Robust inter-satellite dynamic link establishment planning method and device based on adaptive optimization

Abstract

The invention discloses a robust inter-satellite dynamic link establishment planning method and device based on adaptive optimization, and belongs to the field of inter-satellite link establishment planning, and the method comprises the steps: S1, obtaining the position of a satellite and the positions of other satellites in each time slot, and generating a visibility matrix; s2, constructing an inter-satellite dynamic link establishment optimization model to obtain to-be-optimized parameters and an optimization objective function; s3, generating a link establishment planning scheme by using a distributed optimization scheme in combination with a sparrow search optimization algorithm and a pruning strategy; and S4, inter-satellite link establishment is carried out based on the optimized link establishment scheme, and measurement and communication functions are realized. The problems that a fixed link establishment method is poor in autonomy and robustness, and a traditional heuristic algorithm is low in optimization efficiency and poor in optimization performance are solved.

Description

Technical Field

[0001] The present invention relates to the field of inter-satellite link planning, and more specifically, to a robust inter-satellite dynamic link planning method and device based on adaptive optimization. Background Art

[0002] With the rapid development of inter-satellite links, inter-satellite link technology can effectively improve the accuracy and autonomous operation ability of the global satellite constellation system, reduce the dependence on ground stations, and is the main development direction of the new generation of navigation systems.

[0003] In order to enhance the capabilities of inter-satellite links, it is necessary to further optimize the link planning between navigation satellites, thereby improving the geometric distribution factor (PDOP) of the links, while ensuring the connectivity of satellites inside and outside the country to the greatest extent, and enabling satellites outside the country to quickly relay back to the country through inter-satellite links. Currently, the mainstream link establishment scheme adopts a ground station-assisted fixed link establishment mode. The ground operation and control system generates a time slot allocation table for a future period at a certain period, uploads and distributes it to all satellites, and the satellites plan link establishment based on the uploaded time allocation table. However, the fixed link establishment mode requires the support of ground stations and has poor flexibility. Once a satellite in the constellation fails, it is impossible to quickly recover by adjusting the link establishment plan, reducing the impact of the failed satellite node on the performance of the entire network. Although some current research works adopt heuristic algorithms such as simulated annealing, with maximizing the system efficiency as the objective function, to autonomously generate link establishment planning strategies on the satellite. However, most current heuristic algorithms cannot take into account the constraint conditions in the link establishment strategy, and have low optimization efficiency and are prone to falling into local optima. How to improve the efficiency and robustness of the autonomous generation of inter-satellite link planning schemes is a difficult problem that needs to be solved urgently. Summary of the Invention

[0004] The purpose of the present invention is to overcome the deficiencies of the prior art, and provide a robust inter-satellite dynamic link planning method and device based on adaptive optimization, which solves the problems of poor autonomy and weak robustness of the fixed link establishment method, as well as low optimization efficiency and poor optimization performance of traditional heuristic algorithms.

[0005] The purpose of the present invention is achieved through the following solutions:

[0006] A robust inter-satellite dynamic link planning method based on adaptive optimization, comprising the following steps:

[0007] S1, generating a visibility matrix according to the position of the satellite itself and the positions of other satellites in each time slot;

[0008] S2, constructing an inter-satellite dynamic link establishment optimization model to obtain the parameters to be optimized and the optimization objective function;

[0009] S3. Use a distributed optimization scheme combined with the sparrow search optimization algorithm and pruning strategy to generate a link establishment planning scheme;

[0010] S4. Based on the optimized link establishment scheme, perform inter-satellite link establishment and implement measurement and communication functions.

[0011] Further, in step S1, the generating of the visibility matrix according to the positions of the satellite itself and other satellites obtained in each time slot specifically includes the following sub-steps:

[0012] The inter-satellite link uses a time-division system for communication. The same satellite establishes a connection with one satellite node within the same time interval, thus forming a non-fully connected network topology. In the time slot division, the entire planning time period is divided into N superframes. Within each superframe, link establishment is carried out with multiple different satellites at fixed time slot intervals, and the number of link establishment time slots is M. In each link establishment time slot, two-way ranging is adopted, divided into two equal-length segments for transmission and reception operations respectively. At the beginning of each superframe, the visibility matrix V is generated by obtaining the positions of the satellite itself and other satellites, and the link establishment strategy for the next superframe is planned.

