CN109597105A - A kind of GPS/GLONASS tight integration localization method for taking deviation between carrier system into account - Google Patents
A kind of GPS/GLONASS tight integration localization method for taking deviation between carrier system into account Download PDFInfo
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- 230000010354 integration Effects 0.000 title claims description 35
- 230000004807 localization Effects 0.000 title claims description 19
- 230000008569 process Effects 0.000 claims abstract description 14
- 238000005295 random walk Methods 0.000 claims abstract description 14
- 238000001914 filtration Methods 0.000 claims description 22
- 239000011159 matrix material Substances 0.000 claims description 16
- 238000001228 spectrum Methods 0.000 claims description 8
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- -1 GLONASS system Chemical compound 0.000 claims description 3
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/421—Determining position by combining or switching between position solutions or signals derived from different satellite radio beacon positioning systems; by combining or switching between position solutions or signals derived from different modes of operation in a single system
- G01S19/425—Determining position by combining or switching between position solutions or signals derived from different satellite radio beacon positioning systems; by combining or switching between position solutions or signals derived from different modes of operation in a single system by combining or switching between signals derived from different satellite radio beacon positioning systems
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/43—Determining position using carrier phase measurements, e.g. kinematic positioning; using long or short baseline interferometry
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/43—Determining position using carrier phase measurements, e.g. kinematic positioning; using long or short baseline interferometry
- G01S19/44—Carrier phase ambiguity resolution; Floating ambiguity; LAMBDA [Least-squares AMBiguity Decorrelation Adjustment] method
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- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
Abstract
本发明公开了一种顾及载波系统间偏差的GPS/GLONASS紧组合定位方法。首先，将GPS和GLONASS系统内的接收机钟差、硬件延迟和单差模糊度三类参数重参化，构建站间单差整周模糊度可解模型；在此基础上，以GPS为基准系统，构建了载波系统间偏差可估模型，并对其时变特性进行统计分析；基于这一特性，采用谱密度较小的随机游走过程对系统间偏差进行时域建模，建立了GPS和GLONASS紧组合定位模型。定位结果表明，采用系统间紧组合模型可以显著提高定位精度，尤其对于可见卫星数少的遮挡环境提升显著。
The invention discloses a GPS/GLONASS tight combination positioning method which takes into account the deviation between carrier systems. First, the three parameters of receiver clock error, hardware delay and single-difference ambiguity in GPS and GLONASS systems are re-parameterized to build a solvable model of single-difference integer ambiguity between stations; on this basis, GPS is used as the benchmark. Based on this characteristic, a random walk process with small spectral density is used to model the inter-system deviation in time domain, and a GPS is established. Tightly combined positioning model with GLONASS. The positioning results show that the use of the compact combination model between systems can significantly improve the positioning accuracy, especially for the occlusion environment with a small number of visible satellites.
Description
Technical field
The present invention relates to a kind of multisystem fusion navigator fix technology more particularly to a kind of take deviation between carrier system into account
GPS/GLONASS tight integration localization method, belong to GNSS (Global Navigation Satellite System) positioning with
Field of navigation technology.
Background technique
With the modernization of existing GNSS (Global Navigation Satellite System), more satellites can be used for being accurately positioned.Satellite
Between system be applied in combination can it is significant improve GNSS positioning accuracy and reliability, especially in the environment by serious shielding
Under.Real-time kinematical RTK positioning for Centimeter Level, mainly uses two kinds of models: one is the respective reference stars of each Systematic selection
Pine combination model, i.e. difference model in system；Another kind is the tight integration model of different Systematic selection collective reference stars, i.e. system
Between difference model.If deviation between differential system can be handled correctly, difference model is conducive to increase a large amount of redundancy between system
Observation information, therefore facilitate in the case where satellite-signal is easy the serious observing environment being blocked to be positioned.
In recent years, had been extensively studied CDMA (CDMA) system, for example, GPS, BDS, Galileo and QZSS it
Between tight integration model.But for generalling use pine combination model in system using the GLONASS of FDMA (frequency division multiple access), this is not
Conducive to the advantage for preferably playing more GNSS fusion positioning.
Summary of the invention
The technical problems to be solved by the present invention are:
In order to play the advantage of more GNSS fusion positioning, a kind of GPS/GLONASS for taking deviation between carrier system into account is provided
Tight integration localization method.
