Method and device for evaluating the execution effect of low-orbit satellite intervention mission

Abstract

The present invention proposes a method and device for evaluating the execution effect of a low-orbit satellite intervention task. The evaluation method includes: S10, calculating the availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system; S20, based on the obtained availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system, using an improved ADC performance model to obtain the execution effect score of the intervention task of the low-orbit satellite system. The present invention can be used in the simulation process of the execution of the low-orbit satellite intervention task. During the simulation, multiple groups of scenarios with different credibility and reliability parameters can be set to test the effect of the intelligent decision-making algorithm in different scenarios. During the simulation process, as long as the input required by the algorithm is given, the score of the current task execution can be output. According to the score, the algorithm such as the intelligent decision-making can be further improved or different decision-making algorithms can be compared, and finally the effect of the low-orbit satellite in performing the intervention task can be evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field of low-orbit satellites, and in particular to a method and device for evaluating the execution effect of a low-orbit satellite intervention mission. Background Art

[0002] In the process of simulating intervention tasks, a method for evaluating the performance of tasks is needed to guide the decision-making of the low-orbit satellite system. The present invention proposes such a method.

[0003] At present, there is no evaluation method for the execution effect of low-orbit satellite intervention missions in China, but there are relevant research methods for the evaluation of the effectiveness of the coordinated use of drone clusters. The evaluation method for the coordinated use of intelligent drone clusters needs to be carried out through the following steps: 1) Assume the application background; 2) Establish an indicator system; 3) Establish an evaluation model; 4) Select an evaluation method; 5) Calculate the evaluation results; 6) Comprehensive performance evaluation.

[0004] Through the whole process analysis of the intelligent UAV swarm collaborative application system, the research object, possible battlefield environment, influencing factors, application tasks and evaluation purposes are clarified, and military needs and key technologies are studied. The qualitative and quantitative indicators related to the application effectiveness evaluation are determined, and various factors such as the performance indicators of UAV weapons and equipment and attack targets are considered. The comprehensive and complex factors affecting the application effectiveness are decomposed and refined step by step, and the key capabilities that constitute the system application effectiveness are refined. The constituent indicators of each level of capabilities are refined, and an evaluation indicator system that reflects the system application effectiveness as comprehensively and objectively as possible is constructed. The application effectiveness evaluation analysis methods include: hierarchical analysis method, ADC (Availability Dependability Capability) method and artificial neural network method.

[0005] The basic idea of ​​analytic hierarchy process is to build a hierarchical model after an in-depth analysis of the nature, influencing factors and internal relationships of complex problems, and then use the key quantitative information of influencing indicators to mathematize the decision-making thinking process, thereby providing a simple decision-making method for solving complex decision-making problems.

[0006] The ADC effectiveness model is a measure of the degree to which the system is expected to meet a set of specific mission requirements under specified conditions. It is a function of the product of effectiveness, credibility and capability. A represents the effectiveness vector, which can be used to represent the probability of the intelligent drone cluster collaborative operation system being in different states at the beginning of the mission. D represents the credibility matrix, and the values ​​in the matrix represent the probability that the system is in a certain state at the beginning and transfers to another state during operation. C represents the capability matrix, and the values ​​in the matrix represent a certain performance indicator achieved in the final possible state.

[0007] When using artificial neural networks to evaluate the performance of intelligent drone cluster collaborative application systems, we should first analyze the factors that affect the system's performance, which are specifically reflected in the air detection capability, tracking and positioning capability, networking and communication capability, collaborative control capability, protection capability, and collaborative strike capability. The evaluation index is used as the input parameter of the artificial neural network, and the performance is used as the output parameter. The disadvantage is that artificial neural networks need to learn through a steady stream of data, and the determination of the number of hidden layer neurons has always been a difficult problem, and a lot of experimental training is required in actual application.