[0013] Further, in step S2, the constructing of the inter-satellite dynamic link establishment optimization model to obtain the parameters to be optimized and the optimization objective function specifically includes the following sub-steps:

[0014] According to the visibility matrix and the current link establishment situation, construct a distributed collaborative inter-satellite dynamic link establishment optimization model, expressed as follows:

[0015]

[0016] Among them, AJ(·) is the optimization objective function composed of the network average PDOP and the maximum number of hops of the overseas-domestic satellite transmission, L n ∈N×N×M is the link topology matrix of satellite n in M time slots of each superframe, N n is the adjacent node of satellite n, V∈N×N is the visibility matrix, when link establishment is possible v ij =1, when link establishment is not possible v ij =0, and V satisfies the matrix symmetry constraint; at the same time, link establishment can only be carried out when the visibility constraint between satellites is satisfied, and only one satellite can be linked in each time slot; at this time, the parameter to be optimized L = [L1,..., L n ,..., L N is the link establishment planning strategy of each satellite.

[0017] Further, in step S3, the using of the distributed optimization scheme combined with the sparrow search optimization algorithm and pruning strategy to generate a link establishment planning scheme specifically includes the following sub-steps:

[0018] Use the regularization term To achieve local consensus among neighbor nodes, by ensuring that the constellation topology is fully connected within a superframe, the global policy consistency can be satisfied:

[0019] Furthermore, in step S3, the use of the distributed optimization scheme combined with the sparrow search optimization algorithm and pruning strategy to generate a link establishment planning scheme specifically includes the following sub-steps:

[0020] First, initialize the maximum number of iterations T max , the population size NUM_pop, the discovery population ratio PD, the warning group ratio SD, and the warning threshold R; randomly initialize L n And calculate the objective function values for sorting to find the individuals with the minimum and maximum values;

[0021] Then, when updating the position of the discovery group, modify the update method of the original sparrow algorithm to a slow step towards the optimal position, expressed as:

[0022]

[0023] where t is the current iteration number, is the link establishment strategy of individual i at the t-th iteration, G + 1 is a normal random distribution number obeying (1,1), G is a normal random distribution number obeying (0,1), and η ∈ [0.5,1] is the safety threshold;

[0024] Express the update of the follower group position as:

[0025]

[0026] where L worst and are the individuals in the worst position and the local optimal position in the t-th iteration and the (t + 1)-th iteration respectively, A is a multi-dimensional matrix with all elements being 1, is a column vector with all elements being 1;

[0027] Express the update of the warning group position as:

[0028]

[0029] where, is the current optimal link establishment strategy, β is a step-size controllable random number obeying (0,1) distribution; λ is a uniform random number in the range of [-1,1], representing the wandering direction; f i 、f local and f worst are the objective function value, the local optimal objective function value, and the worst objective function value of individual i respectively.

[0030] Further, in step S3, the use of the distributed optimization scheme in combination with the sparrow search optimization algorithm and the pruning strategy to generate the link establishment planning scheme specifically includes the following sub-steps:

[0031] After updating the positions of the population, a Gaussian mutation operator is introduced to perturb the global optimal solution obtained in each iteration, which is specifically expressed as follows:

[0032]

[0033] Among them, is the optimal solution after Gaussian mutation, is the current global optimal solution, and Gauus is a random vector subject to a Gaussian distribution with a mean of 0 and a variance of 1.

[0034] Further, in step S3, the use of the distributed optimization scheme in combination with the sparrow search optimization algorithm and the pruning strategy to generate the link establishment planning scheme specifically includes the following sub-steps:

[0035] After performing Gaussian mutation, the Cauchy mutation algorithm is fused to realize the communication feedback between the worst individual and the best individual, which is expressed as follows:

[0036] L' worst = L worst - Caushy × (L gbest - L worst );

[0037] Among them, Caushy is a random variable that satisfies the Cauchy distribution.