The present invention uses following technical scheme to solve above-mentioned technical problem:
The present invention proposes a kind of GPS/GLONASS tight integration localization method for taking deviation between carrier system into account, including following
Step:
Step 1, the receiver clock-offsets by GPS and GLONASS system, hardware delay and single poor fuzziness three classes parameter weight
Ginsengization, single poor integer ambiguity can solve model between building station；
Step 2, using GPS as benchmark system, deviation can estimate model between constructing carrier system, and between the carrier system partially
The time-varying characteristics of poor parameter are for statistical analysis；
Step 3 is based on model and analysis described in step 2 as a result, using random walk process, when carrying out between deviation system
Domain modeling, obtains GPS and GLONASS tight integration model, and carry out more epoch consecutive trackings.
A kind of foregoing GPS/GLONASS tight integration localization method for taking deviation between carrier system into account, further:
In the step 1, receiver clock-offsets, hardware delay and the single poor fuzziness three classes parameter in GPS and GLONASS system are joined again
Change, between building station single poor integer ambiguity can solve model the following steps are included:
Single poor observation model between station in step 1.1, building GPS and GLONASS system:
Assuming that observing m GPS satellite and n GLONASS satellite altogether, for short baseline, ignore the influence of atmosphere delay
Afterwards, single poor observation model indicates between standing are as follows:
Formula (1) and formula (2) are single poor carrier observations equation and pseudorange observation equation between the station GPS respectively, formula (3) and formula (4)
It is single poor carrier observations equation and pseudorange observation equation between GLONASS stands respectively.In formula,List is poor between indicating GPS satellite station
Carrier observations, unit are rice, wherein subscript s=1G, 2G..., mGIndicate GPS satellite number, subscript j indicates Frequency point；
Single poor station star is away from Δ dT indicates single poor reception machine clock deviation between station, λ between indicating GPS satellite stationJ, GIndicate the wave of GPS satellite signal
It is long, Δ δJ, GSingle poor carrier wave hardware delay between expression GPS satellite receiver end station,Single differential mode is pasted between indicating GPS satellite station
Degree,Single poor carrier wave measures noise between indicating GPS satellite station,Single poor Pseudo-range Observations between the station of expression GPS satellite,
ΔdJ, GSingle poor pseudorange hardware delay between expression GPS satellite receiver end station,Single poor pseudo range measurement between expression GPS satellite station
Noise；Single poor carrier observations between expression GLONASS satellite station, unit is rice, wherein subscript q=1R, 2R..., nRIt indicates
GLONASS satellite number, subscript j indicate Frequency point；Indicate between GLONASS satellite station single poor station star away from,It indicates
GLONASS satellite wavelength, Δ δJ, RSingle poor carrier wave hardware delay between expression GLONASS satellite receiver end station,It indicates
Single poor fuzziness between GLONASS satellite station,Single poor carrier wave measures noise between indicating GLONASS satellite station,It indicates
Single poor Pseudo-range Observations, Δ d between GLONASS satellite stationJ, RSingle poor pseudorange hardware prolongs between indicating GLONASS satellite receiver end station
Late,Code deviation between frequency between expression GLONASS satellite station,Single poor pseudo range measurement is made an uproar between indicating GLONASS satellite station
Sound；
Step 1.2, single poor observation model between being stood according to constructed by step 1.1, receiver clock-offsets, hardware delay and list is poor
Fuzziness three classes parameter ginsengization and carries out parameter decorrelation again, and it is as follows can to solve model for single poor integer ambiguity between can must standing:
Δ dT, Δ δ for GPS, between standing in single poor observation modelJ, G,With correlation, by its heavy ginsengization
Parameter decorrelation is carried out, it is as follows to obtain full rank observational equation:
Wherein:
The full rank observational equation obtained after single poor heavy ginsengization between station in formula (5) and formula (6) i.e. GPS system, in formula,
Single poor fuzziness between the station of expression GPS system reference star,Indicate the double difference fuzziness of GPS system；
And for GLONASS, since every satellite in FDMA system has different wavelength, there is frequency between different frequency
Between code deviation, therefore the observational equation of GLONASS ginseng again is as follows:
The observational equation obtained after single poor heavy ginsengization between station in formula (9) and formula (10) i.e. GLONASS system, in formula,Table
Show the wavelength of GLONASS reference star,Single poor fuzziness between the station of expression GLONASS system reference star；
Formula (9) is rewritten as following form:
From formula (11) as can be seen that since the integer ambiguity of reference star is unknown, therefore formula (11) is still a rank deficient equations；
Thus select second reference satellite, re-start parameterize observational equation is as follows:
Wherein:
It can thus be concluded that the observational equation of other satellites is as follows:
Wherein:
In formula (16), when | k1-k2| when=1,For integer.
