A method and system for sampling a topology of a dual-layer satellite constellation network with controllable delay jitter

Abstract

This invention discloses a two-layer satellite constellation network topology sampling method and system with controllable delay jitter. It primarily addresses the problem that existing technologies suffer from inaccurate discrete topology delay jitter representation due to the highly dynamic operation of low-Earth orbit satellite networks, failing to meet the delay error constraints of deterministic services. The implementation scheme involves: acquiring the basic constellation parameters of the two-layer satellites and preset service error tolerances; obtaining the network physical motion limit characteristics within and between layers; constructing a total jitter rate physical model reflecting the upper limit of the cumulative delay jitter characteristics of the entire network; mapping the service error tolerance to the maximum safe sampling time step that meets physical fidelity requirements, and using this time step to periodically capture network states, generating a discrete topology snapshot sequence with a time continuity index. This invention improves the accuracy of delay representation in discrete topology modeling, ensuring that the sampled sequence meets the requirements of deterministic networks, and can be used for protocol design, performance evaluation, and system simulation of highly dynamic satellite networks.

Description

Technical Field

[0001] This invention belongs to the field of satellite communication technology, and further relates to a two-layer satellite constellation network topology sampling method and system, which can be used for routing planning and simulation verification of satellite networks. Background Technology

[0002] Large-scale low-Earth orbit (LEO) satellite networks are the core infrastructure for building an integrated space-ground information network and achieving seamless global coverage. Due to the high-speed motion of satellites, the network topology changes dynamically over time. To effectively simulate, verify, and optimize the routing protocols, resource allocation, and end-to-end performance of satellite networks, it is typically necessary to discretize the continuous-time network topology, generating a series of discrete-time topology snapshots. Satellite network topology discretization sampling is a fundamental step in network operation and routing planning; without effective discretization sampling, subsequent routing calculations are impossible. Existing fixed-time-interval sampling methods struggle to adapt to changes in link latency within the network. If the interval is too large, it fails to capture transient changes in link states; if the interval is too small, computational redundancy occurs. While event-driven non-fixed-time-interval sampling can reflect connection status, it ignores the actual performance changes of links caused by high-speed relative motion during connection maintenance. Existing methods often rely on high-frequency time-domain evolution simulations, making it difficult to find a balance between ensuring end-to-end latency jitter accuracy and controlling the amount of computational data. This trade-off between accuracy and efficiency is directly reflected in the design flaws of existing topology discretization sampling methods.

[0003] Patent document CN202011572897.7 proposes a control method based on topology time slot partitioning and snapshot deduplication. It effectively reduces the number of redundant time slices and lowers simulation storage and computational overhead by comparing the topology of adjacent time slots and merging snapshots with differences less than a preset threshold. However, this method primarily focuses on the physical connectivity of topological connections. Its core assumption is that the network state is considered stable as long as the connected graph structure remains unchanged or similar. Because it ignores the continuous and drastic changes in the physical length and propagation delay of links in high-speed relative motion scenarios in heterogeneous or multi-layered satellite networks, even if the connectivity remains unchanged, the generated discrete topology sequence severely loses crucial end-to-end delay jitter characteristics, making it difficult to meet the high-fidelity simulation requirements of latency-sensitive services such as real-time control and high-frequency trading.

[0004] Patent document CN202511504089.X discloses a fast topology sampling method based on geometric event-driven sampling. It utilizes constellation configuration parameters and the geometric patterns of satellites traversing critical latitude regions to determine the dynamic timing of topology changes, significantly improving sampling efficiency compared to fixed-step sampling. However, because it still relies on the geometric periodicity of a specific constellation configuration, its applicability to multi-layered hybrid constellations is poor. More importantly, this method only captures topology dynamics from a macroscopic geometric perspective, failing to incorporate the maximum latency jitter caused by relative speed, which reflects network service quality, into the sampling constraints. This results in the inability to provide a theoretical upper bound guarantee for network performance jitter in simulations. When high-speed inter-layer links exist in the network, the coarse sampling granularity can easily lead to severe performance evaluation errors. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of the existing technology by proposing a two-layer satellite constellation network topology sampling method and system with controllable time delay jitter. This improves the accuracy of discrete topology modeling in representing time delay jitter, thereby achieving effective control over end-to-end time delay jitter in the network topology and ensuring that the sampled model meets the requirements of deterministic networks.