[0008] The method for evaluating the effectiveness of the coordinated use of drone clusters cannot be directly adapted to the effectiveness evaluation of the use of low-orbit satellites. The main reasons are as follows: 1) Different operating modes. Low-orbit satellites need to operate in low earth orbits. The energy consumption of changing orbits is high, and they generally do not change orbits. They are far less flexible than drones, so there are certain limitations on mission response; 2) Different weapons and equipment. Low-orbit satellites used for gaming are equipped with high-power electromagnetic interference equipment, not weapons and equipment for destroying satellites; 3) Different application effects. Drone clusters mainly perform destruction and reconnaissance missions, while low-orbit satellites perform electromagnetic interference and reconnaissance missions. The method for evaluating the effectiveness of mission execution needs to be changed. Summary of the invention

[0009] The technical problem to be solved by the present invention is to solve the problem of mission execution effect evaluation in low-orbit satellite simulation and to provide a method and device for evaluating the execution effect of a low-orbit satellite intervention mission.

[0010] A method for evaluating the execution effect of a low-orbit satellite intervention mission according to an embodiment of the present invention includes:

[0011] S10, calculate the availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system;

[0012] S20, based on the availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system, an improved ADC effectiveness model is used to obtain the intervention mission execution effect score of the low-orbit satellite system.

[0013] According to some embodiments of the present invention, in step S10, the availability matrix A is:

[0014] A=[a1,a2,a3,a4];

[0015] Where:

[0016]

[0017]

[0018]

[0019]

[0020] A i The calculation formula is as follows:

[0021]

[0022] Among them, T Fi is the mean time between failures, T Ri The mean time to repair a fault.

[0023] In some embodiments of the present invention, in step S10, the reliability matrix D is:

[0024]

[0025] Among them, R i The reliability function is:

[0026]

[0027] Where, T i It is the working cycle of each subsystem of the low-orbit satellite during the execution of the intervention mission;

[0028] d 1k The value of k is 1, 2, 3, d 11 The probability that all components of a low-orbit satellite remain normal from the beginning to the end of the mission:

[0029]

[0030] d 12 The probability that a low-orbit satellite is in a reconnaissance payload failure while other components remain normal:

[0031]

[0032] d 13 The probability that a low-orbit satellite is in interference load failure while other components remain normal is:

[0033]

[0034] According to some embodiments of the present invention, in step S10, the capability matrix C is:

[0035] C = [C1, C2, C3, C4];

[0036] Among them, C1 is the capability of the low-orbit satellite system when there is no fault; C2 is the capability of the low-orbit satellite when the reconnaissance payload fails; C3 is the capability of the low-orbit satellite when the interference payload fails; C4 is the capability of the low-orbit satellite system when the series system fails.

[0037] In some embodiments of the present invention, the parameters in C in the capability matrix are calculated as follows:

[0038] C i =(λ1,λ2,λ3,λ4)·[c1,c2,c3,c4];

[0039] In the formula, λ i c i The weight of the indicator; c i It is the comprehensive application efficiency evaluation value of the indicator, calculated using the empirical formula:

[0040]

[0041] T i It represents the time delay from the task being issued to producing actual effect, E i To rate the application effect, Q ei is the additional energy consumption of task execution, D i is the time delay for the task to produce actual results, k is the scoring coefficient, and ε and t are weight coefficients.

[0042] According to some embodiments of the present invention, in step S10, the environmental impact parameter G is:

[0043]

[0044] Where P i is the specific score of each factor in the game environment index; i is the corresponding weight value.

[0045] In some embodiments of the present invention, in step S20, the improved ADC performance model calculation formula is as follows:

[0046] E = A·D·C·(1-G);

[0047] Among them, A is the availability matrix, D is the reliability matrix, C is the capability matrix, and G is the environmental impact parameter.

[0048] A low-orbit satellite intervention mission execution effect evaluation device according to an embodiment of the present invention includes:

[0049] A calculation module is used to calculate the availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system;

[0050] The evaluation module is used to obtain the intervention mission execution effect score of the low-orbit satellite system based on the obtained availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system, using the improved ADC effectiveness model.