It can thus be concluded that the full rank observational equation of GLONASS carrier phase is as follows:
A kind of foregoing GPS/GLONASS tight integration localization method for taking deviation between carrier system into account, further:
In the step 2, using GPS as benchmark system, deviation can estimate model between constructing carrier system, and unite to its time-varying characteristics
Meter analysis, specifically includes:
After step 2 obtains the carrier phase full rank observational equation in GPS and GLONASS system, on the basis of GPS system
System only estimates the receiver clock-offsets of GPS, enablesWithDifference between carrier system straggling parameter；Obtain carrier wave
It is as follows can to estimate model for deviation between system:
Wherein, straggling parameter between carrier system are as follows:
A kind of foregoing GPS/GLONASS tight integration localization method for taking deviation between carrier system into account, further:
The spectrum density of random walk process described in step 3 is 0.05 × 0.05cycle2/h。
A kind of foregoing GPS/GLONASS tight integration localization method for taking deviation between carrier system into account, further:
In the step 3, time domain modeling is carried out to deviation system using random walk process, it is fixed to obtain GPS and GLONASS tight integration
Position Filtering Model, comprising the following steps:
Step 3.1 carries out time domain modeling to deviation system using random walk process；
Step 3.2, building GPS and GLONASS tight integration position Filtering Model, carry out more epoch consecutive trackings.
A kind of foregoing GPS/GLONASS tight integration localization method for taking deviation between carrier system into account, further:
The step 3.1 specifically has:
For deviation delta δ between systemGR, time domain modeling is carried out using the lesser random walk model of spectrum density, formula is as follows:
In formula, k indicates epoch, and w indicates process noise,For the variance of w,The spectrum density 0.05 of expression w ×
0.05cycle2/h。
A kind of foregoing GPS/GLONASS tight integration localization method for taking deviation between carrier system into account, further:
The step of more epoch consecutive trackings described in step 3.2 includes:
Step 3.2.1, status predication
Utilize the initial value X of valuation or the filtering of previous momentk-1Obtain the predicted state vector X of later moment in timeK, k-1:
XK, k-1=ΦK, k-1Xk-1 (22)
Meanwhile predicted state vector X can be obtained according to law of propagation of errorsK, k-1Variance-covariance matrix QK, k-1:
Step 3.2.2, filtering gain is calculated
According to the observation model of the covariance information of prediction and current epoch, the gain matrix K of filtering is calculatedk:
Step 3.2.3, valuation updates
Utilize filtering gain matrix KkIn conjunction with the observation vector L at current timek, to Filtering Estimation XK, kIt is updated
XK, k=XK, k-1+Kk(Lk-AkXK, k-1) (25)
Simultaneously to variance-covariance matrix QK, kIt is updated
Qk.k=(I-KkAk)QK, k-1 (26)
Subsequent time repeats above three step, realizes the lasting resolving to positioning result, it is continuous to obtain more epoch
Positioning result.
The invention adopts the above technical scheme compared with prior art, has following technical effect that
(1) present invention carries out the positioning of carrier difference tight integration using GPS and GLONASS, overcomes in existing research and only exists
The shortcomings that positioning of carrier difference tight integration is able to carry out in cdma system；
(2) present invention can reduce parameter to be estimated, and be conducive to enhance observation model stability in the case where blocking environment, and it is fixed to improve
Position precision and reliability.
Detailed description of the invention
Fig. 1 is this method flow chart.
Fig. 2 is the zero base line and short baseline schematic diagram for analyzing deviation between GPS and GLONASS carrier system.
Fig. 3 is deviation time sequence chart between the GPS-GLONASS carrier system under different situations.
Fig. 4 is that GPS+GLONASS pine combination, GPS+GLONASS tight integration block under environment (8 satellites in view) in simulation
N, the 3 days deviations comparison diagrams in the direction E, U.