[0006] The idea behind this invention is to shift the sampling basis from network connectivity to the kinematic characteristics of link performance, analyze the physical limits of intra-layer heterogeneous motion and inter-layer cross-layer motion in a two-layer satellite network, and construct a physical model of total jitter rate that reflects the upper limit of the cumulative latency jitter characteristics of the entire network. Using this model, the deterministic latency error tolerance of the service side is quantitatively mapped to the maximum safe sampling time step that meets the physical fidelity requirements, and the mapping from physical motion limits to sampling frequency is performed to achieve effective control of end-to-end latency jitter of the network topology.

[0007] Based on the above ideas, the technical solution of the present invention includes:

[0008] 1. A method for topology sampling of a two-layer satellite constellation network with controllable delay jitter, characterized in that it includes:

[0009] Based on the basic orbit, constellation configuration, and error tolerance parameters of the multi-layer satellite network, the physical limit characteristics of the network within and between layers are obtained, and a physical model of total jitter rate reflecting the upper limit of the cumulative delay jitter characteristics of the entire network is constructed.

[0010] The maximum safe time step under different service tolerances is determined based on the jitter rate model, and the two-layer satellite network is discretized accordingly.

[0011] Furthermore, the physical model for constructing the total jitter rate, which reflects the upper limit of the cumulative latency jitter characteristics of the entire network, includes:

[0012] 3a) Calculate the cumulative jitter rate component within the layer ;

[0013] 3b) Based on the maximum relative velocity between layers Calculate the interlayer cumulative jitter rate component ;

[0014] 3c) Linearly superimpose the cumulative jitter rate components within and between layers to obtain a physical model of total jitter rate that reflects the upper limit of the cumulative delay jitter characteristics of the entire network. .

[0015] Furthermore, the determination of the maximum safe time step under different service tolerances based on the jitter rate model is based on the speed of light in a vacuum. User-defined end-to-end latency jitter error tolerance and total jitter rate Calculated.

[0016] Furthermore, the discretization sampling of the two-layer satellite network based on the maximum safe time step includes the following implementation:

[0017] 6a) Using the maximum safe time step as the sampling period, periodically capture the dynamic operation process of the dual-layer satellite constellation;

[0018] 6b) Obtain real-time status data of all satellites in the network at each captured sampling time, including the instantaneous spatial position of the satellite in the inertial coordinate system, the velocity vector of motion, and the connection status of the link;

[0019] 6c) Organize the state data extracted at each sampling time according to the time series to generate a series of discrete topological snapshots.

[0020] 2. A two-layer satellite constellation network topology sampling system with controllable time delay jitter, characterized in that it comprises:

[0021] The physical feature extraction module is used to obtain the network physical limit features of the maximum relative velocity of single-layer different orbits within a layer and the maximum relative velocity between layers, based on the basic orbital parameters, constellation configuration parameters, and end-to-end delay jitter error tolerance parameters allowed by the service protocol of the multi-layer satellite network, through dynamic model establishment and differential evolution optimization.

[0022] The sampling step size determination module is used to construct a total jitter rate physical model that reflects the upper limit of the cumulative delay jitter characteristics of the entire network by linearly superimposing the cumulative jitter rate components of the intra-layer and inter-layer networks based on the network physical limit characteristics of the intra-layer and inter-layer networks, and to calculate the maximum safe time step size that meets the physical fidelity requirements using the total jitter rate physical model and the preset error tolerance.

[0023] The sampling execution module is used to periodically capture the dynamic operation process of the two-layer satellite constellation with the maximum safe time step as the sampling period, and generate a series of discrete topological snapshots organized in time sequence.

[0024] Compared with the prior art, the present invention has the following advantages:

[0025] Firstly, this invention utilizes a differential evolution algorithm to search for the maximum relative velocity in the space composed of intra-layer phase, inter-layer phase, and orbital plane angle, thereby obtaining the network physical limit characteristics of intra-layer and inter-layer networks. Compared with fine-grained time evolution and brute-force phase search, this invention is more efficient and accurate, and can determine the physical upper limit of the maximum relative velocity throughout the entire life cycle of a satellite constellation within seconds.

