Spacecraft task scheduling method and system, electronic equipment and storage medium

Abstract

The invention discloses a spacecraft task scheduling method and system, electronic equipment and a storage medium, and relates to the technical field of spacecraft task scheduling, and the method comprises the steps: calculating and obtaining a total score of a preset to-be-scheduled spacecraft task according to a criterion layer weight vector and a factor layer score vector corresponding to the preset to-be-scheduled spacecraft task, and performing priority ranking on all the to-be-scheduled spacecraft tasks according to the size of the total score of each to-be-scheduled spacecraft task, and scheduling and executing all the to-be-scheduled spacecraft tasks according to a priority ranking sequence. Based on the fuzzy hierarchical comprehensive analysis, the accuracy and interpretability of the priority evaluation of the spacecraft tasks can be improved, the priority ranking sequence is more accurate and reliable, and accurate scheduling and execution of the spacecraft tasks can be realized.

Description

Background Art

[0002] With the maturity of key technologies such as launch and recovery of launch vehicles and low-cost miniaturized spacecraft manufacturing, the number of spacecraft entering orbit has increased rapidly, especially in key orbital belts, where spacecraft from various countries are densely distributed and space is becoming increasingly crowded. In addition, due to spacecraft collisions or launch failures, a large amount of space debris will be generated, and the collision of debris with spacecraft will further trigger a chain reaction, threatening the safety of space assets. In order to protect my country's space assets and ensure the smooth operation of spacecraft in orbit, detection equipment is needed to conduct in-orbit observations of space targets. In the face of a large number of spacecraft and space debris, with limited detection equipment, it is necessary to coordinate detection resources to achieve task scheduling, and the spacecraft mission priority is a key indicator to measure the importance of the detection mission. Accurate and efficient evaluation of the detection mission priority can help mission planning be more reasonable and reliable.

[0003] Among the many mission priority evaluation models, the hierarchical analysis method is widely used because it requires less quantitative data and has a clear calculation process. However, when there are too many measurement indicators, the data statistics work is complicated, the degree of weight rationalization decreases, and with less quantitative data, the analysis results are difficult to be convincing, which greatly interferes with the scheduling of spacecraft missions. Summary of the invention

[0004] The technical problem to be solved by the present invention is to address the deficiencies of the prior art and specifically provide a method for scheduling spacecraft tasks, which is as follows:

[0005] 1) In the first aspect, the present invention provides a method for scheduling a spacecraft mission, and the specific technical solution is as follows:

[0006] Calculate and obtain the total score of the preset spacecraft task to be scheduled according to the criterion layer weight vector and the factor layer score vector corresponding to the preset spacecraft task to be scheduled, until the total score of each spacecraft task to be scheduled is obtained, wherein the preset spacecraft task to be scheduled is associated with at least one criterion, each criterion is associated with at least one factor, and the criterion layer weight vector corresponding to the preset spacecraft task to be scheduled includes: the weight corresponding to each criterion associated with the preset spacecraft task to be scheduled, and the preset spacecraft task to be scheduled is any spacecraft task to be scheduled;

[0007] According to the total score of each spacecraft mission to be scheduled, all spacecraft missions to be scheduled are prioritized, and all spacecraft missions to be scheduled are scheduled and executed according to the priority sequence.

[0008] The beneficial effects of a spacecraft mission scheduling method provided by the present invention are as follows:

[0009] Based on fuzzy hierarchical comprehensive analysis (specifically reflected in the weight vector of the criterion layer and the score vector of the factor layer), the accuracy and interpretability of the priority assessment of spacecraft missions can be improved, the priority sorting sequence is more accurate and reliable, and the precise scheduling and execution of spacecraft missions can be achieved.

[0010] On the basis of the above scheme, a method for scheduling a spacecraft mission of the present invention can be further improved as follows.

[0011] Furthermore, it also includes:

[0012] According to the evaluation index score vector corresponding to the preset spacecraft mission to be scheduled, and in combination with the factor layer weight vector group corresponding to the preset spacecraft mission to be scheduled, the factor layer score vector corresponding to the preset spacecraft mission to be scheduled is calculated, wherein each factor associated with the preset spacecraft mission to be scheduled includes at least one evaluation index, and the factor layer weight vector group corresponding to the preset spacecraft mission to be scheduled includes: the factor layer weight vector of each criterion associated with the preset spacecraft mission to be scheduled, and the factor layer weight vector of any criterion includes: the weight of each factor associated with the criterion.

[0013] Furthermore, it also includes:

[0014] The analytic hierarchy process is used to calculate the criterion layer weight vector and factor layer weight vector corresponding to the preset spacecraft mission to be scheduled.

[0015] Furthermore, the process of calculating the evaluation index score vector corresponding to the preset spacecraft mission to be scheduled includes:

[0016] Determine the factor layer function corresponding to each factor associated with the preset spacecraft mission to be scheduled, and construct a task attribute vector as the input of the corresponding factor layer function, and calculate the task attribute probability factor vector, the task attribute vector includes the input amount of each criterion associated with the preset spacecraft mission to be scheduled, the input amount of any criterion includes: the input amount of each factor associated with the criterion, and the factor layer function corresponding to any factor is: the membership function determined from the combination of the membership functions corresponding to each evaluation index of the factor according to the input amount of the factor;

[0017] Normalize the task attribute probability factor vector to obtain the task attribute probability factor matrix;

[0018] According to the task attribute probability factor matrix and the priority score corresponding to each evaluation indicator associated with each factor, the evaluation indicator score vector is calculated.

[0019] 2) In the second aspect, the present invention also provides a scheduling system for spacecraft missions, and the specific technical solution is as follows:

[0020] It includes a total score calculation module and a scheduling execution module;

[0021] The total score calculation module is used to: calculate and obtain the total score of the preset spacecraft task to be scheduled according to the criterion layer weight vector and the factor layer score vector corresponding to the preset spacecraft task to be scheduled, until the total score of each spacecraft task to be scheduled is obtained, wherein the preset spacecraft task to be scheduled is associated with at least one criterion, each criterion is associated with at least one factor, and the criterion layer weight vector corresponding to the preset spacecraft task to be scheduled includes: the weight corresponding to each criterion associated with the preset spacecraft task to be scheduled, and the preset spacecraft task to be scheduled is any spacecraft task to be scheduled;

[0022] The scheduling execution module is used to prioritize all spacecraft tasks to be scheduled according to the total score of each spacecraft task to be scheduled, and schedule and execute all spacecraft tasks to be scheduled according to the priority sorting sequence.

[0023] Based on the above scheme, the scheduling system of a spacecraft mission of the present invention can also be improved as follows.

