A large-scale constellation performance evaluation method

Abstract

This invention relates to a method for large-scale constellation performance evaluation, belonging to the field of performance evaluation technology; and establishes a performance evaluation index system I. i ; Conduct n evaluations of index I i Data collection, the collection result is I i,k The collected data is evaluated, and x is used as the basis for the evaluation. i Indicator I i The evaluation value is obtained after this step; the weights β of the evaluation indicators are determined using the analytic hierarchy process. i ,∑β i =1; The evaluation indicators are classified into static and dynamic indicators. Static evaluation indicators are not subject to weight adjustment, while dynamic evaluation indicators are subject to weight adjustment to obtain the weight β′. i ,∑β′ i =1; Based on the stability of the evaluation indicators, the evaluation indicators are dynamically adjusted in terms of weight, and the adjusted weight is β″. i ; Calculate the system performance of the constellation communication system E = ∑β″ i x i Then, based on the value of E, the performance evaluation result Q is given; this invention realizes real-time correction of the weights of the evaluation indicators; finally, it realizes the performance evaluation of the constellation communication system.

Description

Technical Field

[0001] This invention belongs to the field of performance evaluation technology and relates to a method for large-scale constellation performance evaluation. Background Technology

[0002] Currently, large-scale satellite constellations are experiencing explosive growth internationally, and my country is also actively deploying large-scale constellations. Large-scale satellite communication systems are characterized by their massive network scale, complex networking mechanisms, diverse protocol systems, and dynamic, ever-changing behavior. Directly developing and deploying satellite nodes and protocols would increase R&D risks and make reliability control difficult in the construction of large-scale satellite constellation systems. Therefore, simulation verification and performance evaluation before deployment are particularly important. However, current research on satellite communication system performance evaluation mainly focuses on single-satellite and single-system scenarios; evaluation methods for large-scale satellite constellation scenarios require further research.

[0003] Furthermore, with the development of new technologies, the functions of satellites will change compared to the past. For example, in edge computing, satellite nodes will not only serve as communication relay nodes but also as edge servers providing information processing services to terminals. However, traditional evaluation algorithms are mostly based on the terminal's perspective, treating satellites as relay nodes in transmission, and only considering user experience-oriented indicators such as latency, number of users, and coverage. Moreover, the dynamic adaptability of onboard protocols (such as routing protocols and task offloading algorithms) is a future trend, meaning that indicators affected by these protocols can be optimized later. Finally, compared to early satellite communication networks with fewer nodes, large-scale constellations have numerous nodes and varied network topologies, leading to potential fluctuations in service performance. However, traditional evaluation algorithms use constant weights, which are unchanging and fail to reflect the adjustability and volatility of indicators in future large-scale constellations. Summary of the Invention

[0004] The technical problem solved by this invention is to overcome the shortcomings of the prior art, propose a large-scale constellation performance evaluation method, realize the real-time correction of the weights of the evaluation indicators, and finally realize the performance evaluation of the constellation communication system.

[0005] The solution of the present invention is:

[0006] A large-scale constellation performance evaluation method includes:

[0007] Establish an effectiveness evaluation index system I i , among which, I i Let i represent the i-th evaluation indicator, where i is the number of evaluation indicators.

[0008] Perform n evaluation indexes I iData collection, the collection result is I i,k , among which, I i,k For the kth time I i The numerical values ​​of k, k = 1, 2, ..., n;

[0009] The collected data is evaluated, and x is used. i Indicator I i The evaluation value after this step;

[0010] The weights β of the evaluation indicators were determined using the analytic hierarchy process. i ,∑β i =1;

[0011] The evaluation indicators are classified into static and dynamic indicators. Static evaluation indicators are not subject to weight adjustment, while dynamic evaluation indicators are subject to weight adjustment, resulting in the weight β. i ',∑β i =1;

[0012] Based on the stability of the evaluation indicators, the evaluation indicators are dynamically adjusted in terms of weight, and the adjusted weight is β. i ”;

[0013] Calculate the system performance of a constellation communication system: E = ∑β i x i Then, based on the value of E, the performance evaluation result Q is given.

[0014] In the aforementioned large-scale constellation performance evaluation method, the performance evaluation index system includes a target layer, a criterion layer, and an indicator layer.

[0015] The target layer is the performance evaluation index Q; the target layer corresponds to 5 criteria layers, namely coverage capability, system capacity, transmission capability, access capability and task migration capability.