[0038] Further, in step S3, the use of the distributed optimization scheme in combination with the sparrow search optimization algorithm and the pruning strategy to generate the link establishment planning scheme specifically includes the following sub-steps:

[0039] After obtaining the global optimal solution L gbest , by pruning the one-to-one mapping of the initial link establishment planning table and the link establishment constraint table, the final link topology is generated

[0040] A robust inter-satellite dynamic link establishment planning device based on adaptive optimization includes a processor and a memory. A computer program is stored in the memory. When the computer program is loaded and executed by the processor, the method described in any one of the above is performed.

[0041] The beneficial effects of the present invention include:

[0042] The method of the present invention first constructs an optimization model according to the inter-satellite link establishment constraints and the optimization objective function, and based on a distributed optimization scheme combined with the sparrow optimization algorithm, realizes the autonomous optimization of on-orbit satellites to generate link establishment schemes through an efficient initialization strategy and a pruning strategy based on sub-optimal solutions, improving the capabilities of inter-satellite links and the robustness of the network.

[0043] The method of the present invention reduces the dependence on ground stations through an on-board autonomous distributed collaborative optimization link establishment strategy, reduces the processing difficulty of on-board autonomous planning, and improves the link establishment efficiency and the overall robustness of the network. Compared with the traditional fixed planning link establishment method, in the presence of abnormal nodes, the method proposed by the present invention can effectively reduce the impact of abnormal nodes on inter-satellite links and improve the average PDOP of the network and the average number of hops from overseas to domestic; compared with the schemes based on other heuristic optimization algorithms (dung beetle algorithm (DIDBO), lion group algorithm (DALO), simulated annealing algorithm (DSA)), the method proposed by the present invention has obvious improvements in both the network average PDOP and the average number of hops from overseas to domestic. Brief Description of the Drawings

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0045] Figure 1 It is a flowchart of the implementation steps for adaptive inter-satellite dynamic link establishment planning;

[0046] Figure 2 It is a schematic diagram of time slot division under the time division link establishment system;

[0047] Figure 3 It is a schematic diagram of distributed collaborative optimization link establishment planning;

[0048] Figure 4 It is a schematic diagram of the pruning operation for link establishment planning;

[0049] Figure 5 It is a schematic diagram of the optimization process for adaptive inter-satellite dynamic link establishment planning based on the improved sparrow algorithm;

[0050] Figure 6 It is a graph of the network average PDOP varying with time in the presence of abnormal nodes;

[0051] Figure 7 It is a graph of the average number of hops from overseas to domestic varying with time in the presence of abnormal nodes;

[0052] Figure 8 It is a graph of the network average PDOP varying with time for different algorithms;

[0053] Figure 9 The figure shows the average number of hops from overseas to domestic for different algorithms over time. Detailed implementation manner

[0054] All features disclosed in all embodiments in this specification, or all steps in all methods or processes implicitly disclosed, except for mutually exclusive features and / or steps, can be combined and / or extended, replaced in any manner.

[0055] In a preferred embodiment, the present invention specifically addresses the deficiencies of existing fixed link establishment and traditional heuristic optimization methods, and provides an adaptive inter-satellite dynamic link establishment planning method based on rapid optimization. As Figure 1 shown, the method includes the following steps:

[0056] S1. According to the positions of the satellite itself and other satellites obtained in each time slot, generate a visibility matrix;

[0057] S2. Construct an inter-satellite dynamic link establishment optimization model to obtain the parameters to be optimized and the optimization objective function;

[0058] S3. Use a distributed optimization scheme combined with a sparrow search optimization algorithm and a pruning strategy to generate a link establishment planning scheme.

[0059] S4. Optimize the link establishment planning scheme, and perform inter-satellite link establishment based on the optimized link establishment scheme to implement measurement and communication functions.

[0060] Among them, the distributed optimization model satisfies the following relational expressions:

[0061]

[0062] Among them, AJ(·) is the optimization objective function composed of the network average PDOP and the maximum number of hops of satellite transmission from overseas to domestic, L n ∈N×N×M is the link topology matrix of M time slots in each superframe of satellite n, N n is the adjacent node of satellite n, V∈N×N is the visibility matrix, when the link can be established, v ij =1, when the link cannot be established, v ij =0, and V satisfies the matrix symmetry constraint; at the same time, the link establishment scheme needs to satisfy the link establishment constraint, that is, the satellites need to satisfy the visibility constraint to establish a link, and only one satellite can be linked in each time slot.

