Inter-satellite network route planning method for multi-satellite relay information

Abstract

The invention relates to an inter-satellite network route planning method for multi-satellite relay information. The inter-satellite network route planning method comprises the following steps: S1, establishing a multi-satellite relay forwarding system model; s2, establishing an inter-satellite communication relation graph with a weight value; and S3, solving the optimal route of the multi-satellite network based on a Bellman-Ford minimum cost routing algorithm. According to the method, the problem that an optimal network route is difficult to find among a plurality of inter-satellite links in the presence of interference is solved, and the effectiveness of the proposed routing algorithm is verified by comparing the network throughput rate with other network routing algorithms.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-satellite relay, and in particular to an inter-satellite network routing planning method for multi-satellite relay information. Background Art

[0002] The satellite information system transmits acquired sensing information to the data center, which then transmits various information, including link status, to the control center. The control center, after making comprehensive decisions, issues commands, which are then transmitted via the communications network to the Ground Data Processing and Access Center. After data formatting, the data is sent to the satellite relay platform via the data center management station. After receiving the commands, the satellite communication terminal collaborates with the satellite control module and onboard computer to complete satellite control. Multiple satellites serving as relay platforms are crucial for command transmission and control. However, satellites are highly susceptible to interference, which can affect the transmission and reception of information. Therefore, intersatellite network routing requires careful planning and design to avoid interference-prone satellites and ensure the quality of information transmission.

[0003] When designing intersatellite network routing, to ensure information transmission quality, satellites experiencing interference should be excluded and transmission routes should be planned among the remaining satellites. Furthermore, the characteristics of satellite network routing and command requirements should be considered to ensure a more robust network and better transmission performance. Summary of the Invention

[0004] To address the technical problems existing in the above-mentioned prior art, the present invention aims to provide an inter-satellite network routing planning method for multi-satellite relay information, which is compatible with traditional routing calculation algorithms, has high deployability, and provides effective inter-satellite routing planning in the presence of satellite interference. The effectiveness of the proposed routing algorithm is verified by comparing the network throughput with other network routing algorithms.

[0005] To achieve the above-mentioned object, the present invention provides a method for planning inter-satellite network routing for multi-satellite relay information, comprising the following steps:

[0006] The following steps are involved:

[0007] Step S1: Establish a system model of multiple satellite relay forwarding;

[0008] Step S2: establishing an intersatellite communication relationship diagram with weights;

[0009] Step S3: Calculate the optimal routing of the multi-satellite network based on the Bellman-Ford minimum cost routing algorithm.

[0010] According to a technical solution of the present invention, step S2 specifically includes:

[0011] Step S21: defining a cost function based on multiple factors affecting the optimal route, and calculating the cost functions of different routes;

[0012] Step S22: convert the multi-satellite network system model into a weighted graph.

[0013] According to a technical solution of the present invention, step S21 specifically includes:

[0014] Step S211: parameterize the path delay of the influencing factor and express it as:

[0015]

[0016] td ij for ISL ij Information transmission delay, tb i is the information queuing time of satellite i; then tb i Expressed as:

[0017]

[0018] Among them, A it , q(i) and P t They are satellite channel capacity, queue occupancy, and packet size;

[0019] Step S212: Parameterize the duration of the impact factor path and model the path P. s,d The duration T s,d Expressed as:

[0020]

[0021] Among them, T ij ISL ij The duration of the ,is directly calculated from the satellite's motion parameters;

[0022] Step S213: Parameterize the maximum path bandwidth of the impact factor so that the path P s,d The maximum path bandwidth is expressed as:

[0023]

[0024] Among them, β i is the feasible bandwidth of path i, λ i =e lat / 90 is the available bandwidth adjustment factor, lat is the latitude of the earth;

[0025] Step S214: parameterize the signal-to-interference-noise ratio of the impact factor path and define that in a certain path, if the interference received by a certain satellite k is Interference(k), then in path P i,j In the example, satellite i and satellite j are the starting point and the end point of the path respectively, then the path P s,d The interference received is expressed as:

[0026]

[0027] Step S215: Parameterize the discharge index of the impact factor and model the path P s,d The overall depth of discharge is expressed as:

[0028]

[0029] Among them, ξ i is the discharge depth of satellite i; Indicates whether the satellite is in the Earth's shadow during routing;