[0016] Coverage capability corresponds to two indicator layers: ground coverage I1, which is the ratio of actual coverage area to required coverage area, and time coverage I2, which is the ratio of actual coverage time to required coverage time.

[0017] The system capacity corresponds to two indicator layers: single satellite access capacity I3, which is the maximum number of users a single satellite can accommodate per unit time, and system access capacity I4, which is the maximum number of users the system can accommodate per unit time.

[0018] Transmission capability corresponds to four indicator layers: transmission rate (I5), which is the highest transmission rate that the system can transmit per unit time; transmission delay (I6), which is the sum of transmission delay and satellite network processing delay; bit error rate (I7), which is the ratio of the number of erroneous bits to the total number of transmitted bits; and interruption rate (I8), which is the probability of data transmission interruption between the satellite and ground equipment.

[0019] Access capability corresponds to two indicator layers: access latency (I9), which is the time required for ground equipment to access satellite equipment, and access blocking rate (I). 10 That is, the probability that a transmission request will be blocked;

[0020] Task migration capability corresponds to four indicator layers, namely the task migration ratio I 11 The ratio of the number of tasks that the terminal migrates to the satellite for processing to the total number of task requests initiated by the terminal, i.e., the task completion rate I. 12 That is, the ratio of the number of tasks that the satellite completes for the terminal migration to the number of tasks that the terminal migrates to the satellite, and the task throughput I. 13 That is, the number of terminal migration tasks that the satellite can receive per unit of time, and the task completion time I. 14 This refers to the average time it takes for a satellite to complete its terminal migration mission.

[0021] In the aforementioned method for evaluating the performance of a large-scale constellation, the static evaluation index is a parameter constrained by factors that are not easily changed, including orbit and payload capacity; the dynamic evaluation index is a parameter affected by adjustable factors, including algorithms and system protocols.

[0022] In the aforementioned large-scale constellation performance evaluation method, the method for adjusting the dynamic evaluation indicators using variable weights is as follows:

[0023] β i =a*β i

[0024] In the formula, a is the correction parameter;

[0025] For weight β i After normalization, the weights are β. i ';

[0026]

[0027] In the aforementioned large-scale constellation performance evaluation method, the value of the correction parameter 'a' is:

[0028]

[0029] In the aforementioned large-scale constellation performance evaluation method, the method for dynamically adjusting the weights of the evaluation indicators is as follows:

[0030] S1. Collect sample values ​​of dynamic evaluation indicators over a period of time t, assuming the number of samples collected is n;

[0031] S2, Calculate dynamic evaluation index I i Standard deviation σ i ;

[0032] S3, Calculate evaluation index I i range of change e i If e i If the value is less than the threshold γ, proceed to S7; otherwise, proceed to S4.

[0033] S4. Based on the change range of the evaluation indicators e i Calculate the correction factor α i The value;

[0034] S5. Weighting of evaluation indicators β i 'Make corrections to obtain the corrected index weight β' i ”;

[0035] S6, Return to S1;

[0036] S7. Complete the dynamic weight adjustment of the evaluation indicators.

[0037] In the aforementioned large-scale constellation performance evaluation method, in step S2, the dynamic evaluation index I... i Standard deviation σ i The calculation method is as follows:

[0038]

[0039] Where n is the number of samples;

[0040] I i,k Evaluation index I i The value in the k-th sample;

[0041] μ i Evaluation index I i The mean, i.e.

[0042] In the aforementioned large-scale constellation performance evaluation method, in step S3, the variation magnitude e i The calculation method is as follows:

[0043]

[0044] In the aforementioned large-scale constellation performance evaluation method, in step S4, the correction factor α i The calculation method is as follows:

[0045]

[0046] In the aforementioned large-scale constellation performance evaluation method, in step S5, the indicator weight β i The correction method for "" is as follows:

[0047] β i =αi ·β i '.

[0048] The beneficial effects of this invention compared to the prior art are:

[0049] (1) This invention combines the characteristics of large-scale constellation communication networks and adds task migration evaluation indicators on the basis of traditional communication evaluation indicators, making the evaluation content more comprehensive and detailed.

[0050] (2) This invention refines the parameter classification, takes into account the influence of dynamically adjustable factors, takes into account the volatility brought about by constellation topology changes, and adapts to the development of future technologies.