[0063] In a further implementation manner, the present invention uses a distributed optimization scheme, an improved sparrow optimization algorithm and a pruning strategy to solve the above problems, realizes on-satellite autonomous dynamic link establishment planning, reduces the dependence on the ground station, and enhances the robustness of the entire inter-satellite network. The specific implementation measures are as follows.

[0064] 1. The original problem is solved using a distributed optimization scheme. By reaching local consensus with adjacent nodes, global optimization is achieved, as shown in Figure 2 . Through the distributed optimization scheme, the problem of excessive load on the central node during centralized computing can be avoided, and the computing power requirement for a single satellite node can be reduced.

[0065] 2. An improved sparrow optimization algorithm is used to optimize the link establishment planning scheme on a single satellite node. By means of an efficient initialization strategy based on suboptimal solutions, an improved position update strategy, and a Gaussian mutation strategy, the search ability is enhanced, and the defects of the original algorithm, such as slow optimization speed, reduced population diversity, and easy entrapment in local optima, are solved.

[0066] 3. To address the problem that it is difficult to directly constrain the link establishment planning table through an optimization algorithm, by pruning the one-to-one mapping of the initial link establishment planning table and the link establishment constraint table, an optimal link topology can be generated quickly and accurately.

[0067] Specifically, the following steps are executed:

[0068] Step 1: The inter-satellite link uses a time-division system for communication. In the same time interval, a satellite can only establish a connection with one satellite node, thus forming a non-fully connected network topology. The time slot division scheme is as shown in Figure 2 . The entire planning time period is divided into N superframes. In each superframe, link establishment is carried out with multiple different satellites at fixed time slot intervals, and the number of link establishment time slots is M. Bidirectional ranging is used within each link establishment time slot, which is divided into two equal-length segments for transmission and reception operations respectively. At the beginning of each superframe, a visibility matrix V is generated by obtaining its own position and the positions of other satellites, and the link establishment strategy for the next superframe is planned. According to the visibility matrix and the current link establishment situation, a distributed collaborative link establishment optimization model is constructed, which is expressed as follows:

[0069]

[0070] Among them, AJ(·) is an optimization objective function composed of the network average PDOP and the maximum number of hops for satellite transmission outside and inside the country. L n ∈N×N×M is the link topology matrix of satellite n in M time slots of each superframe. N n is the adjacent node of satellite n. V∈N×N is the visibility matrix. When a link can be established, v ij =1, and when a link cannot be established, v ij =0, and V satisfies the matrix symmetry constraint. At the same time, the link establishment scheme needs to satisfy the link establishment constraint, that is, a link can only be established between satellites when the visibility constraint is met, and only one satellite can be connected in each time slot.

[0071] At this time, the parameter to be optimized is L = [L1,...,Ln ,...,L N ] is the link establishment planning strategy for each satellite.

[0072] Step 2: In order to quickly find the optimal solution while ensuring the consistency of different satellite link planning strategies, the present invention adds a regularization term to the optimization objective (2). To reach a local consensus among neighboring nodes, global policy consistency can be achieved by ensuring that the constellation topology is fully connected within a superframe: like Figure 3 shown.

[0073] Step 3: For satellite n, in order to quickly search for the optimal solution in the feasible solution space, the present invention adopts the improved sparrow algorithm to solve. In the sparrow algorithm, there are discovery groups, following groups and warning groups, among which the discovery group searches the solution space through random walks; the following group follows the discoverer and searches near it to improve the search efficiency; the warning group issues an alarm when the warning value is greater than the safety value to prevent the solution from converging in the wrong direction.

[0074] First, initialize the maximum number of iterations T max , population size NUM_pop, discovered population ratio PD = 20%, warning population ratio SD = 20%, warning threshold R. Randomly initialize L n And calculate the objective function value to sort and find the individuals with minimum and maximum values.