[0030] Step S216: Based on the parameter model defined above, the cost on a single link is expressed as:

[0031] Q ij =a×τ i，j +b×T i,j +c×β i,j +d×Interf i,j +e×η i,j

[0032] Among them, a, b, c, d, and e are used to adjust each factor to an appropriate magnitude and weight it;

[0033] Step S217: Calculate the overall cost function of the intersatellite link on a path according to the satellite network topology. s,d The overall cost is expressed as:

[0034]

[0035] Among them, P s,d is the set of paths from satellite s to satellite d, I ij is the link indicator function, which indicates whether the link from one node to another node is included in the routing path and is defined as:

[0036]

[0037] According to a technical solution of the present invention, step S22 specifically includes:

[0038] Step S221: construct an undirected graph of the satellite intersatellite network;

[0039] Step S222: Construct a weighted multi-satellite network graph.

[0040] According to a technical solution of the present invention, step S222 specifically includes:

[0041] Step S222a: Calculate the cost function of each intersatellite link;

[0042] Step S222b: The intersatellite network is represented by an undirected graph G = (V, E), where V represents the set of satellite nodes in the network and E represents the set of intersatellite links in the network; the edges are then weighted, and the weights are the cost functions of the intersatellite links.

[0043] According to a technical solution of the present invention, step S3 specifically includes:

[0044] Step S31: Calculate the optimal network route using the Bellman-Ford minimum cost routing algorithm;

[0045] Step S32: Update the satellite network information and repeat step S31.

[0046] According to a technical solution of the present invention, step S31 specifically includes:

[0047] In the given graph G(V,E), the source point is s, and the array dist[i] records the path length from the source point to node i;

[0048] During initialization, dist[0] in the dist[i] array is 0, and the remaining elements are infinite;

[0049] For each edge e(u,v), relaxation calculation is performed. If dist[u]+Q uv <dist[v], then let dist[v]=dist[u]+Q uv , where Q uv is the weight of edge e(u,v);

[0050] The comparison and update operation of the dist[.] array elements is repeated n-1 times;

[0051] If the dist[.] array is not updated after the above operation is repeated n-1 times, the shortest path has been found.

[0052] According to a technical solution of the present invention, in step S32, updating the satellite network information specifically includes:

[0053] Step S321: Regularly synchronize the status and topology of each satellite in each LEO satellite network by setting an orbital announcement collection and forwarding satellite in each orbital plane;

[0054] Step S322: When a satellite in the network is disconnected due to interference or damage, the path containing the disconnected link in the original routing table will be deleted from the routing table;

[0055] Step S323: When any target request arrives at the satellite, if no path that meets the request is found in the routing table, a corresponding route is generated in real time using the minimum cost routing algorithm and updated to the routing table.

[0056] According to one aspect of the present invention, an electronic device is provided, comprising: one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs are stored in the memory. When the electronic device is running, the processor executes the one or more computer programs stored in the memory, so that the electronic device executes an inter-satellite network routing planning method for multi-satellite relay information as described in any one of the above technical solutions.

[0057] According to one aspect of the present invention, a computer-readable storage medium is provided for storing computer instructions. When the computer instructions are executed by a processor, an inter-satellite network routing planning method for multi-satellite relay information is implemented as described in any one of the above technical solutions.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] The present invention proposes an inter-satellite network routing planning method for multi-satellite relay information. When multiple satellites relay information, the network routing problem is modeled as a directed graph problem, and the Bellman-Ford minimum cost routing algorithm is used to solve the multi-satellite network routing in interference scenarios. This solves the problem of difficulty in finding an optimal network route among multiple inter-satellite links in the presence of interference. The method is compatible with traditional routing calculation algorithms, has high deployability, and provides effective inter-satellite routing planning in the presence of satellite interference. The effectiveness of the proposed routing algorithm is verified by comparing the network throughput with other network routing algorithms.

[0060] The present invention uses the performance fluctuation of satellite nodes subjected to interference as an important basis for link delay changes, and expands the traditional inter-satellite routing algorithm to a more realistic scenario.

[0061] The present invention can effectively characterize network performance by comparing link throughput rates, and realizes inter-satellite routing calculation based on interference perception.

