CN112950008A - Flight path planning evaluation method of aircraft - Google Patents

Flight path planning evaluation method of aircraft Download PDF

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CN112950008A
CN112950008A CN202110180229.8A CN202110180229A CN112950008A CN 112950008 A CN112950008 A CN 112950008A CN 202110180229 A CN202110180229 A CN 202110180229A CN 112950008 A CN112950008 A CN 112950008A
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王玥
刘劲涛
李东光
庄星
徐东方
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Beijing Institute of Technology BIT
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Abstract

The track planning evaluation method of the aircraft determines the subjective weight of the track planning evaluation index of the aircraft by using an AHP method; determining objective weight of a track planning evaluation index of the aircraft by using an entropy weight method; giving different subjective weights and objective weights to the track planning evaluation indexes of the aircraft to obtain comprehensive weight values of the track planning evaluation indexes of the aircraft; and substituting the comprehensive weight value of the flight path planning evaluation index of the aircraft into a TOPSIS evaluation method to evaluate the flight path planning of the aircraft to obtain a flight path planning evaluation result of the aircraft. The comprehensive weight determination method based on the AHP-entropy weight method endows different influence factors to the subjective weight obtained by the AHP method and the objective weight obtained by the entropy weight method, comprehensively considers the subjective intention of a decision maker and the actual track information, and obtains a more scientific and reasonable final track planning evaluation result through the TOPSIS method.

Description

Flight path planning evaluation method of aircraft
Technical Field
The disclosure belongs to the technical field of computer software design, and particularly relates to a flight path planning evaluation method of an aircraft.
Background
Along with the continuous change of modern war modes, the battlefield environment changes instantly and completely, the operation task executed by only depending on the manned aircraft can not meet the operation requirement under the current battlefield mode, and the unmanned aircraft has received wide attention of various countries and is developed rapidly due to the advantages of high fault-tolerant rate and high operation efficiency. In the process of executing tasks, the unmanned aerial vehicle needs to carry out pre-planning on the flight path of the unmanned aerial vehicle, and the flight path planning scheme is related to the survival probability and the combat efficiency of the unmanned aerial vehicle, so that the flight path planning scheme needs to be evaluated.
Currently, in the field of track evaluation, common multi-attribute evaluation methods include a simple weighting method (SAW), an Analytic Hierarchy Process (AHP), a near ideal ordering method (TOPSIS), an ELECTRE method, and the like. When the method is adopted to evaluate the flight path planning of the aircraft, the influence factors of the judgment matrix are static, so that the actual task requirements of the aircraft cannot be met. The tasks actually performed by the aircraft are dynamic, and if the dynamic characteristics of the aircraft are not fully considered, the aircraft cannot be fully explained to be free from the physical limitation of the aircraft. In addition, the method is carried out independently when the physical limit of the aircraft is processed, the influence of other factors is not considered, when the factors have coupling relation with each other, the evaluation problem becomes complicated, and a general evaluation algorithm is not applicable.
When the planned flight path is comprehensively evaluated, in order to fully reflect the influence degree of each index on the flight path, the weight of each index is usually added into an evaluation algorithm, so that the final evaluation result is more scientific and reasonable. Currently, weighting methods for evaluation indexes mainly include subjective weighting methods and objective weighting methods. The subjective weighting method mainly comprises expert weighting, a binomial coefficient method, an AHP method and other methods, wherein the subjective weighting method determines the weight of each index by judging and analyzing the importance degree of each index by a decision maker. The objective weighting method mainly comprises methods such as an entropy weight method, a standard deviation method and a CRITIC method, and the objective weighting method calculates the weight through a certain mathematical method according to specific data of evaluation indexes.
Disclosure of Invention
In view of the above, the present disclosure provides a track planning evaluation method for an aircraft, which is a comprehensive weight determination method based on an AHP-entropy weight method, and comprehensively considers the subjective intention of a decision maker and actual track information, so that the final track planning evaluation result obtained by the TOPSIS method is more scientific and reasonable.
According to an aspect of the present disclosure, a method for evaluating a flight path planning of an aircraft is provided, the method including:
determining the subjective weight of the track planning evaluation index of the aircraft by using an AHP method;
determining objective weight of a track planning evaluation index of the aircraft by using an entropy weight method;
giving different subjective weights and objective weights to the track planning evaluation indexes of the aircraft to obtain comprehensive weight values of the track planning evaluation indexes of the aircraft;
and substituting the comprehensive weight value of the flight path planning evaluation index of the aircraft into a TOPSIS evaluation method to evaluate the flight path planning of the aircraft to obtain a flight path planning evaluation result of the aircraft.