[0026] Secondly, by utilizing the constructed network-wide cumulative delay jitter upper limit model, this invention maps the preset end-to-end delay error tolerance to the maximum safe sampling step size that meets the physical fidelity requirements. This not only effectively solves the problem of loss of key delay jitter features caused by the existing technology's reliance solely on structural stability sampling, but also achieves effective control over the network topology's end-to-end delay jitter. This ensures that the sampled discrete snapshot sequence can provide a deterministic benchmark with physical fidelity for high-dynamic satellite network simulation. Attached Figure Description

[0027] Figure 1 This is a flowchart illustrating the implementation of the time-delay jitter-controllable two-layer satellite constellation network topology sampling method of the present invention;

[0028] Figure 2 This is a schematic diagram of the inter-satellite link geometry within the layer of the method of the present invention;

[0029] Figure 3 This is a heatmap showing the rate of change of cross-layer link distance in the method of this invention;

[0030] Figure 4 This is a block diagram of the two-layer satellite constellation network topology sampling system with controllable delay jitter according to the present invention;

[0031] Figure 5 This is a simulation comparison chart showing the time delay of discrete sampling using this invention versus the actual time delay;

[0032] Figure 6 This is a drift error analysis diagram for discrete sampling at different sampling intervals using the present invention. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0034] Example 1: A two-layer satellite constellation network topology sampling method with controllable delay jitter

[0035] In engineering practice, large-scale two-layer satellite networks exhibit extremely high dynamism, with the high-speed relative motion between satellite nodes causing continuous changes in the physical properties of the links. To facilitate a detailed description of the implementation steps of this invention, a typical two-layer constellation network is used as an example in the embodiments of this invention to further describe how this invention achieves controllable latency jitter sampling.

[0036] Reference Figure 1 The implementation of this embodiment includes:

[0037] Step 1: Obtain the physical parameters of the multi-layer satellite network.

[0038] In this embodiment of the invention, the dual-layer satellite network is defined as consisting of a polar orbit constellation L1 and an inclined orbit constellation L2. The acquired parameters include two layers of basic orbit parameters and time delay jitter parameters, wherein:

[0039] First track height 780 km, dip angle It has an orbital angle of 86.4° and adopts the Walker-Star configuration, with a number of orbital planes. Number of satellites per orbit ;

[0040] Second track height 1200 km, dip angle It has an angle of 55° and adopts a Walker-Delta configuration, with a number of orbital planes. , .

[0041] Latency jitter parameter: Sets the allowable end-to-end latency jitter error tolerance for the service. ;

[0042] The parameters obtained above are used as the basic parameters for defining the multi-layer constellation architecture and business performance requirements.

[0043] Step 2: Calculate the network physical limit characteristics.

[0044] This step extracts indices that determine the time-varying characteristics of network topology through analytical calculations and dynamic simulations. Its implementation includes:

[0045] 2.1) Calculate the maximum relative velocity of a single-layer differential track. :

[0046] Reference Figure 2 The parameters for calculating the inter-satellite link distance within the layer include: the difference in right ascension of the ascending nodes. track inclination The difference in phase angle ;

[0047] Based on these parameters, for satellites in the same Walker constellation and satellite Calculate its pitch angle relative to the Earth's center. The calculation formula is as follows:

[0048] ;

[0049] According to pitch angle And is the orbital radius Calculate the length of the inter-satellite link distance. :

[0050] ,

[0051] in, and For satellite and satellite The orbital radius;

[0052] Based on the above parameters, the relative velocity within the layer is defined. :

[0053] ;

[0054] In this embodiment of the invention, satellites in the same orbit Since the value is 0, the distance between satellites on the same orbital plane remains constant. The relative motion of L1 in this embodiment is obtained by scanning the relative motion between the satellites on the first orbital plane and those on adjacent orbital planes. The speed is 3036.6 m / s, and the speed of L2 is... It is 3279 m / s.

