CN112330219A - Method for selecting space on-orbit service target - Google Patents
Method for selecting space on-orbit service target Download PDFInfo
- Publication number
- CN112330219A CN112330219A CN202011363182.0A CN202011363182A CN112330219A CN 112330219 A CN112330219 A CN 112330219A CN 202011363182 A CN202011363182 A CN 202011363182A CN 112330219 A CN112330219 A CN 112330219A
- Authority
- CN
- China
- Prior art keywords
- index
- evaluation
- space
- indexes
- orbit service
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 56
- 238000011156 evaluation Methods 0.000 claims abstract description 63
- 238000012545 processing Methods 0.000 claims abstract description 19
- 238000012163 sequencing technique Methods 0.000 claims abstract description 10
- 238000006116 polymerization reaction Methods 0.000 claims abstract description 6
- 239000011159 matrix material Substances 0.000 claims description 54
- 238000010606 normalization Methods 0.000 claims description 21
- 230000000295 complement effect Effects 0.000 claims description 19
- 238000013210 evaluation model Methods 0.000 claims description 13
- 238000011158 quantitative evaluation Methods 0.000 claims description 10
- 239000000654 additive Substances 0.000 claims description 9
- 230000000996 additive effect Effects 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 9
- 238000013507 mapping Methods 0.000 claims description 4
- 230000002776 aggregation Effects 0.000 claims description 3
- 238000004220 aggregation Methods 0.000 claims description 3
- 238000004891 communication Methods 0.000 description 20
- 238000003384 imaging method Methods 0.000 description 9
- 230000009471 action Effects 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 230000006872 improvement Effects 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 150000001875 compounds Chemical class 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000012634 optical imaging Methods 0.000 description 2
- 238000010187 selection method Methods 0.000 description 2
- 241000282412 Homo Species 0.000 description 1
- 241000282414 Homo sapiens Species 0.000 description 1
- 230000003679 aging effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 238000009407 construction method and process Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 239000010763 heavy fuel oil Substances 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003032 molecular docking Methods 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 238000007670 refining Methods 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000013077 scoring method Methods 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/40—Business processes related to the transportation industry
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Theoretical Computer Science (AREA)
- Educational Administration (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method for selecting a space on-orbit service target, and relates to the technical field of space on-orbit services. Firstly, constructing a priority index system of a space on-orbit service target, wherein the priority index system comprises evaluation indexes such as value degree, easy operation degree, service mode suitability degree, decision maker preference and the like; then endowing different weight coefficients to each evaluation index, simultaneously carrying out standardization processing on different levels of indexes, determining a polymerization method among different levels of indexes, and calculating to obtain the value of each evaluation index; and finally, calculating to obtain the comprehensive priority of the space on-orbit service targets, sequencing the targets according to the sequence from high to low, and selecting the target with the highest priority as the optimal target. The method constructs a spatial on-orbit service target priority index system, has wide evaluation comprehensive factor range and high reliability of index weight coefficients, quantitatively evaluates the priority of implementing on-orbit service on different targets, and has strong operability by combining subjective and objective functions.
Description
Technical Field
The invention belongs to the technical field of space on-orbit service, and particularly relates to a method for selecting a space on-orbit service target.
Background
The increasingly frequent and complex space exploration activities of human beings make the in-orbit service technology of the spacecraft a research hotspot in recent years. Space on-orbit service refers to the completion of space assembly, maintenance and service tasks involving the extension of the lives and capabilities of various types of satellites, spacecraft platforms, space station satellite pods and space vehicles in space by humans, robots (or robotic satellites) or both, including repair and replacement of spacecraft components, removal or liquid transfer of spacecraft, replenishment of consumables and consumables (e.g., on-orbit refueling), space on-orbit assembly, and the like. The significance and value of on-orbit services have attracted increasing attention and are becoming one of the major trends in the development of spacecraft technology.
However, space-on-orbit service is space manned or unmanned activity conducted in a space environment far from the earth, in a high vacuum and without gravity, and is very costly and costly. Therefore, in the specific implementation process of the space on-orbit service task, how to scientifically select a reasonable, effective and high-value service target (i.e., a service object) is very important, and therefore, an evaluation and selection method of the space on-orbit service target is urgently needed to be developed. So far, there are few related introductions and reports in the prior art.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a method for selecting a space on-orbit service target, aiming at providing a reference basis and method support for selecting the space on-orbit service target.
In order to achieve the above object, the present invention provides a method for selecting a space on-orbit service target, comprising the following steps:
step one, constructing a priority index system of a space on-orbit service target;
the priority index system comprises evaluation indexes of value degree, easy operation degree, service mode suitability degree and preference of a decision maker; aiming at a specific space on-orbit service target, forming a corresponding evaluation model with a plurality of hierarchical structures for each evaluation index, wherein each evaluation model of the evaluation index comprises a plurality of indexes distributed at different levels;
step two, aiming at the evaluation model of each evaluation index, different weight coefficients are given to each index of different levels;
thirdly, normalizing the values of the indexes of different levels aiming at the evaluation model of each evaluation index;
determining a polymerization method among indexes of different levels to polymerize a lower-layer index to an upper-layer index layer by layer, and finally obtaining quantitative evaluation results of each evaluation index of the space on-orbit service target;
and step five, calculating the comprehensive priority of the space on-orbit service targets according to the quantitative evaluation result and the weight coefficient of each evaluation index, and sequencing the targets from high to low, thereby determining the selection of the space on-orbit service targets.