[0024] Furthermore, it also includes a factor layer score vector calculation module, which is used to:

[0025] According to the evaluation index score vector corresponding to the preset spacecraft mission to be scheduled, and in combination with the factor layer weight vector group corresponding to the preset spacecraft mission to be scheduled, the factor layer score vector corresponding to the preset spacecraft mission to be scheduled is calculated, wherein each factor associated with the preset spacecraft mission to be scheduled includes at least one evaluation index, and the factor layer weight vector group corresponding to the preset spacecraft mission to be scheduled includes: the factor layer weight vector of each criterion associated with the preset spacecraft mission to be scheduled, and the factor layer weight vector of any criterion includes: the weight of each factor associated with the criterion.

[0026] Furthermore, a weight vector calculation module is included, and the weight vector calculation module is used to:

[0027] The analytic hierarchy process is used to calculate the criterion layer weight vector and factor layer weight vector corresponding to the preset spacecraft mission to be scheduled.

[0028] Furthermore, it also includes an evaluation index score vector calculation module, which is used to:

[0029] Determine the factor layer function corresponding to each factor associated with the preset spacecraft mission to be scheduled, and construct a task attribute vector as the input of the corresponding factor layer function, and calculate the task attribute probability factor vector, the task attribute vector includes the input amount of each criterion associated with the preset spacecraft mission to be scheduled, the input amount of any criterion includes: the input amount of each factor associated with the criterion, and the factor layer function corresponding to any factor is: the membership function determined from the combination of the membership functions corresponding to each evaluation index of the factor according to the input amount of the factor;

[0030] Normalize the task attribute probability factor vector to obtain the task attribute probability factor matrix;

[0031] According to the task attribute probability factor matrix and the priority score corresponding to each evaluation indicator associated with each factor, the evaluation indicator score vector is calculated.

[0032] 3) In a third aspect, the present invention further provides an electronic device, comprising a processor, the processor being coupled to a memory, the memory storing at least one computer program, the at least one computer program being loaded and executed by the processor so that the electronic device can implement any one of the above-mentioned scheduling methods for spacecraft missions.

[0033] 4) In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-mentioned methods for scheduling spacecraft missions.

[0034] It should be noted that the beneficial effects achieved by the technical solutions of the second to fourth aspects of the present invention and the corresponding possible implementation methods can be found in the above-mentioned technical effects of the first aspect and its corresponding possible implementation methods, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments of the present invention:

[0036] Figure 1 A schematic diagram of a flow chart of a method for scheduling a spacecraft mission according to an embodiment of the present invention;

[0037] Figure 2 A schematic diagram of the structure of a scheduling system for spacecraft missions according to an embodiment of the present invention;

[0038] Figure 3 The figure is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The principles and features of the present invention are described below. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0040] The technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0041] like Figure 1 As shown, a method for scheduling a spacecraft mission according to an embodiment of the present invention includes the following steps:

[0042] S1. Calculate and obtain the total score of the preset spacecraft task to be scheduled according to the criterion layer weight vector and the factor layer score vector corresponding to the preset spacecraft task to be scheduled, until the total score of each spacecraft task to be scheduled is obtained, wherein the preset spacecraft task to be scheduled is associated with at least one criterion, each criterion is associated with at least one factor, and the criterion layer weight vector corresponding to the preset spacecraft task to be scheduled includes: the weight corresponding to each criterion associated with the preset spacecraft task to be scheduled, and the preset spacecraft task to be scheduled is any spacecraft task to be scheduled;

[0043] S2. Prioritize all the spacecraft tasks to be scheduled according to the total score of each spacecraft task to be scheduled, and schedule and execute all the spacecraft tasks to be scheduled according to the priority sequence.

[0044] Optionally, in the above technical solution, it also includes:

[0045] S01. According to the evaluation index score vector corresponding to the preset spacecraft mission to be scheduled, and in combination with the factor layer weight vector group corresponding to the preset spacecraft mission to be scheduled, the factor layer score vector corresponding to the preset spacecraft mission to be scheduled is calculated, wherein each factor associated with the preset spacecraft mission to be scheduled includes at least one evaluation index, and the factor layer weight vector group corresponding to the preset spacecraft mission to be scheduled includes: the factor layer weight vector of each criterion associated with the preset spacecraft mission to be scheduled, and the factor layer weight vector of any criterion includes: the weight of each factor associated with the criterion.

[0046] Optionally, in the above technical solution, it also includes:

[0047] S02. Calculate the criterion layer weight vector and factor layer weight vector corresponding to the preset spacecraft mission to be scheduled by using the hierarchical analysis method.

[0048] Optionally, in the above technical solution, the process of calculating the evaluation index score vector corresponding to the preset spacecraft mission to be scheduled includes:

[0049] S001. Determine the factor layer function corresponding to each factor associated with the preset spacecraft mission to be scheduled, and construct a task attribute vector as the input of the corresponding factor layer function, and calculate the task attribute probability factor vector, the task attribute vector includes the input amount of each criterion associated with the preset spacecraft mission to be scheduled, the input amount of any criterion includes: the input amount of each factor associated with the criterion, and the factor layer function corresponding to any factor is: the membership function determined from the combination of the membership functions corresponding to each evaluation index of the factor according to the input amount of the factor;

[0050] S002. Normalize the task attribute probability factor vector to obtain a task attribute probability factor matrix;

[0051] S003. Calculate the evaluation index score vector according to the task attribute probability factor matrix and the priority score corresponding to each evaluation index associated with each factor.

[0052] The present invention is illustrated by the following two examples.

[0053] Embodiment 1:

[0054] The method for scheduling spacecraft missions in Example 1 comprises the following steps:

[0055] S10, determining a set of criteria and a set of factors for a preset spacecraft to be scheduled, specifically:

[0056] All the criteria associated with the preset spacecraft to be scheduled constitute the criterion set U of the preset spacecraft to be scheduled. The criterion set U is [u 1 ,u 2 ,…,u n-1 ,u n ], where u i represents the i-th criterion in the criterion set U, i = 1, 2, ..., n-1, n, u i All the factors associated make up u i The set of factors is: Among them, use u i,j Indicates u i The jth factor in the factor set, that is, u i,j is the jth factor of the i-th criterion, j = 1, 2, ..., m i -1,m i , m i It means: the number of all factors associated with the i-th criterion.