[0075] Step 4: When updating the position of the discovered group, in order to avoid the defect of the traditional sparrow algorithm converging to the origin, the update method is modified to a slow step toward the optimal position, which is expressed as:

[0076]

[0077] Where t is the current iteration number, is the chain building strategy of individual i in the tth iteration, G+1 is a normal random distribution number obeying (1,1), G is a normal random distribution number obeying (0,1), and η∈[0.5,1] is the safety threshold.

[0078] The position update of the following group is expressed as:

[0079]

[0080] Where L worst and are the individuals in the worst position and the local optimal position in the t-th iteration and the t+1-th iteration, respectively. A is a multidimensional matrix with all elements being 1. is a column vector whose elements are all 1.

[0081] The updated position of the warning group is expressed as:

[0082]

[0083] where is the current optimal link - building strategy, β is a step - size controllable random number following a (0,1) distribution,; λ is a uniform random number in the range [-1,1], representing the walking direction; f i 、f local and f worst are the objective function value, the local optimal objective function value, and the worst objective function value of individual i, respectively.

[0084] Step 5: After updating the group position, in order to prevent the algorithm from falling into local optimality, a Gaussian mutation operator is introduced to perturb the globally optimal solution obtained in each iteration. It is specifically expressed as follows:

[0085]

[0086] where is the optimal solution after Gaussian mutation, is the current globally optimal solution, and Gauus is a random vector following a Gaussian distribution with a mean of 0 and a variance of 1.

[0087] In order to reduce the search ability of the individual with the worst objective function value, a Cauchy mutation algorithm is integrated to realize the communication feedback between the worst individual and the best individual, which is expressed as follows:

[0088] L' worst = L worst - Caushy×(L gbest - L worst ) (7);

[0089] where Caushy is a random variable satisfying the Cauchy distribution.

[0090] Step 6: After obtaining the globally optimal solution L gbest , by pruning the one - to - one mapping of the initial link - building plan table and the link - building constraint table, the final link topology is generated as Figure 4 shown.

[0091] Step 7: According to Steps 1 - 6, first initialize the population and the initial parameters of the algorithm; calculate the objective function value according to the objective function; update the position according to equations (3), (4), and (5) respectively; perform Gaussian mutation on the globally optimal position according to equation (6), and perform Cauchy mutation on the globally worst position according to (7); and repeat the above steps until the termination condition is met, and output the globally optimal solution L gbest , and obtain the best link topology through pruning measurement The overall algorithm flow is asFigure 5 as shown

[0092] The performance results of the adaptive inter-satellite dynamic link establishment planning method based on fast optimization in the embodiments of the present invention are respectively as Figures 6 - 9 shown. From Figure 6 and Figure 7 it can be seen that at 6.5h - 13.5h, satellites 11 and 15 have anomalies, and at 21h - 22.5h, satellites 7 and 13 have anomalies. Since the traditional link establishment planning method cannot adaptively adjust for abnormal nodes, the performance drops significantly during the relevant time periods; while the DSSA algorithm (self-named term) proposed in the present invention can autonomously avoid abnormal nodes through a distributed cooperation method, adaptively optimize the link establishment topology, and the performance basically has no obvious change. From Figure 8 and Figure 9 it can be seen that compared with other heuristic optimization algorithms (DIDBO, DALO, DSA), the link establishment strategy optimized by the algorithm proposed in the present invention has obvious performance advantages in both the network average PDOP and the average number of out-of-country - in-country hops.

[0093] It should be noted that within the scope of protection defined in the claims of the present invention, the following embodiments can all be combined and / or extended, replaced in any logical manner from the above specific implementation manners, such as the disclosed technical principles, disclosed technical features or implicitly disclosed technical features, etc.

[0094] Embodiment 1

[0095] A robust inter-satellite dynamic link establishment planning method based on adaptive optimization, comprising the following steps:

[0096] S1. According to the satellite's own position and the positions of other satellites obtained in each time slot, generate a visibility matrix;

[0097] S2. Construct an inter-satellite dynamic link establishment optimization model to obtain the parameters to be optimized and the optimization objective function;

[0098] S3. Use a distributed optimization scheme combined with the sparrow search optimization algorithm and a pruning strategy to generate a link establishment planning scheme;

[0099] S4. Based on the optimized link establishment scheme, perform inter-satellite link establishment and implement measurement and communication functions.

