A constellation configuration optimization method and device

Abstract

The application provides a constellation configuration optimization method and device, and belongs to the technical field of constellation configuration design. The method comprises the following steps: an effective point set composed of uniformly distributed scattered points is established for a target region of the earth surface covered by a satellite constellation; each point in the effective point set is taken as a point target accessed by the satellite constellation, and the visibility window of a single satellite participating in the constellation configuration for each point target is calculated; based on the visibility window, the coverage performance of the constellation is analyzed to obtain the success rate of realizing revisit corresponding to each point target; and based on the success rate of realizing revisit, a genetic algorithm is used for optimization design of the constellation configuration to obtain an optimal solution of the characteristic parameters of the constellation under the set constellation configuration. The application can quickly generate a constellation configuration meeting the performance index requirements according to the set coverage range and revisit time requirements, and realizes optimization of the constellation design while ensuring the calculation efficiency.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of constellation configuration design, and particularly relates to a constellation configuration optimization method and device. BACKGROUND

[0002] With the continuous development of space information acquisition and application fields, satellite constellation as an important space infrastructure plays an increasingly important role in the fields of remote sensing, communication, navigation, etc. However, the design and optimization of satellite constellation face many challenges, such as: configuration diversification leads to complex design, the appropriate constellation configuration needs to be selected and optimized for different application requirements; numerous performance indicators are difficult to balance, which need to be considered comprehensively through optimization algorithms; high computational efficiency is required, and traditional constellation design methods have large calculation amount, low efficiency and difficulty in guaranteeing optimal solution. In order to better carry out the research on constellation configuration numerical analysis, it is necessary to establish a strong applicability of constellation optimization design method. SUMMARY

[0003] The purpose of the present application is to overcome the shortcomings of the prior art, and to provide a constellation configuration optimization method and device. The present application can quickly generate a constellation configuration that meets the performance index requirements according to the set coverage range and revisit time requirements, and realize the optimization of satellite constellation design while ensuring the computational efficiency.

[0004] The first aspect of the present application provides a constellation configuration optimization method, comprising:

[0005] Establishing an effective point set composed of uniformly distributed points for the target area of the earth's surface covered by the satellite constellation;

[0006] Taking each point in the effective point set as a point target visited by the constellation, calculating the visibility window of each point target for a single satellite participating in the constellation configuration;

[0007] Based on the visibility window, performing coverage performance analysis of the constellation to obtain the success rate of implementing revisit corresponding to each point target;

[0008] Based on the success rate of implementing revisit, using a genetic algorithm to perform constellation configuration optimization design to obtain the optimal solution of the constellation characteristic parameters under the set constellation configuration.

[0009] In one specific embodiment of the present application, the effective point set is constructed as follows:

[0010] Let X be a random variable uniformly distributed in the range [-1, 1], and Y represent the latitude value of any point in the target area. By mapping X to:

[0011] arcsin=arcsin(X) (1)

[0012] Get a random distribution related to latitude;

[0013] Among them, the number of points in the latitude interval of the target area N Y It is proportional to the area of ​​the interval on the surface of the earth, that is:

[0014] N Y =numof(X∈[sin(Y min ),sin(Y max )]) (3)

[0015] N Y ∝sin(Y max )-sin(Y min )≈ΔYcos(Y) (4)

[0016] Among them, Y min and Y max They represent the minimum and maximum latitudes in the target area, respectively. ΔY represents the latitude interval [Y min ,Y max ], ΔY=Y max -Y min ;

[0017] The point set generated according to formula (1) that is consistent with the change of the earth's surface area with latitude is the valid point set.

[0018] In a specific embodiment of the present invention, the step of calculating the visibility window of each point target from a single satellite to be involved in the constellation configuration includes:

[0019] 1) Based on the simulated observation mission of any satellite in the constellation configuration for the target area, the simulation period is divided into:

[0020] The first segment is from the start time of the simulation observation mission to the maximum latitude point of the satellite's first pass through the target area. The i-th segment is from the maximum latitude point of the satellite's i-1th pass through the target area to the i-th pass through the maximum latitude point. i ≥ 2. The last segment is from the maximum latitude point of the satellite's last pass through the target area to the end time of the simulation observation mission. The entire time of the satellite's orbit advancement is discretized into m equal parts, resulting in a total of m+1 discrete time points. The time sequence composed of all discrete time points is t i ,i=1,2,...m+1, where i=1 corresponds to the start time and i=m+1 corresponds to the end time;

[0021] 2) Based on the results of step 1), calculate each discrete time point t i Whether each point target is within the visible range of the satellite;

[0022] Among them, if at ti If the target point is within the visible range of the satellite at time t i , the satellite is visible to the target point at time t

[0023] 3) Based on the result of step 2), obtain the visibility window of the satellite to each target point;

[0024] Wherein, for any target point, start from i = 1: if the satellite is visible to the target point at time t i , and the satellite is not visible to the target point at time t i-1 , then t i is the time when the visibility window of the satellite to the target point starts; if the satellite is visible to the target point at time t i-1 , and the satellite is not visible to the target point at time t i , then t i is the time when the visibility window of the satellite to the target point ends; until i = m + 1, the determination is completed, and the visibility window of the satellite to the target point is obtained;

[0025] 4) Repeat steps 1) to 3) to obtain the visibility window of each satellite in the constellation to be constructed to each point in the effective point set.

[0026] In one specific embodiment of the present application, it further comprises:

[0027] If the distance of any satellite from the ground is H, the corresponding central angle of the maximum visible range of the satellite is:

[0028]

[0029] Wherein, R e is the radius of the earth;

[0030] Let the maximum preset threshold of the line-of-sight angle of the satellite and the target point be Then determine:

[0031] If the line-of-sight angle of the satellite and any target point is greater than the maximum preset threshold , the target point is not within the visible range of the satellite;

[0032] If the line-of-sight angle of the satellite and any target point is equal to or less than , the target point is within the visible range of the satellite.