[0051] According to some embodiments of the present invention, the calculation formula of the ADC performance model improved by the evaluation module is as follows:

[0052] E = A·D·C·(1-G);

[0053] Among them, A is the availability matrix, D is the reliability matrix, C is the capability matrix, and G is the environmental impact parameter.

[0054] According to the computer storage medium of an embodiment of the present invention, a computer program is stored on the computer storage medium, and when the computer program is executed by a processor, the method for evaluating the execution effect of a low-orbit satellite intervention mission as described above is implemented.

[0055] The present invention has the following beneficial effects:

[0056] The present invention is used in the simulation process of low-orbit satellite intervention mission execution. Since the credibility and reliability parameters are set manually, multiple sets of scenarios with different credibility and reliability parameters can be set during the simulation to test the effect of the intelligent decision-making algorithm in different scenarios. In the simulation process, as long as the input required by the algorithm is given, the score of the current task execution can be output. Based on the score, the algorithm such as intelligent decision-making can be further improved or different decision-making algorithms can be compared, and finally the effect of the low-orbit satellite in performing the intervention mission can be evaluated. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a flow chart of a method for evaluating the execution effect of a low-orbit satellite intervention mission according to an embodiment of the present invention;

[0058] Figure 2 Schematic diagram of a low-orbit satellite intervention mission execution effect evaluation device according to an embodiment of the present invention;

[0059] Figure 3 A schematic diagram of an improved ADC method according to an embodiment of the present invention;

[0060] Figure 4 Schematic diagram of credibility analysis according to an embodiment of the present invention.

[0061] Reference numerals:

[0062] Calculation module 10, evaluation module 20. DETAILED DESCRIPTION

[0063] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined purpose, the present invention is described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0064] The description of the method flow in the specification of the present invention and the steps of the flowchart in the drawings of the specification of the present invention do not have to be strictly executed according to the step numbers, and the method steps can be executed in a different order. Moreover, some steps can be omitted, multiple steps can be combined into one step, and / or one step can be decomposed into multiple steps.

[0065] The purpose of the present invention is to solve the problem of evaluating the performance of missions in low-orbit satellite simulation, to provide a criterion for judging the performance of low-orbit satellite missions, and to provide a reference for intelligent decision-making of low-orbit satellites, so that low-orbit satellites can perform tasks more efficiently. The present invention can be applied in satellite simulation verification work. In the simulation process, the input required by the algorithm is given, and the score of the current mission execution can be output. Based on the score, the algorithm such as intelligent decision-making can be further improved or different decision-making algorithms can be compared.

[0066] like Figure 1 As shown, a method for evaluating the execution effect of a low-orbit satellite intervention mission according to an embodiment of the present invention includes:

[0067] S10, calculate the availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system;

[0068] According to some embodiments of the present invention, in step S10, the availability matrix A is:

[0069] A=[a1,a2,a3,a4];

[0070] Where:

[0071]

[0072]

[0073]

[0074]

[0075] A i The calculation formula is as follows:

[0076]

[0077] Among them, T Fi is the mean time between failures, T Ri The mean time to repair a fault.

[0078] In some embodiments of the present invention, in step S10, the reliability matrix D is:

[0079]

[0080] Among them, R i The reliability function is:

[0081]

[0082] Where, T i It is the working cycle of each subsystem of the low-orbit satellite during the execution of the intervention mission;

[0083] d 1k The value of k is 1, 2, 3, d 11 The probability that all components of a low-orbit satellite remain normal from the beginning to the end of the mission:

[0084]

[0085] d 12 The probability that a low-orbit satellite is in a reconnaissance payload failure while other components remain normal:

[0086]

[0087] d 13 The probability that a low-orbit satellite is in interference load failure while other components remain normal is:

[0088]

[0089] According to some embodiments of the present invention, in step S10, the capability matrix C is:

[0090] C = [C1, C2, C3, C4];

[0091] Among them, C1 is the capability of the low-orbit satellite system when there is no fault; C2 is the capability of the low-orbit satellite when the reconnaissance payload fails; C3 is the capability of the low-orbit satellite when the interference payload fails; C4 is the capability of the low-orbit satellite system when the series system fails.