[0057] S11. Calculate the criterion layer weight vector corresponding to the preset spacecraft mission to be scheduled by using the hierarchical analysis method. Specifically:

[0058] S110, construct a judgment matrix A by using the consistent matrix method, A = [a i′,j′ ] n×n , a i′,j′ >0, i′=1,2,…,n-1,n,j′=1,2,…,n-1,n,i′=i,j′=j,a i′,j′ Meaning: Determine the value of the element in the i'th row and j'th element in the matrix A (also called the scale), that is, use a i′,j′ Represents the importance between the i-th criterion and the j-th criterion. When i′=j′, a i′,j′ =1, the judgment matrix A compares the importance of each two criteria in the criterion set U, rather than comparing all criteria together. In the comparison process, it is necessary to put each two criteria on the same scale to reduce the comparison error or reduce the difficulty of comparison. Saaty's 1-9 scaling method is usually used, as shown in Table 1.

[0059] Table 1:

[0060] <![CDATA[Scale (element a in the judgment matrix i′,j′ )]]> meaning 1 The i-th criterion is as important as the j-th criterion 3 The i-th criterion is slightly more important than the j-th criterion 5 The i-th criterion is significantly more important than the j-th criterion 7 The i-th criterion is more important than the j-th criterion 9 The i-th criterion is much more important than the j-th criterion 2,4,6,8 Between the above two scales

[0061] S111, check the consistency of the judgment matrix A:

[0062] ① It is necessary to find the maximum eigenvalue λ of the judgment matrix A max , and through the maximum eigenvalue λ max Calculate the consistency index CI, which is calculated by the following formula:

[0063]

[0064] Among them, n′ represents the dimension of the judgment matrix A, n′=n, and CI is used to measure the difference between the maximum eigenvalue and the judgment matrix A. CI=0 means that the judgment matrix A is completely consistent; the closer the CI is to 0, the more satisfactory the consistency; the larger the CI is, the more serious the inconsistency of the judgment matrix A is.

[0065] ② Calculate the consistency ratio CR, which is calculated using the following formula:

[0066]

[0067] Among them, RI is the average random consistency index, which is the standard for testing the consistency of the judgment matrix A. RI is only related to the order of the judgment matrix A (the order of the judgment matrix A is equal to n). According to the evaluation standard of the average random consistency index given by Saaty's 1-9 scaling method, it is generally believed that when CR<0.1, the inconsistency of the judgment matrix A is within the allowable range, with satisfactory consistency, and passes the consistency test. The judgment matrix A can be used to calculate the criterion layer weight vector, otherwise a i′,j′ Adjustments are made and the judgment matrix A is reconstructed. It should be noted that for a factor set with 2 elements, no consistency check is required.

[0068] S112, when the consistency check of the judgment matrix A passes, the value of each element in the judgment matrix A is normalized according to the columns in the judgment matrix A, specifically calculated by the following formula:

[0069]

[0070] in, Means: According to the columns in the judgment matrix A, for a i′,j′ The normalized value.

[0071] S113, according to the rows in the judgment matrix A, the normalized values ​​of the elements in the same row are added to obtain the sum vector of the elements in each row, and the sum vector of the elements in each row is divided by the order to obtain the weight corresponding to the elements in each row, which is specifically calculated by the following formula:

[0072]

[0073] Among them, W i′ Indicates: the corresponding weight of the element in the i′th row in the judgment matrix A.

[0074] Since each row of elements in the judgment matrix A corresponds to the same criterion, the weight corresponding to each row of elements is used as the weight of the corresponding criterion, thereby obtaining the criterion layer weight vector V u , that is, W i′ As u i The corresponding weight (because: i′=i).

[0075] S12. Calculate the factor layer weight vector corresponding to the preset spacecraft mission to be scheduled by using the hierarchical analysis method. For details, refer to the specific implementation process of S11, which will not be described here.

[0076] S13. Construct factor layer weight vector group:

[0077] The factor layer weight vectors are stacked to construct the factor layer weight vector group H u , H uFor [H u,1 ,H u,2 ,…,H u,n-1 ,H u,n ], use H u,i″ Represents the factor-level weight vector of the i″th criterion associated with the i″th criterion, i″=1,2,…,n-1,n.

[0078] S14, u i,j All associated evaluation indicators form u i,j Corresponding evaluation index set for use Indicates u i,j The kth evaluation index associated with Indicates: i,j The total number of all associated evaluation indicators, set The corresponding priority value set for The corresponding priorities are The corresponding priorities are The corresponding priorities are: The corresponding priorities are The corresponding priorities are

[0079] S15, determining the factor layer function corresponding to each factor associated with the preset spacecraft mission to be scheduled, as follows:

[0080] Membership is a way to describe the relationship between an element and a set. It changes the relationship between an element and a set from "absolutely belonging or not" to "relatively belonging". The membership function (also called membership function) uses the form of a function to describe the degree to which an element belongs to a set. Commonly used membership functions are as follows:

[0081] 1) Triangle membership function:

[0082]

[0083] 2) Trapezoidal membership function:

[0084]

[0085] 3) Gaussian membership function:

[0086]

[0087] 4) Bell-shaped membership function:

[0088]

[0089] Construct a factor layer function based on each factor in the factor set, specifically:

[0090] A membership function is constructed for each evaluation index of each factor in the factor set. Therefore, the factor layer function corresponding to any factor is: the membership function determined from the combination of the membership functions corresponding to each evaluation index of the factor according to the input of the factor. The triangular membership function or the trapezoidal membership function can be used to construct the factor u i,j The factor layer function, the parameters of each membership function are set according to the actual scope.

[0091] S16. Construct a task attribute vector X as input, and form a task attribute probability factor vector based on the membership function. Specifically:

[0092] The configuration of the task attribute vector X is in, Represents: The i-th criterion u i The input amount, for in, Represents: The i-th criterion u i The input amount of the jth factor.

[0093] For each element in the task attribute vector X (i.e.: ) are transformed into probability factor vectors through corresponding membership functions. The probability factor vector obtained by the corresponding factor layer function conversion is: [f 1 (x),f 2 (x),…,f o (x)].

[0094] S17, normalize the task attribute probability factor vector to obtain the task attribute probability factor matrix, specifically:

[0095] The task attribute probability factor vector is standardized using the following formula:

[0096]

[0097] f p ′(x) is the value of f p (x) The value obtained after normalization, f p (x p ) means: the pth input x in the task attribute vector pThe pth membership function in the input factor layer function, o represents the total number of all factors in the task attribute vector X, which is equal to the total number of all input quantities in the task attribute vector X and the total number of factor layer functions.

[0098] [f 1 (x),f 2 (x),…,f o (x)] is normalized to obtain [f 1 ′(x),f 2 ′(x),…,f o ′(x)], and convert [f′ 1 (x),f′ 2 (x),…,f′ o (x)] are stacked to form the task attribute probability factor matrix J(X).