Further, in the evaluation indexes of the first step, the value degree is an index for evaluating the value of the space on-orbit service target, the ease of operation degree is an index for evaluating the difficulty of operating the service by the spacecraft providing the on-orbit service, the preference of the decision maker is an index for evaluating the subjective selection characteristic of the decision maker on the space on-orbit service target, and the service mode suitability is an index for measuring the suitability for operating the on-orbit service target; wherein, the value degree and the easy operation degree are quantitative indexes, and the preference of the decision maker and the suitability degree of the service mode are qualitative indexes.
Preferably, the second step includes: on the basis of an analytic hierarchy process, an interval addition type complementation judgment matrix is constructed, the addition type complementation judgment matrix is adjusted according to a satisfactory consistency threshold value, and the addition type complementation judgment matrix is used for endowing each evaluation index with a weight coefficient of each level index.
Further, the consistency of the additive complementary judgment matrix and the corresponding weight coefficient thereof are calculated by a linear programming method.
Further, the linear programming method comprises the following specific calculation steps: after an interval addition type complementary judgment matrix is established, a consistency coefficient and a corresponding weight coefficient of the addition type complementary judgment matrix are obtained through linear programming; if the consistency coefficient meets the set consistency threshold, directly taking the weight coefficient as the weight coefficient of each level index contained in the evaluation index; if the consistency threshold value is not met, the additive complementary judgment matrix is adjusted, and then a linear programming method is reused to calculate new consistency coefficients and new weight coefficients.
Preferably, the normalization in the third step includes normalization of qualitative indicators and normalization of quantitative indicators; the normalization processing of the qualitative indexes comprises the following steps: dividing a plurality of levels to describe the capability of the qualitative index, and giving a value corresponding to the qualitative index according to a standardized mapping relation; the normalization processing of the quantitative index comprises the following steps: and (4) discriminating the type of the quantitative index according to the relation between the index value and the value degree, and further selecting a corresponding index normalization function to process the quantitative index.
Preferably, the aggregation method between indexes at different levels in the fourth step adopts a weighted sum method; the weighting sum method is that each lower layer index after normalization processing is multiplied by a corresponding weight coefficient respectively, and then the value of the upper layer index is obtained through summation, and the function expression is as follows:
ek＝ω1e1+ω2e2+…+ωnen，
in the formula, ei(i-1, 2, …, n) is the lower index uiNormalized value of (a), omegai(i-1, 2, …, n) is the lower index uiCorresponding weight coefficient of ekIs an index C of the previous layerkN represents the index C of the previous layerkThe number of lower layer indicators included.
Preferably, the specific calculation method of the comprehensive priority of the space on-orbit service target is as follows: and multiplying the quantitative evaluation result of each evaluation index by the weight coefficient of each evaluation index respectively, and calculating by a summing mode to obtain the comprehensive priority.
Compared with the prior art, the technical scheme of the invention has the following beneficial effects:
1) the concept of comprehensive priority of space on-orbit service targets is introduced, the priority of implementing on-orbit service on different targets is quantitatively evaluated, and a quantitative sorting basis for selecting on-orbit service targets is provided;
2) a spatial on-orbit service target priority index system is constructed, the value degree and the operability of a target, the suitability degree of a service mode and the preference of a decision maker are covered, and the comprehensive evaluation factor range is wide;
3) the preference of a decision maker for selecting the space on-orbit service target is brought into a priority evaluation index system, subjective recognition and objective analysis are combined, and the operability of the space on-orbit service target selection method is improved;
4) and considering the ambiguity existing when the decision-making personnel compares the importance of the indexes pairwise, constructing an interval addition type complementary judgment matrix, and adjusting the interval addition type complementary judgment matrix according to a satisfactory consistency threshold value, thereby improving the reliability of the index weight coefficient determination.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a flow chart of a method for selecting a spatial on-orbit service target according to the present invention;
FIG. 2 is a spatial on-orbit service target priority index system;
FIG. 3 is a remote sensing satellite value index system;
FIG. 4 is a communication satellite value system indicator;
FIG. 5 is a navigation satellite value index system;
FIG. 6 is a spatial on-orbit service target ease of operation index system.
