Constellation configuration acquisition method and device, electronic equipment and storage medium

Abstract

The invention provides a constellation configuration obtaining method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the value range of each to-be-optimized parameter of a constellation; based on the value range of each to-be-optimized parameter, generating a search space; searching a target value of each to-be-optimized parameter in a search space by taking the minimum total number of satellites of the constellation as an optimization target and taking the constellation to realize one-time coverage as a constraint condition; and obtaining the constellation configuration of the constellation based on the target value of each to-be-optimized parameter. Therefore, the target values of the multiple to-be-optimized parameters of the constellation can be jointly acquired by utilizing the search space, and compared with the prior art that the target value of each to-be-optimized parameter is independently solved and the steps are tedious, the scheme is simple and easy to implement and relatively high in implementability, the minimum total number of satellites of the constellation is taken as the optimization target, and the optimization efficiency is improved. The total number of satellites of the constellation is reduced, and the cost of the constellation is

Description

Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a method, device, electronic device and storage medium for acquiring a constellation configuration. Background Art

[0002] At present, the design of constellation configuration is crucial to the cost and coverage performance of the constellation. However, in the related technologies, most of the multiple parameter values ​​of the constellation are solved separately, which is cumbersome and has low feasibility. In addition, the constellation configuration obtained in the related technologies has the problems of high constellation cost and poor coverage performance. Summary of the invention

[0003] The present disclosure aims to solve one of the technical problems in the related art at least to some extent.

[0004] The first aspect of the present disclosure proposes a method for obtaining a constellation configuration, including: obtaining a value range of each parameter to be optimized of the constellation; generating a search space based on the value range of each parameter to be optimized; taking the minimum total number of satellites of the constellation as an optimization goal and taking the realization of single coverage of the constellation as a constraint condition, searching for a target value of each parameter to be optimized in the search space; and obtaining the constellation configuration of the constellation based on the target value of each parameter to be optimized.

[0005] According to the method for obtaining the constellation configuration of the embodiment of the present disclosure, the value range of each parameter to be optimized of the constellation is obtained, and based on the value range of each parameter to be optimized, a search space is generated, with the minimum total number of satellites in the constellation as the optimization goal, and with the constellation achieving single-layer coverage as the constraint condition, the target value of each parameter to be optimized is searched in the search space, and the constellation configuration of the constellation is obtained based on the target value of each parameter to be optimized. Therefore, in this method, the search space can be used to jointly obtain the target values ​​of multiple parameters to be optimized of the constellation. Compared with the related art in which the target value of each parameter to be optimized is solved separately, the steps are cumbersome. This solution is simple and easy to implement, with high feasibility, and with the minimum total number of satellites in the constellation as the optimization goal, and with the constellation achieving single-layer coverage as the constraint condition, it helps to reduce the total number of satellites in the constellation, thereby reducing the cost of the constellation, and improving the coverage performance of the constellation.

[0006] The second aspect embodiment of the present disclosure proposes a constellation configuration acquisition device, including: a first acquisition module, used to acquire the value range of each parameter to be optimized of the constellation; a generation module, used to generate a search space based on the value range of each parameter to be optimized; a search module, used to search for the target value of each parameter to be optimized in the search space with the minimum total number of satellites of the constellation as the optimization goal and the realization of single coverage of the constellation as the constraint condition; a second acquisition module, used to obtain the constellation configuration of the constellation based on the target value of each parameter to be optimized.

[0007] An embodiment of the third aspect of the present disclosure proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for acquiring the constellation configuration as described in the embodiment of the first aspect of the present disclosure is implemented.

[0008] The fourth aspect embodiment of the present disclosure proposes a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for obtaining the constellation configuration as described in the first aspect embodiment of the present disclosure is implemented.

[0009] The fifth aspect embodiment of the present disclosure proposes a computer program product. When the instruction processor in the computer program product executes, it implements the method for acquiring the constellation configuration as described in the first aspect embodiment of the present disclosure.