[0092] In some embodiments of the present invention, the parameters in C in the capability matrix are calculated as follows:

[0093] C i =(λ1,λ2,λ3,λ4)·[c1,c2,c3,c4];

[0094] In the formula, λ i c i The weight of the indicator; c i It is the comprehensive application efficiency evaluation value of the indicator, calculated using the empirical formula:

[0095]

[0096] T i It represents the time delay from the task being issued to producing actual effect, E i To rate the application effect, Q ei is the additional energy consumption of task execution, D i is the time delay for the task to produce actual results, k is the scoring coefficient, and ε and t are weight coefficients.

[0097] According to some embodiments of the present invention, in step S10, the environmental impact parameter G is:

[0098]

[0099] Where P i is the specific score of each factor in the game environment index; i is the corresponding weight value.

[0100] S20, based on the availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system, an improved ADC effectiveness model is used to obtain the intervention mission execution effect score of the low-orbit satellite system.

[0101] In some embodiments of the present invention, in step S20, the improved ADC performance model calculation formula is as follows:

[0102] E = A·D·C·(1-G);

[0103] Among them, A is the availability matrix, D is the reliability matrix, C is the capability matrix, and G is the environmental impact parameter.

[0104] like Figure 2 As shown, the low-orbit satellite intervention mission execution effect evaluation device according to an embodiment of the present invention includes: a calculation module 10 and an evaluation module 20.

[0105] The calculation module 10 is used to calculate the availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system;

[0106] The evaluation module 20 is used to obtain the intervention task execution effect score of the low-orbit satellite system by using the improved ADC performance model based on the obtained availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system.

[0107] According to some embodiments of the present invention, the calculation formula of the ADC performance model improved by the evaluation module 20 is as follows:

[0108] E = A·D·C·(1-G);

[0109] Among them, A is the availability matrix, D is the reliability matrix, C is the capability matrix, and G is the environmental impact parameter.

[0110] According to the computer storage medium of the embodiment of the present invention, a computer program is stored on the computer storage medium, and when the computer program is executed by the processor, the method for evaluating the execution effect of the low-orbit satellite intervention mission as described above is implemented.

[0111] The following is a detailed description of the low-orbit satellite intervention mission execution effect evaluation method of the present invention in conjunction with the accompanying drawings. It should be understood that the following description is only an exemplary description and should not be construed as a specific limitation of the present invention.

[0112] The present invention firstly proposes an empirical analysis formula for evaluating the efficiency and effect of low-orbit satellite operation, which can evaluate the mission execution effect of a single satellite; then the traditional ADC method is improved, taking into account factors such as the credibility, reliability, operation capability and game environment of the low-orbit satellite system, and combined with the empirical analysis formula of a single satellite, the execution effect of the intervention mission of the entire low-orbit satellite system can be evaluated.

[0113] 1. Empirical analysis formula:

[0114] Based on the operating characteristics of satellites and networks, the operational efficiency and effect can be comprehensively considered: efficiency takes into account the energy consumption and timeliness of task execution and is a negative indicator (the lower the better); the effect takes into account the impact on satellite network communications and the duration of intervention.