Detailed Description
The general idea of the invention is as follows:
firstly, integrating factors such as the value degree, the easy operation degree, the service mode suitability degree and the preference of a decision maker of a space on-orbit service target, providing a priority index for target sequencing, and refining and constructing a priority index system of targets including evaluation indexes such as the value degree, the easy operation degree, the service mode suitability degree and the preference of the decision maker by combining the characteristics of various application satellites such as remote sensing, communication, navigation and the like;
then, after a priority index system of a space on-orbit service target is established, different weight coefficients are given to each evaluation index, meanwhile, values of the indexes are obtained by comprehensively using methods such as theoretical analysis, simulation experiments, expert study and the like and are subjected to standardization processing, a polymerization method among indexes of different levels is determined, and values of the indexes such as value degree, easiness in operation degree and the like are obtained through calculation;
and finally, on the basis of determining specific assignments of evaluation indexes such as the value degree, the easy operation degree, the service mode suitability degree, the preference of a decision maker and the like of the space on-orbit service target, calculating and obtaining the comprehensive priority of the space on-orbit service target by combining the index weight coefficient, sequencing the targets according to the sequence from high to low, and selecting the target with the highest priority as the optimal target.
According to the above thought, the method for selecting the spatial on-orbit service target of the present invention includes several steps as shown in fig. 1, which are specifically as follows:
step one, constructing a priority index system of a space on-orbit service target;
the space on-orbit service target object in the embodiment of the invention comprises various satellite targets such as a remote sensing satellite, a communication satellite, a navigation satellite and the like. And then, combining the characteristics of various satellite targets such as remote sensing, communication, navigation and the like to construct a priority index system of the space on-orbit service target.
The priority index system of the spatial on-orbit service target constructed in the embodiment is shown in fig. 1. The priority index system comprises evaluation indexes of value degree, easy operation degree, service mode suitability degree and preference of a decision maker; and forming a corresponding evaluation model with a plurality of hierarchical structures for each evaluation index aiming at a specific space on-orbit service target, wherein each evaluation model of the evaluation index comprises a plurality of indexes distributed at different levels.
Referring to fig. 1, the comprehensive priority of the on-orbit service target is denoted as Y, and in the present embodiment, when considering the priority index system, the consideration factors in the system range, that is, the specific evaluation indexes, are introduced, including the value V, the ease of operation H, the preference P of the decision maker, and the suitability S of the service mode. The value degree V is an index used for evaluating the value of a space on-orbit service target, the easy operation degree H is an index used for evaluating the difficulty degree of operation service of a spacecraft providing on-orbit service, the preference P of a decision maker is an index used for evaluating and commanding the subjective selection characteristic of the decision maker on the space on-orbit service target, and the service mode suitability S is an index used for measuring the suitability degree of operation on the on-orbit service target; the value degree V and the easy operation degree H are quantitative indexes, and the decision maker preference P and the service mode suitability degree S are qualitative indexes. Specific construction methods and processes of these evaluation indexes are described below.
1. Target value degree index of space on-orbit service
The 'value degree' comprehensively reflects the efficiency of the on-orbit service target for providing the application service under the normal condition. And respectively constructing value degree evaluation index systems of various satellites by considering the characteristics and the functions of the applied satellites such as remote sensing, communication, navigation and the like and combining the basic flow of space-based information application.
1) Remote sensing satellite
According to the basic principle of imaging implemented by a remote sensing satellite, the value of the method is mainly embodied in three aspects of timeliness of remote sensing observation, information acquisition level, orbital mobility and the like, as shown in fig. 3.
Aging property VA1The method comprises the following two aspects: the time of imaging the ground by the satellite each time and the time interval between two adjacent imaging times are short. According to the basic principle of orbital mechanics, the timeliness of remote sensing observation mainly depends on the orbit of satellite operation, and the two factors are mainly represented by the transit time length and transit interval of the satellite, so that the timeliness can be decomposed into the average transit time length VA11Minimum transit time VA12Average transit interval VA13And a minimum transit interval VA14And four-term three-level indexes, wherein the longer the average and minimum transit time is, the shorter the average and minimum transit interval is, and the higher the value degree of the remote sensing satellite is.
Information acquisition level VA2The method is used for describing the imaging quality of the remote sensing satellite. Since the load of the remote sensing satellite comprises two types of optical imaging equipment and radar imaging equipment, corresponding three-level indexes are respectively given. For optical imaging loads, the information acquisition level can be the resolution V of the optical imageA21Width V observed to the groundA22And yaw imaging capability VA23The description is that: the higher the resolution, the wider the breadth and the larger the maximum yaw angle, the higher the satellite information acquisition level. For radar imaging load, a detection frequency range V is adoptedA24Signal type VA25Range of action/distance VA26The three-level indexes represent the information acquisition level, the wider the frequency range, the more the signal types, the larger the action distance/range, the higher the radar imaging information acquisition level, and the higher the value degree of the remote sensing satellite.
Maneuverability of track VA3For describing the value of remote sensing satellite with space maneuvering ability, the thrust V is adoptedA31On-orbit working life VA32And performing equal three-level index characterization. The thrust magnitude refers to the action capacity of the satellite orbit control engine, and the larger the thrust is, the larger the orbit maneuverability of the target is; the on-orbit working life reflects the residual fuel and the rail mobility to a certain extent.