In a possible implementation manner, the determining the subjective weight of the trajectory planning evaluation index of the aircraft by using the AHP method includes:
determining the proportion of the influence of the lower-layer track planning evaluation index to the upper-layer track planning evaluation index according to a static track planning evaluation index system of the aircraft, and constructing a judgment matrix;
calculating the weight of each flight path planning evaluation index of the flight path planning of the aircraft according to the judgment matrix to obtain a single-sequencing result of each flight path planning evaluation index, and obtaining a total sequencing result of each flight path planning evaluation index according to the single-sequencing result of each flight path planning evaluation index;
and when the total ordering result of the track planning evaluation indexes of all layers meets the consistency check requirement of a judgment matrix, multiplying the weight vector of the lower-layer track planning evaluation index by the weight vector of the upper-layer track planning evaluation index to obtain the subjective weight of the track planning evaluation index of the aircraft.
In a possible implementation manner, the judgment matrix is
Figure BDA0002941973510000031
Wherein, aijThe relative importance degree of the flight path planning evaluation index i to the flight path planning evaluation index j is set to be 0 & ltaij≤9，aji＝1/aij，aii＝1(i＝1，2，...，n)，j＝1,2,...,n。
In a possible implementation manner, calculating each evaluation index weight of the flight path planning of the aircraft according to the judgment matrix, performing single ranking result of each level of flight path planning evaluation indexes, and obtaining a total ranking result of each level of flight path planning evaluation indexes according to the single ranking result of each level of flight path planning evaluation indexes, the method includes:
each column of the judgment matrix A is normalized into
Figure BDA0002941973510000032
Summing the normalized judgment matrix A into
Figure BDA0002941973510000033
To the above
Figure BDA0002941973510000034
Normalized to obtain wi，
Figure BDA0002941973510000035
Wherein, wiThe weight of the ith evaluation index;
calculating the maximum characteristic root lambda of the judgment matrix A,
Figure BDA0002941973510000036
obtaining the single-sequencing result of each level of track planning evaluation indexes according to the maximum characteristic root lambda of the judgment matrix A
Figure BDA0002941973510000037
And further obtaining the total sequencing result of the evaluation indexes of the flight path planning of each level as follows:
Figure BDA0002941973510000038
where RI is the average random consistency index, ajThe overall ranking weight is the hierarchy.
In one possible implementation, the determining the objective weight of the trajectory planning evaluation index of the aircraft by using an entropy weight method includes:
constructing a data matrix X of the flight path planning evaluation index of the aircraft,
Figure BDA0002941973510000041
wherein, XijAnd planning the value of an evaluation object for the ith track under the jth track planning evaluation index, wherein m is a positive integer.
Carrying out normalization processing on the data matrix X to obtain a normalization result of the data matrix X;
calculating the characteristic specific gravity value of each track planning evaluation object under each evaluation index of the track planning of the aircraft by using the normalization result of the data matrix X;
calculating entropy values and difference coefficients of evaluation indexes of the flight path planning of the aircraft according to the characteristic specific gravity values;
and calculating the weight of each evaluation index of the flight path planning of the aircraft according to the entropy and the difference coefficient, and further obtaining the objective weight of each evaluation index of the flight path planning of the aircraft.
The track planning evaluation method of the aircraft determines the subjective weight of the track planning evaluation index of the aircraft by using an AHP method; determining objective weight of a track planning evaluation index of the aircraft by using an entropy weight method; giving different subjective weights and objective weights to the track planning evaluation indexes of the aircraft to obtain comprehensive weight values of the track planning evaluation indexes of the aircraft; and substituting the comprehensive weight value of the flight path planning evaluation index of the aircraft into a TOPSIS evaluation method to evaluate the flight path planning of the aircraft to obtain a flight path planning evaluation result of the aircraft. The comprehensive weight determination method based on the AHP-entropy weight method endows different influence factors to the subjective weight obtained by the AHP method and the objective weight obtained by the entropy weight method, and comprehensively considers the subjective intention of a decision maker and the actual track information, so that the final track planning evaluation result obtained by the TOPSIS method is more scientific and reasonable.
Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.