[0055] 2.2) Constructing the inter-layer relative velocity model:

[0056] 2.2.1) Establish the unit velocity vector of the satellite in the geocentric inertial coordinate system (ECI). :

[0057]

[0058] in, Argument of latitude Right ascension of the ascending node, The inclination angle of the track;

[0059] 2.2.2) Establish the satellite's position vector :

[0060]

[0061] 2.2.3) To improve calculation accuracy, a perturbation correction term is introduced considering the non-spherical gravitational force of the Earth, and the orbital precession rate is calculated separately. and latitude amplitude drift rate :

[0062] ,

[0063] ,

[0064] in, This is the Earth's second-order zone harmonic constant, with a value of approximately ; The average angular velocity; The radius of the Earth's equator is taken as 6378.137 km; It is a semi-positive focal length;

[0065] 2.2.4) Use and Correcting the velocity vector yields the true velocity vector field. :

[0066] ,

[0067] in, Geocentric inertial coordinate system Unit vector along the axial direction, It is the vector superposition of the satellite's rotational speed around the Earth and its orbital precession speed;

[0068] 2.2.5) The true velocity vector field is a general mathematical model that defines the motion of any satellite in the system after considering physical perturbations. Applying this general model to a specific satellite yields the satellite's motion. and satellite The actual velocity vectors are respectively and Based on this, the relative velocity vector between the two satellites can be calculated. :

[0069] ;

[0070] 2.2.6) According to satellite and satellite The position vector is used to calculate the relative position vector between the two satellites. :

[0071] ;

[0072] 2.2.7) Based on the relative position vectors of the two satellites Constructing interlayer relative rates :

[0073] ,

[0074] in, This represents the actual straight-line physical distance between the two satellites.

[0075] 2.3) Using the differential evolution algorithm to lock the maximum relative velocity between layers Maximum relative speed with single-layer heterogeneous track .

[0076] Because the relative position vectors of the two stars are highly non-convex due to perturbations, this method utilizes existing differential evolution algorithms to optimize within the space composed of intra-layer phase, inter-layer phase, and orbital plane angle. In this embodiment, the algorithm directly locks the maximum inter-layer relative velocity across the entire network. The maximum relative velocity of the inter-layer link is 13499 m / s, as shown in the heat map. Figure 3 As shown.

[0077] Figure 3 It is evident that the maximum interlayer relative velocity exhibits a significant multi-peak, non-convex characteristic, with region ① representing the high relative velocity region and region ② representing the low relative velocity region. From... Figure 3 It is evident that the maximum relative velocity between layers has multiple global maximum ridges, verifying the physical symmetry of the satellite's relative motion, i.e., different phase combinations may produce the same maximum relative velocity.

[0078] Step 3: Construct a physical model of total jitter rate that reflects the upper limit of the cumulative latency jitter characteristics of the entire network.

[0079] 3.1) Set the maximum number of hops for cross-track links. :

[0080] Maximum number of hops on off-track links This refers to the maximum number of links between different orbital planes that must be traversed for communication between any two satellite nodes in a single polar or inclined orbit constellation. In this example, it is determined based on the constellation type and the number of orbital planes.

[0081] For polar orbit constellations, take ;

[0082] For inclined orbit constellations, take ,

[0083] in This represents the total number of orbital planes of the constellation.

[0084] 3.2) Calculate the cumulative jitter rate component within the layer based on the maximum number of hops on the off-track link. :

[0085] ,

[0086] in This represents the maximum number of hops on the off-track link. This represents the maximum relative velocity of a single-layer heterogeneous track.

[0087] 3.3) Based on the maximum relative velocity between layers Calculate the interlayer cumulative jitter rate component :

[0088] ;

[0089] 3.3) The cumulative jitter rate components within the layer and the cumulative jitter rate components between layers are linearly superimposed to obtain the total jitter rate. :

[0090] .

[0091] In this embodiment, L1's The corresponding cumulative jitter rate component within the layer m / s; L2 The corresponding cumulative jitter rate component within the layer m / s; Comparing the calculation results of the two layers, the larger value is selected as the final value of the cumulative jitter rate component within this constellation layer. m / s;

[0092] Interlayer cumulative jitter rate component m / s, total jitter m / s.

[0093] Step 4, based on the total jitter rate Determine the maximum safe time step and perform discretization sampling.