[0051] (3) This invention proposes a suitable performance evaluation method for large-scale constellation communication networks, providing a theoretical reference for the construction of large-scale constellations. Attached Figure Description

[0052] Figure 1 This is a flowchart of the large-scale constellation performance evaluation process of this invention. Detailed Implementation

[0053] The present invention will be further described below with reference to the embodiments.

[0054] This invention provides a method for evaluating the performance of large-scale constellations, adapting to the future development needs of low-Earth orbit satellite constellations. It also employs a dynamic weighting method to evaluate the performance of large-scale constellation communication networks, providing a theoretical reference for the construction of large-scale constellations.

[0055] Large-scale constellation performance evaluation methods, such as Figure 1 As shown, the specific steps include the following:

[0056] Establish an effectiveness evaluation index system I i , among which, I i Let i represent the i-th evaluation indicator, where i is the number of evaluation indicators; the effectiveness evaluation indicator system includes the target layer, the criterion layer, and the indicator layer.

[0057] The target layer is the performance evaluation index Q; the target layer corresponds to 5 criteria layers, namely coverage capability, system capacity, transmission capability, access capability and task migration capability.

[0058] Coverage capability corresponds to two indicator layers: ground coverage I1, which is the ratio of actual coverage area to required coverage area, and time coverage I2, which is the ratio of actual coverage time to required coverage time.

[0059] The system capacity corresponds to two indicator layers: single satellite access capacity I3, which is the maximum number of users a single satellite can accommodate per unit time, and system access capacity I4, which is the maximum number of users the system can accommodate per unit time.

[0060] Transmission capability corresponds to four indicator layers: transmission rate (I5), which is the highest transmission rate the system can transmit per unit time; transmission delay (I6), which is the sum of transmission delay and satellite network processing delay; bit error rate (I7), which is the ratio of the number of erroneous bits to the total number of transmitted bits; and interruption rate (I8), which is the probability of data transmission interruption between the satellite and ground equipment.

[0061] Access capability corresponds to two indicator layers: access latency (I9), which is the time required for ground equipment to access satellite equipment, and access blocking rate (I). 10 This refers to the probability that a transmission request will be blocked.

[0062] Task migration capability corresponds to four indicator layers, namely the task migration ratio I 11 The ratio of the number of tasks that the terminal migrates to the satellite for processing to the total number of task requests initiated by the terminal, i.e., the task completion rate I. 12 That is, the ratio of the number of tasks that the satellite completes for the terminal migration to the number of tasks that the terminal migrates to the satellite, and the task throughput I. 13 That is, the number of terminal migration tasks that the satellite can receive per unit of time, and the task completion time I. 14 This refers to the average time it takes for a satellite to complete its terminal migration mission.

[0063] The details are shown in Table 1.

[0064] Table 1

[0065]

[0066]

[0067] Perform n evaluation indexes I i Data collection, the collection result is I i,k , among which, I i,k For the kth time I i The value of k, k = 1, 2, ..., n.

[0068] The collected data is evaluated, and x is used. i Indicator I i The evaluation value after this step.

[0069] The weights β of the evaluation indicators were determined using the analytic hierarchy process. i ,∑β i =1.

[0070] The evaluation indicators are classified into static and dynamic indicators. Static evaluation indicators are not subject to weight adjustment, while dynamic evaluation indicators are subject to weight adjustment, resulting in the weight β. i ',∑βi =1; The static evaluation index is a parameter constrained by factors that are not easily changed, including those affected by track and load capacity; The dynamic evaluation index is a parameter affected by adjustable factors, including algorithms and system protocols.

[0071] The method for adjusting the weights of dynamic evaluation indicators is as follows:

[0072]

[0073] In the formula, 'a' is the correction parameter; the value of the correction parameter 'a' is:

[0074]

[0075] For weight β i After normalization, the weights are β. i ';

[0076]

[0077] Based on the stability of the evaluation indicators, the evaluation indicators are dynamically adjusted in terms of weight, and the adjusted weight is β. i The method for dynamically adjusting the weights of evaluation indicators is as follows:

[0078] S1. Collect sample values ​​of dynamic evaluation indicators over a period of time t, assuming the number of samples collected is n.

[0079] S2, Calculate dynamic evaluation index I i Standard deviation σ i Dynamic evaluation index I i Standard deviation σ i The calculation method is as follows:

[0080]

[0081] Where n is the number of samples;

[0082] I i,k Evaluation index I i The value in the k-th sample;

[0083] μ i Evaluation index I i The mean, i.e.