[0099] S18. Calculate the evaluation index score vector and factor layer score vector:

[0100] Get the priority score corresponding to each factor, stack all the priority scores by row, and get the evaluation index priority matrix S. Further calculate and get the evaluation index score vector H(X), H(X)=J(X)×S.

[0101] According to the evaluation index score vector corresponding to the preset spacecraft mission to be scheduled, and in combination with the factor layer weight vector group corresponding to the preset spacecraft mission to be scheduled, the factor layer score vector corresponding to the preset spacecraft mission to be scheduled is calculated, specifically:

[0102] Reorganize the evaluation index score vector H(X) into dimensions (reorganize according to the criteria) to obtain H′(X), and use the formula V(X) = H u ×H′(X), and obtain the factor layer score vector V(X).

[0103] S19, using the formula z = V u ×H(X), calculate the total score of the preset spacecraft tasks to be scheduled, until the total score of each spacecraft task to be scheduled is obtained, and all spacecraft tasks to be scheduled are prioritized according to the total score, and all spacecraft tasks to be scheduled are scheduled and executed according to the priority sorting sequence. Among them, the higher the total score, the higher the priority, and the priority is scheduled and executed.

[0104] Embodiment 2:

[0105] The method for scheduling spacecraft tasks in Example 2 includes the following steps:

[0106] S20, determining a set of criteria and a set of factors for a preset spacecraft to be scheduled, specifically:

[0107] All the criteria associated with the preset spacecraft to be scheduled constitute the criterion set U of the preset spacecraft to be scheduled, where U is [u 1 ,u 2 ,…,u n-1 ,u n ], where u i represents the i-th criterion in the criterion set U, i = 1, 2, ..., n-1, n, u i All the factors associated make up u i The factor set is Among them, use u i,j Indicates u i The jth factor in the factor set, that is, u i,j is the jth factor of the i-th criterion, j = 1, 2, ..., m i -1,m i , m i It means: the number of all factors associated with the i-th criterion.

[0108] In Example 2, as shown in Table 2, the criterion set U includes 4 criteria, n = 4, i = 1, 2, 3, 4, and the 4 criteria are: target position, target speed, threat level and hostility level. The target position is used as u 1 , taking the target speed as u 2 , taking the threat level as u 3 , and the hostility level is u 4 ; Target position u 1 The factor set includes 2 factors, namely target distance and target height, m 1 =2, and the target distance is taken as u 1,1 , and take the target height as u 1,2 ; Target speed u 2 The factor set includes three factors, namely radial speed, maneuvering speed and heading, m 2 =3, taking the radial velocity as u 2,1 , taking the maneuvering speed as u 2,2 , and take the heading as u 2,3 ; Threat level u 3 The factor set includes three factors, namely, target trajectory direction, target type and target load, m 3 =3, the target trajectory direction is taken as u 3,1 , set the target type as u 3,2 , taking the target load as u 3,3 ; Hostility level u 4 The factor set includes two factors, namely, the degree of proximity and the enemy and friend situation, m 4 =2, and the degree of closeness is taken as u 4,1 , taking the enemy and our own situation as u4,2 .

[0109] Table 2:

[0110]

[0111]

[0112] S21. Calculate the criterion layer weight vector corresponding to the preset spacecraft mission to be scheduled by using the hierarchical analysis method. Specifically:

[0113] S210, construct a judgment matrix A by using the consistent matrix method, A = [a i′,j′ ] n×n , a i′,j′ >0, i′=1,2,…,n-1,n,j′=1,2,…,n-1,n,i′=i,j′=j,a i′,j′ Meaning: Determine the value of the element in the i'th row and j'th element in the matrix A (also called the scale), that is, use a i′,j′ Represents the importance between the i-th criterion and the j-th criterion. When i′=j′, a i′,j′ =1, the judgment matrix A compares the importance of each two criteria in the criterion set U, rather than comparing all criteria together. In the comparison process, it is necessary to put each two criteria on the same scale to reduce comparison errors or reduce comparison difficulty. Santy's 1-9 scaling method is usually used.

[0114] In Example 2, each element in the judgment matrix A is determined based on expert experience, i′=j′=4, as shown in Table 3.

[0115] Table 3:

[0116] Target location Target speed Threat Level Hostility Target location <![CDATA[a 1,1 =1]]> <![CDATA[a 1,2 =2]]> <![CDATA[a 1,3 =3]]> <![CDATA[a 1,4 =5]]> Target speed <![CDATA[a 2,1 =1 / 2]]> <![CDATA[a 2,2 =1]]> <![CDATA[a 2,3 =2]]> <![CDATA[a 2,4 =4]]> Threat Level <![CDATA[a 3,1 =1 / 3]]> <![CDATA[a 3,2 =1 / 2]]> <![CDATA[a 3,3 =1]]> <![CDATA[a 3,4 =3]]> Hostility <![CDATA[a 4,1 =1 / 5]]> <![CDATA[a 4,2 =1 / 4]]> <![CDATA[a 4,3 =1 / 3]]> <![CDATA[a 4,4 =1]]>

[0117] S211, check the consistency of the judgment matrix A:

[0118] ① It is necessary to find the maximum eigenvalue λ of the judgment matrix A max , and through the maximum eigenvalue λ max Calculate the consistency index CI, which is calculated by the following formula:

[0119]

[0120] Among them, n′ represents the dimension of the judgment matrix A, n′=n, and CI is used to measure the difference between the maximum eigenvalue and the judgment matrix A. CI=0 means that the judgment matrix A is completely consistent; the closer the CI is to 0, the more satisfactory the consistency; the larger the CI is, the more serious the inconsistency of the judgment matrix A is.

[0121] ② Calculate the consistency ratio CR, which is calculated using the following formula:

[0122]

[0123] Among them, RI is the average random consistency index, which is the standard for testing the consistency of the judgment matrix A. RI is only related to the order of the judgment matrix A (the order of the judgment matrix A is equal to n). According to the evaluation criteria for the average random consistency index given by Santy's 1-9 scaling method, as shown in Table 4, it is generally believed that: when CR<0.1, the inconsistency of the judgment matrix A is within the allowable range, with satisfactory consistency, and passes the consistency test. The judgment matrix A can be used to calculate the criterion layer weight vector, otherwise a i′,j′ Adjustments are made and the judgment matrix A is reconstructed. It should be noted that for a factor set with 2 elements, no consistency check is required.

[0124] Table 4:

[0125]

[0126] In Example 2, after calculation, the maximum eigenvalue λ is obtained max The value is 4.05, the consistency index CI is 0.017, and the average random consistency index CR is 0.019. The consistency test is passed and the subsequent steps are continued.