[0094] 4.1) Calculate the maximum safe time step. :

[0095]

[0096] in, Represents the speed of light in a vacuum. This represents the end-to-end latency jitter tolerance set by the user. This represents the total jitter rate.

[0097] In this embodiment, when When the time is 1 ms, we get =7.11 s; when When the time is 5 ms, we get =35.5s; when When the time is 10 ms, we get =71.1 s.

[0098] 4.2) Perform discretization sampling:

[0099] 4.2.1) Using the maximum safe time step as the sampling period, the dynamic operation process of the dual-layer satellite constellation is periodically captured;

[0100] 4.2.2) Obtain real-time status data of all satellites in the network at each captured sampling time, including the instantaneous spatial position of the satellite in the inertial coordinate system, the velocity vector of motion, and the connection status of the link;

[0101] 4.2.3) Organize the state data extracted at each sampling time according to the time series to generate a series of discrete topological snapshots.

[0102] The above method transforms the extreme characteristics of physical motion within and between layers into the theoretical upper limit of the delay fluctuation of the entire network at the physical level, constructs an upper limit model of the total delay jitter rate of a two-layer satellite network, maps the service error tolerance limit to the maximum safe sampling interval that meets the physical fidelity requirements, and performs discretized sampling of network state according to the sampling period. This effectively avoids the problem of loss of delay jitter characteristics caused by existing technologies that rely solely on structural stability sampling. Furthermore, it provides a discretized topology benchmark with deterministic physical guarantees for satellite network simulation without relying on specific inter-layer connection strategies.

[0103] It should be noted that the numbering of the steps is only for the purpose of clearly describing the embodiments of the present invention and for ease of understanding, and the order of the numbers is not limited.

[0104] Example 2: A two-layer satellite constellation network topology sampling system with controllable delay jitter

[0105] Reference Figure 4 This embodiment includes: a physical feature extraction module 1, a sampling step size determination module 2, and a sampling execution module 3. The physical feature extraction module 1 includes a parameter configuration submodule 11, a dynamic modeling submodule 12, and an extreme value optimization submodule 13; the sampling step size determination module 2 includes a component calculation submodule 21, a model synthesis submodule 22, and a step size mapping submodule 23; the sampling execution module 3 includes a state interception submodule 31 and a snapshot sequence generation submodule 32.

[0106] The working principle of the entire system is as follows:

[0107] The physical feature extraction module 1 is used to extract the motion limit data of the two-layer constellation, wherein the parameter configuration submodule 11 is used to input and store the orbital height of each layer of the constellation. Track inclination Right ascension of ascending nodes, number of orbital planes Number of satellites in the plane and the set of delay jitter error tolerances These basic parameters are then transmitted to the dynamic modeling submodule 12 and the sampling step size determination module 2, respectively. The dynamic modeling submodule 12 is used to construct the analytical formula for the rate of change of inter-satellite distance affected by the J2 perturbation correction term, and to establish a satellite velocity vector field model in the geocentric inertial coordinate system. The constructed model information is then input into the extreme value optimization submodule 13. The extreme value optimization submodule 13 is used to perform a global search in the phase and orbital geometry space using the differential evolution algorithm to lock the maximum relative rate of single-layer heterogeneous orbits within the layer and the maximum relative rate between layers. These two network physical limit characteristics are then input into the sampling step size determination module 2.

[0108] The sampling step size determination module 2 is used to construct a physical model of the total jitter rate of the entire network and calculate the sampling time interval that meets the accuracy requirements. The component calculation submodule 21 is used to calculate the cumulative jitter rate components within the layer based on the limiting features and maximum off-track link hop count output by the physical feature extraction module 1. and interlayer cumulative jitter rate component The calculation results are then input into the model synthesis submodule 22; this model synthesis submodule 22 is used to output the physical model of the total jitter rate of the entire network through the intra- and inter-layer components of the linear overlay layer. And input it to the step size mapping submodule 23; the step size mapping submodule 23 is used to utilize the speed of light in a vacuum Error tolerance output by parameter configuration submodule 11 Total jitter rate output by model synthesis submodule 22 Perform proportional calculations and output the maximum safe time step that meets physical fidelity requirements. Give the sampling execution module 3.