[0100] Embodiment 2

[0101] On the basis of Embodiment 1, in step S1, the generating a visibility matrix according to the satellite's own position and the positions of other satellites obtained in each time slot specifically includes the following sub-steps:

[0102] The inter-satellite link uses a time-division system for communication. The same satellite establishes a connection with a satellite node within the same time interval, thus forming a non-fully connected network topology. In the time slot division, the entire planned time period is divided into N superframes. Within each superframe, connections are established with multiple different satellites at fixed time slot intervals, and the number of link establishment time slots is M. In each link establishment time slot, two-way ranging is adopted and divided into two equal-length segments for transmission and reception operations respectively. At the beginning of each superframe, a visibility matrix V is generated by obtaining its own position and the positions of other satellites, and the link establishment strategy for the next superframe is planned.

[0103] Embodiment 3

[0104] Based on Embodiment 2, in step S2, the construction of the inter-satellite dynamic link establishment optimization model to obtain the parameters to be optimized and the optimization objective function specifically includes the following sub-steps:

[0105] According to the visibility matrix and the current link establishment situation, a distributed collaborative inter-satellite dynamic link establishment optimization model is constructed, which is expressed as follows:

[0106]

[0107] Among them, AJ(·) is the optimization objective function composed of the network average PDOP and the maximum number of hops of overseas-domestic satellite transmission, L n ∈N×N×M is the link topology matrix of M time slots in each superframe of satellite n, N n is the adjacent node of satellite n, V∈N×N is the visibility matrix, when the link can be established v ij = 1, when the link cannot be established v ij = 0, and V satisfies the matrix symmetry constraint; at the same time, the satellites need to meet the visibility constraint to establish a link, and only one satellite can be linked in each time slot; at this time, the parameter to be optimized L = [L1,..., L n ,..., L N is the link establishment planning strategy for each satellite.

[0108] Embodiment 4

[0109] Based on Embodiment 3, in step S3, the use of the distributed optimization scheme combined with the sparrow search optimization algorithm and the pruning strategy to generate the link establishment planning scheme specifically includes the following sub-steps:

[0110] Using the regularization term to achieve local consensus among neighbor nodes, by ensuring that the constellation topology is fully connected within one superframe, that is, the global policy consistency can be satisfied:

[0111] Embodiment 5

[0112] Based on Embodiment 3, in step S3, the use of the distributed optimization scheme in combination with the sparrow search optimization algorithm and the pruning strategy to generate the link establishment planning scheme specifically includes the following sub-steps:

[0113] First, initialize the maximum number of iterations T max , the population size NUM_pop, the discovery population ratio PD, the warning population ratio SD, and the warning threshold R; randomly initialize L n and calculate the objective function values for sorting to find the individuals with the minimum and maximum values;

[0114] Then, when updating the position of the discovery group, modify the update method of the original sparrow algorithm to a slow step towards the optimal position, expressed as:

[0115]

[0116] where t is the current iteration number, is the link establishment strategy of individual i in the t-th iteration, G + 1 is a normal random distribution number obeying (1,1), G is a normal random distribution number obeying (0,1), and η ∈ [0.5,1] is the safety threshold;

[0117] Express the update of the follower group position as:

[0118]

[0119] where L worst and are the individuals in the worst position and the local optimal position in the t-th iteration and the (t + 1)-th iteration respectively, A is a multi-dimensional matrix with all elements being 1, is a column vector with all elements being 1;

[0120] Express the update of the warning group position as:

[0121]

[0122] where, is the current optimal link establishment strategy, β is a step-size controllable random number obeying (0,1) distribution; λ is a uniform random number in the range of [-1,1], representing the walking direction; f i 、f local and f worst are the objective function value, the local optimal objective function value, and the worst objective function value of individual i respectively.