[0062] The present invention supports high, medium and low multi-orbit satellite networks and can improve network throughput in an anti-interference manner, thus having great practical significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be derived from these drawings without inventive effort.

[0064] Figure 1 A schematic diagram illustrating an overall flow chart of a method for planning inter-satellite network routing for multi-satellite relay information according to an embodiment of the present invention;

[0065] Figure 2 Schematically showing a schematic diagram of a satellite constellation structure simulation according to one embodiment of the present invention;

[0066] Figure 3 A diagram schematically showing an inter-satellite communication relationship according to an embodiment of the present invention;

[0067] Figure 4 A diagram schematically showing a weighted intersatellite communication relationship according to an embodiment of the present invention;

[0068] Figure 5 Schematically illustrates three different routing solutions Path0, Path1, and Path2 according to an embodiment of the present invention;

[0069] Figure 6 Schematically represents the path output of all routes according to one embodiment of the present invention;

[0070] Figure 7 Schematically showing the cost comparison of various routes according to one embodiment of the present invention;

[0071] Figure 8 Schematically showing a comparison of throughputs of three different routing solutions Path0, Path1, and Path2 according to an embodiment of the present invention;

[0072] Figure 9 The figure schematically shows four different routing schemes Path0, Path1, and Path2 according to an embodiment of the present invention, and a comparison of the throughput of Path2 after interference removal. DETAILED DESCRIPTION

[0073] The description of the embodiments in this specification should be combined with the corresponding drawings, which should be considered a complete part of this specification. In the drawings, the shapes and thicknesses of the embodiments may be exaggerated and indicated for simplicity or convenience. Furthermore, the various structural components in the drawings will be described separately. It is worth noting that components not shown in the drawings or not described in words are known to those of ordinary skill in the art.

[0074] The description of the embodiments herein and any references to directions and orientations are for ease of description only and are not to be construed as limiting the scope of the present invention. The following description of the preferred embodiments may involve combinations of features, which may exist independently or in combination. The present invention is not specifically limited to the preferred embodiments. The scope of the present invention is defined by the claims.

[0075] like Figure 1 and Figure 2 As shown, a method for planning inter-satellite network routing for multi-satellite relay information of the present invention comprises the following steps:

[0076] Step S1: Establish a system model of multiple satellite relays, including multiple GEO satellites, MEO satellites, and LEO satellites; Figure 2 The satellite constellation simulation diagram shown shows a total of 162 satellites: 3 GEO satellites; 27 MEO satellites; and 132 LEO satellites, including 36 polar-orbiting LEO satellites and 96 circular-inclined LEO satellites. Based on this model, we will build a weighted graph for the satellite network and perform network routing planning.

[0077] Step S2: establishing an intersatellite communication relationship diagram with weights;

[0078] Step S3: Calculate the optimal routing of the multi-satellite network based on the Bellman-Ford minimum cost routing algorithm.

[0079] When multiple satellites relay information, the network routing problem is modeled as a directed graph problem, and the Bellman-Ford minimum cost routing algorithm is used to solve the multi-satellite network routing in interference scenarios. This solves the problem of finding an optimal network route between multiple inter-satellite links in the presence of interference. It is compatible with traditional routing calculation algorithms and has high deployability. It provides effective inter-satellite routing planning in the presence of satellite interference. The effectiveness of the proposed routing algorithm is verified by comparing the network throughput with other network routing algorithms.

[0080] The performance fluctuations of satellite nodes affected by interference are used as an important basis for changes in link delay, and the traditional inter-satellite routing algorithm is extended to more realistic scenarios.

[0081] By comparing link throughput, the performance of the network can be effectively characterized, and inter-satellite routing calculation based on interference perception is realized.

[0082] It supports high, medium and low multi-orbit satellite networks; it can improve network throughput in an anti-interference manner, which has great practical significance.

[0083] In some embodiments of the present invention, step S2 specifically includes:

[0084] Step S21: defining a cost function based on multiple factors affecting the optimal route, and calculating the cost functions of different routes, including parameterized modeling of the influencing factor path delay, parameterized modeling of the influencing factor path duration, parameterized modeling of the influencing factor maximum path bandwidth, parameterized modeling of the influencing factor path signal-to-interference-noise ratio, and parameterized modeling of the influencing factor discharge index.