[0033] In one specific embodiment of the present application, the constellation optimization design using genetic algorithm comprises:

[0034] 1) Determine the optimization target and design the fitness function;

[0035] The optimization target is divided into two cases: one is the least number of satellites given the performance requirement, and the other is the optimal performance given the number of satellites; wherein:

[0036] In the case of the least number of satellites given the performance requirement, the least number of satellites required to achieve uninterrupted revisit of the target area within a set time t is realized, and the fitness function is represented as:

[0037] score = -N-μ∑(1-χ) (5)

[0038] Wherein, score represents fitness; N is the number of satellites; μ is a penalty coefficient; χ is the success rate of each point target for realizing revisit;

[0039] In the case of optimal performance given the number of satellites, the highest success rate of revisit of the target area in no less than time t is realized under the set number of satellites, and the fitness function is represented as:

[0040] score = -μ∑(1-χ) (6)

[0041] Wherein, μ is a penalty coefficient;

[0042] 2) Based on the result of step 1), the genetic algorithm is used for optimization to obtain the optimal solution of the constellation characteristic parameters under the set constellation configuration.

[0043] The second aspect embodiment of the present application proposes a constellation configuration optimization device, comprising:

[0044] An effective point set construction module is configured to establish an effective point set composed of uniformly distributed points for a target area of the earth's surface covered by a satellite constellation;

[0045] A visibility window calculation module is configured to calculate the visibility window of each point target for each satellite participating in the constellation configuration as a point target accessed by the constellation.

[0046] A coverage performance analysis module is configured to perform coverage performance analysis of the constellation based on the visibility window to obtain the success rate of each point target for realizing revisit.

[0047] A constellation configuration optimization module is configured to perform constellation configuration optimization design based on the success rate of realizing revisit using a genetic algorithm to obtain the optimal solution of the constellation characteristic parameters under the set constellation configuration.

[0048] In one specific embodiment of the present application, the effective point set construction method is as follows:

[0049] Let X be a random variable uniformly distributed in the range [-1, 1], and Y represent the latitude value of any point in the target area. X is mapped to:

[0050] Y = arcsin(X) (1)

[0051] obtain a random distribution related to latitude;

[0052] wherein N is the number of points in the target area latitude interval Y is proportional to the area of the interval on the earth's surface, that is:

[0053] N Y = numof(X ∈ [sin(Y min ), sin(Y max )]) (3)

[0054] N Y ∝ sin(Y max )- sin(Y min ) ≈ ΔY cos(Y) (4)

[0055] wherein Y min and Y max represent the minimum and maximum values of latitude in the target area latitude interval respectively, and ΔY represents the span of the latitude interval [Y min , Y max ], ΔY = Y max - Y min ;

[0056] According to formula (1), the point set generated in accordance with the change of the earth's surface area with latitude is an effective point set.

[0057] In one specific embodiment of the present application, the calculation of the visibility window of each point target by the single satellite to be involved in the constellation configuration includes:

[0058] 1) Based on the simulation observation task of any satellite to be involved in the constellation configuration for the target area, the simulation period is divided, wherein:

[0059] the first segment is from the start time of the simulation observation task to the first time when the satellite passes the maximum latitude point of the target area, the i-th segment is from the (i-1)-th time when the satellite passes the maximum latitude point of the target area to the i-th time when the satellite passes the maximum latitude point of the target area, i ≥ 2, and the last segment is from the last time when the satellite passes the maximum latitude point of the target area to the end time of the simulation observation task, thereby discretizing the entire time of the satellite orbit advancement into m equal parts, obtaining m+1 discrete time points, and the time sequence composed of all the discrete time points is t i ,i = 1, 2, … m+1, wherein i = 1 corresponds to the start time, and i = m+1 corresponds to the end time;

[0060] 2) Based on the result of step 1), the visibility window of each discrete time point t iWhether each point target is within the visible range of the satellite;

[0061] Among them, if at t i If any target point is within the visible range of the satellite at time t, then the satellite is judged to be i The target is always visible to the point; otherwise it is invisible;

[0062] 3) Based on the result of step 2), obtain the satellite's visibility window for each point target;

[0063] For any point target, the judgment starts from i=1: if the satellite is at t i The target is visible at this time, at t i-1 The target is not visible at this moment, then t i The time when the satellite's visible window to the target begins; if the satellite is at t i-1 The target is visible at this time, at t i If the time is not visible, then t i The time when the satellite's visibility window for the target point ends is determined until i=m+1, thereby obtaining the satellite's visibility window for the target point.

[0064] 4) Repeat steps 1) to 3) to obtain the visibility window of each satellite to be involved in the constellation configuration to each point in the valid point set.

[0065] In a specific embodiment of the present invention, it also includes:

[0066] If the distance between any satellite and the ground is H, then the geocentric angle corresponding to the maximum visible range of the satellite is:

[0067]

[0068] Among them, R e is the radius of the Earth;

[0069] The preset maximum threshold of the line of sight angle between the satellite and the point target is Then determine:

[0070] If the line of sight angle between the satellite and any target is greater than the preset maximum threshold Then the point target is not within the satellite’s visual range;

[0071] If the line of sight angle between the satellite and any target point is equal to or less than Then the point target is within the visible range of the satellite.