[0115] 1) Operational efficiency evaluation: considering the energy consumption and time efficiency of low-orbit satellite mission execution;

[0116] The energy consumption mainly includes the energy consumption of electromagnetic interference equipment and the additional energy consumption of low-orbit satellites for orbit change and attitude adjustment. The additional energy consumption of mission information transmission between satellites is negligible. The timeliness is calculated from the time when the task is issued to the time when the actual effect is produced. The efficiency evaluation formula is as follows:

[0117] Q=εQ e +tD (1);

[0118] 2) Application effect evaluation: considering the duration of intervention and the actual effect of intervention;

[0119] The intervention duration is the duration of the low-orbit satellite using electromagnetic interference equipment to paralyze some target low-orbit satellites. The actual effect of the intervention is the hindering effect of the intervention behavior on the information transmission of the low-orbit satellite Internet constellation, which is manifested in the increase of packet loss rate and network transmission delay. The application effect evaluation formula is as follows:

[0120] E=e(k1Δd+k2ΔL) (2);

[0121] Among them, E represents the application effect score, Δd represents the increase in average network transmission delay, ΔL represents the increase in average packet loss rate, k1 and k2 are weight coefficients. Among them, e is the effect ratio coefficient, which is obtained by dividing the number of intervening satellites by the impact range.

[0122]

[0123] Combining the application efficiency and application effect, we get the following formula:

[0124]

[0125] c i represents the comprehensive score, T i It represents the time delay from the task being issued to producing actual effect, E i To rate the application effect, Q ei is the additional energy consumption of task execution, D i is the time delay for the task to produce actual results, k is the scoring coefficient, and ε and t are weight coefficients.

[0126] The above gives the execution effect score of a single satellite mission. The average score of all satellites participating in the intervention mission is the final score of the intervention mission.

[0127] 2) Improved ADC method:

[0128] The traditional ADC model evaluates the effectiveness of weapon systems through the three elements of weapon system availability, credibility, and capability matrix. The specific model expression is:

[0129] E = A·D·C (5);

[0130] Among them, A is the system availability matrix, D is the credibility matrix, and C is the capability matrix.

[0131] According to the characteristics of low-orbit satellite operation, the game environment elements are added and improved into the following formula:

[0132] E = A·D·C·(1-G) (6);

[0133] Among them, G is the environmental impact parameter. The factors considered in each indicator are as follows Figure 3 Each indicator is analyzed below.

[0134] ①Availability A analysis:

[0135] The availability of a low-orbit satellite indicates its status before the execution of an intervention mission and is a measure of the degree to which it can undertake a mission. When a low-orbit satellite performs a mission, its internal structure can be decomposed into six parts: satellite subsystem, ground station subsystem, signal transmission and recovery device, communication link, reconnaissance payload, and interference payload. These parts are in a series relationship. If one of the subsystems fails, the mission cannot be completed. Based on the relationship between the subsystems, an availability block diagram can be constructed, such as Figure 4 There are four working states of the low-orbit satellite system, as shown in Table 1.

[0136] Table 1 Working status of low-orbit satellite system

[0137] Serial number state 1. All working properly 2. ⑤Fault, others are normal 3. ⑥Fault, others are normal 4. At least one of ①②③④ is faulty or both ⑤⑥ are faulty

[0138] The availability of low-orbit satellites A is expressed in terms of the mean time between failures T Fi Divide by the mean time between failures and the mean time to repair failures T Ri The formula is as follows:

[0139]

[0140] In the formula, i is Figure 4 For the 4 working states in Table 1, the low-orbit satellite availability matrix is:

[0141] A=[a1,a2,a3,a4];

[0142] Where:

[0143]

[0144]

[0145]

[0146]

[0147] ②Reliability D analysis:

[0148] The reliability D of a low-orbit satellite refers to the ability of each subsystem of the low-orbit satellite to work normally and complete the intervention task during the mission execution under the condition that the availability A is determined. Assuming that the failure distribution time of the operating subsystem of the low-orbit satellite system follows an exponential distribution, the reliability function represented by parameters such as system failure rate and mean failure time is:

[0149]

[0150] Where T i It is the working cycle of each subsystem of the low-orbit satellite during the execution of the intervention mission.