[0085] Step S22: converting the multi-satellite network system model into a weighted graph, specifically including:

[0086] Step S221: construct an undirected graph of the satellite intersatellite network;

[0087] Step S222: Construct a weighted multi-satellite network graph.

[0088] A reasonable optimal route must consider many factors in the routing link, including path delay, duration, channel bandwidth, channel quality, and discharge time. The purpose of a routing algorithm is to first define a cost function that accounts for the combined impact of these various factors, then calculate the cost functions for different routes, and finally, from among the many possible routes, find the route that minimizes the cost function.

[0089] In some embodiments of the present invention, step S21 specifically includes:

[0090] Step S211: parameterize the path delay of the influencing factor and express it as:

[0091]

[0092] td ij for ISL ij Information transmission delay, tb i is the information queuing time of satellite i; then tb i Expressed as:

[0093]

[0094] Among them, A it , q(i) and P tThey are satellite channel capacity, queue occupancy, and packet size;

[0095] Step S212: Parameterize the duration of the impact factor path and model the path P. s,d The duration T s,d Expressed as:

[0096]

[0097] Among them, T ij ISL ij The duration of the ,is directly calculated from the satellite's motion parameters;

[0098] Step S213: Parameterize the maximum path bandwidth of the impact factor so that the path P s,d The maximum path bandwidth is expressed as:

[0099]

[0100] Among them, β i is the feasible bandwidth of path i, λ i =e lat / 90 is the available bandwidth adjustment factor, lat is the latitude of the earth;

[0101] Step S214: parameterize the signal-to-interference-noise ratio of the impact factor path and define that in a certain path, if the interference received by a certain satellite k is Interference(k), then in path P i,j In the example, satellite i and satellite j are the starting point and the end point of the path respectively, then the path P s,d The interference received is expressed as:

[0102]

[0103] Step S215: Parameterize the discharge index of the impact factor and model the path P s,d The overall depth of discharge is expressed as:

[0104]

[0105] Among them, ξ i is the discharge depth of satellite i; Indicates whether the satellite is in the Earth's shadow during routing;

[0106] Step S216: Based on the parameter model defined above, the cost on a single link is expressed as:

[0107] Q ij =a×τ i,j +b×T i,j +c×βi,j +d×Interf i,j +e×η i,j

[0108] Among them, a, b, c, d, and e are used to adjust each factor to an appropriate magnitude and weight it;

[0109] Step S217: Calculate the overall cost function of the intersatellite link on a path according to the satellite network topology. s,d The overall cost is expressed as:

[0110]

[0111] Among them, P s,d is the set of paths from satellite s to satellite d, I ij is the link indicator function, which indicates whether the link from one node to another node is included in the routing path and is defined as:

[0112]

[0113] In some embodiments of the present invention, step S222 specifically includes:

[0114] Step S222a: Calculate the cost function of each intersatellite link;

[0115] Step S222b: The intersatellite network is represented by an undirected graph G = (V, E), where V represents the set of satellite nodes in the network and E represents the set of intersatellite links in the network; the edges are then weighted, and the weights are the cost functions of the intersatellite links.

[0116] Weight the cost function on each path to Figure 3 The intersatellite communication diagram shown in the figure shows Figure 4 The weighted intersatellite communication relationship diagram shown.

[0117] In some embodiments of the present invention, step S3 specifically includes:

[0118] Step S31: Calculate the optimal network route using the Bellman-Ford minimum cost routing algorithm;

[0119] Step S32: Update the satellite network information and repeat step S31.

[0120] In some embodiments of the present invention, step S31 specifically includes:

[0121] In the given graph G(V,E), the source point is s, and the array dist[i] records the path length from the source point to node i;

[0122] During initialization, dist[0] in the dist[i] array is 0, and the remaining elements are infinite;

[0123] For each edge e(u,v), relaxation calculation is performed. If dist[u]+Q uv <dist[v], then let dist[v]=dist[u]+Q uv , where Q uv is the weight of edge e(u,v);

[0124] The comparison and update operation of the dist[.] array elements is repeated n-1 times;

[0125] If the dist[.] array is not updated after the above operation is repeated n-1 times, the shortest path has been found.