Specific embodiment
Technical solution of the present invention is described in further detail with reference to the accompanying drawing:
Those skilled in the art can understand that unless otherwise defined, all terms used herein (including skill
Art term and scientific term) there is meaning identical with the general understanding of those of ordinary skill in fields of the present invention.Also
It should be understood that those terms such as defined in the general dictionary should be understood that have in the context of the prior art
The consistent meaning of meaning will not be explained in an idealized or overly formal meaning and unless defined as here.
Fig. 1 show flow chart of the method for the present invention.As shown in Figure 1, the present invention provides one kind to take into account between carrier system
The GPS/GLONASS tight integration localization method of deviation, comprising the following steps:
Step 1, the receiver clock-offsets by GPS and GLONASS system, hardware delay and single poor fuzziness three classes parameter weight
Ginsengization, single poor integer ambiguity can solve model between building station；
Step 2, using GPS as benchmark system, deviation can estimate model between constructing carrier system, and between the carrier system partially
The time-varying characteristics of poor parameter are for statistical analysis；
Step 3 is based on model and analysis described in step 2 as a result, using random walk process, when carrying out between deviation system
Domain modeling, obtains GPS and GLONASS tight integration model, and carry out more epoch consecutive trackings.
In the step 1, by receiver clock-offsets, hardware delay and the single poor fuzziness three classes in GPS and GLONASS system
Parameter ginseng again, between building station single poor integer ambiguity can solve model the following steps are included:
Single poor observation model between station in step 2.1, building GPS and GLONASS system:
Assuming that observing m GPS satellite and n GLONASS satellite altogether, for short baseline, the shadow of atmosphere delay can be ignored
It rings, single poor observation model can indicate between standing are as follows:
Formula (1) and formula (2) are single poor carrier observations equation and pseudorange observation equation between the station GPS respectively, formula (3) and formula (4)
It is single poor carrier observations equation and pseudorange observation equation between GLONASS stands respectively.In formula,(subscript s=1G, 2G..., mGTable
Show that GPS satellite, subscript j indicate Frequency point) indicate single poor carrier observations (rice) between GPS satellite station,Indicate GPS satellite station
Between single poor station star away from Δ dT indicates list poor reception machine clock deviation between station, λJ, GIndicate the wavelength of GPS satellite signal, Δ δJ, GIndicate GPS
Single poor carrier wave hardware delay between satellite receiver end station,Single poor fuzziness between expression GPS satellite station,Indicate GPS
Single poor carrier wave measures noise between satellite station,Single poor Pseudo-range Observations, Δ d between the station of expression GPS satelliteJ, GIndicate GPS satellite
Single poor pseudorange hardware delay between receiver end station,Single poor pseudo range measurement noise between expression GPS satellite station；(subscript q
=1R, 2R..., nRIndicate that GLONASS satellite, subscript j indicate Frequency point) indicate single poor carrier observations between GLONASS satellite station
(rice),Indicate between GLONASS satellite station single poor station star away from,Indicate GLONASS satellite wavelength, Δ δJ, RIt indicates
Single poor carrier wave hardware delay between GLONASS satellite receiver end station,Single poor fuzziness between expression GLONASS satellite station,Single poor carrier wave measures noise between indicating GLONASS satellite station,Single poor pseudorange observation between expression GLONASS satellite station
Value, Δ dJ, RSingle poor pseudorange hardware delay between expression GLONASS satellite receiver end station,Frequency between expression GLONASS satellite station
Between code deviation,Single poor pseudo range measurement noise between expression GLONASS satellite station.
Step 2.2, single poor observation model between being stood according to constructed by step 2.1, receiver clock-offsets, hardware delay and list is poor
Fuzziness three classes parameter ginsengization and carries out parameter decorrelation again, and it is as follows can to solve model for single poor integer ambiguity between can must standing:
For GPS, due to the Δ dT, Δ δ in poor observation model single between stationJ, G,With correlation, thus need by
Its heavy ginsengization carries out parameter decorrelation, and it is as follows to obtain full rank observational equation:
Wherein:
The full rank observational equation obtained after single poor heavy ginsengization between station in formula (5) and formula (6) i.e. GPS system, in formula,
Single poor fuzziness between the station of expression GPS system reference star,Indicate the double difference fuzziness of GPS system.
