CN106199662A - A kind of Big Dipper high-precision locating method based on analytic hierarchy process (AHP) - Google Patents

Abstract

The invention discloses a kind of Big Dipper high-precision locating method based on analytic hierarchy process (AHP), it is characterized in that carrying out as follows: first monitoring period of time is divided into multiple sub-period, calculates the positioning result of each sub-period respectively；Then according to the satellite distribution of each sub-period, error source, satellite number epoch, analytic hierarchy process (AHP) is used to determine the location credibility of each positioning result；Location credibility weighted filtering is finally utilized to go out the final positioning result of whole monitoring period of time.The present invention has refined positioning calculation process, take into full account the every factor affecting positioning precision, making final positioning result reach higher positioning precision, particularly in monitoring period of time, in the case of Changes in weather, positioning precision advantage is notable, has broad application prospects.

Description

A kind of Big Dipper high-precision locating method based on analytic hierarchy process (AHP)

Technical field

The invention belongs to satellite navigation positioning field, a kind of Big Dipper based on analytic hierarchy process (AHP) is high-precision fixed Method for position.

Background technology

Big Dipper hi-Fix refers to utilize Beidou navigation satellite " static relative positioning technology " to obtain monitoring point high accuracy Coordinate (grade), thus analyze displacement or the sedimentation judging dam, bridge, ground etc., there is important using value.

At present, " static phase when using aeronautical satellite (GPS, GLONASS, the Big Dipper) technology to carry out hi-Fix, is all used To localization method ".The method thinks monitoring station transfixion, by gathering Satellite Observations long, substantial amounts of, and application Baseline vector between least square adjustment principle solving base station and monitoring station.Because having substantial amounts of Satellite Observations, So iterative computation Stepwise Refinement can be passed through, calculate high-precision baseline vector, thus obtain the location knot of " grade " Really.

As it is shown in figure 1, traditional static relative positioning method is to utilize all Satellite Observations of a longer period of time, Positioning result L ' is calculated in the way of post processing.Owing within this period, satellite spatial distribution can change, weather also can become Changing, therefore receiving satellite data quality is change, and some sub-period satellite data quality is good, some sub-period satellite data Quality is general or poor.Traditional method does not also differentiate between the diversity of this quality of data, broadly utilizes all satellite data meters Calculate positioning result, thus result in positioning result error and increase, it is difficult to meet high-precision applications demand.

Summary of the invention

In place of the present invention solves above-mentioned the deficiencies in the prior art, it is provided that a kind of Big Dipper based on analytic hierarchy process (AHP) High-precision locating method, to refining positioning calculation process, takes into full account the every factor affecting positioning precision, thus effectively Improving positioning precision, in the case of particularly there is Changes in weather or power-off in monitoring period of time, positioning precision advantage is notable, tool Have broad application prospects.

In order to achieve the above object, the technical solution adopted in the present invention is:

A kind of Big Dipper high-precision locating method based on analytic hierarchy process (AHP) of the present invention, be applied to by Beidou navigation satellite, In the monitoring of environmental of base station and rover station composition；Described base station receives satellite number epoch that described Beidou navigation satellite sends According to and be sent to rover station；Described rover station receives satellite data epoch and the described base station that described Beidou navigation satellite sends Send base station satellite data epoch and carry out difference processing, it is thus achieved that Differential positioning data, be designated as X；It is characterized in, described north Bucket high-precision locating method is carried out as follows:

Step 1, Differential positioning data X to described rover station were split according to the time period, it is thus achieved that N number of sub-time period Differential positioning data, are designated as X={X₁,X₂,…,X_n,…,X_N}；X_nRepresent n-th period of the day from 11 p.m. to 1 a.m in Differential positioning data X of rover station Between the Differential positioning data of section；1≤n≤N；

Step 2, Differential positioning data X to described N number of sub-time period are respectively adopted static relative positioning algorithm and count Calculate, it is thus achieved that N number of positioning result, be designated as L={L₁,L₂,…,L_n,…,L_N}；L_nRepresent that the difference of rover station n-th sub-time period is fixed Bit data X_nPositioning result；

Step 3, utilize analytic hierarchy process (AHP) obtain N number of sub-time period location credibility Y；