As can be seen from FIG. 3, the structural model of the evaluation index of the remote sensing satellite value degreeType, which comprises three levels: the first level index is the value V of the remote sensing satelliteAIs a top level indicator; the second level index is timeliness VA1Information acquisition level VA2And track mobility VA3(ii) a The third-level index is a detailed index belonging to each index of the second level, for example, belonging to the timeliness VA1Average transit time V ofA11Minimum transit time VA12Average transit interval VA13And a minimum transit interval VA14Motor of track VA3Magnitude of thrust VA31And on-orbit operational life VA32And the like.
2) Communication satellite
The communication satellite can support users to obtain reliable and effective communication at a specific time and a specific place. The higher the support degree of the communication satellite on the ground communication activities, the higher the value degree of the communication satellite for carrying out on-orbit service, therefore, the value degree can be decomposed into a communication range VB1Signal transmission and processing capacity VB2And adjustability VB3Three secondary indexes are shown in figure 4.
Communication range VB1Indicating how large spatial and frequency ranges a communication satellite can provide communication services to users, respectively with a spatial coverage VB11And an operating frequency band range VB12And (4) showing. Spatial coverage refers to the area covered by the satellite beams on the earth's surface.
Signal transmission and processing capability VB2Embodies the capability of the communication satellite to support the user requirement and is divided into system capacity VB21Single link rate VB22And data processing capability VB23Three indexes. The system capacity is expressed in terms of the sum of the transmission rates that can be achieved within a given bandwidth, an index that is closely related to the number of users that can be accessed. Single link rate refers to the highest rate at which a satellite provides communication services to a single user; the data processing capability is used for evaluating the capability of processing and exchanging the uplink and downlink signals and is a qualitative index.
Adjustability VB3Means that the satellite can provide communication service for users through orbital maneuver, beam adjustment and other meansForce, divided into orbital maneuvering capability VB31Beam tunability VB32Resource scheduling capability VB33Three-level indexes. The capability of the orbit mobility is similar to that of a remote sensing satellite and is a qualitative index; the beam adjustability is a qualitative index indicating whether the satellite beam can adjust the pointing direction and the coverage range in orbit; the resource scheduling capability indicates whether the satellite can emergently allocate communication resources according to the demand, and is also a qualitative index.
3) Navigation satellite
The navigation satellite provides a uniform space-time reference for users in a constellation networking mode. Similar to communication satellites, navigation satellites mainly provide space-time reference services, and the value degree of the space-time reference services can adopt a coverage range VC1Positioning accuracy VC2Speed measurement precision VC3Time service precision VC4And the like, as shown in fig. 5. Coverage refers to providing space-time reference services globally or locally, all-time, or part-time; the positioning/speed measurement precision refers to the difference between the user position and speed measured by the navigation satellite and an actual value; the time service precision is the precision level of the navigation satellite system for carrying out unified time service.
2. Target easy operation degree index of space on-orbit service
The easy operation degree H refers to the difficulty degree of the spacecraft providing the on-orbit service to operate and service the space on-orbit service target, and the capability H can be obtained through attitude and orbit information1Space rendezvous and docking capability H2Target Capture Capacity H3And ease of operation H4Four secondary metrics, as shown in fig. 6. The higher the value of these capabilities, the easier the object is to handle, i.e., the greater the value of the ease of handling.
By constructing the structural model of the evaluation index system with respect to different specific satellite targets in detail, such as the degree of merit, the degree of ease of operation, and the like, an index evaluation model having a plurality of hierarchical structures can be obtained for each evaluation index, as shown in fig. 3 to 6.
Step two, aiming at the evaluation model of each evaluation index, different weight coefficients are given to each index of different levels;
spatial on-orbit service targetThe evaluation index system relates to a plurality of indexes distributed at different levels, and each index has different contribution degrees to the top-level indexes such as the upper-level indexes and the value degree, the easy operation degree and the like which belong to the index. The weight coefficient reflects the degree of importance of a plurality of indices governed by the same index to each other. Taking the hierarchical index system as an example, the upper level index is set as CkThe index of the next layer is u1，u2，…，unThen u is1，u2，…，unFor index CkThe relative importance of (b) is the weight. In practice, the weights of these elements can be determined by an analytic hierarchy process, and the basic principle is to compare two by two different indexes of the same level to construct a judgment matrix, analyze and adjust the consistency of the judgment matrix, and calculate and determine the weight coefficients of each criterion according to the result. In this embodiment, on the basis of an analytic hierarchy process, an interval additive complementation determination matrix is constructed in consideration of ambiguity existing when a decision-maker compares two indexes in importance, the additive complementation determination matrix is adjusted according to a satisfactory consistency threshold, and the additive complementation determination matrix is used to assign a weight coefficient of each level index included in each evaluation index.
1. Number of intervals and operation thereof
Definition 1: if real numberaAnd
respectively representing the lower limit and the upper limit of a certain interval, then the product is called
Is a number of intervals; when in use
The number of intervals degenerates to a real number.
Definition 2: if matrix a ═ aij)m×nEach element A ofijIf the numbers are interval numbers, a is called an interval matrix, wherein subscripts m and n are the number of rows and columns of the matrix respectively.