[0123] Embodiment 6

[0124] Based on Embodiment 5, in step S3, the method of generating a link establishment planning scheme by combining a distributed optimization scheme with a sparrow search optimization algorithm and a pruning strategy specifically includes the following sub-steps:

[0125] After updating the positions of the population, a Gaussian mutation operator is introduced to perturb the globally optimal solution obtained in each iteration, which is specifically expressed as follows:

[0126]

[0127] where, is the optimal solution after Gaussian mutation, is the current globally optimal solution, and Gauus is a random vector obeying a Gaussian distribution with a mean of 0 and a variance of 1.

[0128] Embodiment 7

[0129] Based on Embodiment 6, in step S3, the method of generating a link establishment planning scheme by combining a distributed optimization scheme with a sparrow search optimization algorithm and a pruning strategy specifically includes the following sub-steps:

[0130] After performing Gaussian mutation, a Cauchy mutation algorithm is fused to realize the communication feedback between the worst individual and the best individual, which is expressed as follows:

[0131] L' worst = L worst - Caushy × (L gbest - L worst );

[0132] where, Caushy is a random variable satisfying the Cauchy distribution.

[0133] Embodiment 8

[0134] Based on Embodiment 7, in step S3, the method of generating a link establishment planning scheme by combining a distributed optimization scheme with a sparrow search optimization algorithm and a pruning strategy specifically includes the following sub-steps:

[0135] After obtaining the globally optimal solution L gbest , by pruning the one-to-one mapping of the initial link establishment planning table and the link establishment constraint table, the final link topology is generated

[0136] Embodiment 9

[0137] A robust inter-satellite dynamic link establishment planning device based on adaptive optimization includes a processor and a memory. A computer program is stored in the memory. When the computer program is loaded and executed by the processor, the method according to any one of Embodiments 1 to 8 is performed.

[0138] The units involved in the embodiments of the present invention can be implemented in software or in hardware, and the described units can also be provided in a processor. Among them, the names of these units do not constitute a limitation on the units themselves in some cases.

[0139] According to one aspect of the embodiments of the present invention, there is provided a computer program product or a computer program, the computer program product or the computer program including computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in the above various alternative implementation manners.

[0140] As another aspect, the embodiments of the present invention further provide a computer-readable medium, which may be included in the electronic device described in the above embodiments; or may exist alone without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the one or more programs are executed by an electronic device, the electronic device implements the methods described in the above embodiments.

Claims

1. A robust inter-satellite dynamic link establishment planning method based on adaptive optimization, characterized in that It includes the following steps: S1. According to the satellite's own position and the positions of other satellites obtained in each time slot, generate a visibility matrix; S2. Construct an inter-satellite dynamic link establishment optimization model to obtain the parameters to be optimized and the optimization objective function; S3. Use a distributed optimization scheme combined with a sparrow search optimization algorithm and a pruning strategy to generate a link establishment planning scheme; S4. Based on the optimized link establishment scheme, perform inter-satellite link establishment and implement measurement and communication functions.

2. The robust inter-satellite dynamic link establishment planning method based on adaptive optimization according to claim 1, wherein In step S1, the generating of the visibility matrix according to the satellite's own position and the positions of other satellites obtained in each time slot specifically includes the following sub-steps: The inter-satellite link uses a time-division system for communication. The same satellite establishes a connection with a satellite node within the same time interval, thus forming a non-fully connected network topology. In the time slot division, the entire planning time period is divided into N superframes. Within each superframe, link establishment is carried out with multiple different satellites at fixed time slot intervals, and the number of link establishment time slots is M. In each link establishment time slot, two-way ranging is adopted, which is divided into two equal-length segments for transmission and reception operations respectively; At the beginning of each superframe, generate a visibility matrix V by obtaining the satellite's own position and the positions of other satellites, and plan the link establishment strategy for the next superframe.

3. The robust inter-satellite dynamic link establishment planning method based on adaptive optimization according to claim 2, wherein In step S2, the constructing of the inter-satellite dynamic link establishment optimization model to obtain the parameters to be optimized and the optimization objective function specifically includes the following sub-steps: According to the visibility matrix and the current link establishment situation, construct a distributed cooperative inter-satellite dynamic link establishment optimization model, which is expressed as follows: Among them, AJ(·) is the optimization objective function composed of the network average PDOP and the maximum number of hops of satellite transmission from overseas to domestic, and L n ∈N×N×M is the link topology matrix of M time slots in each superframe of satellite n, and N n is the adjacent node of satellite n, V∈N×N is the visibility matrix, and v ij =1 when a link can be established, and v ij =0 when a link cannot be established, and V satisfies the matrix symmetry constraint; at the same time, a link can only be established between satellites when the visibility constraint is met, and only one satellite can be linked in each time slot; at this time, the parameter to be optimized L = [L1,..., L n ,..., L N is the link establishment planning strategy for each satellite.