Step 3.1, structure overall merit hierarchical model；

Using described N number of positioning result L as the solution layer of described overall merit hierarchical model, positioning result L will be produced Geometric dilution of precision, upper atmosphere error and satellite quantity epoch of impact is as the criterion of described overall merit hierarchical model Layer；Using the location credibility of described N number of sub-time period as the destination layer of described overall merit hierarchical model；

Step 3.2, structure pairwise comparison matrix；

Using described geometric dilution of precision, upper atmosphere error and satellite quantity epoch as three units of described rule layer Element；The comparative result two-by-two of three elements according to described rule layer, constructs three rank pairwise comparison matrix A=(a_ij)_3×3； a_ijRepresent that i-th element is relative to the jth element ratio to the importance of described destination layer；i,j∈{1,2,3}；

Step 3.3, calculating weight vector；

A ω=λ ω is utilized to obtain all eigenvalue λ and characteristic vector ω of described three rank pairwise comparison matrix A；Will be all Eigenvalue of maximum λ in eigenvalue λ_maxCorresponding characteristic vector ω^*It is normalized, obtains weight vector

Step 3.4, consistency check；

Judge a in described three rank pairwise comparison matrix A_ijWhether meet formula (1), if meeting, then it represents that paired comparison square Battle array is consistency matrix, and performs step 3.5；Otherwise, carry out consistency check, if upchecking, execution step 3.5, otherwise, Reconfigure comparator matrix；

a_ika_kj=a_ij (1)

In formula (1), a_ikRepresent that i-th element is relative to the kth element relative weighting to described destination layer；k∈{1,2, 3}；

Step 3.5, data obscure normalization；

Step 3.5.1, the geometric dilution of precision of the obtained by satellite signal receiver n-th sub-time period tried to achieve Meansigma methods, satellite quantity epoch that meansigma methods, upper atmosphere error are tried to achieve are designated as GDOP respectively_n、Δτ_n、N_n。

Step 3.5.2, formula (2), formula (3) and formula (4) three elements respectively to described rule layer are utilized to carry out fuzzy returning One change processes, and obtains the normalized value GDOP of geometric dilution of precision_n', the normalized value Δ τ of upper atmosphere error_n', satellite epoch The normalized value N of the optimum of quantity_n':

$N_n^{\′}=\frac{N_n}{N^{*}}---\left(4\right)$

In formula (2), formula (3) and formula (4), GDOP^*、Δτ^*、N^*Represent the optimum of described geometric dilution of precision, height respectively The empty optimum of atmosphere errors, the optimum of satellite quantity epoch；

Step 3.6, utilize formula (5) calculate the n-th sub-time period positioning result L_nLocation credibility Y_n, thus obtain N The location credibility of individual sub-time period, is designated as Y={Y₁,Y₂,···,Y_n,···,Y_N}；

$Y_n=\[{\mathrm{GDOP}}_n^{\′},{\mathrm{\Δ\τ}}_n^{\′},N_n^{\′}\]\·\stackrel{\‾}{\mathrm{\ω}}---\left(5\right)$

Step 4, utilize formula (6) that N number of positioning result of rover station is weighted Filtering Processing, it is thus achieved that final positioning result L^*；

$L^{*}=\frac{Y_1}{\underset{i=1}{\overset{N}{\Σ}}{Y}_i}{L}_1+\frac{Y_2}{\underset{i=1}{\overset{N}{\Σ}}{Y}_i}{L}_2+\mathrm{...}+\frac{Y_n}{\underset{i=1}{\overset{N}{\Σ}}{Y}_i}{L}_n+\mathrm{...}+\frac{Y_1}{\underset{i=1}{\overset{N}{\Σ}}{Y}_i}{L}_N---\left(6\right)$

In formula (6), Y_iRepresent the positioning result L of rover station i-th sub-time period_iLocation credibility, 1≤i≤N.