[0010] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description or learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above and / or additional aspects and advantages of the present disclosure will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0012] Figure 1 A schematic diagram of a flow chart of a method for acquiring a constellation configuration provided by an embodiment of the present disclosure;

[0013] Figure 2 A schematic diagram of satellite coverage provided by an embodiment of the present disclosure;

[0014] Figure 3 A schematic diagram of track surface connection provided by an embodiment of the present disclosure;

[0015] Figure 4 A schematic diagram of a process of searching for a target value in a search space in a method for acquiring a constellation configuration provided by an embodiment of the present disclosure;

[0016] Figure 5A schematic diagram of a flow chart of obtaining a target value in a method for obtaining a constellation configuration provided in an embodiment of the present disclosure;

[0017] Figure 6 A schematic diagram of a flow chart of another method for acquiring a constellation configuration provided by an embodiment of the present disclosure;

[0018] Figure 7 A schematic diagram of the structure of a constellation configuration acquisition device provided by an embodiment of the present disclosure;

[0019] Figure 8 The invention is a block diagram of an electronic device for a method for acquiring a constellation configuration according to an exemplary embodiment. DETAILED DESCRIPTION

[0020] Embodiments of the present disclosure are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0021] The following describes a constellation configuration acquisition method, device, electronic device, and storage medium according to an embodiment of the present disclosure with reference to the accompanying drawings.

[0022] Figure 1 A flowchart of a method for acquiring a constellation configuration provided in an embodiment of the present disclosure is provided.

[0023] like Figure 1 As shown, the method for obtaining the constellation configuration may include the following steps:

[0024] S101, obtaining a value range of each parameter to be optimized of a constellation.

[0025] It should be noted that there are no excessive restrictions on the constellation, for example, the constellation may include a low-orbit constellation. In one embodiment, the constellation may include a near-polar orbit star constellation.

[0026] It should be noted that there are not too many restrictions on the parameters to be optimized. For example, the parameters to be optimized include at least one of the number of satellites in the orbital plane, the number of orbital planes, the orbital inclination, the orbital altitude, the right ascension difference of the ascending node, and the phase difference between adjacent orbital planes.

[0027] The phase difference between adjacent orbital planes may include the phase difference between satellites with the same number on adjacent orbital planes. For example, orbital planes A and B are adjacent, and both orbital planes A and B include satellites numbered 1 to 6. The phase difference between orbital planes A and B includes the phase difference between the satellite numbered j on orbital plane A and the satellite numbered j on orbital plane B, where j is a positive integer not greater than 6.

[0028] It should be noted that there is no excessive limitation on the number of parameters to be optimized. For example, the number of parameters to be optimized may be 6.

[0029] S102: Generate a search space based on the value range of each parameter to be optimized.

[0030] It should be noted that the value range of the parameter to be optimized is not too limited. Different parameters to be optimized may correspond to different value ranges.

[0031] For example, the value range of each parameter to be optimized of the constellation is shown in Table 1.

[0032] Table 1 Value range of each parameter to be optimized for the constellation

[0033]

[0034] In one implementation, the value range of the parameter to be optimized is preset. For example, the value range of the parameter to be optimized may be calibrated to obtain a calibrated value range of the parameter to be optimized.

[0035] In one embodiment, based on the value range of each parameter to be optimized, a search space is generated, including determining the i-th parameter to be optimized as the i-th dimension of the search space, and determining the value range of the i-th parameter to be optimized as the value range of the i-th dimension of the search space. Wherein, i is a positive integer not greater than the number of parameters to be optimized. It can be understood that the parameters to be optimized correspond to the dimensions of the search space one by one, that is, the number of dimensions of the search space is equal to the number of parameters to be optimized, and the i-th dimension of the search space is used to characterize the i-th parameter to be optimized.

[0036] For example, continuing with Table 1, the number of satellites S in the orbital plane can be determined as the first dimension of the search space, the number of orbital planes P can be determined as the second dimension of the search space, the orbital inclination i can be determined as the third dimension of the search space, the orbital altitude h can be determined as the fourth dimension of the search space, the ascending node right ascension difference ΔΩ can be determined as the fifth dimension of the search space, and the phase difference Δu between adjacent orbital planes can be determined as the sixth dimension of the search space.