[0109] The sampling execution module 3 is used for the extraction and encapsulation of discrete topology snapshots to obtain the final snapshot result. Specifically, the state extraction submodule 31 is used to record the position, velocity, and logical connection status of all satellites in the network at each sampling time in real time, using the maximum safe time step output by the step size mapping submodule 23 as the trigger frequency. The extracted state data is then input into the snapshot sequence generation submodule 32. This snapshot sequence generation submodule 32 encapsulates the extracted discrete state data according to timestamps, generating a discrete topology snapshot sequence with a time continuity index, thus obtaining the final snapshot result.

[0110] Through the collaborative work of the above modules, this system can automatically adjust the sampling frequency according to the physical motion limits, effectively avoiding the loss of key time delay jitter features caused by blindly selecting the sampling step size, and ensuring that the topological sequence of the output after sampling can strictly meet the requirements of deterministic networks.

[0111] It should be noted that the above functional modules can be implemented, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, they can be implemented, in whole or in part, as program instruction products. A program instruction product includes one or a set of program instructions. When the program instructions are loaded and executed on a computer, the described process or function is generated, in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The program instructions can be stored in a computer-readable and writable storage medium, or transferred from one computer's readable and writable storage medium to another.

[0112] In this embodiment, direct coupling or communication connections between modules can be achieved through indirect coupling or communication connections via interfaces, devices, or modules. The functional modules and sub-modules in this embodiment can dynamically reside within a single processing unit, or each module can exist physically independently, or two or more modules can dynamically reside within a single processing unit. When these dynamic components are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable and writable storage medium. This storage medium can be a memory, disk, or optical disc, etc.

[0113] The technical effects of the present invention will be further described below with reference to simulation experiments.

[0114] I. Simulation Experiment Conditions:

[0115] The software platform for the simulation experiment of this invention is: Windows 11 operating system, PyCharm 2024.2.3.

[0116] The heterogeneous two-layer constellation parameters are set as shown in Table 1. The service latency jitter tolerances are 1 and 10ms respectively. The path is a cross-layer end-to-end path consisting of 2 cross-layer links and 5 intra-layer links.

[0117] Table 1. Orbital parameters of the dual-layer satellite constellation

[0118]

[0119] II. Simulation Content and Result Analysis

[0120] Simulation 1: Under the above simulation conditions, time delay sampling is performed using the method of this invention, and the sampled time delay is compared with the actual time delay to obtain time delay comparison curves under different sampling step sizes, as shown below. Figure 5 As shown. Wherein:

[0121] The continuous solid line at the top, Real Latency, represents the actual end-to-end continuous latency variation in the satellite network, serving as the benchmark for evaluation.

[0122] The dashed line below, 1 ms Tol, represents the experimental group mapped using this algorithm when the preset error tolerance is 1 ms;

[0123] The dotted line below, 10 ms Tol, indicates the experimental group mapped using this algorithm when the tolerance is 10 ms;

[0124] The bottom dotted line "fixed 150 s" indicates the reference group that uses a fixed sampling period of 150 s.

[0125] from Figure 5 It is evident that when a large fixed step size of 150 s is used, the discrete step cannot reflect the fluctuation trend of the real curve, resulting in severe distortion of the time delay characteristics. This method ensures that the discrete step can always remain within the fluctuation range of the real curve by calculating the maximum safe step size. Although the offset objectively exists, the sampling points selected in this invention can keep the degree of offset under control.

[0126] Simulation 2: Under the above simulation conditions, the present invention is used for time delay sampling, and the time delay error drift is statistically analyzed. This drift is then compared with the time delay error drift of a fixed 150s periodic reference sampling to obtain a time delay error distribution diagram, as shown below. Figure 6 As shown, where:

[0127] The dashed line 1 ms Strat represents the time delay drift experimental group statistically analyzed after mapping using this invention when the preset error tolerance is 1 ms;

[0128] The dotted-dash line 10 ms Strat indicates the experimental group with a time delay drift statistically calculated using the mapping method of this invention when the tolerance is 10 ms;

[0129] The dotted line "fixed 150 s" indicates a time delay drift reference group that uses a fixed sampling period of 150 s.