[0127] S212, when the consistency check of the judgment matrix A passes, the value of each element in the judgment matrix A is normalized according to the columns in the judgment matrix A, specifically calculated by the following formula:

[0128]

[0129] in, Means: According to the columns in the judgment matrix A, for a i′,j′ The normalized value.

[0130] S213, according to the rows in the judgment matrix A, the normalized values ​​of the elements in the same row are added to obtain the sum vector of the elements in each row, and the sum vector of the elements in each row is divided by the order to obtain the weight corresponding to the elements in each row, which is specifically calculated by the following formula:

[0131]

[0132] Among them, W i′ Indicates: the corresponding weight of the element in the i′th row in the judgment matrix A.

[0133] Since each row of elements in the judgment matrix A corresponds to the same criterion, the weight corresponding to each row of elements is used as the weight of the corresponding criterion, thereby obtaining the criterion layer weight vector V u , V u is [0.47, 0.29, 0.17, 0.07], that is, W i′ As u i The corresponding weight (because: i′=i).

[0134] S22. Calculate the factor layer weight vector corresponding to the preset spacecraft mission to be scheduled by using the hierarchical analysis method. Specifically:

[0135] is the target position u 1 Constructed judgment matrix A 1 The elements in are shown in Table 5.

[0136] Table 5:

[0137] Target distance Target height Target distance 1 3 Target height 1 / 3 1

[0138] Since the target position u 1 There are only two elements in the factor set, and no consistency check is required. The target position u is obtained by calculation. 1 The factor layer weight vector H u,1 , H u,1 is [0.75,0.25].

[0139] is the target speed u 2 Constructed judgment matrix A 2 The elements in are shown in Table 6.

[0140] Table 6:

[0141] Radial velocity Maneuvering speed course Radial velocity 1 1 / 3 5 Maneuvering speed 3 1 9 course 1 / 5 1 / 9 1

[0142] After calculation, we get the judgment matrix A 2 The maximum eigenvalue is 3.03, the consistency index CI is 0.015, and the average random consistency index CR is 0.025. Through the consistency test, the target speed u is calculated. 2 The factor layer weight vector H u,2 , H u,2 is [0.27,0.67,0.06].

[0143] The threat level u 3 Constructed judgment matrix A 3 The elements in are shown in Table 7.

[0144] Table 7:

[0145] Target trajectory direction Target Type Target load Target trajectory direction 1 1 / 5 1 / 3 Target Type 5 1 2 Target load 3 1 / 2 1

[0146] After calculation, we get the judgment matrix A 3 The maximum eigenvalue is 3.00, the consistency index CI is 0.0018, and the average random consistency index CR is 0.0032. Through the consistency test, the threat level u is calculated. 3 The factor layer weight vector H u,3 , H u,3 is [0.11,0.58,0.31].

[0147] The hostility level u 4 Constructed judgment matrix A 4 The elements in are shown in Table 8.

[0148] Table 8:

[0149] Proximity Enemy and Friends Proximity 1 1 / 3 Enemy and Friends 3 1

[0150] Due to the hostility 4 There are only two elements in the factor set, and no consistency check is required. The hostility degree u is calculated. 4 The factor layer weight vector H u,4 , H u,4 is [0.25,0.75].

[0151] S23. Construct factor layer weight vector group:

[0152] The factor layer weight vectors are stacked to construct the factor layer weight vector group H u , i″=1,2,3,4,H u =(H u,1 ,H u,2 ,H u,3 ,H u,4 ).

[0153] S24. Will u i,j All associated evaluation indicators form u i,j Corresponding evaluation index set for use Indicates u i,j The jth evaluation index associated with Indicates: i,j The total number of all associated evaluation indicators, set The corresponding priority value set for The corresponding priority is divided into The corresponding priority is divided into The corresponding priority is divided into: The corresponding priority is divided into The corresponding priority is divided into Specifically as follows:

[0154] 1) Target distance u 1,1 All associated evaluation indicators include: "near", "medium", and "far", then Target distance u 1,1 The corresponding evaluation indicator set Includes: Taking "near" as Taking "medium" as Taking "far" as Is [9, 5, 1].

[0155] 2) Target height u 1,2 All associated evaluation indicators include: "low", "medium", and "high", then Target height u 1,2 The corresponding evaluation indicator set Includes: Taking "low" as Taking "medium" as Taking "high" as Is [9, 5, 1].

[0156] 3) Radial velocity u 2,1 All associated evaluation indicators include: "slow", "medium", and "fast", then Radial velocity u 2,1 The corresponding evaluation indicator set Includes: Taking "slow" as Taking "medium" as Taking "fast" as Is [1, 5, 9].

[0157] 4) Maneuvering speed u 2,2 All associated evaluation indicators include: "slow", "medium", and "fast", then Radial velocity u 2,2 The corresponding evaluation indicator set Includes: Taking "slow" as Taking "medium" as Taking "fast" as is [1,5,9].

[0158] 5) Heading u 2,3 All associated evaluation indicators include: "approaching our direction", "tangent direction" and "away from our direction", then Heading u 2,3 Corresponding evaluation index set include: "Close to my direction" Set Tangent Direction as "Away from our direction" is [9,5,1].

[0159] 6) Target trajectory direction u 3,1 All associated evaluation indicators include: "approaching in trajectory direction", "tangent direction" and "moving away from trajectory direction", then Target trajectory direction u 3,1 Corresponding evaluation index set include: Set "Trajectory direction approaching" as Set Tangent Direction as Set Track Direction Away as is [9,5,1].

[0160] 7) Target type u 3,2 All associated evaluation indicators include: "no kill target", "low kill target" and "high kill target", then Target Type 3,2 Corresponding evaluation index set include: The “no-kill target” As a "low-kill target" As a "high lethality target" is [1,5,9].

[0161] 8) Target load u 3,3 All the associated evaluation indicators include: "load is not dangerous", "load is not dangerous and small" and "load is not dangerous and large", then Target load u 3,3 Corresponding evaluation index set include: "Load is not dangerous" as Take "load is safe and small" as Take "load without risk" as Is [1, 5, 9].

[0162] 9) Degree of proximity u 4,1 All associated evaluation indicators include: "low", "medium", and "high", then Degree of proximity u 4,1 The corresponding set of evaluation indicators Includes: Take "low" as Take "medium" as Take "high" as Is [1, 5, 9].

[0163] 10) Friendly and enemy situation u 4,2 All associated evaluation indicators include: "non-hostile", "unknown", and "hostile", then Friendly and enemy situation u 4,2 The corresponding set of evaluation indicators Includes: Take "non-hostile" as Take "unknown" as Take "hostile" as Is [1, 5, 9].