And for GLONASS, since every satellite in FDMA system has different wavelength, there is frequency between different frequency
Between code deviation, therefore the observational equation of GLONASS ginseng again is as follows:
The observational equation obtained after single poor heavy ginsengization between station in formula (9) and formula (10) i.e. GLONASS system, in formula,Table
Show the wavelength of GLONASS reference star,Single poor fuzziness between the station of expression GLONASS system reference star.
Formula (9) is rewritten as following form:
From formula (11) as can be seen that since the integer ambiguity of reference star is unknown, therefore formula (11) is still a rank deficient equations.
Second reference satellite is selected thus, and re-starting parametrization, can to obtain observational equation as follows:
Wherein:
It can thus be concluded that the observational equation of other satellites is as follows:
Wherein:
In formula (16), when | k1-k2| when=1,For integer.
It can thus be concluded that the full rank observational equation of GLONASS carrier phase is as follows:
In the step 2, using GPS as benchmark system, deviation can estimate model between constructing carrier system, and to its time-varying spy
Property is statisticallyd analyze, comprising the following steps:
After step 2 obtains the carrier phase full rank observational equation in GPS and GLONASS system, on the basis of GPS system
System only estimates the receiver clock-offsets of GPS, thenWithDifference can form a new parameter, as carry
Straggling parameter between wave system system, therefore deviation between carrier system can be obtained can to estimate model as follows:
Wherein:
In the step 3, time domain modeling is carried out to deviation system using random walk process, constructs GPS and GLONASS
Tight integration positions Filtering Model, specifically:
For deviation delta δ between the system that can estimateGR, time domain modeling is carried out using the lesser random walk model of spectrum density, with
It is that may be present slowly varying to absorb its, formula is as follows:
In formula, k indicates epoch, and w indicates process noise,For the variance of w,The spectrum density for indicating w, according to practical feelings
0.05 × 0.05cycle can be used in condition2/h。
As shown in Fig. 2, straggling parameter is stable at any time between carrier system, it can be steady using it in more epoch consecutive trackings
It is qualitative to obtain more redundancy observations.More epoch consecutive trackings the following steps are included:
Based on the time domain modeling model of deviation between system, the positioning of GPS and GLONASS tight integration is established using Kalman filter
State equation and observational equation shown in Filtering Model, i.e. formula (20) and formula (21):
Xk=ΦK, k-1Xk-1+wk (20)
Lk=AkXk+vk
In formula, XkAnd Xk-1Respectively indicate tkAnd tk-1The state vector at moment；ΦK, k-1Indicate tk-1Moment is to tkWhen etching system
The state-transition matrix of state；wkExpression system dynamic noise vector；LkIndicate tkThe observation vector at moment；AkFor observational equation
Coefficient matrix；vkFor observation noise vector.In GNSS data processing, system noise w is commonly assumed thatkWith observation noise vkMutually
It is uncorrelated, and the characteristic with zero-mean and white Gaussian noise, i.e.,
In formula, QwkAnd RkThe respectively variance matrix of the variance matrix of system noise and measurement noise.
It mainly includes updating the time to update two parts with observation that Kalman filtering, which carries out parameter Estimation, specific to calculate
Step are as follows:
(1) status predication
Utilize the initial value X of valuation or the filtering of previous momentk-1Obtain the predicted state vector X of later moment in timeK, k-1:
XK, k-1=ΦK, k-1Xk-1 (22)
Meanwhile predicted state vector X can be obtained according to law of propagation of errorsK, k-1Variance-covariance matrix QK, k-1:
(2) filtering gain is calculated
According to the observation model of the covariance information of prediction and current epoch, the gain matrix K of filtering is calculatedk:
(3) valuation updates
Utilize filtering gain matrix KkIn conjunction with the observation vector L at current timek, to Filtering Estimation XK, kIt is updated
XK, k=XK, k-1+Kk(Lk-AkXK, k-1) (25)
Variance-covariance matrix is updated simultaneously
Qk.k=(I-KkAk)QK, k-1 (26)
In subsequent time, above three step is repeated, to realize the lasting resolving to positioning result, obtains go through more
First consecutive tracking result.