[0126] The Bellman-Ford minimum cost routing algorithm and parameter settings in step S31 are described as follows:

[0127] Table 1 Minimum cost routing algorithm based on Bellman-Ford

[0128]

[0129] Some of the simulation parameter settings involved are shown in Table 2 and Table 3:

[0130] Table 2 Simulation parameter settings

[0131]

[0132] Table 3 Satellite simulation settings

[0133]

[0134] The simulation scenario is set to satellite communication in the Ka band. The maximum distance threshold for direct communication between satellites is set to 1000km. That is, if the distance between two satellites exceeds this threshold, the two satellites cannot communicate directly and need to rely on other satellites for relay. If the value is set larger, more satellites will be able to communicate directly, and the satellite network scale will be larger.

[0135] In some embodiments of the present invention, in step S32, updating the satellite network information specifically includes:

[0136] Step S321: Regularly synchronize the status and topology of each satellite in each LEO satellite network by setting an orbital announcement collection and forwarding satellite in each orbital plane;

[0137] Step S322: When a satellite in the network is disconnected due to interference or damage, the path containing the disconnected link in the original routing table will be deleted from the routing table;

[0138] Step S323: When any target request arrives at the satellite, if no path that meets the request is found in the routing table, a corresponding route is generated in real time using the minimum cost routing algorithm and updated to the routing table.

[0139] To verify the superiority of the proposed algorithm, this embodiment conducted simulations based on the theoretical content described above. The simulations first used the path derived by the proposed algorithm as Path0 (considering both inter-satellite distance and interference, minimizing the weighted sum of these factors). This was then compared with two other different paths: Path1 (considering only inter-satellite interference, minimizing the interference experienced by the satellites) and Path2 (considering only inter-satellite distance, minimizing the path distance). The algorithm's superiority was then verified. The shortest path was then determined by comparing the results of other routing verification algorithms. Finally, the necessity of anti-interference was verified by comparing Path2 in the interference removal mode.

[0140] The simulation sets the starting satellite (source node satellite) number of the route to 34, and after running the main program of the routing part, the following is obtained: Figure 5 As shown. Figure 5 It can be seen that the command line window will output the path prompt between the source node satellite and the target node satellite. Figure 5 Three different routes, Path0, Path1, and Path2, are output, corresponding to the three different solutions described above. In the simulation, we assume that satellite 60 is subject to interference. Both Path0 and Path1 avoid satellite 60. Although Path2 offers the shortest distance, it cannot avoid the interference. Therefore, the optimal path is Path0, which minimizes the weighted sum of the inter-satellite distance and interference, by considering both the inter-satellite distance and the interference.

[0141] Figure 6 The code output shows all possible paths between the source and destination satellites. The routes in the table show that most routes have more than eight hops. Due to the large scale of satellite networks, the source node may transmit to the destination node via multiple hops. The permutations and combinations of multiple relay satellites result in an excessive number of possible routes. As the number of relay hops increases, the route distance increases, and therefore the routing cost. This result is based on a maximum inter-satellite communication distance threshold of 1000 km. For larger inter-satellite communication distance thresholds, the total number of routes will increase as the network scale increases.

[0142] Figure 7Fifteen routes are randomly selected and compared with the routing algorithm designed by the present invention. It can be seen that under the same cost modeling, the route selected by the BellmanFord algorithm has the shortest path selectivity.

[0143] Figure 8 The figure shows a comparison of throughput achieved by three different schemes. The green curve represents the multi-satellite network routing algorithm designed by this invention, namely Path 0; the blue curve represents the algorithm that only considers inter-satellite interference, namely Path 1; and the red curve represents the algorithm that only considers inter-satellite distance, namely Path 2.

[0144] from Figure 8 It can be seen that Path0 > Path1 > Path2. This phenomenon occurs because when modeling the routing cost, we consider both the inter-satellite distance and satellite interference. The greater the inter-satellite distance, the greater the routing cost, and the greater the satellite interference, the greater the routing cost. Therefore, if a satellite in a route is subject to interference, the cost of that route will be high, and the Bellman Ford algorithm will not select that path during execution, thus avoiding the interference. The shortest-distance route selected by considering only the inter-satellite distance does not consider satellite interference. Although the transmission distance is the lowest, the impact of interference will also lead to lower throughput. The route selected by considering only interference, while avoiding the impact of interference, has a longer transmission distance, resulting in greater losses and reduced throughput. Therefore, the algorithm proposed in this invention considers both the inter-satellite distance and satellite interference, combining the advantages of the other two solutions and achieving better throughput performance.