[0164] Among them, the course is the angle between the direction of the spacecraft's velocity and the direction of the line connecting the spacecraft and the protected object; the target trajectory direction is the angle between the tangent direction of the target trajectory and the direction of the line connecting the spacecraft and the protected object.

[0165] S25. Determine the membership function corresponding to each factor associated with the preset spacecraft mission to be scheduled, specifically as follows:

[0166] Membership is a way to describe the relationship between an element and a set. It changes the relationship between the element and the set from "absolutely belonging or not" to "relatively belonging", and the membership function (also known as the membership function) uses the form of a function to describe the degree to which an element belongs to a set. The commonly used membership functions mainly include the following several types:

[0167] 1) Triangular membership function:

[0168]

[0169] 2) Trapezoidal membership function:

[0170]

[0171] 3) Gaussian membership function:

[0172]

[0173] 4) Bell-shaped membership function:

[0174]

[0175] Construct a factor layer function based on each factor in the factor set, specifically:

[0176] A membership function is constructed for each evaluation index of each factor in the factor set. Therefore, the factor layer function corresponding to any factor is: a membership function determined from the combination of the membership functions corresponding to each evaluation index of the factor according to the input amount of the factor. In Example 2, a triangular membership function or a trapezoidal membership function is selected to construct the factor u i,j The parameter of each membership function is set according to the actual scope of action, as shown in Table 9.

[0177] Table 9:

[0178]

[0179]

[0180] S26. Construct a task attribute vector X as input, and form a task attribute probability factor vector based on the membership function. Specifically:

[0181] The configuration of the task attribute vector X is in, Represents: The i-th criterion u i The input amount, for in, Represents: The i-th criterion u i The input amount of the jth factor.

[0182] For each element in the task attribute vector X (i.e. ) are transformed into probability factor vectors through corresponding membership functions. The probability factor vector obtained by the corresponding factor layer function conversion is: [f 1 (x),f 2 (x),…,f o (x)].

[0183] In Example 2, let the task attribute vector X be [700, 500, 3, 0.4, 180, 90, 0.1, 0.5, 0.9, 0.8], and the probability factor obtained by conversion by the corresponding factor layer function is:

[0184] F JL (700) = [0, 0.5, 0.33], F GD (500) = [0, 1, 0], FJX (3) = [0.33, 0.5, 0], F JD (0.4)

[0185] =[0,0.75,0], F HX (135) = [0, 0.17, 0.17], F GJ (90) = [0, 1, 0], F LX (0.1) = [1, 0, 0], F ZH (0.5) = [0, 1, 0], F JJ (0.9) = [0,0,1], F DW (0.8) = [0, 0.25, 0.67].

[0186] This constitutes the task attribute probability factor vector: [f 1 (x),f 2 (x),…,f o (x)], where f 1 (x) = F JL (700), f 2 (x) = F GD (500), f 3 (x) = F JX (3), f 4 (x) = F JD (0.4), f 5 (x) = F HX (135), f 6 (x) = F GJ (90), f 7 (x) = F LX (0.1), f 8 (x) = F ZH (0.5), f 9 (x) = F JJ (0.9), f 10 (x) = F DW (0.8).

[0187] S27, normalize the task attribute probability factor vector to obtain the task attribute probability factor matrix, specifically:

[0188] The task attribute probability factor vector is standardized using the following formula:

[0189]

[0190] In Example 2, f p ′(x) is the value of f p (x) The value obtained after normalization, f p (xp ) means: the pth input x in the task attribute vector p The pth membership function in the input factor layer function, o represents the total number of all factors in the task attribute vector X, which is equal to the total number of all input quantities in the task attribute vector X and the total number of factor layer functions.

[0191] [f 1 (x),f 2 (x),…,f o (x)] is normalized to obtain [f 1 ′(x),f 2 ′(x),…,f o ′(x)], specifically:

[0192] f 1 ′(x)=[0,0.6,0.4],f 2 ′(x)=[0,1,0],f 3 ′(x)=[0.4,0.6,0],f 4 ′(x)=[0,1,0],f′ 5 (x) = [0, 0.5, 0.5], f′ 6 (x) = [0, 1, 0], f′ 7 (x) = [1, 0, 0], f′ 8 (x) = [0, 1, 0], f′ 9 (x) = [0, 0, 1], f′ 10 (x) = [0, 0.27, 0.73].

[0193] Press [f 1 ′(x),f 2 ′(x),…,f o ′(x)] are stacked to form the task attribute probability factor matrix J(X), which is:

[0194] [f 1 (x),f 2 (x),f 3 (x),f 4 (x),f 5 (x),f 6 (x),f 7 (x),f 8 (x),f 9 (x),f 10 (x)]

[0195] Get the priority score corresponding to each element, stack all the priority scores by row, and get the evaluation index priority matrix S. The evaluation index priority matrix S is: Specifically: [[9,5,1],[9,5,1],[1,5,9],[1,5,9],[9,5,1],[9,5,1],[1,5,9],[1,5,9],[1,5,9],[1,5,9]].

[0196] Then the evaluation index score vector H(X) is calculated. Specifically: 1 ′(x)=[0,0.6,0.4]、f 2 ′(x)=[0,1,0]、f 3 ′(x)=[0.4,0.6,0]、f 4 ′(x)=[0,1,0],f 5 ′(x)=[0,0.5,0.5]、f 6 ′(x)=[0,1,0],f 7 ′(x)=[1,0,0]、f 8 ′(x)=[0,1,0]、f 9 ′(x)=[0,0,1]、f 1 ' 0 Substitute (x) = [0, 0.27, 0.73] and [[9, 5, 1], [9, 5, 1], [1, 5, 9], [1, 5, 9], [9, 5, 1], [9, 5, 1], [1, 5, 9], [1, 5, 9], [1, 5, 9]] into the formula: H(X) = J(X) × S and calculate the evaluation index score vector H(X). The evaluation index score vector H(X) is: [3.4, 5, 3.4, 5, 3, 5, 1, 5, 9, 7.92].

[0197] The evaluation index score vector H(X) is reorganized (reorganized according to the criteria) to obtain H′(X), which is [[3.4,5],[3.4,5,3],[5,1,5],[9,7.92]], H u For [H u,1 ,H u,2 ,H u,3 ,H u,4 ], specifically: [[0.75, 0.25], [0.27, 0.67, 0.06], [0.11, 0.58, 0.31], [0.25, 0.75]], substitute into the formula: V(X) = H u ×H′(X), we get the factor layer score vector V(X), V(X) is [3.8, 4.448, 2.68, 8.19].