FIG. 1 illustrates a flow chart of a method for evaluating a flight path planning for an aircraft according to an embodiment of the present disclosure;
FIG. 2 illustrates a flowchart of a further defining method of step S1 according to an embodiment of the present disclosure;
FIG. 3 illustrates a flowchart of a further defining method of step S2 according to an embodiment of the present disclosure;
FIG. 4 illustrates a flow chart of a method for evaluating a flight path planning for an aircraft according to another embodiment of the disclosure.
Detailed Description
Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.
FIG. 4 illustrates a flow chart of a method for evaluating a flight path planning for an aircraft according to another embodiment of the disclosure.
The invention provides a flight path planning evaluation method of an aircraft, which is based on an AHP-entropy weight method comprehensive weight determination method and adopts a TOPSIS (approach to ideal ordering method) method to solve the flight path planning evaluation problem of the aircraft.
As shown in fig. 4, the subjective weight of the aircraft track planning evaluation index is obtained according to the AHP method by using the established known static track evaluation index system. For example, a judgment matrix of the track planning evaluation is constructed, the weight and the level order of each track planning evaluation index are calculated, the consistency of the judgment construction matrix is checked, the subjective weight of the track planning evaluation index is calculated, and the like, so that the total subjective weight of the aircraft track planning evaluation index is obtained;
and the established known static track evaluation index system also obtains the objective weight of the aircraft track planning evaluation index through an entropy weight method. For example, the total objective weight of the aircraft track planning evaluation index is obtained by constructing the data standardization of the track planning index layer, carrying out the normalization processing on the original data matrix, calculating the characteristic proportion of each track planning evaluation index, calculating the entropy value of each track planning evaluation index, calculating the weight of each track planning evaluation index and the like.
Giving different subjective weight and objective weight to the aircraft track planning evaluation indexes, comprehensively considering subjective intention of a decision maker and actual track information to obtain comprehensive weight of each evaluation index of the aircraft track planning, substituting the comprehensive weight into TOPSIS to evaluate a known track planning scheme, finishing evaluation of the aircraft track planning scheme, and obtaining a relatively reasonable weight distribution result of the aircraft track planning index. The specific process of the flight path planning evaluation is as follows.
FIG. 1 illustrates a flow chart of a method for evaluating a flight path planning for an aircraft according to an embodiment of the present disclosure; as shown in fig. 1, the method may include:
step S1: and determining the subjective weight of the track planning evaluation index of the aircraft by using an AHP method.
AHP (Analytic Hierarchy Process) refers to a decision method for performing qualitative and quantitative analysis on elements always related to a decision by decomposing the elements into levels such as targets, criteria, schemes, and the like.
FIG. 2 shows a flowchart of a further defining method of step S1 according to an embodiment of the present disclosure.
As shown in fig. 2, step S1 may include:
step S11: and determining the proportion of the influence of the lower-layer track planning evaluation index to the upper-layer track planning evaluation index according to the static track planning evaluation index system of the aircraft, and constructing a judgment matrix.
Wherein the decision matrix may be A, i.e.
Figure BDA0002941973510000061
Wherein, aijThe relative importance degree of the flight path planning evaluation index i to the flight path planning evaluation index j is set to be 0 & ltaij≤9，aji＝1/aij，aii1, and i and j are positive integers, i 1, 2.
aijAnd ajiThe positive integers 1 to 9 and the reciprocal thereof are used as scales, for example, the scale is 1, and the positive integers represent that the track planning evaluation indexes of the two aircrafts have the same importance compared with each other; the scale is 3, which indicates that the track planning evaluation indexes of one aircraft are slightly more important than those of the other aircraft compared with the track planning evaluation indexes of the two aircrafts; the scale is 5, which shows that compared with the track planning evaluation indexes of two aircrafts, the track planning evaluation index of one aircraft is obviously more important than the track planning evaluation index of the other aircraft; the scale is 7, which indicates that compared with the track planning evaluation indexes of two aircrafts, the track planning evaluation index of one aircraft is more important than the track planning evaluation index of the other aircraft; the scale is 9, which indicates that the track planning evaluation indexes of two aircrafts are compared, and the track planning evaluation index of one aircraft is extremely important compared with the track planning evaluation index of the other aircraft; scales 2, 4, 6, 8, representing intermediate states of comparison on scales 1, 3, 5, 7, 9; the reciprocal denoted 1/aij represents the ratio of the importance of factor j to factor i.
Constrain flight performance B1Navigation probability constraint B2Environmental threat constraint B3Enemy threat zone constraints B4Synergistic constraint B5Setting as a first-level track planning evaluation index.