[0072] In a specific embodiment of the present invention, the constellation configuration optimization design using a genetic algorithm includes:

[0073] 1) Determine the optimization objective and design the fitness function;

[0074] The optimization objectives are divided into two cases: one is to require the minimum number of satellites for a given performance, and the other is to require the best performance for a given number of satellites;

[0075] Given the minimum number of satellites required for performance, the minimum number of satellites required to achieve uninterrupted revisit of the target area within the set time t is the fitness function:

[0076] score=-N-μ∑(1-χ) (5)

[0077] Among them, score represents fitness; N is the number of satellites; μ is the penalty coefficient; χ is the success rate of revisiting each point target;

[0078] When the performance is optimal for a given number of satellites, the target area is revisited at a maximum success rate of not less than time t under the set number of satellites. The fitness function is expressed as:

[0079] score=-μ∑(1-χ) (6)

[0080] Among them, μ is the penalty coefficient;

[0081] 2) Based on the result of step 1), a genetic algorithm is used for optimization to obtain the optimal solution of the constellation characteristic parameters under the set constellation configuration.

[0082] A third embodiment of the present invention provides an electronic device, including:

[0083] at least one processor; and a memory communicatively coupled to the at least one processor;

[0084] The memory stores instructions that can be executed by the at least one processor, and the instructions are configured to execute the above-mentioned constellation configuration optimization method.

[0085] A fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions for enabling the computer to execute the above-mentioned constellation configuration optimization method.

[0086] The characteristics and beneficial effects of the present invention are:

[0087] During the satellite constellation configuration design and optimization process, the constellation must meet specific coverage range and revisit time requirements, while achieving efficient, flexible, and reliable coverage performance. This invention first utilizes a uniform point distribution algorithm on the Earth's surface to ensure that the point distribution density is proportional to the Earth's surface area, thereby ensuring the balance and accuracy of coverage analysis. Secondly, by analyzing the interaction mechanism between satellites and the ground, a method for estimating regional target visibility is proposed. Incorporating spherical geometry principles, the intersection area between the satellite's field of view and the target area is calculated, effectively assessing the constellation's coverage performance. Furthermore, this invention incorporates a genetic algorithm for constellation configuration optimization. By constructing a multi-objective optimization model, it supports both "minimizing the number of satellites for a given performance requirement" and "optimizing performance for a given number of satellites." Combining an elitist strategy with multiple crossover and mutation operations, this method gradually converges to a near-optimal solution while ensuring computational efficiency. This invention can be applied to the optimization design of various satellite constellations, such as remote sensing, communications, and navigation, providing a powerful tool for promoting the diversified development of constellation configurations and improving satellite system performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] Figure 1 The figure is an overall flow chart of a constellation configuration optimization method in a specific embodiment of the present invention.

[0089] Figure 2 Schematic diagram of the area calculation principle of any latitude interval in a specific embodiment of the present invention.

[0090] Figure 3 Schematic diagram of the interactive position of the satellite and the earth under the conical field of view in a specific embodiment of the present invention.

[0091] Figure 4 Schematic diagram of the position relationship between satellites and the earth in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0092] The present invention provides a constellation configuration optimization method and apparatus, which are further described in detail below with reference to the accompanying drawings and specific embodiments.

[0093] A first embodiment of the present invention provides a constellation configuration optimization method, including:

[0094] Establish a valid point set consisting of evenly distributed points for the target area on the earth's surface covered by the satellite constellation;

[0095] Taking each point in the valid point set as a point target for constellation access, and calculating the visibility window of a single satellite to be involved in the constellation configuration for each point target;

[0096] Performing a coverage performance analysis of the constellation based on the visibility window to obtain a revisit success rate corresponding to each point target;

[0097] Based on the success rate of achieving revisit, a genetic algorithm is used to optimize the constellation configuration design to obtain an optimal solution for the constellation characteristic parameters under the set constellation configuration.

[0098] In a specific embodiment of the present invention, the overall process of the constellation configuration optimization method is as follows: Figure 1 As shown, the following steps are included:

[0099] 1) Establish a valid point set consisting of evenly distributed points for the target area on the earth's surface covered by the satellite constellation.

[0100] In this embodiment, to ensure balanced and accurate global coverage, it is necessary to first achieve a uniform distribution of points within the target area. The target area is the area where researchers wish to conduct coverage performance analysis, that is, the specific area where the satellite constellation's coverage effectiveness needs to be evaluated. It can be a regular shape, such as a rectangle, circle, or triangle, or an irregular shape, such as an island, city, or specific geographic area.

[0101] Specifically, for a uniform sphere, the latitude interval of the target area is [Y min ,Y max ], where Y min and Y max They represent the minimum and maximum latitudes within the target area's latitude range. The area of ​​this latitude range can be calculated using the following formula:

[0102]

[0103] Figure 2 FIG. 1 is a schematic diagram of the area calculation principle of any latitude interval in a specific embodiment of the present invention. Figure 2 As shown, ΔS is the area of ​​the latitude interval, is the Y value in this latitude range min The corresponding angle between the latitude circle connecting the center of the sphere and the equatorial plane is, Y for the latitude interval min and Y max The angle formed by the connection between the two weft loops and the center of the sphere, R e is the radius of the sphere, in this embodiment it is the radius of the earth, and the NS axis is the earth's rotation axis.

[0104] Therefore, in order to achieve uniform distribution of points within the target area, the embodiment of the present invention designs a random distribution function, setting X as a random variable uniformly distributed in the range [-1, 1], and Y as the latitude value of any point in the target area, by mapping X to:

[0105] Y=arcsin(X) (1)

[0106] A random distribution related to the latitude of the earth's surface can be obtained. This mapping relationship ensures that in the specified interval of Y [Y min ,Y max ], the number of points N in the latitude interval of the target area Y It is proportional to the area of ​​the interval on the surface of the earth, that is:

[0107] N Y =numof(X∈[sin(Y min ),sin(Y max )]) (2)

[0108] N Y ∝sin(Y max )-sin(Y min )≈ΔYcos(Y)(3)

[0109] Among them, ΔY represents the latitude interval [Y min ,Y max ], that is, ΔY=Y max -Y min .