Table 1
Table 1 is zero base line used and short baseline information.Using Australian Curtin University's polyphyly as shown in Figure 2 and Table 1
System GNSS zero base line and short baseline carry out experimental analysis, can be calculated between GPS-GLONASS carrier system according to above-mentioned steps 2
Deviation single epoch valuation sequence, fig. 3, it is shown that ignoring the influence of observation noise, no matter for identical receiver class
Type or different receivers type, between carrier system deviation change over time all be it is relatively stable, compared to equal within the scope of three days
Within 0.1 week, standard deviation is better than 0.01 week the amplitude of value.Fig. 4 gives when satellites in view quantity is 8, using normal
Advise positioning result comparison when pine combination model and tight integration model of the present invention, it can be seen that can significantly mention using tight integration model
High position precision is respectively increased 13.5%, 15.0% and 46.2% on tri- directions N, E, U.
The above is only some embodiments of the invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered
It is considered as protection scope of the present invention.
Claims (7)
1. a kind of GPS/GLONASS tight integration localization method for taking deviation between carrier system into account, which is characterized in that including following step
It is rapid:
Step 1, the receiver clock-offsets by GPS and GLONASS system, hardware delay and single poor fuzziness three classes parameter are joined again
Change, single poor integer ambiguity can solve model between building station；
Step 2, using GPS as benchmark system, deviation can estimate model between constructing carrier system, and join between deviation the carrier system
Several time-varying characteristics are for statistical analysis；
Step 3 is based on model and analysis described in step 2 as a result, using random walk process, carries out time domain to deviation system and builds
Mould obtains GPS and GLONASS tight integration model, and carries out more epoch consecutive trackings.
2. a kind of GPS/GLONASS tight integration localization method for taking deviation between carrier system into account according to claim 1, special
Sign is: in the step 1, by receiver clock-offsets, hardware delay and the single poor fuzziness three classes in GPS and GLONASS system
Parameter ginseng again, between building station single poor integer ambiguity can solve model the following steps are included:
Single poor observation model between station in step 1.1, building GPS and GLONASS system:
Assuming that observing m GPS satellite and n GLONASS satellite altogether, stand after the influence for ignoring atmosphere delay for short baseline
Between single poor observation model indicate are as follows:
Formula (1) and formula (2) are single poor carrier observations equation and pseudorange observation equation between the station GPS respectively, and formula (3) and formula (4) are respectively
It is single poor carrier observations equation and pseudorange observation equation between GLONASS stands.In formula,Single poor carrier wave between expression GPS satellite station
Observation, unit are rice, wherein subscript s=1G,2G,…,mGIndicate GPS satellite number, subscript j indicates Frequency point；It indicates
Single poor station star is away from Δ dT indicates single poor reception machine clock deviation between station, λ between GPS satellite stationj,GIndicate the wavelength of GPS satellite signal, Δ
δj,GSingle poor carrier wave hardware delay between expression GPS satellite receiver end station,Single poor fuzziness between expression GPS satellite station,Single poor carrier wave measures noise between indicating GPS satellite station,Single poor Pseudo-range Observations, Δ between the station of expression GPS satellite
dj,GSingle poor pseudorange hardware delay between expression GPS satellite receiver end station,Single poor pseudo range measurement is made an uproar between indicating GPS satellite station
Sound；Single poor carrier observations between expression GLONASS satellite station, unit is rice, wherein subscript q=1R,2R,…,nRIt indicates
GLONASS satellite number, subscript j indicate Frequency point；Indicate between GLONASS satellite station single poor station star away from,It indicates
GLONASS satellite wavelength, Δ δj,RSingle poor carrier wave hardware delay between expression GLONASS satellite receiver end station,It indicates
Single poor fuzziness between GLONASS satellite station,Single poor carrier wave measures noise between indicating GLONASS satellite station,It indicates
Single poor Pseudo-range Observations, Δ d between GLONASS satellite stationj,RSingle poor pseudorange hardware prolongs between indicating GLONASS satellite receiver end station
Late,Code deviation between frequency between expression GLONASS satellite station,Single poor pseudo range measurement noise between expression GLONASS satellite station；
Step 1.2, single poor observation model between being stood according to constructed by step 1.1, by receiver clock-offsets, hardware delay and single differential mode paste
Degree three classes parameter ginsengization and carries out parameter decorrelation again, and singly can to solve model as follows for poor integer ambiguity between can must standing:
Δ dT, Δ δ for GPS, between standing in single poor observation modelj,G,With correlation, its heavy ginsengization is joined
Number decorrelation, it is as follows to obtain full rank observational equation:
Wherein:
The full rank observational equation obtained after single poor heavy ginsengization between station in formula (5) and formula (6) i.e. GPS system, in formula,It indicates
Single poor fuzziness between the station of GPS system reference star,Indicate the double difference fuzziness of GPS system；
And for GLONASS, since every satellite in FDMA system has a different wavelength, there are codes between frequency between different frequency
Deviation, therefore the observational equation of GLONASS ginseng again is as follows:
The observational equation obtained after single poor heavy ginsengization between station in formula (9) and formula (10) i.e. GLONASS system, in formula,It indicates
The wavelength of GLONASS reference star,Single poor fuzziness between the station of expression GLONASS system reference star；
Formula (9) is rewritten as following form:
From formula (11) as can be seen that since the integer ambiguity of reference star is unknown, therefore formula (11) is still a rank deficient equations；Thus
Select second reference satellite, re-start parameterize observational equation is as follows:
Wherein:
It can thus be concluded that the observational equation of other satellites is as follows:
Wherein:
In formula (16), when | k1-k2| when=1,For integer.