4. The robust inter-satellite dynamic link establishment planning method based on adaptive optimization according to claim 3, wherein In step S3, the generating of the link establishment planning scheme by using a distributed optimization scheme combined with a sparrow search optimization algorithm and a pruning strategy specifically includes the following sub-steps: Using regular terms to achieve local consensus among neighbor nodes. By ensuring that the constellation topology is fully connected within a superframe, global policy consistency can be satisfied:

5. The robust inter-satellite dynamic link establishment planning method based on adaptive optimization according to claim 3, wherein, In step S3, the generating of the link establishment planning scheme by using a distributed optimization scheme combined with a sparrow search optimization algorithm and a pruning strategy specifically includes the following sub-steps: First, initialize the maximum number of iterations T max , the population size NUM_pop, the discovery population ratio PD, the warning population ratio SD, and the warning threshold R; randomly initialize L n And calculate the objective function values for sorting, and find the individuals with the minimum and maximum values; Then, when updating the discovered group position, modify the update method of the original sparrow algorithm to a slow step towards the optimal position, which is expressed as: where t is the current iteration number, is the chain-building strategy of individual i in the t-th iteration, G+1 is a normally distributed random number following (1,1), G is a normally distributed random number following (0,1), and η∈[0.5,1] is the safety threshold; Express the update of the follower group position as: Among them, L worst and are individuals in the worst position and the local optimal position in the t-th iteration and the (t + 1)-th iteration respectively. A is a multi-dimensional matrix with all elements being 1, is a column vector with all elements being 1; Express the update of the warning group position as: Among them, is the current optimal chain building strategy, β is a step size controllable random number obeying the (0,1) distribution; λ is a uniform random number within the range of [-1,1], representing the walking direction; f i , f local and f worst are the objective function value, the local optimal objective function value and the worst objective function value of individual i respectively.

6. The robust inter-satellite dynamic link establishment planning method based on adaptive optimization according to claim 5, wherein, In step S3, the generating of the link establishment planning scheme by using a distributed optimization scheme combined with a sparrow search optimization algorithm and a pruning strategy specifically includes the following sub-steps: After updating the group position, introduce a Gaussian mutation operator to perturb the global optimal solution obtained in each iteration, which is specifically expressed as follows: Among them, is the optimal solution after Gaussian mutation, is the current global optimal solution, and Gauus is a random vector following a Gaussian distribution with a mean of 0 and a variance of 1.

7. The robust inter-satellite dynamic link establishment planning method based on adaptive optimization according to claim 6, wherein In step S3, the generating of the link establishment planning scheme by using a distributed optimization scheme combined with a sparrow search optimization algorithm and a pruning strategy specifically includes the following sub-steps: After performing Gaussian mutation, fuse the Cauchy mutation algorithm to realize the communication feedback between the worst individual and the best individual, which is expressed as follows: L' worst = L worst - Caushy × (L gbest - L worst ); Where Caushy is a random variable that satisfies the Cauchy distribution.

8. The method for robust inter-satellite dynamic link establishment planning based on adaptive optimization according to claim 7, characterized in that In step S3, the generating of the link establishment planning scheme by using a distributed optimization scheme combined with a sparrow search optimization algorithm and a pruning strategy specifically includes the following sub-steps: After obtaining the global optimal solution L gbest After pruning the one-to-one mapping of the initial link establishment planning table and the link establishment constraint table, the final link topology is generated 9. A robust inter-satellite dynamic link establishment planning device based on adaptive optimization, characterized in that, It includes a processor and a memory. The memory stores a computer program, and when the computer program is loaded and executed by the processor, it performs the method according to any one of claims 1 to 8.

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