The feature of Big Dipper high-precision locating method based on analytic hierarchy process (AHP) of the present invention lies also in, described step Consistency check process in 3.4 is as follows:

Step 3.4.1, utilize formula (7) calculate coincident indicator CI:

$CI=\frac{{\mathrm{\λ}}_{max}-M}{M-1}---\left(7\right)$

In formula (7), M represents the element number of described rule layer；

Step 3.4.2, utilize formula (8) calculate consistency ration CR:

$CR=\frac{CI}{RI}---\left(8\right)$

In formula (8), RI represents Aver-age Random Consistency Index, and by acquisition of tabling look-up；

Step 3.4.3, concordance judge:

As CR ＜ 0.1, represent that the concordance of described three rank pairwise comparison matrix A is in tolerance interval；Otherwise it is assumed that Described three rank pairwise comparison matrix A pass through consistency check.

Compared with the prior art, the invention have the benefit that

1, the data that a longer period of time obtains are divided into multiple sub-period by the present invention, utilize the satellite of each sub-period Observation data calculate each sub-positioning result respectively, distribute to each sub-location according to the diversity of each sub-period satellite data quality The weight that result is different, thus improve positioning precision.

2, present invention introduces analytic hierarchy process (AHP), by the three big elements affecting positioning result precision by constructing paired comparison square Battle array is converted into quantitative Analysis problem, it is thus possible to obtain the location credibility of each sub-positioning result.

3, the present invention proposes location this concept of credibility, positions with a high credibility, this period satellite data quality is described Good, position with a low credibility, illustrate that this period satellite data is of poor quality, distribute son according to the difference of day part location credibility The weight of positioning result, and in the way of weighted filtering, solve final positioning result, thus improve positioning precision.

Accompanying drawing explanation

Fig. 1 is traditional static relative positioning method figure；

Fig. 2 is piece-wise stationary relative positioning method figure of the present invention；

Fig. 3 is that the present invention is determined the internal association figure of location credibility by the quality of data；

Fig. 4 is the present invention Big Dipper based on analytic hierarchy process (AHP) high-precision locating method flow chart；

Fig. 5 is analytic hierarchy process (AHP) flow chart of steps of the present invention；

Fig. 6 is overall merit hierarchical model of the present invention；

Fig. 7 is the Comparison of experiment results figure of the inventive method and traditional static relative positioning method.

Detailed description of the invention

In the present embodiment, a kind of Big Dipper high-precision locating method based on analytic hierarchy process (AHP), the principle of the method such as Fig. 2 institute Show, monitoring period of time is divided into multiple sub-period, calculates the positioning result of each sub-period respectively, take into full account impact location knot Really every factor of precision is as shown in Figure 3.The method is the prison being applied to be made up of Beidou navigation satellite, base station and rover station Survey in environment；Base station receives satellite Data Concurrent epoch of Beidou navigation satellite transmission and gives rover station；Rover station receives north Bucket aeronautical satellite send satellite data epoch and base station send base station satellite data epoch and carry out difference processing, obtain Obtain Differential positioning data, be designated as X；

As shown in Figure 4, Big Dipper high-precision locating method is carried out as follows:

Step 1, Differential positioning data X to rover station were split according to the time period, it is thus achieved that the difference of N number of sub-time period Location data, such as, become 12 sub-periods, each sub-period 2 hours by 24 hours observation Time segments division；It is designated as X={X₁, X₂,…,X_n,…,X_N}；X_nRepresent the Differential positioning data of the n-th sub-time period in Differential positioning data X of rover station；1≤n ≤N；

Step 2, Differential positioning data X to N number of sub-time period are respectively adopted static relative positioning algorithm and calculate, and obtain Obtain N number of positioning result, be designated as L={L₁,L₂,…,L_n,…,L_N}；L_nRepresent the Differential positioning number of rover station n-th sub-time period According to X_nPositioning result；The content of static relative positioning algorithm is shown in " technique study of carrier phase differential dynamic positioning " have Jie Continue；

Step 3, utilize analytic hierarchy process (AHP) obtain N number of sub-time period location credibility Y；

Obtained the positioning result L of each sub-period according to step 2, the location credibility of these results there are differences, It is relevant with many factors, such as geometric dilution of precision, upper atmosphere error, satellite quantity epoch etc..If can be comprehensive Factors above and the location credibility of each result can be obtained by quantitative analysis, it will help improve the precision of positioning result L '.