2. Additive complementary judging matrix
Aiming at the above-constructed space on-orbit service target evaluation index system, two indexes u in the same layer are evaluatediAnd ujAnd carrying out scaling treatment on the qualitative judgment conclusion of the decision maker according to the scale shown in the table 1. It is noted that table 1 gives a scale for the determination; the index u may occur in a practical problemiAnd ujIn contrast, where the importance is between two scales (e.g., "apparently unimportant" and "equally important"), the number of intervals is used
To characterize the importance relationship between the two.
TABLE 1 Scale and its meanings (u)iAnd ujPhase comparison)
| Means of | Of extreme importance | Is obviously not important | Of equal importance | Of obvious importance | Of extreme importance |
| Scale | 0.1 | 0.3 | 0.5 | 0.7 | 0.9 |
By the method, the interval addition type complementary judgment matrix can be constructed:
in the formula (I), the compound is shown in the specification,
the preference degree of the index i and the index j is represented, and the upper and lower boundaries of the interval satisfy:
and
to pair
Is true.
3. Consistency and improvements thereof
The spatial on-orbit service target evaluation relates to a plurality of specific indexes, and when a decision maker compares every two of the specific indexes to construct a judgment matrix, the situation that judgment logics are inconsistent easily occurs. For example, three evaluation indexes u1、u2And u3Make two-by-two comparison, the decision maker considers u1Is relatively u2Of extreme importance, u2Is relatively u3Equally important; if in comparison u1And u3When it is u1Is relatively u3And if the judgment is extremely important, the judgment of the decision maker is completely consistent, otherwise, the judgment is inconsistent. In actual operation, obtaining a completely consistent judgment matrix is difficult, and satisfactory consistency can be adopted for processing.
In this embodiment, a linear programming method is used to calculate the consistency of the specified interval-adding complementary judgment matrix and the corresponding weight coefficient thereof, and an adjustment method of the judgment matrix is provided for the case that the consistency is less than the satisfactory consistency. The method has the advantages that the consistency of the interval judgment matrix can be analyzed simultaneously through linear programming, and corresponding index weights can be obtained.
The linear programming method comprises the following specific calculation steps: after an interval addition type complementary judgment matrix is established, a consistency coefficient and a corresponding weight coefficient of the addition type complementary judgment matrix are obtained through linear programming; if the consistency coefficient meets the set consistency threshold, directly taking the weight coefficient as the weight coefficient of each level index contained in the evaluation index; if the consistency threshold value is not met, the additive complementary judgment matrix is adjusted, and then a linear programming method is reused to calculate new consistency coefficients and new weight coefficients.
1) Weight coefficient and consistency calculation
For the interval addition type complementary judgment matrix, the corresponding index weight vector is recorded as omega ═ omega1,ω2,…,ωn]TConstructing a satisfaction function
Wherein the content of the first and second substances,
in the formula (d)ijRepresenting expert vs. solution weights ωiAnd ωjThe allowable deviation of the comparison is compared with the allowable deviation,
is a section judgment
The midpoint of (a).
Obviously, muPThe larger the value of (omega), the more satisfied the expert is with the sequencing vector, and the solution of the sequencing vector of the interval judgment matrix can be converted into the following optimizationThe problems are as follows:
this problem can ultimately be translated into the following linear programming problem: finding an order vector ω1,ω2,…,ωnAnd λ, so that the performance index shown by equation (3) is minimized:
J＝-λ (3)
while satisfying the following linear constraints:
solving the mathematical programming problem formed by the equations (3) - (5) can obtain the consistency coefficient of the interval addition type complementary judgment matrix and the corresponding weight vector.
2) Consistency improvement
When the objective function value obtained by the above planning problem is less than 1, it can be considered that the interval number judgment matrix does not satisfy consistency. The above inconsistency can be measured by a bias matrix, which is defined as follows:
judging matrix for interval
The weight vector obtained by equations (3) to (5) is ω ═ ω1,ω2,…,ωn]T，W＝(ωi/(ωi+ωj))n×n W＝(ωi/(ωi+ωj))n×n W＝(ωi/(ωi+ωj))n×nFor the characteristic matrix formed by ω, then B is called (B)ij)n×nIs a deviation matrix of a and W, wherein,
in the formula (I), the compound is shown in the specification,
determining matrix element a for a rangeijThe interval width of (2).
Consider that in practical terms, it is often only required that the decision matrix has a satisfactory consistency, i.e. for a given threshold value
Only need to satisfy
And (4) finishing. The consistency improvement algorithm of the interval judgment matrix A is given as follows:
firstly, an objective function value lambda and a sorting vector omega of a section judgment matrix A are obtained by using linear programming models shown in formulas (3) to (5). If it is not
Outputting a judgment matrix A and a sequencing vector omega, and exiting the algorithm; otherwise, turning to the step II;
constructing a feature matrix W by using the sequencing vector omega, calculating a judgment matrix A and a deviation matrix B of the feature matrix W, and calculating a maximum value B of upper triangular elements of the judgment matrix A and the feature matrix Wrs＝max{bijI j > i }, let α be (0, b)rs]。
③ if
Then order
If it is
Order to
And (5) turning to the step I when the other judgment values are unchanged.