[0084] S3, Calculate evaluation index I i range of change e i If e i If the value is less than the threshold γ, proceed to S7; otherwise, proceed to S4; the change range e i The calculation method is as follows:

[0085]

[0086] S4. Based on the change range of the evaluation indicators e i Calculate the correction factor α i The value of the correction factor α; i The calculation method is as follows:

[0087]

[0088] S5. Weighting of evaluation indicators β i 'Make corrections to obtain the corrected index weight β' i ";Indicator weight β i The correction method for "" is as follows:

[0089] β i =α i ·β i '.

[0090] S6, Return to S1.

[0091] S7. Complete the dynamic weight adjustment of the evaluation indicators.

[0092] Calculate the system performance of a constellation communication system: E = ∑β i x i Then, based on the value of E, the performance evaluation result Q is given.

[0093] Example

[0094] The performance evaluation technology for constellation satellite communication systems mainly includes six steps: 1) Determining the performance evaluation index system for the constellation satellite communication system; 2) Collecting data and evaluating and quantifying the collected data; 3) Applying the analytic hierarchy process (AHP) to determine the weights of the performance evaluation indexes for the constellation satellite communication system; 4) Classifying the evaluation indexes into static and dynamic categories, and adjusting the weights accordingly; 5) Adjusting the dynamic weights of the evaluation indexes based on their stability; 6) Calculating the system performance of the constellation communication system and providing the performance evaluation results. The specific process is as follows:

[0095] Step 1: Establish an evaluation index system for the constellation satellite communication system, as shown in Table 2.

[0096] Table 2. Evaluation Indicators for Satellite Communication Systems

[0097]

[0098] Step 2: Data collection and evaluation of the collected data.

[0099] Because the evaluation indicators have different dimensions and different value ranges, an expert scoring evaluation method is adopted in order to achieve a unified measurement. That is, data is collected first, and then an expert scoring evaluation method is used based on the collected data. The evaluation result ranges from [0 to 100].

[0100] Step 3: Determine the weights using the Analytic Hierarchy Process (AHP).

[0101] Since the evaluation index system of a satellite constellation communication system has a multi-level structure, and the Analytic Hierarchy Process (AHP) is precisely the algorithm for handling the weights of evaluation indexes in such an architecture, this invention uses the AHP to determine the weights of the evaluation indexes for the satellite constellation communication system. The specific process is as follows:

[0102] Step 3.1 Constructing the judgment matrix: Multiple experts are asked to conduct pairwise comparisons and score the importance of each indicator relative to the previous level to determine the evidence for judgment at each level. The results are as follows:

[0103] 1) Judgment matrix of the criterion layer

[0104]

[0105]

[0106]

[0107]

[0108] The specific values ​​of the judgment matrix are determined using the 1-9 scale method proposed by TLSatty, as shown in Table 3:

[0109] Table 3

[0110]

[0111]

[0112] Step 3.2 Calculate the maximum eigenvalues ​​and corresponding maximum eigenvectors of the judgment matrices U, U1, U2, U3, U4, and U5, normalize them, and perform a consistency check to determine the weights of the constellation satellite communication evaluation indicators. The results are shown in Table 4.

[0113] Table 4: Weight Allocation Results of Indicators for Satellite Communication Systems

[0114]

[0115] Step 4: Classify indicators and adjust their weights accordingly based on their characteristics.

[0116] In the future, ground-based systems will have the capability to perform on-board software configuration of satellite constellations. Therefore, unlike in the past, evaluation indicators for future satellites, which are influenced by system protocols, will be adjustable. Based on this consideration, the evaluation indicators for satellite constellations are divided into two categories: static and dynamic parameters, with the dynamic parameters being weighted less.

[0117] Step 4.1: Divide the evaluation indicators into two categories: static and dynamic. Among them, parameters such as coverage capacity and system capacity, which are mainly constrained by factors that are not easily changed, such as track and load capacity, are classified as static parameters, while parameters such as transmission capacity, access capacity, and migration capacity, which are affected by adjustable factors such as system protocols, are classified as dynamic parameters.