Owing to needs consider many factors, introduce analytic hierarchy process (AHP) (Analytic Hierarchy the most herein Process, AHP) obtain the location credibility of L, it is designated as Y={Y₁,Y₂,···,Y_n,···,Y_N}。

Analytic hierarchy process (AHP) be the U.S. plan strategies for scholar Saaty teach in early 1970s propose a kind of systematic analysis side Method, can carry out quantitative analysis, particularly in target factor structure complexity and the situation of the data lacking necessity to non-quantitation event Under, when needing the micro-judgment quantification by policymaker, this method is very useful.The method is widely used in administrative evaluation, economy is sent out Exhibition compare be widely used in administrative evaluation, economic contrast, MRP analysis, Accident Causes Analysis, human quality evaluation and The aspects such as security and economy analysis.

Analytic hierarchy process (AHP) includes building overall merit hierarchical model, structure pairwise comparison matrix, weight vector calculating with consistent Property inspection and data obscure normalization four part, its step is as shown in Figure 5.

Step 3.1, structure overall merit hierarchical model；

According to above-mentioned analysis, using N number of positioning result L as the solution layer of overall merit hierarchical model, will be to positioning result L Produce geometric dilution of precision, upper atmosphere error and the satellite quantity epoch criterion as overall merit hierarchical model of impact Layer；Using location credibility as the destination layer of overall merit hierarchical model, build overall merit hierarchical model as shown in Figure 6.

Wherein, the big element content of rule layer three is as follows:

(1) geometric dilution of precision GDOP

It reflects the space geometry relation between monitoring station and satellite.GDOP value and monitoring station are to satellite activity's vector end The polyhedron volume that point is formed is inversely proportional to, and the GDOP value of the combinations of satellites that polyhedron volume is the biggest is the least.In observation error one Regularly, GDOP value is the least, and positioning precision is the highest.

(2) upper atmosphere error delta τ

It reflects the impact on positioning result of overhead, the monitoring station Atmosphere changes.Upper atmosphere error is the least, positioning result Precision is the highest；Otherwise, positioning result precision is the lowest.

(3) satellite quantity N epoch

The most sufficient precision directly determining positioning result of satellite quantity epoch.For static relative positioning, satellite is gone through Unit's quantity is the biggest, and positioning result precision is the highest；Otherwise, positioning result precision is the lowest.

Above-mentioned three big elements all can be obtained by satellite signal receiver.

Step 3.2, structure pairwise comparison matrix；

Using geometric dilution of precision, upper atmosphere error and satellite quantity epoch as three elements of rule layer；According to standard Then three elements of layer carry out multilevel iudge two-by-two by specialists meeting, construct three rank pairwise comparison matrix A= (a_ij)_3×3, a_ijRepresent that i-th element is relative to the jth element ratio to the importance of destination layer；i,j∈{1,2,3}；Three row Geometric dilution of precision GDOP, upper atmosphere error delta τ and satellite quantity N epoch is represented respectively with three row；

Wherein, a_ijValue refer to the proposal of Saaty, by 1～9 assignment, concrete scale is as follows:

a_ij=1, represent element i no less important compared with element j；

a_ij=3, represent that element i is the most important compared with element j；

a_ij=5, represent that element i is the most important compared with element j；

a_ij=7, represent that element i is the most important compared with element j；

a_ij=9, represent that element i is extremely important compared with element j；

a_ij=2l, l=1,2,3,4 represent element i compared with element j importance between a_ij=2l-1 and a_ij=2l+1 it Between.

And if only if a_ij=l.

Example:

A in upper example₁₂=2 represent geometric dilution of precision GDOP and the upper atmosphere error delta τ ratio to the importance of destination layer Be 2, i.e. the former with the latter compare importance between no less important and the most important between；

a₁₃=6 represent that geometric dilution of precision GDOP are 6 with satellite quantity N epoch to the ratio of the importance of destination layer, i.e. before Person compared with the latter importance between the most important and the most important；

a₂₃=3 represent that upper atmosphere error delta τ are 3 with satellite quantity N epoch to the ratio of the importance of destination layer, i.e. the former Compared with the latter the most important.

Step 3.3, calculating weight vector；

Three element comparative result two-by-two of step 3.2 pass criteria layer have obtained pairwise comparison matrix Α, the most also need into One step calculates geometric dilution of precision GDOP, upper atmosphere error delta τ, tri-elements of satellite quantity N epoch to certain sub-time The weight vectors of the location credibility of the positioning result of section, i.e. the weight vector of calculation criterion layer.