Thirdly, normalizing the values of the indexes of different levels aiming at the evaluation model of each evaluation index;
according to the spatial on-orbit service target priority evaluation index system, indexes of the same level often comprise qualitative indexes and quantitative indexes, and different methods are needed for processing to obtain quantitative index values. Meanwhile, the quantitative indexes have inconsistent dimensions, and the indexes with high values are easy to phagocytose other indexes when the indexes are polymerized to the upper-level indexes, so that the final priority evaluation result is influenced. Therefore, before the priority of the calculation space on-orbit service target is evaluated, the evaluation index is usually normalized, and the index values originally having different dimensions or meanings are converted into the 'grading values' capable of being aggregated to the upper layer according to a uniform reference.
1. Normalization of qualitative indicators
The normalization processing of the qualitative indexes comprises the following steps: and dividing a plurality of levels to describe the capability of the qualitative index, and giving a value corresponding to the qualitative index according to a normalized mapping relation. Specifically, in this embodiment, for the qualitative indexes, the capability of each qualitative index may be described in five levels of "good", "general", "poor", and "poor" by using an expert scoring method, and the number of intervals corresponding to each qualitative index is given according to the normalized mapping relationship shown in table 2.
TABLE 2 normalization of qualitative indices
| Qualitative index value | Is very good | Good taste | In general | Is poor | Difference (D) |
| Value of credit | 90 | 80 | 65 | 50 | 30 |
2. Normalization of quantitative indicators
The normalization processing of the quantitative index comprises the following steps: and (4) discriminating the type of the quantitative index according to the relation between the index value and the value degree, and further selecting a corresponding index normalization function to process the quantitative index.
In this embodiment, the quantitative index may be roughly classified into various types such as benefit type and cost type according to the relationship between the index value and the target priority. Take the evaluation index system of remote sensing satellite value degree as an example, in which the resolution VA21Width V observed to the groundA22And yaw imaging capability VA23With respect to the information acquisition level VA2The indexes are benefit indexes, namely the larger the index value is, the higher the value of the satellite on the ground action is. In the actual operation of this embodiment, the types of linear increment, upward convex increment, downward convex increment and the like are further discriminated according to the increasing relationship between the index value and the value degree, and then a responsive index normalization function is selected to process the quantitative index. Specifically, for a large index system, such as the remote sensing satellite value evaluation index system shown in fig. 3, which may include three layers of indexes below, the third layer of indexes, i.e., the end indexes, should be normalized according to whether the third layer of indexes is in an increasing or decreasing relationship with the previous layer of indexes.
Determining a polymerization method among indexes of different levels to polymerize a lower-layer index to an upper-layer index layer by layer, and finally obtaining quantitative evaluation results of each evaluation index of the space on-orbit service target;
for the spatial on-orbit service target priority evaluation hierarchical structure model, a weighting sum method is adopted to aggregate lower layer indexes to upper layer indexes layer by layer, namely, each lower layer index after normalized processing is multiplied by a corresponding weight coefficient respectively, and then the values of the upper layer indexes are obtained through summation. Under the weighting and processing mode, the value of a single index is zero, the integral value of the upper-layer index is not influenced, and the function expression is as follows:
ek＝ω1e1+ω2e2+…+ωnen (6)
in the formula, ei(i-1, 2, …, n) is the lower index uiNormalized value of (a), omegai(i-1, 2, …, n) is the lower index uiCorresponding weight coefficient of ekIs an index C of the previous layerkN represents the index C of the previous layerkThe number of lower layer indicators included.
And finally, quantitative evaluation results of indexes such as the value degree, the easy operation degree and the like of the space on-orbit service target can be obtained through bottom-to-top layer-by-layer polymerization. Because the index weight coefficient obtained by adopting the interval addition type complementary judgment matrix is a single determined value, the index values of the value degree, the easy operation degree and the like finally obtained through index aggregation are single determined values.
And step five, calculating the comprehensive priority of the space on-orbit service targets according to the quantitative evaluation result and the weight coefficient of each evaluation index, and sequencing the targets from high to low, thereby determining the selection of the space on-orbit service targets.
The target priority is formed by further considering the suitability of the service mode and the preference of a decision maker on the basis of the value degree and the easy operation degree. Through the second step to the fourth step, on the basis of determining specific assignments of evaluation indexes such as the value degree, the easy operation degree, the service mode suitability degree, the preference of a decision maker and the like of the space on-orbit service target, the comprehensive priority of the space on-orbit service target is obtained through calculation by combining the index weight coefficient, the targets are sorted according to the sequence from high to low, and the comprehensive priority sorting result is given, so that the selection of the optimal target is determined.
In this embodiment, a specific calculation method of the comprehensive priority includes: and multiplying the quantitative evaluation result of each evaluation index by the weight coefficient of each evaluation index respectively, and calculating by a summing mode to obtain the comprehensive priority. Assuming that evaluation indexes such as the value degree, the ease of operation, the service mode suitability, the decision maker preference and the like determined for the six space on-orbit service targets 01 to 06 are listed in table 3, and the weight coefficients of the indexes given are [0.48,0.22,0.19,0.11], the comprehensive priority of the six space on-orbit service targets is calculated and obtained as the rightmost column in table 3.