[0037] The value range of the number of satellites S in the orbital plane is 1 to 20, which is determined as the value range of the first dimension of the search space. The value range of the number of orbital planes P is 1 to 20, which is determined as the value range of the second dimension of the search space. The value range of the orbital inclination i is 85° to 95°, which is determined as the value range of the third dimension of the search space. The value range of the orbital altitude h is 1000km to 1100km, which is determined as the value range of the fourth dimension of the search space. The value range of the right ascension difference ΔΩ of the ascending node is 0° to (190 / P)°, which is determined as the value range of the fifth dimension of the search space. The value range of the phase difference Δu between adjacent orbital planes is 0° to (360 / S)°, which is determined as the value range of the sixth dimension of the search space.

[0038] S103, taking the minimum total number of satellites in the constellation as the optimization goal and taking the constellation achieving single-layer coverage as the constraint condition, searching for a target value of each parameter to be optimized in the search space.

[0039] It should be noted that the optimization goal is used to evaluate the value of each parameter to be optimized, also called the objective function, and the constraint condition is used to constrain the value of each parameter to be optimized, also called the constraint function or design constraint. Both the objective function and the constraint condition are functions of the value of the parameter to be optimized.

[0040] For example, the optimization goal is to minimize the total number of satellites in the constellation, including constructing an objective function with the value of the parameter to be optimized as the independent variable and the total number of satellites in the constellation as the dependent variable, and solving for the minimum value of the objective function.

[0041] For example, taking the constellation achieving single-layer coverage as a constraint condition, including taking the value of the parameter to be optimized as an independent variable and taking the coverage multiplicity of the constellation as a dependent variable to construct a constraint function, and the value of the constraint function is greater than or equal to 1.

[0042] It should be noted that the total number of satellites in the constellation is the minimum under the target value of each parameter to be optimized, and the constellation achieves single coverage. It should be noted that the coverage multiplicity refers to the number of satellites in the constellation that are simultaneously visible to the observation area (such as a hot spot area) at the observation time, and is also the number of satellites in the observation area covered by satellites in the constellation at the observation time. The coverage multiplicity can include single coverage and multiple coverage (such as double coverage).

[0043] It should be noted that the optimization goal is to minimize the total number of satellites in the constellation, and the constellation is constrained to achieve single-layer coverage. The target value of each parameter to be optimized in the search space can be searched by any parameter optimization method in the relevant technology, and no excessive restrictions are made here. For example, a particle swarm algorithm can be used to achieve this.

[0044] It should be noted that the constellation achieving single-layer coverage means that the constellation achieves single-layer coverage of the ground area, and the constraint conditions for the constellation to achieve single-layer coverage can be achieved by using the conditions for any constellation to achieve single-layer coverage in the relevant technology, and no excessive restrictions are made here.

[0045] In one embodiment, the method further includes obtaining a threshold based on the orbital inclination of the constellation and the coverage bandwidth of the constellation to achieve single-layer coverage, and determining a constraint condition based on the number of orbital planes of the constellation, the maximum angular separation between adjacent orbital planes in the same direction of the constellation, and the threshold, so as to obtain the constraint condition for the constellation to achieve single-layer coverage.

[0046] In some cases, the orbital inclination i is lower than i min =π / 2-C1 constellation cannot achieve single-layer coverage in the polar regions. In order to achieve single-layer coverage in each orbital plane (i.e., the 1st to Pth orbital planes), the threshold The calculation process is as follows:

[0047]

[0048] Wherein, i is the orbit inclination, and C1 is the coverage bandwidth of the constellation to achieve single-layer coverage.

[0049] For example, the satellite coverage diagram is as follows Figure 2 As shown, taking the constellation as a near-polar orbit star constellation as an example, the calculation process of the satellite coverage angle θ is as follows:

[0050]

[0051] Among them, R e is the radius of the earth, α is the minimum altitude angle, and h is the orbital altitude.