[0198] S28. In Example 2, V(X) is [3.8, 4.448, 2.68, 8.19], V uis [0.47, 0.29, 0.17, 0.07], substitute into the formula z=V u ×V(X), the total score of the preset spacecraft tasks to be scheduled is calculated until the total score of each spacecraft task to be scheduled is obtained. According to the size of the total score, all spacecraft tasks to be scheduled are prioritized, and all spacecraft tasks to be scheduled are scheduled and executed according to the priority sorting sequence. Among them, the higher the total score, the higher the priority, and the priority is scheduled and executed.

[0199] The beneficial effects of the present invention are as follows: the evaluation of spacecraft mission priority is realized based on fuzzy hierarchical comprehensive analysis. The fuzzy hierarchical comprehensive analysis method transforms the evaluation object from a mission attribute vector into a more information-rich mission attribute probability factor matrix through fuzzification, which can more accurately characterize the evaluated object, further process the fuzzy evaluation object through precise digital means, and mine the hidden information to present a scientific, reasonable, and practical quantitative evaluation, which can improve the accuracy and interpretability of spacecraft mission priority evaluation and realize the precise scheduling and execution of spacecraft missions.

[0200] In the above embodiments, although the steps are numbered S1, S2, etc., these are only specific embodiments given by the present invention. Those skilled in the art may adjust the execution order of S1, S2, etc. according to actual conditions, which is also within the protection scope of the present invention. It can be understood that in some embodiments, some or all of the above embodiments may be included.

[0201] like Figure 2 As shown, a scheduling system 200 for a spacecraft mission according to an embodiment of the present invention includes a total score calculation module 201 and a scheduling execution module 202;

[0202] The total score calculation module 201 is used to: calculate and obtain the total score of the preset spacecraft task to be scheduled according to the criterion layer weight vector and the factor layer score vector corresponding to the preset spacecraft task to be scheduled, until the total score of each spacecraft task to be scheduled is obtained, wherein the preset spacecraft task to be scheduled is associated with at least one criterion, each criterion is associated with at least one factor, and the criterion layer weight vector corresponding to the preset spacecraft task to be scheduled includes: the weight corresponding to each criterion associated with the preset spacecraft task to be scheduled, and the preset spacecraft task to be scheduled is any spacecraft task to be scheduled;

[0203] The scheduling execution module 202 is used to prioritize all the spacecraft tasks to be scheduled according to the total score of each spacecraft task to be scheduled, and schedule and execute all the spacecraft tasks to be scheduled according to the priority ranking sequence.

[0204] Optionally, in the above technical solution, a factor layer score vector calculation module is further included, and the factor layer score vector calculation module is used to:

[0205] According to the evaluation index score vector corresponding to the preset spacecraft mission to be scheduled, and in combination with the factor layer weight vector group corresponding to the preset spacecraft mission to be scheduled, the factor layer score vector corresponding to the preset spacecraft mission to be scheduled is calculated, wherein each factor associated with the preset spacecraft mission to be scheduled includes at least one evaluation index, and the factor layer weight vector group corresponding to the preset spacecraft mission to be scheduled includes: the factor layer weight vector of each criterion associated with the preset spacecraft mission to be scheduled, and the factor layer weight vector of any criterion includes: the weight of each factor associated with the criterion.

[0206] Optionally, in the above technical solution, a weight vector calculation module is further included, and the weight vector calculation module is used to:

[0207] The analytic hierarchy process is used to calculate the criterion layer weight vector and factor layer weight vector corresponding to the preset spacecraft mission to be scheduled.

[0208] Optionally, in the above technical solution, an evaluation index score vector calculation module is further included, and the evaluation index score vector calculation module is used to:

[0209] Determine the factor layer function corresponding to each factor associated with the preset spacecraft mission to be scheduled, and construct a task attribute vector as the input of the corresponding factor layer function, and calculate the task attribute probability factor vector, the task attribute vector includes the input amount of each criterion associated with the preset spacecraft mission to be scheduled, the input amount of any criterion includes: the input amount of each factor associated with the criterion, and the factor layer function corresponding to any factor is: the membership function determined from the combination of the membership functions corresponding to each evaluation index of the factor according to the input amount of the factor;

[0210] Normalize the task attribute probability factor vector to obtain the task attribute probability factor matrix;

[0211] According to the task attribute probability factor matrix and the priority score corresponding to each evaluation indicator associated with each factor, the evaluation indicator score vector is calculated.

[0212] It should be noted that the beneficial effects of the scheduling system 200 for a spacecraft mission provided in the above embodiment are the same as the beneficial effects of the scheduling method for a spacecraft mission provided in the above embodiment, which will not be described in detail here. In addition, when the system provided in the above embodiment realizes its functions, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the system can be divided into different functional modules according to actual conditions to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be described in detail here.

[0213] Among them, the scheduling system of the spacecraft mission of the present invention can be a computer program (including program code) running in a computer device. For example, the scheduling system of the spacecraft mission of the present invention is an application software that can be used to execute the corresponding steps in the scheduling method of the spacecraft mission of the present invention.

[0214] In some embodiments, the scheduling system of the spacecraft mission of the present invention can be implemented by a combination of software and hardware. As an example, the scheduling system of the spacecraft mission of the present invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the scheduling method of the spacecraft mission of the present invention. For example, the processor in the form of a hardware decoding processor can adopt one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs) or other electronic components.

[0215] The modules involved in the embodiments of the present invention may be implemented in software or hardware. The name of a module does not limit the module itself in some cases.

[0216] An electronic device according to an embodiment of the present invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, any one of the above-mentioned methods for scheduling spacecraft missions is implemented. That is to say, an electronic device according to an embodiment of the present invention may include but is not limited to: a processor and a memory; a memory for storing a computer program; a processor for executing any one of the methods for scheduling spacecraft missions shown in any one of the embodiments of the present invention by calling a computer program.

[0217] In an alternative embodiment, an electronic device is provided, such as Figure 3 As shown, Figure 3The electronic device 4000 shown includes: a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, such as through a bus 4002. Optionally, the electronic device 4000 may also include a transceiver 4004, which may be used for data interaction between the electronic device and other electronic devices, such as data transmission and / or data reception. It should be noted that in actual applications, the transceiver 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0218] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of the present invention. Processor 4001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0219] The bus 4002 may include a path to transmit information between the above components. The bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 4002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 In the figure, only one thick line is used to represent the bus 4002, but this does not mean that there is only one bus or one type of bus.

[0220] The memory 4003 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to this.

[0221] The memory 4003 is used to store the application code (computer program) for executing the solution of the present invention, and the execution is controlled by the processor 4001. The processor 4001 is used to execute the application code stored in the memory 4003 to implement the content shown in the above method embodiment.