[0145] Figure 9 The black curve represents Path 2, which is free from interference at the physical layer. The throughput achieved by Path 2 is compared with that of Path 0, Path 1, and Path 2. In the absence of interference, Path 2 has the highest throughput, while the throughput of Path 0 with interference mitigation is close to that of Path 2, demonstrating the necessity of interference mitigation in this invention.

[0146] Experiments show that the optimal network routing algorithm proposed in this embodiment can find the optimal routing path while resisting interference and improve network throughput.

[0147] According to one aspect of the present invention, an electronic device is provided, comprising: one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs are stored in the memory. When the electronic device is running, the processor executes the one or more computer programs stored in the memory, so that the electronic device executes an inter-satellite network routing planning method for multi-satellite relay information as described in any one of the above technical solutions.

[0148] According to one aspect of the present invention, a computer-readable storage medium is provided for storing computer instructions. When the computer instructions are executed by a processor, an inter-satellite network routing planning method for multi-satellite relay information is implemented as described in any one of the above technical solutions.

[0149] Computer-readable storage media may include any medium capable of storing or transmitting information. Examples of computer-readable storage media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, and the like. The code segments may be downloaded via a computer network such as the Internet, an intranet, and the like.

[0150] The present invention provides a method for planning intersatellite network routing for multi-satellite relay information, comprising the following steps: Step S1: establishing an infrared characteristic characterization model for an aerial target and a full-link simulation model for a space-based infrared detection system; Step S2: analyzing the spectral radiation intensity of the aerial target and the background; Step S3: statistically analyzing the target detection contrast and detection energy acquisition factors based on the aerial target infrared characteristic characterization model to determine a preferred detection spectrum segment; and Step S4: jointly optimizing the target motion velocity limit, earth background limit, and detection sensitivity of the space-based infrared detection system based on the preferred detection spectrum segment. The present invention establishes a full-link simulation model for space-based infrared detection that considers the spatiotemporal differential characteristics of aerial target motion within the integration time and the detector pixel response model. By analyzing the spectral radiation intensity of the aerial target and the complex earth background, the detection spectrum segment is optimized by comprehensively considering the target detection contrast and detection energy acquisition factors. Finally, referring to a modular detection efficiency evaluation method, the system parameters are traversed and optimized considering the two boundary conditions of the integration time background limit and the target motion velocity limit, achieving the optimal design of the detection system parameters for a specific photoelectric detector, providing a theoretical basis for high-sensitivity detection of aerial targets under a complex infrared earth background and system parameter design.

[0151] Furthermore, it should be noted that the present invention may be provided as a method, apparatus, or computer program product. Thus, embodiments of the present invention may take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media containing computer-usable program code.

[0152] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the process in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0153] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for implementing the process in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0154] It should also be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or terminal device comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or terminal device comprising the element.

[0155] Finally, it should be noted that the above is a preferred embodiment of the present invention. It should be noted that although the preferred embodiment of the present invention has been described, it is clear that those skilled in the art, once they understand the basic inventive concept of the present invention, can make various improvements and modifications without departing from the principles of the present invention. Such improvements and modifications should also be considered as within the scope of protection of the present invention. Therefore, the appended claims are intended to be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the embodiments of the present invention.

Claims

1. A method for planning intersatellite network routing for multi-satellite relay information, characterized in that: The following steps are involved: Step S1, establishing a system model of multiple satellite relay forwarding; Step S2, establishing an inter-satellite communication relationship diagram with weights; Step S3: solving the optimal routing of the multi-satellite network based on the Bellman-Ford minimum cost routing algorithm.

2. The inter-satellite network routing planning method for multi-satellite relay information according to claim 1, characterized in that: The step S2 specifically includes: Step S21, defining a cost function based on multiple factors affecting the optimal route, and calculating the cost functions of different routes; Step S22: convert the multi-satellite network system model into a weighted graph.