TABLE 3 space confrontation target priority end index assignment
The comprehensive priorities of the targets obtained by the quantitative analysis in the table 3 are sorted from high to low, and the sorting result is as follows: target 03> target 04> target 01> target 05> target 06> target 02, so target 03 is the optimal target.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (8)
1. A method for selecting a space on-orbit service target is characterized by comprising the following steps:
step one, constructing a priority index system of a space on-orbit service target;
the priority index system comprises evaluation indexes of value degree, easy operation degree, decision maker preference and service mode suitability degree; aiming at a specific space on-orbit service target, forming a corresponding evaluation model with a plurality of hierarchical structures for each evaluation index, wherein each evaluation model of the evaluation index comprises a plurality of indexes distributed at different levels;
step two, aiming at the evaluation model of each evaluation index, different weight coefficients are given to each index of different levels;
thirdly, normalizing the values of the indexes of different levels aiming at the evaluation model of each evaluation index;
determining a polymerization method among indexes of different levels to polymerize a lower-layer index to an upper-layer index layer by layer, and finally obtaining quantitative evaluation results of each evaluation index of the space on-orbit service target;
and step five, calculating the comprehensive priority of the space on-orbit service targets according to the quantitative evaluation result and the weight coefficient of each evaluation index, and sequencing the targets from high to low, thereby determining the selection of the space on-orbit service targets.
2. The method for selecting a space on-orbit service target according to claim 1, wherein in the evaluation indexes of the first step, the value degree is an index for evaluating the value of the space on-orbit service target itself, the ease of operation degree is an index for evaluating the difficulty of operating a spacecraft that provides an on-orbit service, the preference of the decision maker is an index for evaluating the subjective selection characteristic of the decision maker on the space on-orbit service target, and the service mode suitability is an index for measuring the suitability for operating the on-orbit service target; wherein, the value degree and the easy operation degree are quantitative indexes, and the preference of the decision maker and the suitability degree of the service mode are qualitative indexes.
3. The method for selecting the spatial on-orbit service target of claim 1, wherein the second step comprises: on the basis of an analytic hierarchy process, an interval addition type complementation judgment matrix is constructed, the addition type complementation judgment matrix is adjusted according to a satisfactory consistency threshold value, and the addition type complementation judgment matrix is used for endowing each evaluation index with a weight coefficient of each level index.
4. The method of claim 3, wherein the consistency of the additive complementary decision matrix and the corresponding weight coefficient thereof are calculated by a linear programming method.
5. The method for selecting the spatial on-orbit service target according to claim 4, wherein the linear programming method comprises the following specific steps: after an interval addition type complementary judgment matrix is established, a consistency coefficient and a corresponding weight coefficient of the addition type complementary judgment matrix are obtained through linear programming; if the consistency coefficient meets the set consistency threshold, directly taking the weight coefficient as the weight coefficient of each level index contained in the evaluation index; if the consistency threshold value is not met, the additive complementary judgment matrix is adjusted, and then a linear programming method is reused to calculate new consistency coefficients and new weight coefficients.
6. The method for selecting the spatial on-orbit service target according to any one of claims 1 to 5, wherein the normalization in the third step includes normalization of qualitative indicators and normalization of quantitative indicators;
the normalization processing of the qualitative indexes comprises the following steps: dividing a plurality of levels to describe the capability of the qualitative index, and giving a value corresponding to the qualitative index according to a standardized mapping relation;
the normalization processing of the quantitative index comprises the following steps: and (4) discriminating the type of the quantitative index according to the relation between the index value and the value degree, and further selecting a corresponding index normalization function to process the quantitative index.
7. The method for selecting the space on-orbit service target according to any one of claims 1 to 5, wherein the aggregation method among the indexes of different levels in the fourth step adopts a weighted sum method; the weighting sum method is that each lower layer index after normalization processing is multiplied by a corresponding weight coefficient respectively, and then the value of the upper layer index is obtained through summation, and the function expression is as follows:
ek＝ω1e1+ω2e2+…+ωnen，
in the formula, ei(i-1, 2, …, n) is the lower index uiNormalized value of (a), omegai(i-1, 2, …, n) is the lower index uiCorresponding weight coefficient of ekIs an index C of the previous layerkN represents the index C of the previous layerkThe number of lower layer indicators included.
