the primary population selected subsequently with the global best individual in a set A of the primary population selected last time, and output the global best individual in the set A of the primary population, until all sets A of the primary population are compared, and the update of the global best individual in the set A of the primary population is completed; The set B of the initial population adopts the same method as the set A of the initial population to select the local optimal individual and the global optimal individual in the set B of the initial population respectively.

6. The large-scale constellation ultra-high precision phase adjustment method considering camera light avoidance and eccentricity control according to claim 4, characterized in that: In the step S405, the set A of the primary population is updated based on the local optimal individual and the global optimal individual in the set A of the primary population, and the set B of the primary population is updated based on the local optimal individual and the global optimal individual in the set B of the primary population and the global optimal individual in the set B of the primary population, specifically as follows: A i =a i +rand*c1*(a_a i -a i )+rand*c2*(a_p i -a i ); Among them, c1 and c2 are inertia coefficients, rand is a random number between 0 and 1, and a_p i is the local optimal individual in the set A of the initial population or the local optimal individual in the set B of the initial population, a_a i is the global optimal individual in the set A of the initial population or the global optimal individual in the set B of the initial population, a i is any element in the set A of the initial population or any element in the set B of the initial population, A i It is the updated set A of the initial population or the updated set B of the initial population.

7. The large-scale constellation ultra-high precision phase adjustment method considering camera light avoidance and eccentricity control according to claim 1, characterized in that: In step S5, the optimal orbit control time within the number of orbit control circles of the satellite is selected as follows: The satellite is in the earth's shadow, and the difference between the absolute value of the latitude argument and the perigee argument in the earth's shadow is closest to 180°.

8. A large-scale constellation ultra-high precision phase adjustment system considering camera light avoidance and eccentricity control, characterized by: Includes the following modules: Module S1, respectively inputs the initial orbit information of multiple satellites in a large constellation; Module S2, sorting multiple satellites based on average orbital initial altitudes in initial orbital information of multiple satellites in a large constellation, and taking the satellite with the highest average orbital initial altitude as a reference satellite; Module S3, selects a satellite other than the reference satellite in the large constellation, and obtains the orbital control days and orbital control circles of the satellite; Module S4, after optimizing the orbit control days and orbit control circles of the satellite respectively, obtain the optimal orbit control days and optimal orbit control circles of the satellite respectively; Module S5, based on the optimal orbit control circle number of the satellite, selecting the orbit control time within the optimal orbit control circle number of the satellite; Module S6, repeatedly executes the operations of modules S3 to S6, and optionally selects another satellite in the large constellation except the reference satellite, until the orbit control time of all satellites in the large constellation is determined, and the phase adjustment of the large constellation is completed.

9. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, for implementing the method steps described in any one of claims 1 to 7 when executing a program stored in a memory.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method steps described in any one of claims 1 to 7 are implemented.

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