It can thus be concluded that the full rank observational equation of GLONASS carrier phase is as follows:
3. a kind of GPS/GLONASS tight integration localization method for taking deviation between carrier system into account according to claim 1, special
Sign is: in the step 2, using GPS as benchmark system, deviation can estimate model between constructing carrier system, and to its time-varying spy
Property is for statistical analysis, specifically includes:
After step 2 obtains the carrier phase full rank observational equation in GPS and GLONASS system, it is on the basis of GPS system
System only estimates the receiver clock-offsets of GPS, enablesWithDifference between carrier system straggling parameter；Obtain carrier wave system
It is as follows can to estimate model for deviation between system:
Wherein, straggling parameter between carrier system are as follows:
4. a kind of GPS/GLONASS tight integration localization method for taking deviation between carrier system into account according to claim 1, special
Sign is: the spectrum density of random walk process described in step 3 is 0.05 × 0.05cycle2/h。
5. a kind of GPS/GLONASS tight integration localization method for taking deviation between carrier system into account according to claim 1, special
Sign is: in the step 3, carrying out time domain modeling to deviation system using random walk process, obtains GPS and GLONASS
Tight integration positions Filtering Model, comprising the following steps:
Step 3.1 carries out time domain modeling to deviation system using random walk process；
Step 3.2, building GPS and GLONASS tight integration position Filtering Model, carry out more epoch consecutive trackings.
6. a kind of GPS/GLONASS tight integration localization method for taking deviation between carrier system into account according to claim 5, special
Sign is: the step 3.1 specifically has:
For deviation delta δ between systemGR, time domain modeling is carried out using the lesser random walk model of spectrum density, formula is as follows:
In formula, k indicates epoch, and w indicates process noise,For the variance of w,Indicate 0.05 × 0.05cycle of spectrum density of w2/
h。
7. a kind of GPS/GLONASS tight integration localization method for taking deviation between carrier system into account according to claim 5, special
Sign is: the step of more epoch consecutive trackings described in step 3.2 includes:
Step 3.2.1, status predication
Utilize the initial value X of valuation or the filtering of previous momentk-1,k-1Obtain the predicted state vector X of later moment in timek,k-1:
Xk,k-1=Φk,k-1XK-1, k-1 (22)
Meanwhile predicted state vector X can be obtained according to law of propagation of errorsk,k-1Variance-covariance matrix QK, k-1:
Step 3.2.2, filtering gain is calculated
According to the observation model of the covariance information of prediction and current epoch, the gain matrix K of filtering is calculatedk:
Step 3.2.3, valuation updates
Utilize filtering gain matrix KkIn conjunction with the observation vector L at current timek, to Filtering Estimation XK, kIt is updated
Xk,k=Xk,k-1+Kk(Lk-AkXk,k-1) (25)
Simultaneously to variance-covariance matrix Qk,kIt is updated
Qk.k=(I-KkAk)Qk,k-1 (26)
Subsequent time repeats above three step, realizes the lasting resolving to positioning result, obtains more epoch consecutive trackings
As a result.
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