[0130] from Figure 6 As can be seen, the maximum offset of the 150s baseline reached 13.55 ms, exceeding the 10 ms threshold required by the business requirements. However, under the 1ms tolerance strategy, the maximum offset of this invention is strictly locked at 0.67 ms; under the 10 ms tolerance strategy, the maximum offset is only 6.7 ms, meeting the business requirement threshold. This demonstrates that this invention can ensure that latency jitter strictly meets business constraints at the path level, exhibiting deterministic latency jitter control capabilities.

[0131] Simulation results show that the present invention can achieve deterministic control of discrete topology time delay jitter error.

[0132] The above descriptions are merely a few specific examples of the present invention and do not constitute any limitation on the present invention. Obviously, those skilled in the art, after understanding the content and principles of the present invention, may make various modifications and changes in form and detail without departing from the principles and structure of the present invention. For example, the maximum relative motion velocity of the physical motion feature used to establish the upper limit model of delay jitter in a two-layer network can be calculated in other ways besides the calculation formula of the present invention; similarly, the number of hops in the intra-layer and inter-layer jitter components used to establish the upper limit model of delay jitter in a two-layer network can be selected using other ratios besides the specific ratio of the present invention; and the delay jitter tolerance used to select the sampling period can have other values ​​besides the numerical values ​​of the present invention. However, these modifications and changes based on the ideas of the present invention are still within the scope of protection of the claims of the present invention.

Claims

1. A method for topology sampling of a delay-jitter-controllable dual-layer satellite constellation network, characterized in that, include: Based on the basic orbit, constellation configuration, and error tolerance parameters of the multi-layer satellite network, the physical limit characteristics of the network within and between layers are obtained, and a physical model of total jitter rate reflecting the upper limit of the cumulative delay jitter characteristics of the entire network is constructed. The maximum safe time step under different service tolerances is determined based on the jitter rate model, and the two-layer satellite network is discretized accordingly.

2. The method according to claim 1, characterized in that, The process of obtaining the network physical limit characteristics within and between layers based on the basic orbit, constellation configuration, and error tolerance parameters of the multi-layer satellite network includes: 2a) The basic orbital parameters obtained include: the orbital altitude h, orbital inclination β, and the distribution pattern of the right ascension of the ascending node of each constellation layer, which are used to determine the orbital speed and geometric position of the multi-layer satellites in inertial space; 2b) The obtained constellation configuration parameters, including the number of orbital planes P, the number of satellites on each orbital plane S, and the phase factor F, are used to determine the spatial distribution density of nodes in the network and the connection range of the logical topology within the layer; 2c) The acquired latency jitter parameters include: setting the set of end-to-end latency jitter error tolerances δ allowed by the simulation system or service protocol, used to define the latency jitter within a single discrete time step. Within the network, the maximum variation in end-to-end propagation delay that the network can tolerate is used to determine the fidelity level and sampling accuracy requirements of the simulation; 2d) Obtain the network physical limits within and between layers, including the maximum relative velocity of single-layer heterogeneous orbits. Maximum relative velocity between layers : The maximum relative velocity of this single-layer differential orbit This refers to using the first orbital plane as a reference standard, scanning the relative motion state between satellites on this orbital plane and adjacent orbital planes, and obtaining local maxima as the physical upper limit of motion of the satellite network at this layer. The maximum relative velocity between layers Inter-layer motion refers to finding all pairs of satellites that can see each other between satellites at different altitudes, forming them into a visible set, calculating the relative motion velocity of each pair of satellites in this set, and taking the maximum value of these velocities as the physical extreme value of the inter-layer motion. 2e) The maximum relative velocity is searched in the space consisting of intra-layer phase, inter-layer phase and orbital plane angle to obtain the network physical limit characteristics of intra-layer and inter-layer.