A ω=λ ω is utilized to obtain all eigenvalue λ and characteristic vector ω of three rank pairwise comparison matrix A；By all features Eigenvalue of maximum λ in value λ_maxCorresponding characteristic vector ω^*It is normalized, obtains weight vector

In upper example, three eigenvalues of pairwise comparison matrix A are respectively 0,0,3, eigenvalue of maximum λ_max=3, by Big eigenvalue characteristic of correspondence vector normalized obtains weight vectorIt represents several What dilution of precision GDOP, upper atmosphere error delta τ, tri-elements of satellite quantity N epoch positioning result to certain sub-time period The weight of location credibility be respectively 0.6,0.3,0.1.

Step 3.4, consistency check；

Known consistency matrix eigenvalue of maximum characteristic of correspondence vector necessarily obtains weight vector after normalization, the most right In step 3.2, the pairwise comparison matrix A of structure to test, inspection A and the difference degree of consistency matrix, so that it is determined that step In rapid 3.3, pairwise comparison matrix A calculatesCan be as final weight vector.Concrete checkout procedure is as follows:

Judge a in three rank pairwise comparison matrix A_ijWhether meet formula (1), if meeting, then it represents that pairwise comparison matrix A is just It is consistency matrix, the most above-mentioned ω₁,ω₂,ω₃It is exactly the weight of each element, and performs step 3.5；Otherwise, concordance need to be carried out Inspection, inspection A and the similarity degree of consistency matrix, if upchecking, then can be by ω₁,ω₂,ω₃Approximation is as each element Weight, continues executing with step 3.5, otherwise, reconfigures the most relatively matrix；

a_ika_kj=a_ij (1)

In formula (1), a_ikRepresent that i-th element is relative to the kth element relative weighting to destination layer；k∈{1,2,3}；

Above-mentioned testing sequence is as follows:

1st step calculating coincident indicator CI (Consistency Index):Wherein M is expressed as contrast Relatively matrix exponent number, this method takes M=3.

2nd step is tabled look-up and is determined Aver-age Random Consistency Index RI (Random Index). according to the rank of pairwise comparison matrix Number, tabling look-up 1 obtains Aver-age Random Consistency Index.

Table 1 Aver-age Random Consistency Index

M	1	2	3	4	5	6
							RI	0	0	0.58	0.90	1.12	1.24

3rd step calculating consistency ration CR (Consistency Ratio):

4th step concordance judges.As CR ＜ 0.1, it is believed that the concordance of pairwise comparison matrix is in tolerance interval；No Then, it is believed that not by consistency check, need the ratio being sequentially adjusted in remaining to be discussed in pairwise comparison matrix so that it is CR can connect In the range of being subject to.

A in upper example, in pairwise comparison matrix A_ijMeet formula (1), then A is consistency matrix, can be by 0.6,0.3,0.1 point Not as final geometric dilution of precision GDOP, upper atmosphere error delta τ, tri-elements of satellite quantity N epoch to certain sub-time period The weight of location credibility of positioning result.Now, if A is carried out consistency check, its CR=0.

Step 3.5, data obscure normalization；

The unit dimension of each element is different, and its value also has bigger difference, it is therefore desirable to carry out the normalization of data.

Step 3.5.1, the geometric dilution of precision of the obtained by satellite signal receiver n-th sub-time period tried to achieve Meansigma methods, satellite quantity epoch that meansigma methods, upper atmosphere error are tried to achieve are designated as GDOP respectively_n、Δτ_n、N_n；

The optimum of geometric dilution of precision, the optimum of upper atmosphere error, satellite quantity epoch optimum are remembered respectively For GDOP^*、Δτ^*、N^*, and by lot of experiments, make GDOP respectively^*=3, Δ τ^*=1.5, N^*=7200 (when sub-period is Two hours, when the frequency of receiver output data is 1Hz)；

Step 3.5.2, utilizing formula (2), formula (3) and formula (4) to be respectively aligned to, three elements of layer carry out fuzzy normalization Process, obtain the normalized value GDOP of geometric dilution of precision_n', the normalized value Δ τ of upper atmosphere error_n', satellite quantity epoch Normalized value N_n':

$N_n^{\′}=\frac{N_n}{N^{*}}---\left(4\right)$

Step 3.6, utilize formula (5) calculate the n-th sub-time period positioning result L_nLocation credibility Y_n, thus obtain N Location credibility Y of the positioning result L of individual sub-time period.