[0110] Since X itself is uniformly distributed, the distribution of Y also remains uniform, thus ensuring that the distribution of area with latitude remains consistent. The point set that can be generated by formula (1) that is consistent with the change of the earth's surface area with latitude is a valid point set.

[0111] 2) Based on the result of step 1), each point in the valid point set is used as a point target for constellation access, and the visibility window of a single satellite to be involved in the constellation configuration to each point in the valid point set is calculated.

[0112] In this embodiment, the valid point set obtained in step 1) represents discrete points in the target area, and the coverage of the satellite on the point target is evaluated by calculating the visibility window of each point in the point set at different time steps.

[0113] Furthermore, before calculating the visibility window, this embodiment first describes the satellite field of view type. Common satellite field of view types include conical field of view, rectangular field of view, and the like.

[0114] For example, in the conical field of view, the satellite and ground interaction positions are as follows: Figure 3 As shown in the figure, we can see the cone half angle, P represents the center of the cone field of view, S represents an arbitrary ground point, and r is the radius of the cone field of view.

[0115] Judgment: Let sp be the distance from any ground point to the center of the conical field of view. If sp < r, the ground point is within the satellite field of view and the target ground point is visible; if sp > r, the ground point is not within the satellite field of view and the target ground point is not visible.

[0116] Specifically, the calculation process of the visibility window in the embodiment is as follows:

[0117] 2-1) Based on the simulation observation task of any satellite in the constellation configuration to be participated to the target area, the simulation period is segmented, wherein: from the starting time of the simulation observation task to the first time that the satellite passes the latitude maximum point of the target area, it is the first segment, from the first time that the satellite passes the latitude maximum point of the target area to the second time that the satellite passes the latitude maximum point, and so on, the last time that the satellite passes the latitude maximum point of the target area to the end time of the simulation observation task is the last segment, thereby discretizing the entire time of the satellite orbit advancement into m equal parts, a total of m+1 discrete time points, and the time sequence composed of all the discrete time points is t i , i = 1, 2,... m+1, wherein i = 1 corresponds to the starting time, and i = m+1 corresponds to the end time;

[0118] 2-2) Based on the result of step 2-1), calculate whether each discrete time point t i , each point target is in the visible range of the satellite.

[0119] Wherein, if any point target is in the visible range of the satellite at t i , it is considered that the satellite is visible to the point target at the discrete time point t i ; otherwise, it is not visible.

[0120] Therefore, in order to determine whether the point target is in the visible range of the satellite, an estimation model of the satellite and the earth interaction position is established in the embodiment, wherein:

[0121] If the distance of any satellite in the constellation from the ground is H, the corresponding earth central angle of the maximum visible range of the satellite is:

[0122]

[0123] Figure 4 It is a schematic diagram of the position relationship between the satellite and the earth in one specific embodiment of the application. Figure 4 In the formula, R e is the radius of the earth. In the embodiment, the maximum threshold of the line-of-sight angle of the satellite and the ground point target is denoted as (the threshold value ranges from 0 to 90°, which can be set by the user according to the situation of the satellite field of view, wherein for the conical field of view, the threshold value is the conical half angle), and then it is determined:

[0124] If the line-of-sight angle of the satellite and any point target (the line-of-sight angle is related to the load carried by the satellite, which can be set by the user) is greater than , the satellite cannot directly observe the point target, that is, the point target is not in the visible range of the satellite.

[0125] On the contrary, if the sight angle is equal to or less than Then the point target is within the visible range of the satellite.

[0126] 2-3) Based on the result of step 2-2), the satellite's visibility window for each point target is obtained.

[0127] For any point target, the judgment starts from i=1: if the satellite is at t i The target is visible at this time, at t i-1 The target is not visible at this moment, then t i The time when the satellite's visible window to the target begins; if the satellite is at t i-1 The target is visible at this time, at t i If the time is not visible, then t i The time when the satellite's visibility window for the point target ends is determined until i=m+1, thereby obtaining the satellite's visibility window for the target point. In this embodiment, for a single point target, the visibility window of a satellite can be multiple segments.

[0128] 2-4) Repeat steps 2-1) to 2-3) to obtain the visibility window of each satellite to be involved in the constellation configuration for each point in the valid point set.

[0129] In this embodiment, the valid point set obtained in step 1) plays a key role in the visibility window calculation. By calculating the visibility windows of point targets in the valid point set at different time steps, the satellite coverage of the target area can be evaluated, thereby optimizing the design and configuration of the satellite constellation.

[0130] 3) Based on the result of step 2), the coverage performance of the constellation is analyzed to obtain the success rate of revisiting each point target in the effective point set.

[0131] In this embodiment, by summarizing the visibility window information obtained in step 2), a coverage performance analysis of the entire constellation over the target area can be constructed, which can be used to calculate key indicators such as the coverage time ratio of the constellation over the target area and the revisit time interval.

[0132] Based on the visibility window sequence of each satellite to the point target obtained in step 2), all valid visibility time windows within the set revisit time threshold t (ie, window interval ≤ t) are counted.

[0133] If any target point is revisited by a satellite at least once within t, it is considered a successful revisit. Then:

[0134] The success rate of revisiting = (number of point targets successfully revisited / total number of point targets) × 100%.

[0135] In this embodiment, the index will directly serve the genetic algorithm optimization of step 4) to ensure that the constellation configuration meets the coverage continuity requirements.

[0136] 4) Based on the results of step 3), the constellation configuration optimization design is carried out.