The maximum range constraint index C1 and the minimum horizontal flight distance constraint index C2Turn number constraint index C3Maximum turning angle constraint index C4Scene matching probability constraint index C5And a random signal navigation probability constraint index C6Terrain threat constraint index C7Weather threat constraint index C8Constraint index C of radar threat area9Air-defense fire threat zone constraint index C10Time synergistic constraint index C11And spatial cooperative constraint index C12And setting as a secondary track planning evaluation index.
By comparing the importance degrees of the track planning evaluation indexes of the layers, pairwise judgment matrixes of the first-level track planning evaluation index and the second-level track planning evaluation index are respectively constructed, and are specifically shown in tables 2-7.
TABLE 1 first-level track planning evaluation index judgment matrix
Figure BDA0002941973510000071
TABLE 2 one of the two-stage track planning evaluation index judgment matrixes
Figure BDA0002941973510000072
Figure BDA0002941973510000081
TABLE 4 two-stage track planning evaluation index judgment matrix II
Figure BDA0002941973510000082
TABLE 5 evaluation index determination matrix III for two-stage track planning
Figure BDA0002941973510000083
TABLE 6 four of the two-stage track planning evaluation index judgment matrix
Figure BDA0002941973510000084
TABLE 7 five of the two-stage track planning evaluation index judgment matrix
Figure BDA0002941973510000085
Step S12: and calculating the weight of each evaluation index of the flight path plan according to the judgment matrix to obtain a single sequencing result of each evaluation index of each layer of flight path plan, and obtaining a total sequencing result of each evaluation index of each layer of flight path plan according to the single sequencing result of each evaluation index of each layer of flight path plan.
For example, each column of the decision matrix A is normalized into
Figure BDA0002941973510000091
Summing the normalized judgment matrix A into
Figure BDA0002941973510000092
To pair
Figure BDA0002941973510000093
Normalization processing to obtain Wi，
Figure BDA0002941973510000094
Wherein, WiPlanning the weight of the evaluation index for the ith track;
the maximum characteristic root lambda of the decision matrix a is calculated,
Figure BDA0002941973510000095
obtaining the single-sequencing result of each level of track planning evaluation indexes according to the maximum characteristic root lambda of the judgment matrix A
Figure BDA0002941973510000096
And further obtaining the total sequencing result of the evaluation indexes of the flight path planning of each level as follows:
Figure BDA0002941973510000097
wherein R isIAs an average random consistency index, ajThe overall ranking weight is the hierarchy. When CR is reached<At 0.10, the overall ordering result of the hierarchy has more satisfactory consistency.
Step S13: and when the total sequencing result of the flight path planning evaluation indexes of each level meets the consistency inspection requirement of the judgment matrix, multiplying the weight vector of the lower-layer flight path planning evaluation index by the weight vector of the upper-layer flight path planning evaluation index to obtain the subjective weight of the flight path planning evaluation index of the aircraft.
For example, the consistency check is performed on the weights obtained by the first-level track planning evaluation index and the second-level track planning evaluation index of the aircraft, and the weight of the first-level track planning evaluation index of the aircraft is obtained as
Figure BDA0002941973510000098
The weights of the secondary track planning evaluation indexes of the aircraft are respectively as follows:
Figure BDA0002941973510000099
after the single-layer weights of the first-level track planning evaluation indexes and the second-level track planning evaluation indexes are obtained, multiplying the weight vector of the second-level track planning evaluation indexes by the weight of the corresponding first-level track planning evaluation indexes to obtain the total weight of each track planning evaluation index of the track planning evaluation index layer in the whole evaluation system, for example, the total weight of the track planning evaluation indexes is as follows:
Figure BDA0002941973510000101
then the subjective weight of the track planning evaluation index, that is, the total subjective weight set of the track evaluation index, is: ω '{ ω'1,ω'2,...ω'12}。
Step S2: and determining the objective weight of the flight path planning evaluation index of the aircraft by using an entropy weight method.
Generally, for a certain index, the Entropy Weight Method (EWM) can use an entropy value to determine a dispersion degree of the certain index, and the smaller the information entropy value is, the greater the dispersion degree of the index is, the greater the influence (i.e., weight) of the index on the comprehensive evaluation is, and if the values of the certain index are all equal, the index does not work in the comprehensive evaluation. The weight of each index can be calculated by an entropy weight method, and a basis is provided for comprehensive evaluation of the indexes.
FIG. 3 shows a flowchart of a further defining method of step S2 according to an embodiment of the present disclosure.
As shown in fig. 3, step S2 may include:
step S21: and constructing a data matrix X of the flight path planning evaluation index of the aircraft.