$Y_n=\[{\mathrm{GDOP}}_n^{\′},{\mathrm{\Δ\τ}}_n^{\′},N_n^{\′}\]\·\stackrel{\‾}{\mathrm{\ω}}---\left(5\right)$

Assume the normalized value GDOP of geometric dilution of precision in step 3.5_n', the normalized value Δ τ of upper atmosphere error_n′、 The normalized value N of satellite quantity epoch_n' it is respectively 0.8,0.7,0.6, with upper example obtain weight vectorCalculated by formula (5), obtain the positioning result L of the n-th sub-time period_nDetermine Position credibility Y_n=0.75.

Step 4, utilize formula (6) that N number of positioning result of rover station is weighted Filtering Processing, it is thus achieved that final positioning result L^*；

$L^{*}=\frac{Y_1}{\underset{i=1}{\overset{N}{\Σ}}{Y}_i}{L}_1+\frac{Y_2}{\underset{i=1}{\overset{N}{\Σ}}{Y}_i}{L}_2+\mathrm{...}+\frac{Y_n}{\underset{i=1}{\overset{N}{\Σ}}{Y}_i}{L}_n+\mathrm{...}+\frac{Y_N}{\underset{i=1}{\overset{N}{\Σ}}{Y}_i}{L}_N---\left(6\right)$

In formula (6), Y_iRepresent the positioning result L of rover station i-th sub-time period_iLocation credibility, 1≤i≤N.

Experimental result:

Use this patent method and traditional static relative positioning method simultaneously, carry out the positioning result monitoring of 15 days, high Journey result of variations is as shown in Figure 7.

During the monitoring of the 11st day, occur in that by the fine unsettled turning thunder shower in monitoring period of time, as Fig. 7 can Seeing, the monitoring result of traditional static relative positioning method creates bigger fluctuation, and error is obvious, and this patent method is the most effective Inhibit the adverse effect that positioning result precision brought by Changes in weather.From experimental result, this patent method and tradition It is more stable that static relative positioning method compares positioning result, and precision is higher.

Claims (2)

1. a Big Dipper high-precision locating method based on analytic hierarchy process (AHP), be applied to by Beidou navigation satellite, base station and In the monitoring of environmental of rover station composition；Described base station receives satellite Data Concurrent epoch of described Beidou navigation satellite transmission and send To rover station；Described rover station receives satellite data epoch and the base of described base station transmission that described Beidou navigation satellite sends Quasi-station satellite data epoch also carry out difference processing, it is thus achieved that Differential positioning data, are designated as X；It is characterized in that, described Big Dipper high accuracy Localization method is carried out as follows:

Step 1, Differential positioning data X to described rover station were split according to the time period, it is thus achieved that the difference of N number of sub-time period Location data, are designated as X={X₁,X₂,…,X_n,…,X_N}；X_nRepresent the n-th sub-time period in Differential positioning data X of rover station Differential positioning data；1≤n≤N；

Step 2, Differential positioning data X to described N number of sub-time period are respectively adopted static relative positioning algorithm and calculate, and obtain Obtain N number of positioning result, be designated as L={L₁,L₂,…,L_n,…,L_N}；L_nRepresent the Differential positioning number of rover station n-th sub-time period According to X_nPositioning result；

Step 3, utilize analytic hierarchy process (AHP) obtain N number of sub-time period location credibility Y；

Step 3.1, structure overall merit hierarchical model；

Using described N number of positioning result L as the solution layer of described overall merit hierarchical model, positioning result L will be produced impact Geometric dilution of precision, upper atmosphere error and satellite quantity epoch as the rule layer of described overall merit hierarchical model；Will The location credibility of described N number of sub-time period is as the destination layer of described overall merit hierarchical model；