[0151] Assume d 11 is the probability that all components of the low-orbit satellite remain normal from the beginning to the end of the mission, then there is the following formula:

[0152]

[0153] Assume d 12 The probability that a low-orbit satellite is in a reconnaissance payload failure while other components remain normal is given by the following formula:

[0154]

[0155] Assume d 13 The probability that a low-orbit satellite is in interference load failure while other components remain normal is given by the following formula:

[0156]

[0157] The low-orbit satellite system consists of five subsystems connected in series and two payload systems connected in parallel. Failure of a subsystem will degrade the capability of the entire system or cause it to fail as a whole. Its reliability matrix is ​​a triangular matrix. According to equations (8) and (9), the reliability parameter matrix can be obtained as follows:

[0158]

[0159] ③Application ability C analysis

[0160] The low-orbit satellite capability matrix C reflects the ability of the low-orbit satellite to complete the intervention mission under different conditions, and reflects the degree of compliance between the system performance and the actual combat capability requirements. Formula (4) is used to calculate the application effect of the low-orbit satellite:

[0161] C i =(λ1,λ2,λ3,λ4)·[c1,c2,c3,c4] (13);

[0162] Where λ i c i The weight of the indicator; c i is the comprehensive performance evaluation value of the indicator, calculated using the empirical formula (4).

[0163] The available capability matrix C is:

[0164] C = [C1, C2, C3, C4] (14);

[0165] Among them, C1 is the capability when the whole system is fault-free; C2 is the capability when the detection load fails; C3 is the capability when the interference load fails; C4 is the capability when the series system fails, C4=0.

[0166] ④Analysis of game environment G:

[0167] The low-orbit satellite game environment G refers to the construction of a realistic game environment during the execution of the intervention mission, such as an electromagnetic interference environment, to fully evaluate the effectiveness of the low-orbit satellite under this condition.

[0168]

[0169] Where: P i is the specific score of each factor in the game environment index; i is the corresponding weight value.

[0170] In summary, the present invention uses empirical analysis formulas and improved ADC methods to achieve the evaluation of the execution effect of low-orbit satellite intervention tasks. The present invention improves the existing effect evaluation method used in the use of drone clusters, applies it to the field of low-orbit satellite simulation, and provides an evaluation method for the simulation of the execution effect of low-orbit satellite intervention tasks. Compared with the application scenario of drone clusters, the algorithm is adapted to the characteristics of low-orbit satellites, and factors such as energy consumption and timeliness are taken into account, highlighting the importance of low-orbit satellite energy consumption and mission timeliness.

[0171] The present invention has the following beneficial effects:

[0172] The present invention is used in the simulation process of low-orbit satellite intervention mission execution. Since the credibility and reliability parameters are set manually, multiple sets of scenarios with different credibility and reliability parameters can be set during the simulation to test the effect of the intelligent decision-making algorithm in different scenarios. In the simulation process, as long as the input required by the algorithm is given, the score of the current task execution can be output. Based on the score, the algorithm such as intelligent decision-making can be further improved or different decision-making algorithms can be compared, and finally the effect of the low-orbit satellite in performing the intervention mission can be evaluated.

[0173] Through the description of the specific implementation methods, a deeper and more specific understanding of the technical means and effects adopted by the present invention to achieve the predetermined purpose should be obtained. However, the accompanying drawings are only for reference and illustration purposes and are not intended to limit the present invention.