[0052] like Figure 2 As shown, the angle between the straight line between the satellite and the Earth's North Pole and the Earth's North Pole horizon is 10°.

[0053] Schematic diagram of track surface connection Figure 3 As shown, the calculation process of the coverage bandwidth C1 of the constellation to achieve single-layer coverage is as follows:

[0054]

[0055] Where S is the number of satellites in the orbital plane.

[0056] The calculation process of the maximum angular separation Δλ1 between adjacent orbital planes in the same direction of the constellation is as follows:

[0057]

[0058] In some examples, based on the number of orbital planes of the constellation, the maximum angular separation between adjacent orbital planes in the same direction of the constellation, and a threshold, a constraint condition is determined, including obtaining the difference between the number of orbital planes and 1, and determining the product between the difference and the maximum angular separation to be greater than or equal to the threshold as the constraint condition.

[0059] For example, the constraints for a constellation to achieve single-layer coverage are as follows:

[0060]

[0061] Where P is the number of orbital planes.

[0062] like Figure 3 As shown, C2 is half of the coverage bandwidth of the constellation to achieve double coverage.

[0063] S104: Obtain a constellation configuration of the constellation based on a target value of each parameter to be optimized.

[0064] In one implementation, obtaining a constellation configuration of a constellation based on a target value of each parameter to be optimized includes combining the target value of each parameter to be optimized to obtain the constellation configuration of the constellation.

[0065] In one embodiment, a constellation configuration of a constellation is obtained based on a target value of each parameter to be optimized, including obtaining target values ​​of remaining parameters of the constellation except the parameter to be optimized, and obtaining the constellation configuration of the constellation based on the target value of each parameter to be optimized and the target values ​​of the remaining parameters.

[0066] In summary, according to the method for obtaining the constellation configuration of the embodiment of the present disclosure, the value range of each parameter to be optimized of the constellation is obtained, and based on the value range of each parameter to be optimized, a search space is generated, with the minimum total number of satellites in the constellation as the optimization goal, and with the constellation achieving single-layer coverage as the constraint condition, the target value of each parameter to be optimized is searched in the search space, and the constellation configuration of the constellation is obtained based on the target value of each parameter to be optimized. Therefore, in this method, the search space can be used to jointly obtain the target values ​​of multiple parameters to be optimized of the constellation. Compared with the related art in which the target value of each parameter to be optimized is solved separately, the steps are cumbersome. This solution is simple and easy to implement, with high feasibility, and with the minimum total number of satellites in the constellation as the optimization goal, and with the constellation achieving single-layer coverage as the constraint condition, it helps to reduce the total number of satellites in the constellation, thereby reducing the cost of the constellation, and improving the coverage performance of the constellation.

[0067] Based on any of the above embodiments, Figure 4 As shown, in step S103, searching for the target value of each parameter to be optimized in the search space includes the following steps:

[0068] S401, constructing a particle swarm, wherein the position of particles in the particle swarm is used to characterize each parameter to be optimized, and the value range of the position is the search space.

[0069] It should be noted that there is no excessive limitation on the number of particles in the particle group. For example, the number of particles is 20.

[0070] It should be noted that particles can move in the search space, that is, the search space is the moving range of the particles, and the value range of the particle position is the search space. The dimensions of the particle position correspond one-to-one to the parameters to be optimized, that is, the number of dimensions of the particle position is equal to the number of parameters to be optimized and the number of dimensions of the search space, and the i-th dimension of the particle position is used to represent the i-th parameter to be optimized.

[0071] In one implementation, the position and velocity of each particle may be initialized.

[0072] S402, in the Nth round of searching, searching for the Nth round position of the particle in the search space, and judging whether to update the target position of the particle based on the Nth round position of the particle and the target position of the particle, where N is a positive integer.