[0118] ②Based on the degree to which the dynamic parameters are affected by the institutional agreement, the weights are adjusted according to the following formula;

[0119] β i =a*β i

[0120] The value of the correction parameter 'a' is:

[0121]

[0122] Among the evaluation parameters, I5 is mainly limited by factors such as power and antenna, and is weakly correlated with the system protocol, with a correction factor of 0.9; I6 is equal to the sum of transmission delay (mainly dependent on orbital altitude) and processing delay (mainly dependent on on-board resources and routing algorithms, etc.), and is generally correlated with the system protocol; similarly, I7, I8, and I... 10 I 13 I 14 Generally related to the impact of institutional agreements; I9, I 11 I 12 The influence of institutional agreements is strongly correlated. Therefore, {I5,I6,I7,I8,I9,I... 10 ,I 11 ,I 12 ,I 13 ,I 14 The corrected parameters for} are: {0.9, 0.7, 0.7, 0.7, 0.5, 0.7, 0.5, 0.5, 0.7, 0.7}. The corrected weights are: {0.1521, 0.01001, 0.021, 0.00539, 0.04315, 0.12075, 0.02135, 0.01325, 0.03304, 0.01449}.

[0123] ③ Regarding the weight β i After normalization, the weights are β. i '

[0124]

[0125] The adjusted weights are shown in Table 5:

[0126] Table 5 Adjusted Weights

[0127]

[0128]

[0129] Step 5: Employ a dynamic weighting adjustment method to adjust the constant weight β of the evaluation index. i The specific steps for dynamic correction are as follows:

[0130] ① Collect sample values ​​of dynamic evaluation indicators over a period of time t, assuming the number of samples collected is n;

[0131] ② Calculate dynamic evaluation index I i Standard deviation σ i

[0132]

[0133] Where n is the number of samples, I i,k Evaluation index I i The value of μ in the k-th sample i Evaluation index I i The mean, i.e.

[0134] ③ Calculate evaluation index I i range of change e i If the jump threshold γ is set to 0.1, then if e i If the value is less than 0.1, proceed to step ⑦;

[0135]

[0136] ④ Based on the change range e of the evaluation indicators i Calculate the correction factor α i ;

[0137]

[0138] ⑤ Weighting of evaluation indicators β i 'Make corrections, the correction method is: β i =α i .β i ';

[0139] ⑥ Return to step ①;

[0140] ⑦ The constant weight β of the evaluation index is completed. i Dynamic correction.

[0141] Task migration ratio I 11 For example, suppose the collected data set is {0.5,0.45,0.51,0.6,0.44,0.6,0.52,0.41,0.52,0.55}.

[0142] Then the mean μ 11 =0.51, standard deviation σ 11 =0.06;

[0143] Variation e 11 =0.06 / 0.51=0.1176>0.1;

[0144] Correction factor

[0145] The corrected index weight β i =0.8948 * 0.0257 = 0.030.

[0146] And so on, for all evaluation indicators, β i 'Make corrections.'

[0147] Step 6: Determine the communication system performance of the satellite constellation.

[0148]

[0149] Where E represents system performance, x i This represents the quantified evaluation value of the i-th indicator. Finally, the result Q is determined based on the interval in which this performance value falls. The division of the performance interval is shown in the following formula.

[0150]

[0151] This invention combines the characteristics of large-scale constellation communication networks, adding a task migration evaluation index to the traditional communication evaluation index; it refines parameter classification, considers the influence of dynamically adjustable factors, takes into account the volatility brought about by constellation topology changes, adapts to future technological developments, and proposes a suitable performance evaluation method for large-scale constellation communication networks, providing a theoretical reference for the construction of large-scale constellations.

[0152] Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications to the technical solutions of the present invention by utilizing the methods and techniques disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solutions of the present invention shall fall within the protection scope of the technical solutions of the present invention.