3. The method according to claim 1, characterized in that, The physical model for constructing the total jitter rate, which reflects the upper limit of the cumulative latency jitter characteristics of the entire network, includes the following implementation: 3a) Calculate the cumulative jitter rate component within the layer. : ； in This represents the maximum number of hops on the off-track link. This represents the maximum relative velocity of a single-layer heterogeneous track. 3b) Based on the maximum relative velocity between layers Calculate the interlayer cumulative jitter rate component : ； 3c) Linearly superimpose the cumulative jitter rate components within and between layers to obtain a physical model of total jitter rate that reflects the upper limit of the cumulative delay jitter characteristics of the entire network. : 。 4. The method according to claim 3, characterized in that, The maximum number of hops on the off-track link This refers to the maximum number of links between different orbital planes that must be traversed for communication between any two satellite nodes in a single polar or inclined orbit constellation. It is determined based on the constellation type and the number of orbital planes. For polar orbit constellations, take ; For inclined orbit constellations, take , in This represents the total number of orbital planes of the constellation.

5. The method according to claim 1, characterized in that, The formula for determining the maximum safe time step under different service tolerances based on the jitter rate model is as follows: ； in, Represents the maximum safe time step. Represents the speed of light in a vacuum; This represents the end-to-end latency jitter tolerance set by the user. This represents the total jitter rate.

6. The method according to claim 1, characterized in that, The discretization sampling of the two-layer satellite network based on the maximum safe time step includes the following implementation: 6a) Using the maximum safe time step as the sampling period, periodically capture the dynamic operation process of the dual-layer satellite constellation; 6b) Obtain real-time status data of all satellites in the network at each captured sampling time, including the instantaneous spatial position of the satellite in the inertial coordinate system, the velocity vector of motion, and the connection status of the link; 6c) Organize the state data extracted at each sampling time according to the time series to generate a series of discrete topological snapshots.

7. A two-layer satellite constellation network topology sampling system with controllable time delay jitter, characterized in that, include: The physical feature extraction module is used to obtain the network physical limit features of the maximum relative velocity of single-layer different orbits within a layer and the maximum relative velocity between layers, based on the basic orbital parameters, constellation configuration parameters, and end-to-end delay jitter error tolerance parameters allowed by the service protocol of the multi-layer satellite network, through dynamic model establishment and differential evolution optimization. The sampling step size determination module is used to construct a total jitter rate physical model that reflects the upper limit of the cumulative delay jitter characteristics of the entire network by linearly superimposing the cumulative jitter rate components of the intra-layer and inter-layer networks based on the network physical limit characteristics of the intra-layer and inter-layer networks, and to calculate the maximum safe time step size that meets the physical fidelity requirements using the total jitter rate physical model and the preset error tolerance. The sampling execution module is used to periodically capture the dynamic operation process of the two-layer satellite constellation with the maximum safe time step as the sampling period, and generate a series of discrete topological snapshots organized in time sequence.

8. The system according to claim 7, characterized in that, The physical feature extraction module includes: The parameter configuration submodule is used to input and store the orbital heights of each constellation layer. Track inclination Right ascension of ascending nodes, number of orbital planes Number of satellites in the plane and the set of delay jitter error tolerances ; The dynamic modeling submodule is used to construct the analytical formula for the rate of change of inter-satellite distance affected by the J2 perturbation correction term, and to establish a satellite velocity vector field model in the geocentric inertial coordinate system; The extreme value optimization submodule is used to perform a global search in the phase and orbital geometry space using the differential evolution algorithm to lock the maximum relative velocity of single-layer heterogeneous orbits within the layer and the maximum relative velocity between layers.

9. The system according to claim 7, characterized in that, The sampling step size determination module includes: The component calculation submodule is used to calculate the maximum number of hops on the off-track link. Calculate the cumulative jitter rate components within each layer. and interlayer cumulative jitter rate component ; The model synthesis submodule is used to output a physical model of the total jitter rate of the entire network by linearly superimposing the intra-layer and inter-layer components. ; The step size mapping submodule is used to map the speed of light in a vacuum. Error tolerance With the total jitter rate Perform proportional calculations and output the maximum safe time step that meets physical fidelity requirements. .

10. The system according to claim 7, characterized in that, The sampling execution module includes: The status capture submodule is used to record the position, velocity, and logical connection status of all satellites in the network in real time, with the maximum safe time step as the trigger frequency. The snapshot sequence generation submodule is used to encapsulate the extracted discrete state data according to timestamps and generate a discrete topological snapshot sequence with time continuity index.

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