[0073] It can be understood that the N-th round positions of different particles may be the same or different, the target positions of different particles may be the same or different, and the target position of a particle refers to the best position of the particle. Before the N-th round of search process, the target position of a particle refers to the best position among the positions of the 1st to N-1th rounds, and after the N-th round of search process, the target position of a particle refers to the best position among the positions of the 1st to Nth rounds.

[0074] In one embodiment, searching for the Nth round position of the particle in the search space includes searching for the Nth round position of the particle in the search space according to the search scene parameters. It should be noted that the search scene parameters are not overly limited. For example, the search scene parameters include a simulation time of 24 hours, a ground area range of 0° to 90° latitude band, divided into grids with a 10° accuracy for coverage calculation, a minimum communication angle of 15° between the satellite and the earth station, and a setting of the number of search rounds to 20 times.

[0075] In one embodiment, based on the N-th round position of the particle and the target position of the particle, it is determined whether to update the target position of the particle, including evaluating the N-th round fitness value of the particle based on the N-th round position of the particle, and evaluating the target fitness value of the particle based on the target position of the particle, if the N-th round fitness value of the particle is greater than the target fitness value of the particle, updating the target position of the particle to the N-th round position of the particle, conversely, if the N-th round fitness value of the particle is less than or equal to the target fitness value of the particle, maintaining the target position of the particle, that is, not updating the target position of the particle.

[0076] S403: If the search end condition is met, a target value of each parameter to be optimized is obtained based on the target position of each particle.

[0077] It should be noted that there are not too many restrictions on the search end conditions, for example, it may include the number of search rounds reaching a set number of search rounds.

[0078] In one embodiment, based on the target position of each particle, a target value of each parameter to be optimized is obtained, including extracting candidate values ​​of each parameter to be optimized from the target position of the particle, and obtaining the target value of the parameter to be optimized based on the candidate values ​​of the parameter to be optimized extracted from the target position of each particle.

[0079] In some examples, a target value of the parameter to be optimized is obtained based on candidate values ​​of the parameter to be optimized extracted from the target position of each particle, including taking a weighted average of the candidate values ​​of the parameter to be optimized extracted from the target position of each particle to obtain the target value of the parameter to be optimized, or screening the target value of the parameter to be optimized from the candidate values ​​of the parameter to be optimized extracted from the target position of each particle.

[0080] Therefore, a particle swarm is constructed in the method, and the position of the particles in the particle swarm is used to characterize each parameter to be optimized. The value range of the position is the search space. During the Nth round of search, the Nth round position of the particle is searched in the search space, and based on the Nth round position of the particle and the target position of the particle, it is determined whether to update the target position of the particle. If the search end condition is met, the target value of each parameter to be optimized is obtained based on the target position of each particle, and the target value of each parameter to be optimized can be searched in the search space based on the particle swarm algorithm.

[0081] Based on any of the above embodiments, Figure 5 As shown, in step S403, based on the target position of each particle, the target value of each parameter to be optimized is obtained, including the following steps:

[0082] S501, selecting a final position from target positions of multiple particles.

[0083] S502: extracting the target value of each parameter to be optimized from the final position.

[0084] In one embodiment, selecting the final position from the target positions of the plurality of particles includes randomly selecting the final position from the target positions of the plurality of examples.

[0085] In one embodiment, selecting the final position from the target positions of multiple particles includes obtaining the weights of the particles and determining the target position of the particle with the largest weight as the final position. It is understandable that different particles may correspond to different weights, and the weights of the particles may be updated in real time according to a set algorithm.

[0086] In one embodiment, the final position is screened out from the target positions of multiple particles, including extracting a candidate value of each parameter to be optimized from the target position of the particle, obtaining a double coverage parameter of the constellation based on the candidate value of each parameter to be optimized, and screening out the final position from the target positions of the multiple particles based on the double coverage parameters corresponding to the target positions of the multiple particles. Therefore, in this method, the final position can be screened out from the target positions of multiple particles based on the double coverage parameters, which helps to improve the coverage performance of the constellation, especially the double coverage performance.