Claims

1. A method for evaluating the execution effect of a low-orbit satellite intervention mission, characterized in that: include: S10, calculate the availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system; S20, based on the availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system, the improved ADC effectiveness model is used to obtain the intervention mission execution effect score of the low-orbit satellite system; In step S10, the availability matrix A is: A=[a1,a2,a3,a4]; Where: A i The calculation formula is as follows: Among them, T Fi is the mean time between failures, T Ri is the mean time to repair a problem; The reliability matrix D is: Among them, R i The reliability function is: Where, T i It is the working cycle of each subsystem of the low-orbit satellite during the execution of the intervention mission; d 1k The value of k is 1, 2, 3, d 11 The probability that all components of a low-orbit satellite remain normal from the beginning to the end of the mission: d 12 The probability that a low-orbit satellite is in a reconnaissance payload failure while other components remain normal: d 13 The probability that a low-orbit satellite is in interference load failure while other components remain normal is: The capability matrix C is: C = [C1, C2, C3, C4]; Among them, C1 is the capability of the low-orbit satellite system when there is no fault; C2 is the capability of the low-orbit satellite when the reconnaissance payload fails; C3 is the capability of the low-orbit satellite when the interference payload fails; C4 is the capability of the low-orbit satellite system when the series system fails; The parameters in C in the capability matrix are calculated as follows: C i =(λ1,λ2,λ3,λ4)·[c1,c2,c3,c4]; In the formula, λ i is the weight of the ith indicator; c i It is the comprehensive application efficiency evaluation value of the indicator, calculated using the empirical formula: T i It represents the time delay from the task being issued to producing actual effect, E i To rate the application effect, Q ei is the additional energy consumption of task execution, D i is the time delay from task issuance to actual effect, k is the scoring coefficient, ε and t are weight coefficients; In step S20, the improved ADC performance model calculation formula is as follows: E = A·D·C·(1-G); Among them, A is the availability matrix, D is the reliability matrix, C is the capability matrix, and G is the environmental impact parameter.

2. The method for evaluating the execution effect of a low-orbit satellite intervention mission according to claim 1, characterized in that: In step S10, the environmental impact parameter G is: Where P i is the specific score of each factor in the game environment index; i is the corresponding weight value.

3. A low-orbit satellite intervention mission execution effect evaluation device, characterized in that: include: A calculation module is used to calculate the availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system; An evaluation module is used to obtain the intervention mission execution effect score of the low-orbit satellite system based on the availability matrix, reliability matrix, capability matrix and environmental impact parameters of the low-orbit satellite system, using an improved ADC effectiveness model; The availability matrix A is: A=[a1,a2,a3,a4]; Where: A i The calculation formula is as follows: Among them, T Fi is the mean time between failures, T Ri is the mean time to repair a problem; The reliability matrix D is: Among them, R i The reliability function is: Where, T i It is the working cycle of each subsystem of the low-orbit satellite during the execution of the intervention mission; d 1k The value of k is 1, 2, 3, d 11 The probability that all components of a low-orbit satellite remain normal from the beginning to the end of the mission: d 12 The probability that a low-orbit satellite is in a reconnaissance payload failure while other components remain normal: d 13 The probability that a low-orbit satellite is in interference load failure while other components remain normal is: The capability matrix C is: C = [C1, C2, C3, C4]; Among them, C1 is the capability of the low-orbit satellite system when there is no fault; C2 is the capability of the low-orbit satellite when the reconnaissance payload fails; C3 is the capability of the low-orbit satellite when the interference payload fails; C4 is the capability of the low-orbit satellite system when the series system fails; The parameters in C in the capability matrix are calculated as follows: C i =(λ1,λ2,λ3,λ4)·[c1,c2,c3,c4]; In the formula, λ i is the weight of the ith indicator; c i It is the comprehensive application efficiency evaluation value of the indicator, calculated using the empirical formula: T i It represents the time delay from the task being issued to producing actual effect, E i To rate the application effect, Q ei is the additional energy consumption of task execution, D i is the time delay from task issuance to actual effect, k is the scoring coefficient, ε and t are weight coefficients; The calculation formula of the ADC performance model improved by the evaluation module is as follows: E = A·D·C·(1-G); Among them, A is the availability matrix, D is the reliability matrix, C is the capability matrix, and G is the environmental impact parameter.

4. A computer storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method for evaluating the execution effect of a low-orbit satellite intervention mission as described in any one of claims 1 to 2 is implemented.

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