3. The inter-satellite network routing planning method for multi-satellite relay information according to claim 2, characterized in that: The step S21 specifically includes: Step S211: parameterize the path delay of the influencing factor and express it as: td ij For ISL ij Information transmission delay, tb i is the information queuing time of satellite i; then tb i It is expressed as: Among them, A it , q(i) and P t They are satellite channel capacity, queue occupancy, and packet size; Step S212: Parameterize the duration of the impact factor path and model the path P s,d The duration T s,d It is expressed as: Among them, T ij ISL ij The duration of the ,is calculated directly from the satellite's motion parameters; Step S213: parameterize the maximum path bandwidth of the influencing factor so that path P s,d The maximum path bandwidth is expressed as: in, βi is the feasible bandwidth of path i, λ i =e lat / 90 is the available bandwidth adjustment factor, lat is the latitude of the earth; Step S214: parameterize the signal-to-interference-to-noise ratio of the influencing factor path, and define that in a certain path, if a certain satellite k is subject to interference (k), in path P i,j In the example, satellite i and satellite j are the starting point and end point of the path respectively. Then the path P s,d The interference is expressed as: Step S215: parameterize the discharge index of the influencing factor, path P s,d The overall depth of discharge is expressed as: Among them, ξ i is the discharge depth of satellite i; Indicates whether the satellite is in the Earth's shadow during routing; Step S216: Based on the parameter model defined above, the cost on a single link is expressed as: Q ij =a×τ i,j +b×T i,j +c×β i,j +d×Interf i,j +e×η i,j Among them, a, b, c, d, and e are used to adjust each factor to a suitable order of magnitude and weight it; Step S217: Calculate the overall cost function of the intersatellite link on a path according to the satellite network topology. s, The overall cost of d is expressed as: Among them, P s,d is the set of paths from satellite s to satellite d, I ij is the link indicator function, indicating whether the link from one node to another node is included in the routing path, and is defined as:

4. The method for planning intersatellite network routing for multi-satellite relay information according to claim 3, characterized in that: The step S22 specifically includes: Step S221, constructing an undirected graph of the satellite intersatellite network; Step S222: construct a weighted multi-satellite network graph.

5. The method for planning intersatellite network routing for multi-satellite relay information according to claim 4, characterized in that: The step S222 specifically includes: Step S222a, calculating the cost function of each intersatellite link; Step S222b, the intersatellite network is represented by an undirected graph G=(V,E), where V represents the set of satellite nodes in the network, and E represents the set of intersatellite links in the network; and then the edges are weighted, and the weight is the cost function of the intersatellite link.

6. The method for planning intersatellite network routing for multi-satellite relay information according to claim 3, characterized in that: The step S3 specifically includes: Step S31, using Bellman-Ford's minimum cost routing algorithm to calculate the best network route; Step S32: Update satellite network information and repeat step S31.

7. The method for planning intersatellite network routing for multi-satellite relay information according to claim 6, characterized in that: The step S31 specifically includes: In the given graph G(V,E), the source point is s, and the array dist[i] records the path length from the source point to node i; During initialization, dist[0] in the dist[i] array is 0, and the remaining elements are infinite; For each edge e(u,v), relax the calculation. If dist[u]+Q uv <dist[v], then let dist[v]=dist[u]+Q uv , where Q uv is the weight of edge e(u,v); The comparison and update operation of dist[.] array elements is looped n-1 times; If the dist[.] array is not updated after the above operation is repeated n-1 times, the shortest path has been found.

8. The method for planning intersatellite network routing for multi-satellite relay information according to claim 6, characterized in that: In step S32, updating the satellite network information specifically includes: Step S321, by setting an orbital announcement collection and forwarding satellite in each orbital plane, regularly synchronize the status and topology of each satellite in each LEO satellite network; Step S322: When a satellite in the network is disconnected due to interference or damage, the path containing the disconnected link in the original routing table will be deleted from the routing table; Step S323: When any target request arrives at the satellite, if no path matching the request is found in the routing table, a corresponding route is generated in real time through the minimum cost routing algorithm and updated to the routing table.

9. An electronic device, characterized in that: include: One or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs are stored in the memory. When the electronic device is running, the processor executes the one or more computer programs stored in the memory, so that the electronic device executes the inter-satellite network routing planning method for multi-satellite relay information as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, implement the inter-satellite network routing planning method for multi-satellite relay information as described in any one of claims 1 to 8.

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