[0087] It should be noted that obtaining the double coverage parameters of the constellation based on the candidate values ​​of each parameter to be optimized can be achieved by using any double coverage parameter obtaining method in the related art, which is not limited too much here.

[0088] In one embodiment, the larger the double coverage parameter, the better the double coverage performance of the constellation, and based on the double coverage parameters corresponding to the target positions of multiple particles, the final position is screened out from the target positions of multiple particles, including determining the target position with the largest double coverage parameter as the final position.

[0089] For example, if the number of particles is 20, a data set of number t can be extracted from the target position of the particle of number t, wherein the data set of number t includes candidate values ​​of each parameter to be optimized, and based on the candidate values ​​of each parameter to be optimized in the data set of number t, the double coverage parameters of the constellation are obtained, and based on the double coverage parameters corresponding to the target positions of the particles of numbers 1 to 20, the final position is screened out from the target positions of the particles of numbers 1 to 20. For example, the target position of the particle of number 2 can be determined as the final position. Wherein, t is a positive integer not greater than 20.

[0090] For example, the candidate value of the number of orbital planes P in the data set No. 12 is 20, and the candidate value of the number of satellites S in the orbital plane is 4, which is not conducive to constellation deployment and the establishment of inter-satellite links and should not be used as target values.

[0091] Therefore, in this method, a final position is screened out from the target positions of multiple particles, and a target value of each parameter to be optimized is extracted from the final position.

[0092] Figure 6 A schematic flow chart of another method for acquiring a constellation configuration provided in an embodiment of the present disclosure.

[0093] like Figure 6 As shown, the method for obtaining the constellation configuration may include the following steps:

[0094] S601: Obtain a value range of each parameter to be optimized of a constellation.

[0095] S602: Generate a search space based on the value range of each parameter to be optimized.

[0096] S603, constructing a particle swarm, wherein the positions of particles in the particle swarm are used to characterize each parameter to be optimized, and the value range of the position is the search space.

[0097] S604, taking the minimum total number of satellites in the constellation as the optimization goal and taking the constellation achieving single-layer coverage as the constraint condition, during the N-th round of search, searching for the N-th round position of the particle in the search space, and judging whether to update the target position of the particle based on the N-th round position of the particle and the target position of the particle, where N is a positive integer.

[0098] S605: If the search end condition is met, a final position is selected from the target positions of the multiple particles.

[0099] S606: extract the target value of each parameter to be optimized from the final position.

[0100] For the relevant contents of steps S601-S606, please refer to the above embodiment and will not be repeated here.

[0101] In order to implement the above embodiment, the present disclosure also proposes a constellation configuration acquisition device.

[0102] Figure 7 A schematic diagram of the structure of a constellation configuration acquisition device provided in an embodiment of the present disclosure.

[0103] like Figure 7 As shown, the constellation configuration acquisition device 100 includes: a first acquisition module 110 , a generation module 120 , a search module 130 and a second acquisition module 140 .

[0104] The first acquisition module 110 is used to obtain the value range of each parameter to be optimized of the constellation;

[0105] The generating module 120 is used to generate a search space based on the value range of each parameter to be optimized;

[0106] The search module 130 is used to search for a target value of each parameter to be optimized in the search space with the minimum total number of satellites in the constellation as an optimization goal and with the constellation achieving single coverage as a constraint condition;

[0107] The second acquisition module 140 is used to obtain the constellation configuration of the constellation based on the target value of each parameter to be optimized.

[0108] In one embodiment of the present disclosure, the search module 130 is further used to: obtain a threshold based on the orbital inclination of the constellation and the coverage bandwidth of the constellation to achieve single-layer coverage; and determine the constraint condition based on the number of orbital planes of the constellation, the maximum angular separation between adjacent orbital planes in the same direction of the constellation and the threshold.

[0109] In one embodiment of the present disclosure, the search module 130 is further used to: obtain the difference between the number of orbital planes and 1; and determine the product of the difference and the maximum angular separation to be greater than or equal to the threshold as the constraint condition.

[0110] In one embodiment of the present disclosure, the search module 130 is also used to: construct a particle swarm, wherein the position of the particle in the particle swarm is used to characterize each of the parameters to be optimized, and the value range of the position is the search space; during the Nth round of search, the Nth round position of the particle is searched in the search space, and based on the Nth round position of the particle and the target position of the particle, it is determined whether to update the target position of the particle, wherein N is a positive integer; if the search end condition is met, the target value of each parameter to be optimized is obtained based on the target position of each of the particles.

[0111] In one embodiment of the present disclosure, the search module 130 is further used to: filter out a final position from a plurality of target positions of the particles; and extract a target value of each parameter to be optimized from the final position.

[0112] In one embodiment of the present disclosure, the search module 130 is also used to: extract candidate values ​​of each parameter to be optimized from the target position of the particle; obtain the double coverage parameters of the constellation based on the candidate values ​​of each parameter to be optimized; and filter out the final position from the target positions of multiple particles based on the double coverage parameters corresponding to the target positions of multiple particles.

[0113] In one embodiment of the present disclosure, the parameters to be optimized include at least one of the number of satellites in the orbital plane, the number of orbital planes, the orbital inclination, the orbital altitude, the right ascension difference of the ascending node, and the phase difference between adjacent orbital planes.

[0114] It should be noted that the above explanation of the embodiment of the method for obtaining the constellation configuration is also applicable to the apparatus for obtaining the constellation configuration of this embodiment, and will not be repeated here.

[0115] The device for acquiring the constellation configuration of the embodiment of the present disclosure acquires the value range of each parameter to be optimized of the constellation, generates a search space based on the value range of each parameter to be optimized, takes the minimum total number of satellites in the constellation as the optimization goal, and takes the constellation to achieve single-layer coverage as the constraint condition, searches for the target value of each parameter to be optimized in the search space, and obtains the constellation configuration of the constellation based on the target value of each parameter to be optimized. Therefore, the method can use the search space to jointly acquire the target values ​​of multiple parameters to be optimized of the constellation. Compared with the related art in which the target value of each parameter to be optimized is solved separately, the steps are cumbersome. This solution is simple and easy to implement, has high feasibility, and takes the minimum total number of satellites in the constellation as the optimization goal, and takes the constellation to achieve single-layer coverage as the constraint condition, which helps to reduce the total number of satellites in the constellation, thereby reducing the cost of the constellation and improving the coverage performance of the constellation.

[0116] In order to implement the above embodiments, the present application also proposes an electronic device, such as Figure 8 As shown, Figure 8 The invention is a block diagram of an electronic device for a method for acquiring a constellation configuration according to an exemplary embodiment.

[0117] like Figure 8 As shown, the electronic device 200 includes:

[0118] The memory 210 and the processor 220, a bus 230 connecting different components (including the memory 210 and the processor 220), the memory 210 stores a computer program, and when the processor 220 executes the program, the method for obtaining the constellation configuration described in the embodiment of the present disclosure is implemented.

[0119] Bus 230 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnect (PCI) bus.

[0120] The electronic device 200 typically includes a variety of electronic device readable media. These media can be any available media that can be accessed by the electronic device 200, including volatile and non-volatile media, removable and non-removable media.

[0121] The memory 210 may also include computer system readable media in the form of volatile memory, such as random access memory (RAM) 240 and / or cache memory 250. The electronic device 200 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 260 may be used to read and write non-removable, non-volatile magnetic media ( Figure 8 not shown, usually called a "hard drive"). Although Figure 8 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 230 via one or more data medium interfaces. The memory 210 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present disclosure.

[0122] A program / utility 280 having a set (at least one) of program modules 270 may be stored, for example, in the memory 210, such program modules 270 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 270 generally perform the functions and / or methods of the embodiments described in the present disclosure.