For example, let M tracks to be evaluated, i.e. M ═ M for the evaluated object1,M2,...,MmThe evaluation index D of the flight path planning is { D ═ D1,D2,...,D12}, the evaluated object MiCorresponding track planning evaluation index DjIs denoted as Xij(i 1, 2.. multidot.m; j 1, 2.. multidot.12), and a raw data matrix for obtaining a track planning evaluation index of the aircraft is as follows:
Figure BDA0002941973510000102
wherein, XijThe value of the ith evaluation target under the jth evaluation index is m, which is a positive integer.
Step S22: and carrying out normalization processing on the data matrix X to obtain a normalization result of the data matrix X.
For example, the dimensions of the route planning schemes related to 12 route planning evaluation indexes are different, and the numerical difference is large. In order to make each track planning evaluation index comparable, it is necessary to normalize the data of each track planning evaluation index.
For more and more optimal track planning evaluation indexes, such as scene matching probability constraint index C5Constraint index C of radar threat area9And (3) carrying out normalization processing on the equal track planning evaluation indexes by using the following formula:
Figure BDA0002941973510000111
wherein x isjAnd planning the data value of the evaluation index for the jth track.
For the more optimal and smaller flight path planning evaluation indexes, such as the maximum flight path constraint index C1Turn number constraint index C3The evaluation indexes of the equal flight path planning are normalized by the following formulaChemical treatment:
Figure BDA0002941973510000112
wherein V is more than or equal to 0ij≤1。
Step S23: and calculating the characteristic specific gravity value of each evaluation object under each evaluation index of the flight path planning of the aircraft by using the normalization result of the data matrix X.
For example, under the jth track planning evaluation index, the characteristic proportion of the ith track planning evaluation object is PijUsing the normalization result V of the data matrix X calculated in step S22ijAnd calculating the characteristic proportion P of the evaluation object under each evaluation index of the flight path planning of the aircraft according to the following formula:
Figure BDA0002941973510000113
in the formula, V is more than or equal to 0ijIs less than or equal to 1, is less than or equal to 0 and is less than or equal to Pij≤1。
Step S24: and calculating the entropy value and the difference coefficient of each evaluation index of the flight path planning of the aircraft according to the characteristic specific gravity value.
For example, if the entropy of the jth track planning evaluation index is ejAccording to the formula of entropy calculation:
Figure BDA0002941973510000114
in the formula, the larger the data difference of the jth track planning evaluation index of each evaluation object in the track planning is, the larger the information amount reflected by the track planning evaluation index is, and the entropy value e of the information amount isjThe smaller.
Step S24: and calculating the weight of each evaluation index of the flight path planning of the aircraft according to the entropy and the difference coefficient, and further obtaining the objective weight of each evaluation index of the flight path planning of the aircraft.
For example, let D be the difference coefficient of the jth track planning evaluation indexjAccording to the calculation formula of the difference coefficient: dj＝1-ejCalculating the jth navigationWeight ω ″' of trace planning evaluation indexjComprises the following steps:
Figure BDA0002941973510000115
similarly, the weight of each evaluation index of the flight path plan of the aircraft can be calculated, and then an objective weight set of each evaluation index of the flight path plan of the aircraft is obtained, namely ω ═ ω ″1,ω″2,...ω″12}。
Step S3: and giving different influence factors to the subjective weight and the objective weight of the track planning evaluation index of the aircraft to obtain the comprehensive weight value of the track planning evaluation index of the aircraft.
Giving different influence factors mu and v to the subjective weight set and the objective weight set of each evaluation index of the flight path planning of the aircraft calculated in the step S1 and the step S2 to obtain the comprehensive weight value of each evaluation index of the flight path planning of the aircraft, such as omegai＝μω′i+vω″i，
Wherein i is 1,2, …, 12; mu is an influence factor of subjective weight, ν is an influence factor of objective weight, and μ + ν is 1, and the values of μ and ν can be determined according to the subjective experience of the decision maker and the requirements of the actual task, which is not specifically limited herein.
Step S4: and substituting the comprehensive weight value of the flight path planning evaluation index of the aircraft into a TOPSIS evaluation method to evaluate the flight path planning of the aircraft to obtain a flight path planning evaluation result of the aircraft.