8. The method for selecting the spatial on-orbit service targets according to any one of claims 1 to 5, wherein the specific calculation method of the comprehensive priority of the spatial on-orbit service targets is as follows: and multiplying the quantitative evaluation result of each evaluation index by the weight coefficient of each evaluation index respectively, and calculating by a summing mode to obtain the comprehensive priority.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011363182.0A CN112330219A (en) | 2020-11-27 | 2020-11-27 | Method for selecting space on-orbit service target |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011363182.0A CN112330219A (en) | 2020-11-27 | 2020-11-27 | Method for selecting space on-orbit service target |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112330219A true CN112330219A (en) | 2021-02-05 |
Family
ID=74308098
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011363182.0A Pending CN112330219A (en) | 2020-11-27 | 2020-11-27 | Method for selecting space on-orbit service target |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112330219A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113743811A (en) * | 2021-09-10 | 2021-12-03 | 上海卫星工程研究所 | Comprehensive efficiency evaluation method and system adopting coefficient weighting calculation |
| CN114884828A (en) * | 2022-04-29 | 2022-08-09 | 中国空间技术研究院 | Space-based networking efficiency evaluation system and method based on analytic hierarchy process |
| CN114955009A (en) * | 2022-05-20 | 2022-08-30 | 北京航天飞行控制中心 | Selection method, system, medium and equipment of earth orbit intersection butt joint |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20160011776A (en) * | 2014-07-22 | 2016-02-02 | 성균관대학교산학협력단 | Method for obtaining solutions based on weighting analytic hierarchy process, grey number and entropy for multiple-criteria group decision making problems |
| CN108629511A (en) * | 2018-05-04 | 2018-10-09 | 上海微小卫星工程中心 | A kind of satellite synthetic effectiveness evaluation method based on multifactor fuzzy theory reasoning and Analytic hierarchy process |
-
2020
- 2020-11-27 CN CN202011363182.0A patent/CN112330219A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20160011776A (en) * | 2014-07-22 | 2016-02-02 | 성균관대학교산학협력단 | Method for obtaining solutions based on weighting analytic hierarchy process, grey number and entropy for multiple-criteria group decision making problems |
| CN108629511A (en) * | 2018-05-04 | 2018-10-09 | 上海微小卫星工程中心 | A kind of satellite synthetic effectiveness evaluation method based on multifactor fuzzy theory reasoning and Analytic hierarchy process |
Non-Patent Citations (2)
| Title |
|---|
| 李岩;蔡远文;程龙;任江涛;伯伟;同江;: "在轨服务系统评估方案研究", 航天控制, no. 02, pages 2 * |
| 项磊 等: ""基于层次分析法与模糊理论的卫星效能评估"", 《计算机仿真》, vol. 30, no. 2, pages 55 - 61 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113743811A (en) * | 2021-09-10 | 2021-12-03 | 上海卫星工程研究所 | Comprehensive efficiency evaluation method and system adopting coefficient weighting calculation |
| CN114884828A (en) * | 2022-04-29 | 2022-08-09 | 中国空间技术研究院 | Space-based networking efficiency evaluation system and method based on analytic hierarchy process |
| CN114955009A (en) * | 2022-05-20 | 2022-08-30 | 北京航天飞行控制中心 | Selection method, system, medium and equipment of earth orbit intersection butt joint |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112330219A (en) | Method for selecting space on-orbit service target | |
| Eastman et al. | Multi-criteria and multi-objective decision making for land allocation using GIS | |
| Giraldo et al. | Continuous time-varying kriging for spatial prediction of functional data: An environmental application | |
| Articte | Raster procedures for M ulti-criteria/multi-0biective decisions | |
| Yoon | The propagation of errors in multiple-attribute decision analysis: a practical approach | |
| Kuroki et al. | UAV navigation by an expert system for contaminant mapping with a genetic algorithm | |
| US20080255911A1 (en) | Method and system for adaptive closed loop resource management | |
| CN104732079A (en) | Effectiveness determining method for remote sensing satellite system | |
| Kikuchi et al. | Hayabusa2 landing site selection: surface topography of Ryugu and touchdown safety | |
| US20060010443A1 (en) | Analytic hierarchy process based rules for sensor management | |
| CN112950008A (en) | Flight path planning evaluation method of aircraft | |
| CN111612241A (en) | Comprehensive evaluation method for realizing intelligent ship path planning function | |
| Walton | Models for the management of satellite-based sensors | |
| US9869800B2 (en) | Peak height for the calculation of wind load calculation apparatus and method | |
| CN110826891A (en) | Relative collision risk degree obtaining method based on ship cluster situation | |
| CN106570270A (en) | Method for rapidly determining multi-satellite combined coverage characteristics for system-oriented design | |
| Ridolfi et al. | Complex-systems design methodology for systems-engineering collaborative environment | |
| CN116091939A (en) | Forest on-ground biomass downscaling method based on multiscale geographic weighted regression | |
| CN114679214A (en) | Method and system for calculating number of satellites visible to user, electronic equipment and storage medium | |
| Klaproth et al. | Investigation of Mission Performance Sensitivities for Unmanned Aerial Vehicles Based on Parametric Similarity Assessment of Mission Requirements | |
| CN113758467A (en) | Remote sensing satellite region observation method based on region division and local grid nesting | |
| CN113220425A (en) | Distributed reconfigurable satellite system organization method based on mosaic splicing | |
| Israeli et al. | Justification of global positioning systems purchase using the analytic hierarchical process—The case of the Israeli Defense Force | |
| Galal et al. | Satellite battery sensor values prediction using Bayesian ridge regression models | |
| Sourwine et al. | An information based approach to improving overhead imagery collection |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |