CN104516006B - Carrier phase smoothing pseudorange algorithm based on improved Kalman filtering - Google Patents

Carrier phase smoothing pseudorange algorithm based on improved Kalman filtering Download PDF

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CN104516006B
CN104516006B CN201410625635.0A CN201410625635A CN104516006B CN 104516006 B CN104516006 B CN 104516006B CN 201410625635 A CN201410625635 A CN 201410625635A CN 104516006 B CN104516006 B CN 104516006B
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pseudorange
carrier phase
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CN104516006A (en
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张帆
彭伟
张晨星
王哲
韩钊
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CETC 20 Research Institute
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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
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/35—Constructional details or hardware or software details of the signal processing chain
    • G01S19/37—Hardware or software details of the signal processing chain
    • 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

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Signal Processing (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

The invention provides a carrier phase smoothing pseudorange algorithm based on improved Kalman filtering. The carrier phase smoothing pseudorange algorithm includes acquiring correct pseudorange recursion initial values; estimating predictor and variance estimator of carrier phase smoothing pseudorange; using a smoothing time constant to smooth pseudorange, and calculating variance estimator; circulating recursion till reaching smoothing epoch number. The carrier phase smoothing pseudorange algorithm has the advantages of being better in multi-epoch smoothing effect than that of a conventional smoothing algorithm, small in calculation amount and easy to realize in realtime.

Description

A kind of carrier phase smoothing pseudo-range algorithm based on improved Kalman filter
Technical field
The invention belongs to field of satellite navigation, is a kind of raising pseudorange positioning in Satellite navigation users receiver navigation calculation The algorithm of precision.
Background technology
Satellite navigation users receiver produces two fundamental distance measured values of pseudorange and carrier phase with reality to every satellite Now position.Both pseudorange and carrier phase have significant difference, and again in complementary characteristic, pseudo-range measurements reflect satellite and receive The distance between machine, can avoid the problems such as solving fuzziness and process cycle slip using pseudorange positioning；But due to its include clock correction, The various errors such as air time delay, observation noise is big, easily receive Multi-Path Effects, relatively low using pseudo-range positioning accuracy.Carrier wave phase Position measured value has the advantages that range accuracy is high, has particularly important meaning to hi-Fix, but carrier phase measurement Its part less than a wavelength can only be determined, there is complete cycle uncertain problem.In the base of high accuracy satellite navigation receiver In band signal process, the coarse, pseudo-range measurements without fuzziness are smoothed using accurate, smooth carrier-phase measurement The precision higher than pseudo-range measurements can be obtained.
Traditional carrier phase smoothing pseudo-range adopts Hatch filtering algorithms, although traditional algorithm extensively should in engineering With, but which has the following disadvantages：
(1) pseudo range observed quantity for assuming each epoch is equally accurate, ignores the impact of Carrier Phase Noise, smoothingtime Constant is only relevant with smooth number of times.Smoothed precision is improved with the increase of smooth epoch number in theory, but actually due to passing In system algorithm, smoothing time constant does not consider the impact of carrier phase observation noise, during smooth selected in many epoch are smooth Between constant be not optimum.
(2) first pseudo-range measurements after the initial value selective receiver locking carrier phase of smoothing pseudo range.
If smoothing pseudo range initial value has a larger deviation, smoother then needs one section of long period eliminate partially Difference, therefore the initial value of smoothing pseudo range should be as accurate as possible.
The content of the invention
In order to overcome the deficiencies in the prior art, the present invention to provide a kind of carrier phase based on improved Kalman filter and put down Sliding pseudorange algorithm, by selecting optimal smoothing time constant and selection, accurately pseudorange initial value improves pseudo- anomaly to algorithm as far as possible Spermatorrhea degree.
The technical solution adopted for the present invention to solve the technical problems is comprised the following steps：
Step 1：The pseudorange variable quantity estimation reflected by the difference of pseudo range observed quantity and adjacent epoch carrier phase observed quantity Multiple pseudorange values, using the meansigma methodss of multiple estimated values as pseudorange recursion initial value,
Pseudorange recursion initial valueWherein, M be initial value evaluation times, M >=1； ρmFor tmThe pseudo range observed quantity of epoch；Carrier wavelengths of the λ for satellite-signal；φmFor tmThe carrier phase observed quantity of epoch；φ1For t1The carrier phase observed quantity of epoch；
Step 2：Estimation tkThe premeasuring of epoch carrier phase smoothing pseudo-range, the premeasuring of latter epoch carrier phase smoothed pseudorange The pseudorange variable quantity of the difference reflection of pseudorange, former and later two epoch carrier phases by previous epoch after smooth is obtained；
tkThe premeasuring ρ of epoch carrier phase smoothed pseudorangei -(tk)=ρi +(tk-1)+λ(φk-φk-1)=ρi +(tk-1)+δρ i (tk-1, tk),Wherein, ρi +(tk-1) for tk-1Pseudorange after epoch is smooth, initial value ρi +(tk-1)=ρm,1；φkFor tkEpoch carrier phase Observed quantity；φk-1For tk-1Epoch carrier phase observed quantity；δρ i(tk-1,tk) for tk-1、tkThe difference of two epoch carrier phase observed quantity The pseudorange variable quantity of reflection；
Step 3：Solve tkVariance evaluation amount p of epoch carrier phase smoothing pseudo-range premeasuringi -(tk)=pi +(tk-1)+2 σ2 c, wherein, pi -(tk) for ρi -(tk) variance evaluation amount；pi +(tk-1) for ρi +(tk-1) variance evaluation amount, initial value pi +(t1)=0； 2σ2 cFor δρ i(tk-1,tk) variance evaluation amount, σ2 cFor the variance of carrier phase observation error；
Step 4：Smoothing time constant is represented with the variance of the variance evaluation amount and pseudo range observed quantity of pseudorange；tkSelected by epoch Smoothing time constant k (the t for takingk)=pi -(tk)(pi -(tk)+σ2 p)-1, wherein, σ2 pFor the variance of pseudo range observed quantity；
Step 5：tkPseudorange t after epoch is smoothkEpoch carrier phase smoothing pseudo-range premeasuring, smoothing time constant and tkEpoch pseudo range observed quantity is represented；tkPseudorange after epoch is smoothWherein, ρ (tk) for tkEpoch pseudo range observed quantity；
Step 6：tkThe variance evaluation amount of pseudorange after epoch is smoothAs In next recursive process in step 3
Step 7：As smooth epoch number K of smooth epoch number k less than setting, algorithm return to step 2 carries out recursion, until K=K, algorithm recursion terminate.
The invention has the beneficial effects as follows：Improved Kalman filter algorithm is on the premise of smoothing pseudo range mean square error minimum Optimal smoothing time constant is chosen, the smooth effect of many epoch is better than traditional smoothing algorithm；Further, since algorithm adopts scalar Formal operation, amount of calculation are little, it is easy to real-time implementation, therefore have in high-precision satellite navigation receiver base band signal process There is important practical significance.
Description of the drawings
Fig. 1 is method of the present invention flow chart；
Fig. 2 is not smoothed pseudo range observed quantity schematic diagram；
Fig. 3 is the pseudorange schematic diagram Jing after traditional algorithm is smooth；
Fig. 4 is the pseudorange schematic diagram after improved type Kalman filtering algorithm is smoothed.
Specific embodiment
The present invention is further described with reference to the accompanying drawings and examples, and the present invention includes but are not limited to following enforcements Example.
In theory, Hatch filtering algorithms smooth epoch number K is bigger, and smoothed precision is higher, in practice as smooth epoch number Increase, when smooth epoch number be more than 500 when, carrier phase observation error is to be ignored relative to total smoothed precision 's.Jing analyses know, pseudorange observation error, carrier phase observation error and it is smooth after pseudorange observation error this 3 parameters altogether With the selection for determining smoothing time constant.Thought of the improved Kalman filter algorithm by Kalman filtering, latter epoch Pseudorange of the premeasuring of carrier phase smoothed pseudorange by previous epoch after smooth, the pseudorange change of former and later two epoch carrier phase reflections Measure, consider in filtering pseudorange observation error, carrier phase observation error and it is smoothed after pseudorange observation miss Poor impact.Algorithm on the premise of the variance of the variance and carrier phase observation error that correctly estimate pseudorange observation error, The smoothing time constant of optimum is selected under conditions of smoothing pseudo range error mean square value minimum.Improved Kalman filter carrier wave phase Position smoothing pseudo range algorithm flow is as shown in Figure 1.
Step 1：Algorithm firstly the need of more correct pseudorange recursion initial value is obtained, by pseudo range observed quantity and adjacent epoch The pseudorange variable quantity of the difference reflection of carrier phase observed quantity estimates multiple pseudorange values, using the meansigma methodss of multiple estimated values as pseudorange Recursion initial value is as shown in Equation 1.
Wherein：ρm,1：The pseudorange initial value for estimating；M：Initial value evaluation times, M >=1；ρm：tmThe pseudorange observation of epoch Amount；λ：The carrier wavelength of satellite-signal；φm：tmThe carrier phase observed quantity of epoch；φ1：t1The carrier phase observed quantity of epoch.
Step 2：Estimation tkThe premeasuring of epoch carrier phase smoothing pseudo-range, it is by the thought of Kalman filtering, latter to go through Pseudorange of the premeasuring of first carrier phase smoothed pseudorange by previous epoch after smooth, the puppet of the difference reflection of former and later two epoch carrier phases Obtain away from variable quantity.By tk-1Epoch is to tkThe premeasuring of epoch carrier phase smoothed pseudorange is as shown in Equation 2.
ρi -(tk)=ρi +(tk-1)+λ(φk-φk-1)=ρi +(tk-1)+δρ i(tk-1, tk) (2)
Wherein：ρi -(tk)：tkThe premeasuring of epoch carrier phase smoothing pseudo-range；ρi +(tk-1)：tk-1Pseudorange after epoch is smooth, Initial value ρi +(tk-1)=ρm,1；φk：tkEpoch carrier phase observed quantity；φk-1：tk-1Epoch carrier phase observed quantity；δρ i(tk-1, tk)：tk-1、tkThe pseudorange variable quantity of the difference reflection of two epoch carrier phase observed quantity.
Step 3：Improved Kalman filter algorithm considers pseudorange observation error, carrier phase observation error and Jing and puts down The impact of the pseudorange observation error after cunning, solves tkThe variance evaluation amount of epoch carrier phase smoothing pseudo-range premeasuring such as 3 institute of formula Show.
pi -(tk)=pi +(tk-1)+2σ2 c (3)
Wherein：pi -(tk)：ρi -(tk) variance evaluation amount；pi +(tk-1)：ρi +(tk-1) variance evaluation amount, initial value pi +(t1) =0；2σ2 c：δρ i(tk-1,tk) variance evaluation amount, σ2 cThe variance of carrier phase observation error.
Step 4：In traditional smoothing algorithm, smoothing time constant is only relevant with the epoch number of smooth selection, when epoch number compared with When big, carrier phase observation error relative to total smoothed precision is can not be ignored.In improved Kalman filter algorithm The variance of the variance evaluation amount and pseudo range observed quantity of smoothing time constant pseudorange is represented.tkSmoothingtime selected by epoch is normal Number is as shown in Equation 4.
k(tk)=pi -(tk)(pi -(tk)+σ2 p)-1 (4)
Wherein：k(tk)：Smoothing time constant, σ2 p：The variance of pseudo range observed quantity.
Step 5：tkPseudorange t after epoch is smoothkEpoch carrier phase smoothing pseudo-range premeasuring, smoothing time constant and tkEpoch pseudo range observed quantity is represented.Pseudorange after smooth is as shown in Equation 5.
Wherein：tkPseudorange after epoch is smooth；ρ(tk)：tkEpoch pseudo range observed quantity.
Step 6：tkAfter epoch is smooth, the variance evaluation amount of pseudorange is as shown in Equation 6.
Wherein：Variance evaluation amount, as in step 3 in next recursive process
Step 7：Algorithm recursion
As smooth epoch number K of smooth epoch number k less than setting, algorithm return to step 2 carries out recursion, until k=K, Algorithm recursion terminates.
In certain scientific research project, actual Beidou II satellite-signal is received by receiver, pseudorange and carrier wave is obtained Phase observations amount, using Matlab to not smoothed pseudorange (shown in Fig. 2), pseudorange (Fig. 3 institutes Jing after traditional algorithm is smooth Show) and the pseudorange (shown in Fig. 4) after improved type Kalman filtering algorithm is smooth emulated.In emulation smooth epoch at intervals of 1s, epoch number are 2000.Pseudo range difference amount can intuitively embody the smooth effect of pseudorange, adjacent epoch pseudo range difference quantitative change Change value is less, and pseudorange smoothing effect is better.
The present invention gives a kind of carrier phase smoothing pseudo-range algorithm based on improved Kalman filter, algorithm is by card Kalman Filtering thought selects optimal smoothing time constant and averages by estimation to select pseudorange initial value as accurate as possible to carry High pseudorange smoothing precision.
Step 1：Obtain carrier phase observed quantity and pseudo range observed quantity measured data
In certain scientific research project, actual Big Dipper B3 frequency satellite-signals are received by receiver, receiver is defended to per Star produces pseudo range observed quantity and carrier phase observed quantity, pseudo range observed quantity and carrier phase observed quantity is entered by upper computer software Row record, wherein adjacent epoch observed quantity is at intervals of 1s, chooses K=2000 epoch.
Step 2：Estimation pseudorange initial value
In order to obtain more correct pseudorange initial value, the pseudorange initial value of smoothing algorithm, i.e. t in algorithm are estimated using formula 11 Pseudorange after epoch is smoothed is as shown in Equation 7.
ρi +(t1)=ρs,1 (7)
Wherein：ρs,1：The pseudorange initial value estimated with formula 1, in emulation：M=10 in formula 1, when adjacent epoch interval compared with Hour can select more epoch pseudorange estimation initial values.
Step 3：Calculate tkThe premeasuring of epoch carrier phase smoothing pseudo-range
The corresponding pseudorange of pseudorange, former and later two epoch carrier phase differences after the premeasuring of pseudorange and previous epoch are smooth becomes Change amount is relevant, calculates as shown in Equation 2.
In emulation：ρi +(t1) value is the pseudorange initial value estimated in step 2, ρi +(tk) (k >=2) value obtained by step 6；δρ i (tk-1,tk) adjacent carrier phase observations amount to obtain in step 1 difference.
Step 4：Calculate tkThe variance evaluation amount of epoch carrier phase smoothing pseudo-range premeasuring
tkThe epoch variance of carrier phase smoothed pseudorange premeasuring is as shown in Equation 3.
In emulation：pi +(t1)=0, pi +(tk) (k >=2) are obtained by step 7 recursion；σ in recursive process2 cFor a constant, Variance is asked to obtain by the 2000 epoch carrier phase observed quantities obtained in step 1.
Step 5：Calculate tkSmoothing time constant selected by epoch
Smoothing time constant by pseudorange observation error, carrier phase observation error and it is smooth after pseudorange observation error this 3 parameters are together decided on, and smoothing time constant calculates as shown in Equation 4.
In emulation：tkVariance P of epoch carrier phase smoothed pseudorange premeasuringi -(tk) obtained by step 4, σ in recursive process2 pFor One constant, asks variance to obtain by the 2000 epoch pseudo range observed quantities obtained in step 1.
Step 6：Amendment tkPseudorange of the epoch Jing after smoothing the phase of carrier wave
tkPseudorange t of the epoch Jing after smoothing the phase of carrier wavekEpoch carrier phase smoothing pseudo-range premeasuring, smoothingtime are normal Number and tkEpoch pseudo range observed quantity represents that its computation of pseudoranges after smoothing is as shown in Equation 5.
In emulation：tkEpoch carrier phase smoothed pseudorange premeasuring ρi -(tk) obtained by step 3, tkEpoch smoothing time constant k (tk) obtained by step 5, tkEpoch pseudo range observed quantity ρ (tk) obtained by step 1.
Step 7：Calculate smoothing pseudo range variance evaluation amount
Pseudorange variance after smoothed is by tkEpoch smoothing time constant and tkEpoch smoothing pseudo range premeasuring variance is obtained, Calculate as shown in Equation 6.
In emulation：tkVariance P of epoch carrier phase smoothed pseudorange premeasuringi -(tk) obtained by step 4, smoothing time constant k (tk) obtained by step 5.tkPseudorange variance after epoch is smoothAs in next recursive process step 4
Step 8：Algorithm recursion and simulation comparison
During the smooth epoch number K set in smooth epoch number k is less than step 1, algorithm return to step 3 carries out recursion, directly To k=K, algorithm recursion terminates.
Step 9：Algorithm simulating and compare
Traditional Hatch filtering is as shown in Equation 8 using typical double gradient control methods：
ρi(tk)、ρi(tk-1)：tkAnd tk-1Pseudorange after epoch is smoothed；1/k：Smoothing time constant, the initial one of recursion Part is ρi(t1)=ρ (t1)。
In emulation：2000 epoch not smoothed pseudo range observed quantity has been obtained by step 1；Obtained by step 1 2000 epoch pseudo range observed quantities and carrier phase observed quantity, can obtain 2000 Jing after Hatch filterings using formula 8 Pseudorange, mapping are as shown in Figure 3；Pseudorange of 2000 epoch Jing after this algorithm is smooth can be obtained by step 6 recursion, mapping is such as Shown in Fig. 4.Relatively Fig. 2,3 and 4 can show that the carrier phase smoothing pseudo-range algorithm based on improved Kalman filter is smooth smart Degree is better than convention carrier carrier phase smoothed pseudorange algorithm.

Claims (1)

1. a kind of carrier phase smoothing pseudo-range algorithm based on improved Kalman filter, it is characterised in that comprise the steps：
Step 1：Estimate multiple by the pseudorange variable quantity that the difference of pseudo range observed quantity and adjacent epoch carrier phase observed quantity reflects Pseudorange value, using the meansigma methodss of multiple estimated values as pseudorange recursion initial value,
Pseudorange recursion initial valueWherein, M be initial value evaluation times, M >=1；ρmFor tmThe pseudo range observed quantity of epoch；Carrier wavelengths of the λ for satellite-signal；φmFor tmThe carrier phase observed quantity of epoch；φ1For t1Go through The carrier phase observed quantity of unit；
Step 2：Estimation tkThe premeasuring of epoch carrier phase smoothing pseudo-range, the premeasuring of latter epoch carrier phase smoothed pseudorange is by front The pseudorange variable quantity of the difference reflection of pseudorange, former and later two epoch carrier phases after one epoch is smooth is obtained；
tkThe premeasuring ρ of epoch carrier phase smoothed pseudorangei -(tk)=ρi +(tk-1)+λ(φk-φk-1)=ρi +(tk-1)+δρ i(tk-1, tk), wherein, ρi+(tk-1) for tk-1Pseudorange after epoch is smooth, initial value ρi +(tk-1)=ρm,1；φkFor tkEpoch carrier phase is observed Amount；φk-1For tk-1Epoch carrier phase observed quantity；δρ i(tk-1,tk) for tk-1、tkThe difference reflection of two epoch carrier phase observed quantity Pseudorange variable quantity；
Step 3：Solve tkVariance evaluation amount p of epoch carrier phase smoothing pseudo-range premeasuringi -(tk)=pi +(tk-1)+2σ2 c, its In, pi-(tk) for ρi-(tk) variance evaluation amount；pi+(tk-1) for ρi+(tk-1) variance evaluation amount, initial value pi+(t1)=0；2σ2 c For δρ i(tk-1,tk) variance evaluation amount, σ2 cFor the variance of carrier phase observation error；
Step 4：Smoothing time constant is represented with the variance of the variance evaluation amount and pseudo range observed quantity of pseudorange；tkSelected by epoch Smoothing time constant k (tk)=pi -(tk)(pi -(tk)+σ2 p)-1, wherein, σ2 pFor the variance of pseudo range observed quantity；
Step 5：tkPseudorange t after epoch is smoothkEpoch carrier phase smoothing pseudo-range premeasuring, smoothing time constant and tkGo through First pseudo range observed quantity is represented；tkPseudorange after epoch is smoothWherein, ρ (tk) For tkEpoch pseudo range observed quantity；
Step 6：tkThe variance evaluation amount of pseudorange after epoch is smooth Pass as next During pushing away in step 3
Step 7：As smooth epoch number K of smooth epoch number k less than setting, algorithm return to step 2 carries out recursion, until k= K, algorithm recursion terminate.
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CN105068097A (en) * 2015-09-01 2015-11-18 中国电子科技集团公司第二十研究所 Self-adaptive filtering method for carrier smoothed code pseudorange
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2010050433A1 (en) * 2008-10-28 2010-05-06 古野電気株式会社 Satellite navigation device
CN101825717A (en) * 2010-04-16 2010-09-08 北京航空航天大学 Carrier smoothing code pseudorange technology-based dynamic attitude positioning method
CN102004259A (en) * 2010-09-17 2011-04-06 浙江大学 Satellite navigation positioning resolving method based on Doppler smoothing pseudorange under high-sensitivity environment
CN102426372A (en) * 2011-10-31 2012-04-25 北京中微星通电子有限公司 Carrier smoothing pseudo range method and device
CN102565813A (en) * 2010-12-31 2012-07-11 和芯星通科技(北京)有限公司 Method and device for performing pseudorange observation estimation by carrier smoothing
CN103792558A (en) * 2014-01-10 2014-05-14 中国人民解放军63921部队 GNSS carrier phase smoothness pseudo-range processing method

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2010050433A1 (en) * 2008-10-28 2010-05-06 古野電気株式会社 Satellite navigation device
CN101825717A (en) * 2010-04-16 2010-09-08 北京航空航天大学 Carrier smoothing code pseudorange technology-based dynamic attitude positioning method
CN102004259A (en) * 2010-09-17 2011-04-06 浙江大学 Satellite navigation positioning resolving method based on Doppler smoothing pseudorange under high-sensitivity environment
CN102565813A (en) * 2010-12-31 2012-07-11 和芯星通科技(北京)有限公司 Method and device for performing pseudorange observation estimation by carrier smoothing
CN102426372A (en) * 2011-10-31 2012-04-25 北京中微星通电子有限公司 Carrier smoothing pseudo range method and device
CN103792558A (en) * 2014-01-10 2014-05-14 中国人民解放军63921部队 GNSS carrier phase smoothness pseudo-range processing method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
基于模糊自适应卡尔曼滤波的平滑伪距算法;康德功 等;《计算机仿真》;20140531;第31卷(第5期);第385-388,401页 *
基于自适应补充Kalman滤波的平滑伪距算法;卢超 等;《火力与指挥控制》;20121130;第37卷(第11期);第46-48页 *

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