[0222] Among them, the electronic device can also be a terminal device, and the terminal device can be any terminal device that can install applications and access web pages through applications, including at least one of a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, a smart TV, and a smart car device.

[0223] It should be noted that Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0224] A computer-readable storage medium according to an embodiment of the present invention stores a computer program, which, when executed by a processor, implements any of the above-mentioned methods for scheduling spacecraft missions.

[0225] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0226] In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device performs any of the above-mentioned methods for scheduling spacecraft missions.

[0227] Computer program code for performing the operations of the present invention may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0228] It should be understood that the flow charts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the module, the program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0229] The computer-readable storage medium provided by the embodiment of the present invention may be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or component.

[0230] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device executes the method shown in the above embodiment.

[0231] The above description is only a preferred embodiment of the present invention and an explanation of the technical principles used. Those skilled in the art should understand that the disclosure scope involved in the present invention is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present invention (but not limited to) by each other.

[0232] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present invention can be specifically implemented in the following forms, namely: it can be complete hardware, it can be complete software (including firmware, resident software, microcode, etc.), or it can be a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" herein. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.

[0233] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for scheduling a spacecraft mission, characterized in that: include: Calculate and obtain the total score of the preset spacecraft task to be scheduled according to the criterion layer weight vector and the factor layer score vector corresponding to the preset spacecraft task to be scheduled, until the total score of each spacecraft task to be scheduled is obtained, wherein the preset spacecraft task to be scheduled is associated with at least one criterion, each criterion is associated with at least one factor, and the criterion layer weight vector corresponding to the preset spacecraft task to be scheduled includes: the weight corresponding to each criterion associated with the preset spacecraft task to be scheduled, and the preset spacecraft task to be scheduled is any spacecraft task to be scheduled; According to the total score of each spacecraft mission to be scheduled, all spacecraft missions to be scheduled are prioritized, and all spacecraft missions to be scheduled are scheduled and executed according to the priority sequence.

2. A method for scheduling spacecraft missions according to claim 1, characterized in that: Also includes: According to the evaluation index score vector corresponding to the preset spacecraft mission to be scheduled, and in combination with the factor layer weight vector group corresponding to the preset spacecraft mission to be scheduled, the factor layer score vector corresponding to the preset spacecraft mission to be scheduled is calculated, wherein each factor associated with the preset spacecraft mission to be scheduled includes at least one evaluation index, and the factor layer weight vector group corresponding to the preset spacecraft mission to be scheduled includes: the factor layer weight vector of each criterion associated with the preset spacecraft mission to be scheduled, and the factor layer weight vector of any criterion includes: the weight of each factor associated with the criterion.

3. A method for scheduling spacecraft missions according to claim 2, characterized in that: Also includes: The criterion layer weight vector and the factor layer weight vector corresponding to the preset spacecraft mission to be scheduled are calculated by using the hierarchical analysis method.

4. A method for scheduling spacecraft missions according to claim 3, characterized in that: The process of calculating the evaluation index score vector corresponding to the preset spacecraft mission to be scheduled includes: Determine the factor layer function corresponding to each factor associated with the preset spacecraft mission to be scheduled, and construct a task attribute vector as the input of the corresponding factor layer function, and calculate the task attribute probability factor vector, wherein the task attribute vector includes the input amount of each criterion associated with the preset spacecraft mission to be scheduled, and the input amount of any criterion includes: the input amount of each factor associated with the criterion, and the factor layer function corresponding to any factor is: the membership function determined from the combination of the membership functions corresponding to each evaluation index of the factor according to the input amount of the factor; Normalizing the task attribute probability factor vector to obtain a task attribute probability factor matrix; The evaluation indicator score vector is calculated based on the task attribute probability factor matrix and the priority score corresponding to each evaluation indicator associated with each factor.

5. A spacecraft mission scheduling system, characterized in that: It includes a total score calculation module and a scheduling execution module; The total score calculation module is used to: calculate and obtain the total score of the preset spacecraft task to be scheduled according to the criterion layer weight vector and factor layer score vector corresponding to the preset spacecraft task to be scheduled, until the total score of each spacecraft task to be scheduled is obtained, wherein the preset spacecraft task to be scheduled is associated with at least one criterion, each criterion is associated with at least one factor, and the criterion layer weight vector corresponding to the preset spacecraft task to be scheduled includes: the weight corresponding to each criterion associated with the preset spacecraft task to be scheduled, and the preset spacecraft task to be scheduled is any spacecraft task to be scheduled; The scheduling execution module is used to: prioritize all the spacecraft tasks to be scheduled according to the total score of each spacecraft task to be scheduled, and schedule and execute all the spacecraft tasks to be scheduled according to the priority ranking sequence.

6. A spacecraft mission scheduling system according to claim 5, characterized in that: It also includes a factor layer score vector calculation module, which is used to: According to the evaluation index score vector corresponding to the preset spacecraft mission to be scheduled, and in combination with the factor layer weight vector group corresponding to the preset spacecraft mission to be scheduled, the factor layer score vector corresponding to the preset spacecraft mission to be scheduled is calculated, wherein each factor associated with the preset spacecraft mission to be scheduled includes at least one evaluation index, and the factor layer weight vector group corresponding to the preset spacecraft mission to be scheduled includes: the factor layer weight vector of each criterion associated with the preset spacecraft mission to be scheduled, and the factor layer weight vector of any criterion includes: the weight of each factor associated with the criterion.

7. A spacecraft mission scheduling system according to claim 6, characterized in that: It also includes a weight vector calculation module, which is used to: The criterion layer weight vector and the factor layer weight vector corresponding to the preset spacecraft mission to be scheduled are calculated by using the hierarchical analysis method.

8. A spacecraft mission scheduling system according to claim 7, characterized in that: It also includes an evaluation index score vector calculation module, which is used to: Determine the factor layer function corresponding to each factor associated with the preset spacecraft mission to be scheduled, and construct a task attribute vector as the input of the corresponding factor layer function, and calculate the task attribute probability factor vector, wherein the task attribute vector includes the input amount of each criterion associated with the preset spacecraft mission to be scheduled, and the input amount of any criterion includes: the input amount of each factor associated with the criterion, and the factor layer function corresponding to any factor is: the membership function determined from the combination of the membership functions corresponding to each evaluation index of the factor according to the input amount of the factor; Normalizing the task attribute probability factor vector to obtain a task attribute probability factor matrix; The evaluation indicator score vector is calculated based on the task attribute probability factor matrix and the priority score corresponding to each evaluation indicator associated with each factor.

9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements a method for scheduling a spacecraft mission as described in any one of claims 1 to 4 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for scheduling a spacecraft mission as described in any one of claims 1 to 4 is implemented.

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