[0137] In this embodiment, the uniform discretization of the target area is achieved by the earth surface uniform point algorithm in step 1), the satellite-ground interaction mechanism modeling in step 2) provides the geometric basis for the calculation of single-satellite coverage capability, and finally the constellation-level coverage performance index (such as coverage time ratio, revisit interval, etc.) is obtained in step 3). These indexes constitute the quantitative evaluation standard of constellation optimization. However, in the process of constellation design optimization, due to the high degree of freedom of optimizing the parameters of each satellite, it is difficult to achieve ideal results in a limited time. Therefore, in this embodiment, genetic algorithm is adopted, based on specific constellation configuration, and the parameters of these specific configurations are optimized. The individual characteristics in genetic algorithm are the differences between population individuals. If Walker constellation is regarded as a population collective, the configuration of Walker constellation is determined by three parameters N, P and F, where N represents the total number of satellites in the constellation, P represents the number of orbital planes in the constellation, and F represents the phase factor. At the same time, the orbit inclination inc, orbit semi-major axis axis and eccentricity e describing the characteristics of single-satellite orbit, and a vector f0 describing the initial relative position relationship are also considered, which together determine the uniqueness of Walker constellation. Therefore, the above characteristic parameters [N, P, F, inc, axis, e, f0] constitute the individual characteristics of Walker constellation in the population, and the individual characteristics of rose constellation can be obtained in the same way [1, P, F, inc, axis, e, f0].

[0138] Based on this, this embodiment evaluates the adaptability of the constellation based on specific constellation configuration, and optimizes the individual characteristics of the constellation through genetic algorithm; the specific steps are as follows:

[0139] 4-1) Determine the optimization target and design the fitness function.

[0140] In this embodiment, the optimization target is divided into two cases: one is to minimize the number of satellites given the performance requirement, and the other is to optimize the performance given the number of satellites. Among them:

[0141] 4-1-1) In the case of minimizing the number of satellites given the performance requirement:

[0142] In this embodiment, the performance requirement is set as follows: the minimum number of satellites required to achieve uninterrupted revisit of the entire target area within a specified time t. This requirement aims to ensure that the constellation configuration can provide continuous coverage of the target area within the specified time, thereby meeting specific observation needs. Therefore, for constellation configurations that cannot meet this performance requirement, their competitiveness in the genetic process should be weakened, i.e., constellation configurations that result in revisit times greater than t should be eliminated. However, in order to ensure that the genetic algorithm can obtain guiding information, a penalty mechanism is introduced in the fitness calculation of individuals that approach but fail to fully meet the performance requirement, to reflect the gap between them and the ideal performance requirement.

[0143] Since the number of satellites is a key variable in the optimization process, the design of the fitness function should reflect the optimization goal of the number of satellites. In this embodiment, the fitness function can be represented as:

[0144] score = -N - μ∑(1 - χ) (5)

[0145] where score represents the fitness, N is the number of satellites, μ is the penalty coefficient to ensure that the penalty effect is significant, so the value is usually large and can be adjusted according to the optimization goal and problem size, and χ is the success rate of each point target implementation revisit, which comes from the coverage performance analysis results of step 3).

[0146] In this way, the fitness function not only considers the optimization of the number of satellites, but also ensures that the algorithm can pay attention to the importance of the success rate of revisit by imposing a penalty on individuals that fail to fully meet the performance requirement while pursuing the minimum number of satellites.

[0147] 4-1-2) In the case of optimal performance given the number of satellites:

[0148] The number of satellites is set as follows: under the requirement of a specified number of satellites, the success rate of revisit of the entire target area for no less than time t is the highest. This may result in a part of the satellites in the constellation being able to achieve revisit of the point target, while another part of the satellites cannot. In order to guide the evolution of the constellation population towards maximizing the success rate of revisit, the invention introduces a penalty mechanism for point targets that fail to achieve revisit. This mechanism adjusts the fitness function to encourage constellation configurations to develop towards the direction of being able to meet the revisit of point targets. Therefore, the fitness function can be designed as:

[0149] score = -μ∑(1 - χ) (6)

[0150] Here, μ is the penalty coefficient, and χ is the revisit success rate for each point target. In this way, the fitness function not only considers the revisit success rate of each point target but also penalizes those that fail to revisit. This ensures that the constellation configuration prioritizes global revisit performance during optimization, thereby improving the revisit success rate for the entire constellation.

[0151] 4-2) Based on the result of step 4-1), a genetic algorithm is used to optimize and obtain the optimal solution of the constellation characteristic parameters under the set constellation configuration.

[0152] In order to accelerate the process of approaching the optimal state, this embodiment introduces an innovative selection mechanism. This mechanism selects the top 10% of individuals with the highest fitness from the population, and uses the roulette wheel selection method to determine 40% of individuals as parents for crossover operation. The roulette wheel selection method, also known as the proportional selection operator, is based on the principle of assigning a corresponding selection probability to an individual based on its fitness value, that is, the higher the fitness, the greater the probability of being selected. Assume that the population size is n, and the fitness of individual i is F i ,The specific implementation steps of roulette wheel selection are as follows:

[0153] 4-2-1) Calculate the probability that individual i is selected and passed on to the next generation:

[0154]

[0155] is the generation probability.

[0156] 4-2-2) Calculate the cumulative probability of individual i:

[0157]

[0158] 4-2-3) Generate a random number r in the interval [0,1];

[0159] 4-2-4) Decision: If r < Q1, select individual 1; otherwise, select individual k so that Q k-1 ≤r≤Q k Establishment

[0160] The above is the roulette method. The selection method that combines retaining the best individual and roulette is more conducive to retaining the best individual, thereby accelerating the convergence of the optimal solution.

[0161] In a specific embodiment of the present invention, the method described in this embodiment ultimately obtains an optimization result of the characteristic parameters of the constellation configuration, namely: [N, P, F, inc, axis], where N represents the total number of satellites in the constellation, P represents the number of orbital planes in the constellation, F represents the phase factor, inc represents the orbital inclination, and axis represents the orbital semi-major axis.

[0162] Further, the method described in the embodiment is further described in detail as follows in combination with a specific embodiment.

[0163] In a specific embodiment of the present application:

[0164] In the case of the least number of satellites given the performance requirements:

[0165] In view of the satellite launch cost, the present application sets an upper limit of 400 satellites to avoid over-investment and waste of resources, so as to achieve the design of the constellation with the least number of satellites under the given coverage performance requirements, i.e., the coverage interval time is within 300s, the first island chain region is the coverage region.

[0166] The optimal constellation configuration obtained after analysis and optimization is: [181 181 19 0.577704 6.978e+06];

[0167] Among them, the parameter meanings are: 1 satellite per orbital plane, 181 orbital planes, phase factor is 19, orbital inclination is 0.577704 rad, about 33.1 deg, and orbital semi-major axis is about 6978 km.

[0168] In the case of optimal performance given the number of satellites:

[0169] In a specific embodiment of the present application, the number of satellites is given as 500, and under this condition, the average coverage weight is used as the coverage performance evaluation parameter, and the coverage interval time requirement is 0s, i.e., full coverage. The optimal constellation configuration with the best coverage performance is obtained through genetic algorithm analysis.

[0170] The optimal constellation configuration obtained after analysis and optimization is: [500 25 2 0.551524 6.978e+06];

[0171] Among them, the parameter meanings are: 20 satellites per orbital plane, 25 orbital planes, phase factor is 2, orbital inclination is 0.551524 rad, about 31.6 deg, and orbital semi-major axis is about 6978 km.

[0172] To achieve the above embodiment, a constellation configuration optimization device is provided in a second aspect of the present application, comprising:

[0173] An effective point set construction module is configured to establish an effective point set composed of uniformly distributed points for a target region of the earth's surface covered by the satellite constellation;

[0174] A visibility window calculation module is configured to calculate the visibility window of each point target for each single satellite participating in the constellation configuration as a point target accessed by the constellation.

[0175] a coverage performance analysis module, configured to perform coverage performance analysis of the constellation based on the visibility window to obtain a success rate of implementing revisit corresponding to each point target;

[0176] a constellation configuration optimization module, configured to perform constellation configuration optimization design based on the success rate of implementing revisit by using a genetic algorithm to obtain an optimal solution of constellation characteristic parameters under a set constellation configuration.

[0177] In one specific embodiment of the present application, the effective point set is constructed as follows:

[0178] Let X be a random variable uniformly distributed in the range of [-1, 1], and Y represent the latitude value of any point in the target area. A latitude-related random distribution is obtained by mapping X to:

[0179] arcsin = arcsin (X) (1)

[0180]

[0181] wherein the number N of points in the latitude interval of the target area Y is proportional to the area of the interval on the earth's surface, that is:

[0182] N Y = numof (X ∈ [sin (Y min ), sin (Y max )]) (3)

[0183] N Y ∝ sin (Y max )- sin (Y min ) ≈ ΔY cos (Y) (4)

[0184] wherein Y min and Y max represent the minimum and maximum values of latitude in the latitude interval of the target area, and ΔY represents the span of the latitude interval [Y min , Y max ], ΔY = Y max - Y min .

[0185] According to formula (1), the point set consistent with the change of the earth's surface area with latitude is the effective point set.

[0186] In one specific embodiment of the present application, the calculation of the visibility window of each point target by the satellite to be involved in the constellation configuration comprises:

[0187] 1) based on the simulation observation task of any satellite to be involved in the constellation configuration to the target area, the simulation period is divided, wherein: ​

[0188] The first segment is from the start time of the simulation observation mission to the maximum latitude point of the satellite's first pass through the target area. The i-th segment is from the maximum latitude point of the satellite's i-1th pass through the target area to the i-th pass through the maximum latitude point. i ≥ 2. The last segment is from the maximum latitude point of the satellite's last pass through the target area to the end time of the simulation observation mission. The entire time of the satellite's orbit advancement is discretized into m equal parts, resulting in a total of m+1 discrete time points. The time sequence composed of all discrete time points is t i ,i=1,2,...m+1, where i=1 corresponds to the start time and i=m+1 corresponds to the end time;

[0189] 2) Based on the results of step 1), calculate each discrete time point t i Whether each point target is within the visible range of the satellite;

[0190] Among them, if at t i If any target point is within the visible range of the satellite at time t, then the satellite is judged to be i The target is always visible to the point; otherwise it is invisible;

[0191] 3) Based on the result of step 2), obtain the satellite's visibility window for each point target;

[0192] For any point target, the judgment starts from i=1: if the satellite is at t i The target is visible at this time, at t i-1 The target is not visible at this moment, then t i The time when the satellite's visible window to the target begins; if the satellite is at t i-1 The target is visible at this time, at t i If the time is not visible, then t i The time when the satellite's visibility window for the target point ends is determined until i=m+1, thereby obtaining the satellite's visibility window for the target point.

[0193] 4) Repeat steps 1) to 3) to obtain the visibility window of each satellite to be involved in the constellation configuration to each point in the valid point set.

[0194] In a specific embodiment of the present invention, it also includes:

[0195] If the distance between any satellite and the ground is H, then the geocentric angle corresponding to the maximum visible range of the satellite is:

[0196]

[0197] Among them, R e is the radius of the Earth;

[0198] The preset maximum threshold of the line of sight angle between the satellite and the point target is Then determine:

[0199] If the line of sight angle between the satellite and any target is greater than the preset maximum threshold Then the point target is not within the satellite’s visual range;

[0200] If the line of sight angle between the satellite and any target point is equal to or less than Then the point target is within the visible range of the satellite.

[0201] In a specific embodiment of the present invention, the constellation configuration optimization design using a genetic algorithm includes:

[0202] 1) Determine the optimization objective and design the fitness function;

[0203] The optimization objectives are divided into two cases: one is to require the minimum number of satellites for a given performance, and the other is to require the best performance for a given number of satellites;

[0204] Given the minimum number of satellites required for performance, the minimum number of satellites required to achieve uninterrupted revisit of the target area within the set time t is the fitness function:

[0205] score=-N-μ∑(1-χ) (5)

[0206] Among them, score represents fitness; N is the number of satellites; μ is the penalty coefficient; χ is the success rate of revisiting each point target;

[0207] When the performance is optimal for a given number of satellites, the target area is revisited at a maximum success rate of not less than time t under the set number of satellites. The fitness function is expressed as:

[0208] score=-μ∑(1-χ) (6)

[0209] Among them, μ is the penalty coefficient;

[0210] 2) Based on the result of step 1), a genetic algorithm is used for optimization to obtain the optimal solution of the constellation characteristic parameters under the set constellation configuration.

[0211] This enables the rapid generation of a constellation configuration that meets performance requirements based on the set coverage range and revisit time requirements, optimizing the satellite constellation design while ensuring computational efficiency.

[0212] To implement the above embodiment, a third aspect of the present invention provides an electronic device, including:

[0213] at least one processor; and a memory communicatively coupled to the at least one processor;

[0214] The memory stores instructions that can be executed by the at least one processor, and the instructions are configured to execute the above-mentioned constellation configuration optimization method.

[0215] To implement the above embodiment, a fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the above constellation configuration optimization method.

[0216] It should be noted that the computer-readable medium mentioned above in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or component. In the present disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0217] The computer-readable medium may be included in the electronic device, or may exist independently and not incorporated into the electronic device. The computer-readable medium carries one or more programs. When executed by the electronic device, the one or more programs cause the electronic device to perform the constellation configuration optimization method of the above-mentioned embodiment.

[0218] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0219] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" 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 can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0220] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of such features. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0221] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0222] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing it in a suitable manner if necessary, and then storing it in a computer memory.

[0223] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0224] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0225] In addition, each of the functional units in the various embodiments of the present application can be integrated in one processing module, or each of the units can be physically present separately, or two or more units can be integrated in one module. The integrated module can be realized in the form of hardware or in the form of a software functional module. When the integrated module is realized in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer readable storage medium.

[0226] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A constellation configuration optimization method, characterized in that: include: Establish a valid point set consisting of evenly distributed points for the target area on the earth's surface covered by the satellite constellation; Taking each point in the valid point set as a point target for constellation access, and calculating the visibility window of a single satellite to be involved in the constellation configuration for each point target; Performing a coverage performance analysis of the constellation based on the visibility window to obtain a revisit success rate corresponding to each point target; Based on the success rate of achieving revisit, a constellation configuration optimization design is performed using a genetic algorithm to obtain an optimal solution for constellation characteristic parameters under the set constellation configuration; The effective point set is constructed as follows: Let X be a random variable uniformly distributed in the range [-1, 1], and Y represent the latitude value of any point in the target area, by mapping X to: Y=arcsin(X) (1) Get a random distribution related to latitude; Among them, the number of points in the latitude interval of the target area N Y It is proportional to the area of ​​the interval on the surface of the earth, that is: N Y =numof(X∈[sin(Y min ),without(And max )]) (3) N Y ∝sin(And max )-sin(And min )≈ΔYcos(Y) (4) Among them, Y min and Y max They represent the minimum and maximum latitudes in the target area, respectively. ΔY represents the latitude interval [Y min ,Y max ], ΔY=Y max -Y min ; The point set generated according to formula (1) that is consistent with the change of the earth's surface area with latitude is the valid point set.

2. The method according to claim 1, characterized in that The calculating of the visibility window of each point target from a single satellite to be involved in the constellation configuration includes: 1) Based on the simulated observation mission of any satellite in the constellation configuration for the target area, the simulation period is divided into: The first segment is from the start time of the simulation observation mission to the maximum latitude point of the satellite's first pass through the target area. The i-th segment is from the maximum latitude point of the satellite's i-1th pass through the target area to the i-th pass through the maximum latitude point. i ≥ 2. The last segment is from the maximum latitude point of the satellite's last pass through the target area to the end time of the simulation observation mission. The entire time of the satellite's orbit advancement is discretized into m equal parts, resulting in a total of m+1 discrete time points. The time sequence composed of all discrete time points is t i ,i=1,2,...m+1, where i=1 corresponds to the start time and i=m+1 corresponds to the end time; 2) Based on the results of step 1), calculate each discrete time point t i Whether each point target is within the visible range of the satellite; Among them, if at t i If any target point is within the visible range of the satellite at time t, then the satellite is judged to be i The target is always visible to the point; otherwise it is invisible; 3) Based on the result of step 2), obtain the satellite's visibility window for each point target; For any point target, the judgment starts from i=1: if the satellite is at t i The target is visible at this time, at t i-1 The target is not visible at this moment, then t i The time when the satellite's visible window to the target begins; if the satellite is at t i-1 The target is visible at this time, at t i If the time is not visible, then t i The time when the satellite's visibility window for the target point ends is determined until i=m+1, thereby obtaining the satellite's visibility window for the target point. 4) Repeat steps 1) to 3) to obtain the visibility window of each satellite to be involved in the constellation configuration to each point in the valid point set.

3. The method according to claim 2, characterized in that Also includes: If the distance between any satellite and the ground is H, then the geocentric angle corresponding to the maximum visible range of the satellite is: Among them, R e is the radius of the Earth; The preset maximum threshold of the line of sight angle between the satellite and the point target is Then determine: If the line of sight angle between the satellite and any target is greater than the preset maximum threshold Then the point target is not within the satellite’s visual range; If the line of sight angle between the satellite and any target point is equal to or less than Then the point target is within the visible range of the satellite.