Claims

1. A method for large-scale constellation performance evaluation, characterized in that: include: Establish a performance evaluation indicator system I i ,in, I i Indicates the first i Evaluation indicators i The number of evaluation indicators; conduct n Sub-evaluation indicators I i Data collection, the collection results are I i,k ,in, I i,k For the first k Second-rate I i The value, k =1,2,….., n ; The collected data is evaluated and used... Indicators I i The evaluation value after this step; The weights of the evaluation indicators were determined using the analytic hierarchy process. β i , ∑ β i = 1; The evaluation indicators are classified into static and dynamic indicators. Static evaluation indicators are not subject to weight adjustment, while dynamic evaluation indicators are subject to weight adjustment to obtain normalized weights. , ∑ = 1; The method for dynamically adjusting the weights of evaluation indicators is as follows: S1, Statistics over a period of time t The sample values ​​of the dynamic evaluation indicators within, assuming the number of samples collected is... n ; S2. Calculate dynamic evaluation indicators I i Standard deviation σ i ; S3, Calculate evaluation indicators I i range of change ,if If the value is less than the threshold γ, proceed to S7; otherwise, proceed to S4. S4. Based on the change range of the evaluation indicators Calculate the correction factor α i The value; S5. Weighting of evaluation indicators Make corrections to obtain the corrected indicator weights. ; S6, Return to S1; S7. Complete the dynamic weight adjustment of the evaluation indicators; Based on the stability of the evaluation indicators, the evaluation indicators are dynamically adjusted in terms of weight. The adjusted weights are: ; Computing the system performance of constellation communication systems Then according to E The value is given to provide the performance evaluation result. Q .

2. The method for evaluating the effectiveness of a large-scale constellation according to claim 1, characterized in that: The performance evaluation indicator system includes the target layer, the criteria layer, and the indicator layer; The target layer consists of performance evaluation indicators. Q The target layer corresponds to five criteria layers: coverage capability, system capacity, transmission capability, access capability, and task migration capability. Coverage capability corresponds to two indicator layers: ground coverage and ground coverage. I 1, which is the ratio of actual coverage area to required coverage area, and time coverage. I 2, which is the ratio of actual coverage time to required coverage time; System capacity corresponds to two indicator layers: single-satellite access capacity and single-satellite access capacity. I 3, which refers to the maximum number of users a single satellite can accommodate per unit time and the system access capacity. I 4, which is the maximum number of users the system can accommodate per unit of time; Transmission capability corresponds to four indicator layers, namely transmission rate. I 5, which refers to the maximum transmission rate and transmission delay that the system can transmit per unit time. I 6, which is the sum of transmission delay and satellite network processing delay, plus the bit error rate. I 7, which is the ratio of the number of erroneous bits to the total number of transmitted bits during transmission, or the interruption rate. I 8 represents the probability of data transmission interruption between satellite and ground equipment; Access capability corresponds to two metric layers: access latency and access speed. I 9 refers to the time required for ground equipment to connect to satellite equipment and the access blocking rate. I 10 That is, the probability that a transmission request will be blocked; Task migration capability corresponds to four indicator layers, namely, task migration ratio. I 11 This refers to the ratio of the number of tasks that the terminal migrates to the satellite for processing to the total number of task requests initiated by the terminal, and the task completion rate. I 12 This refers to the ratio of the number of tasks a satellite completes for terminal relocation to the number of tasks a terminal relocation to the satellite, or the task throughput. I 13 This refers to the number of terminal migration tasks that a satellite can receive per unit of time, and the task completion time. I 14 This refers to the average time it takes for a satellite to complete its terminal migration mission.

3. The method for large-scale constellation performance evaluation according to claim 1, characterized in that: The static evaluation index is a parameter constrained by factors that are not easily changed, including those affected by the track and payload capacity; the dynamic evaluation index is a parameter affected by adjustable factors, including algorithms and system protocols.

4. The method for large-scale constellation performance evaluation according to claim 3, characterized in that: The method for adjusting the weights of dynamic evaluation indicators is as follows: β i = a β i In the formula, a To correct the parameters; weight β i Normalization is performed, and the normalized weights are: ; 。 5. The method for evaluating the effectiveness of a large-scale constellation according to claim 4, characterized in that: The correction parameter a The value can be: 。 6. The method for evaluating the effectiveness of a large-scale constellation according to claim 1, characterized in that: In S2, the dynamic evaluation index I i Standard deviation σ i The calculation method is as follows: in, n The number of samples; I i,k Evaluation indicators I i In the k The values ​​in each sample; µ i Evaluation indicators I i The mean, i.e. .

7. A method for evaluating the effectiveness of large-scale constellations according to claim 6, characterized in that: In S3, the change range The calculation method is as follows: ×100%。 8. The method for evaluating the effectiveness of a large-scale constellation according to claim 7, characterized in that: In S4, the correction factor α i The calculation method is as follows: 。 9. A method for evaluating the effectiveness of a large-scale constellation according to claim 8, characterized in that: In S5, the indicator weight The correction method is as follows: 。

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