Step 3.2, structure pairwise comparison matrix；

Using described geometric dilution of precision, upper atmosphere error and satellite quantity epoch as three elements of described rule layer；Root According to the comparative result two-by-two of three elements of described rule layer, construct three rank pairwise comparison matrix A=(a_ij)_3×3；a_ijTable Show that i-th element is relative to the jth element ratio to the importance of described destination layer；i,j∈{1,2,3}；

Step 3.3, calculating weight vector；

A ω=λ ω is utilized to obtain all eigenvalue λ and characteristic vector ω of described three rank pairwise comparison matrix A；By all features Eigenvalue of maximum λ in value λ_maxCorresponding characteristic vector ω^*It is normalized, obtains weight vector

Step 3.4, consistency check；

Judge a in described three rank pairwise comparison matrix A_ijWhether meet formula (1), if meeting, then it represents that pairwise comparison matrix is Consistency matrix, and perform step 3.5；Otherwise, carrying out consistency check, if upchecking, performing step 3.5, otherwise, again Structure is to comparator matrix；

a_ika_kj=a_ij (1)

In formula (1), a_ikRepresent that i-th element is relative to the kth element relative weighting to described destination layer；k∈{1,2,3}；

Step 3.5, data obscure normalization；

Step 3.5.1, the geometric dilution of precision of the obtained by satellite signal receiver n-th sub-time period is tried to achieve average Meansigma methods, satellite quantity epoch that value, upper atmosphere error are tried to achieve are designated as GDOP respectively_n、Δτ_n、N_n；

Step 3.5.2, formula (2), formula (3) and formula (4) three elements respectively to described rule layer are utilized to carry out fuzzy normalization Process, obtain the normalized value GDOP ' of geometric dilution of precision_n, the normalized value Δ τ ' of upper atmosphere error_n, satellite quantity epoch The normalized value N ' of optimum_n:

$N_n^{\′}=\frac{N_n}{N^{*}}---\left(4\right)$

In formula (2), formula (3) and formula (4), GDOP^*、Δτ^*、N^*Represent that the optimum of described geometric dilution of precision, high-altitude are big respectively The optimum of gas error, the optimum of satellite quantity epoch；

Step 3.6, utilize formula (5) calculate the n-th sub-time period positioning result L_nLocation credibility Y_n, thus obtain N number of son The location credibility of time period, is designated as Y={Y₁,Y₂,···,Y_n,···,Y_N}；

$Y_n=\[{\mathrm{GDOP}}_n^{\′},{\mathrm{\Δ\τ}}_n^{\′},N_n^{\′}\]\·\stackrel{\‾}{\mathrm{\ω}}---\left(5\right)$

Step 4, utilize formula (6) that N number of positioning result of rover station is weighted Filtering Processing, it is thus achieved that final positioning result L^*；

$L^{*}=\frac{Y_1}{\underset{i=1}{\overset{N}{\Σ}}{Y}_i}{L}_1+\frac{Y_2}{\underset{i=1}{\overset{N}{\Σ}}{Y}_i}{L}_2+...+\frac{Y_n}{\underset{i=1}{\overset{N}{\Σ}}{Y}_i}{L}_n+...+\frac{Y_N}{\underset{i=1}{\overset{N}{\Σ}}{Y}_i}{L}_N---\left(6\right)$

In formula (6), Y_iRepresent the positioning result L of rover station i-th sub-time period_iLocation credibility, 1≤i≤N.

Big Dipper high-precision locating method based on analytic hierarchy process (AHP) the most according to claim 1, is characterized in that, described step Consistency check process in 3.4 is as follows:

Step 3.4.1, utilize formula (7) calculate coincident indicator CI:

$CI=\frac{{\mathrm{\λ}}_{max}-M}{M-1}---\left(7\right)$

In formula (7), M represents the element number of described rule layer；

Step 3.4.2, utilize formula (8) calculate consistency ration CR:

$CR=\frac{CI}{RI}---\left(8\right)$

In formula (8), RI represents Aver-age Random Consistency Index, and by acquisition of tabling look-up；

Step 3.4.3, concordance judge:

As CR ＜ 0.1, represent that the concordance of described three rank pairwise comparison matrix A is in tolerance interval；Otherwise it is assumed that it is described Three rank pairwise comparison matrix A pass through consistency check.