[0123] The electronic device 200 may also communicate with one or more external devices 290 (e.g., keyboard, pointing device, display 291, etc.), one or more devices that enable a user to interact with the electronic device 200, and / or any device that enables the electronic device 200 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed through an input / output (I / O) interface 292. Furthermore, the electronic device 200 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 423. Figure 8 As shown, the network adapter 293 communicates with other modules of the electronic device 200 via the bus 230. It should be understood that although Figure 8 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 200, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0124] The processor 220 executes various functional applications and data processing by running the programs stored in the memory 210 .

[0125] It should be noted that the implementation process and technical principles of the electronic device of this embodiment refer to the aforementioned explanation of the method for obtaining the constellation configuration of the embodiment of the present disclosure, and will not be repeated here.

[0126] In order to implement the above embodiments, the present application further proposes a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method for obtaining the constellation configuration described in the above embodiments is implemented.

[0127] In order to implement the above embodiments, the present disclosure further provides a computer program product. When an instruction processor in the computer program product is executed, the method for acquiring the constellation configuration described in the above embodiments is executed.

[0128] In the description of this specification, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0129] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0130] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for obtaining a constellation configuration, characterized in that: include: Obtain the value range of each parameter to be optimized of the constellation; Generate a search space based on the value range of each parameter to be optimized; Taking the minimum total number of satellites in the constellation as an optimization goal and taking the realization of single coverage by the constellation as a constraint condition, searching for a target value of each parameter to be optimized in the search space; Based on the target value of each parameter to be optimized, a constellation configuration of the constellation is obtained.

2. The method according to claim 1, characterized in that The method further comprises: Obtaining a threshold value based on the orbital inclination of the constellation and a coverage bandwidth of the constellation to achieve single-layer coverage; The constraint condition is determined based on the number of orbital planes of the constellation, the maximum angular separation between adjacent orbital planes of the constellation in the same direction, and the threshold.

3. The method according to claim 2, characterized in that The determining the constraint condition based on the number of orbital planes of the constellation, the maximum angular separation between adjacent orbital planes of the constellation in the same direction, and the threshold value comprises: Obtain the difference between the number of track surfaces and 1; The product of the difference and the maximum angular separation is greater than or equal to the threshold, which is determined as the constraint condition.

4. The method according to claim 1, characterized in that: The step of searching the search space for a target value of each parameter to be optimized includes: Constructing a particle swarm, wherein the position of the particles in the particle swarm is used to characterize each of the parameters to be optimized, and the value range of the position is the search space; In the Nth round of searching, searching the Nth round position of the particle in the search space, and judging whether to update the target position of the particle based on the Nth round position of the particle and the target position of the particle, wherein N is a positive integer; If the search end condition is met, the target value of each parameter to be optimized is obtained based on the target position of each particle.

5. The method according to claim 4, characterized in that The step of obtaining a target value of each parameter to be optimized based on the target position of each particle comprises: selecting a final position from a plurality of target positions of the particles; A target value of each parameter to be optimized is extracted from the final position.

6. The method according to claim 5, characterized in that The step of selecting a final position from the target positions of the plurality of particles comprises: Extracting candidate values ​​of each of the parameters to be optimized from the target position of the particle; Based on each candidate value of the parameter to be optimized, obtaining a double coverage parameter of the constellation; The final position is selected from the target positions of the particles based on the double coverage parameters corresponding to the target positions of the particles.

7. The method according to any one of claims 1 to 6, characterized in that The parameters to be optimized include at least one of the number of satellites in the orbital plane, the number of orbital planes, orbital inclination, orbital altitude, right ascension difference of ascending node and phase difference between adjacent orbital planes.

8. A device for acquiring a constellation configuration, characterized in that: include: A first acquisition module is used to obtain a value range of each parameter to be optimized of the constellation; A generation module, used to generate a search space based on the value range of each parameter to be optimized; A search module, configured to search for a target value of each parameter to be optimized in the search space with the minimum total number of satellites in the constellation as an optimization goal and with the constellation achieving single coverage as a constraint condition; The second acquisition module is used to obtain the constellation configuration of the constellation based on the target value of each parameter to be optimized.

9. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for acquiring the constellation configuration according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for acquiring the constellation configuration according to any one of claims 1 to 7 is implemented.

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