4. The method according to claim 2, characterized in that The constellation configuration optimization design using a genetic algorithm includes: 1) Determine the optimization objective and design the fitness function; The optimization objectives are divided into two cases: one is to require the minimum number of satellites for a given performance, and the other is to require the best performance for a given number of satellites; Given the minimum number of satellites required for performance, the minimum number of satellites required to achieve uninterrupted revisit of the target area within the set time t is the fitness function: score=-N-μ∑(1-χ) (5) Among them, score represents fitness; N is the number of satellites; μ is the penalty coefficient; χ is the success rate of revisiting each point target; When the performance is optimal for a given number of satellites, the target area is revisited at a maximum success rate of not less than time t under the set number of satellites. The fitness function is expressed as: score=-μ∑(1-χ) (6) Among them, μ is the penalty coefficient; 2) Based on the result of step 1), a genetic algorithm is used for optimization to obtain the optimal solution of the constellation characteristic parameters under the set constellation configuration.

5. A constellation configuration optimization device, characterized in that: include: The effective point set construction module is used to establish an effective point set consisting of evenly distributed scattered points for the target area on the earth's surface covered by the satellite constellation; a visibility window calculation module, configured to take each point in the valid point set as a point target to be accessed by the constellation, and calculate the visibility window of a single satellite to be involved in the constellation configuration for each point target; a coverage performance analysis module, configured to perform coverage performance analysis of the constellation based on the visibility window to obtain a revisit success rate corresponding to each point target; A constellation configuration optimization module is used to optimize the constellation configuration design using a genetic algorithm based on the success rate of achieving revisit, so as to obtain an optimal solution for constellation characteristic parameters under the set constellation configuration; The effective point set is constructed as follows: Let X be a random variable uniformly distributed in the range [-1, 1], and Y represent the latitude value of any point in the target area, by mapping X to: Y=arcsin(X) (1) Get a random distribution related to latitude; Among them, the number of points in the latitude interval of the target area N Y It is proportional to the area of ​​the interval on the surface of the earth, that is: N Y =numof(X∈[sin(Y min ),without(And max )]) (3) N Y ∝sin(And max )-sin(And min )≈ΔYcos(Y) (4) Among them, Y min and Y max They represent the minimum and maximum latitudes in the target area, respectively. ΔY represents the latitude interval [Y min ,Y max ], ΔY=Y max -Y min ; The point set generated according to formula (1) that is consistent with the change of the earth's surface area with latitude is the valid point set.

6. The device according to claim 5, characterized in that The calculating of the visibility window of each point target from a single satellite to be involved in the constellation configuration includes: 1) Based on the simulated observation mission of any satellite in the constellation configuration for the target area, the simulation period is divided into: The first segment is from the start time of the simulation observation mission to the maximum latitude point of the satellite's first pass through the target area. The i-th segment is from the maximum latitude point of the satellite's i-1th pass through the target area to the i-th pass through the maximum latitude point. i ≥ 2. The last segment is from the maximum latitude point of the satellite's last pass through the target area to the end time of the simulation observation mission. The entire time of the satellite's orbit advancement is discretized into m equal parts, resulting in a total of m+1 discrete time points. The time sequence composed of all discrete time points is t i ,i=1,2,...m+1, where i=1 corresponds to the start time and i=m+1 corresponds to the end time; 2) Based on the results of step 1), calculate each discrete time point t i Whether each point target is within the visible range of the satellite; Among them, if at t i If any target point is within the visible range of the satellite at time t, then the satellite is judged to be i The target is always visible to the point; otherwise it is invisible; 3) Based on the result of step 2), obtain the satellite's visibility window for each point target; For any point target, the judgment starts from i=1: if the satellite is at t i The target is visible at this time, at t i-1 The target is not visible at this moment, then t i The time when the satellite's visible window to the target begins; if the satellite is at t i-1 The target is visible at this time, at t i If the time is not visible, then t i The time when the satellite's visibility window for the target point ends is determined until i=m+1, thereby obtaining the satellite's visibility window for the target point. 4) Repeat steps 1) to 3) to obtain the visibility window of each satellite to be involved in the constellation configuration to each point in the valid point set.

7. The device according to claim 6, characterized in that Also includes: If the distance between any satellite and the ground is H, then the geocentric angle corresponding to the maximum visible range of the satellite is: Among them, R e is the radius of the Earth; The preset maximum threshold of the line of sight angle between the satellite and the point target is Then determine: If the line of sight angle between the satellite and any target is greater than the preset maximum threshold Then the point target is not within the satellite’s visual range; If the line of sight angle between the satellite and any target point is equal to or less than Then the point target is within the visible range of the satellite.

8. The device according to claim 6, characterized in that The constellation configuration optimization design using a genetic algorithm includes: 1) Determine the optimization objective and design the fitness function; The optimization objectives are divided into two cases: one is to require the minimum number of satellites for a given performance, and the other is to require the best performance for a given number of satellites; Given the minimum number of satellites required for performance, the minimum number of satellites required to achieve uninterrupted revisit of the target area within the set time t is the fitness function: score=-N-μ∑(1-χ) (5) Among them, score represents fitness; N is the number of satellites; μ is the penalty coefficient; χ is the success rate of revisiting each point target; When the performance is optimal for a given number of satellites, the target area is revisited at a maximum success rate of not less than time t under the set number of satellites. The fitness function is expressed as: score=-μ∑(1-χ) (6) Among them, μ is the penalty coefficient; 2) Based on the result of step 1), a genetic algorithm is used for optimization to obtain the optimal solution of the constellation characteristic parameters under the set constellation configuration.

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