The disclosed method for evaluating flight path planning of aircraft carries out flight path evaluation based on TOPSISI method of AHP-entropy weight method, which not only avoids excessive intervention of decision maker in evaluation process, but also does not completely stop participation of decision maker in evaluation process, and calculates objective weight by entropy weight method according to specific data of evaluation index while introducing subjective weight, then determines comprehensive weight of evaluation index by comprehensively measuring proportion of subjective weight and objective weight, thereby making final evaluation result more accurate and credible. The method can avoid the influence of extreme values on the evaluation result in a simple linear weighting method, does not need to give the order relation of each index as in the ELECTRE method, can evaluate a flight path planning scheme with clear evaluation index data, and achieves the technical effects of improving the evaluation efficiency and the like.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims (5)

1. A method for evaluating a flight path planning for an aircraft, the method comprising:
determining the subjective weight of the track planning evaluation index of the aircraft by using an AHP method;
determining objective weight of a track planning evaluation index of the aircraft by using an entropy weight method;
giving different subjective weights and objective weights to the track planning evaluation indexes of the aircraft to obtain comprehensive weight values of the track planning evaluation indexes of the aircraft;
and substituting the comprehensive weight value of the flight path planning evaluation index of the aircraft into a TOPSIS evaluation method to evaluate the flight path planning of the aircraft to obtain a flight path planning evaluation result of the aircraft.
2. The method according to claim 1, wherein the determining the subjective weight of the flight path planning evaluation index of the aircraft by using an AHP method comprises:
determining the proportion of the influence of the lower-layer track planning evaluation index to the upper-layer track planning evaluation index according to a static track planning evaluation index system of the aircraft, and constructing a judgment matrix;
calculating the weight of each evaluation index of the flight path planning of the aircraft according to the judgment matrix to obtain a single-sequencing result of each layer of flight path planning evaluation indexes, and obtaining a total sequencing result of each layer of flight path planning evaluation indexes according to the single-sequencing result of each layer of flight path planning evaluation indexes;
and when the total ordering result of the track planning evaluation indexes of all layers meets the consistency check requirement of a judgment matrix, multiplying the weight vector of the lower-layer track planning evaluation index by the weight vector of the upper-layer track planning evaluation index to obtain the subjective weight of the track planning evaluation index of the aircraft.
3. The method according to claim 2, wherein the decision matrix is
Figure FDA0002941973500000011
Wherein, aijThe relative importance degree of the flight path planning evaluation index i to the flight path planning evaluation index j is set to be 0 & ltaij≤9，aji＝1/aij，aii1, and i and j are positive integers, i 1,2, a.
4. The flight path planning evaluation method according to claim 2, wherein the step of calculating the weight of each evaluation index of the flight path planning of the aircraft according to the judgment matrix, performing single ranking results of each ranking evaluation index, and obtaining the total ranking result of each ranking evaluation index according to the single ranking results of each ranking evaluation index comprises the steps of:
each column of the judgment matrix A is normalized into
Figure FDA0002941973500000021
Figure FDA0002941973500000022
Summing the normalized judgment matrix A into
Figure FDA0002941973500000023
Figure FDA0002941973500000024
To the above
Figure FDA0002941973500000025
Normalization processing to obtain Wi，
Figure FDA0002941973500000026
Wherein, WiThe weight of the ith evaluation index;
calculating the maximum characteristic root lambda of the judgment matrix A,
Figure FDA0002941973500000027
obtaining the single-sequencing result of each hierarchy evaluation index according to the maximum characteristic root lambda of the judgment matrix A
Figure FDA0002941973500000028
Further, the total ranking result of each ranking evaluation index is as follows:
Figure FDA0002941973500000029
Figure FDA00029419735000000210
where RI is the average random consistency index, ajThe overall ranking weight is the hierarchy.
5. The method according to claim 1, wherein the determining the objective weight of the flight path planning evaluation index of the aircraft by using the entropy weight method comprises:
constructing a data matrix X of the flight path planning evaluation index of the aircraft,
Figure FDA00029419735000000211
wherein, XijThe value of the ith evaluation target under the jth evaluation index is m, which is a positive integer.
Carrying out normalization processing on the data matrix X to obtain a normalization result of the data matrix X;
calculating the characteristic specific gravity value of each evaluation object under each evaluation index of the flight path planning of the aircraft by using the normalization result of the data matrix X;
calculating entropy values and difference coefficients of evaluation indexes of the flight path planning of the aircraft according to the characteristic specific gravity values;
and calculating the weight of each evaluation index of the flight path planning of the aircraft according to the entropy and the difference coefficient, and further obtaining the objective weight of each evaluation index of the flight path planning of the aircraft.
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