CN109059751A - A kind of deformation data monitoring method and system - Google Patents
A kind of deformation data monitoring method and system Download PDFInfo
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- CN109059751A CN109059751A CN201811049111.6A CN201811049111A CN109059751A CN 109059751 A CN109059751 A CN 109059751A CN 201811049111 A CN201811049111 A CN 201811049111A CN 109059751 A CN109059751 A CN 109059751A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B7/00—Measuring arrangements characterised by the use of electric or magnetic techniques
- G01B7/16—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring the deformation in a solid, e.g. by resistance strain gauge
Abstract
The present invention discloses a kind of deformation data monitoring method and system, and the monitoring method obtains phase/Pseudo-range Observations between reference station and subscriber station first with GNSS receiver；The acceleration observation of subscriber station is obtained using acceleration；Obtain auxiliary parameter；Secondly phase/Pseudo-range Observations, acceleration observation and auxiliary parameter are pre-processed, obtains observation data；Then double difference observation model and state model are determined according to observation data；It is finally based on double difference observation model and state model, parameter calculation is carried out using kalman filter method, obtains deformation monitoring result；The present invention obtains high-precision low-frequency phase/Pseudo-range Observations using GNSS technology, high-frequency acceleration observation is obtained using accelerometer, pass through the fusion of the two, high and low frequency message complementary sense can not only be realized, also effectively inhibit GNSS noise, enhancing solves intensity, and then improves and determine deformation monitoring result accuracy and convergence rate.
Description
Technical field
The present invention relates to data monitoring technical fields, more particularly to a kind of deformation data monitoring method and system.
Background technique
Global navigation satellite GNSS real-time dynamic positioning RTK technology is mainly used for deformation data monitoring at present, still
RTK can only provide low frequency displacement information, the serious pollution because signal noise exists of the velocity and acceleration information of high frequency, because without
It is easy and fast to, the slight change of accurate measurements deformation.Based on the above issues, how quickly, accurately high frequency deformation data is carried out
Monitoring becomes this field urgent problem.
Summary of the invention
The object of the present invention is to provide a kind of deformation data monitoring method and systems, fast and accurately determine shape to realize
Become monitoring result.
To achieve the above object, the present invention provides a kind of deformation data monitoring method, the monitoring method includes:
Phase/Pseudo-range Observations between reference station and subscriber station are obtained using GNSS receiver；It is obtained using acceleration
The acceleration observation of subscriber station；Obtain auxiliary parameter；
Phase/the Pseudo-range Observations, the acceleration observation and the auxiliary parameter are pre-processed, seen
Measured data；
Double difference observation model and state model are determined according to the observation data；
Based on the double difference observation model and state model, parameter calculation is carried out using kalman filter method, obtains shape
Become monitoring result；
The deformation monitoring to deformable body is realized according to the deformation monitoring result.
Optionally, the auxiliary parameter includes broadcast ephemeris, survey station coordinate, antenna model, antenna phase center correction text
Part and earth rotation parameter (ERP).
Optionally, described that the phase/Pseudo-range Observations, the acceleration observation and the auxiliary parameter are carried out in advance
Processing obtains observation data, specifically includes:
Data integrity inspection is carried out to the phase/Pseudo-range Observations, the acceleration observation and the auxiliary parameter
It looks into, the processing of elimination of rough difference and Detection of Cycle-slip；
To treated, data carry out the theory of relativity, tide, antenna phase center, troposphere and earth rotation error repairs
Just, observation data are obtained；The observation data include: pretreated double difference phase observation value, double difference Pseudo-range Observations, survey station
Acceleration.
It is optionally, described to determine double difference observation model, specific formula according to the observation data are as follows:
Wherein, footmark b and r is respectively reference station and subscriber station, and k indicates epoch serial number, and i is i-th of satellite, and j-th of j
Satellite,The pretreated double difference Pseudo-range Observations between k epoch i, j satellite b, r survey station,For on k epoch survey station r
I, difference, s between the star of unit rotating vector between the two Satellite ground jr(k) to be displaced reduction on k epoch survey station r,For k
Double difference ionospheric error between epoch i, j satellite b, r survey station,Double difference troposphere is missed between k epoch i, j satellite b, r survey station
Difference,The double difference geometric distance between k epoch i, j satellite b, r survey station, εpIt (k) is k epoch pseudorange observation noise,For k
Pretreated double difference phase observation value between epoch i, j satellite b, r survey station, λ is carrier wavelength,It is defended for k epoch i, j
Double difference fuzziness between star b, r survey station, εφIt (k) is k epoch phase observations noise,For phase observations noise variance,For pseudorange
Observation noise variance.
It is optionally, described to determine state model, specific formula according to the observation data are as follows:
Wherein, s is coordinate basic lineal vector, and v is the speed of survey station, and u is baseline drift error, and amb is all double difference moulds
Paste degree, τ are the sample frequency of GNSS, βkFor the dynamic noise of k-th of epoch, a is pretreated survey station acceleration, QEIt is
State state-noise battle array, qaFor acceleration variance, quFor the variance of baseline drift.
The present invention also provides a kind of deformation data to monitor system, and the monitoring system includes:
Module is obtained, for obtaining phase/Pseudo-range Observations between reference station and subscriber station using GNSS receiver；Benefit
The acceleration observation of subscriber station is obtained with acceleration；Obtain auxiliary parameter；
Preprocessing module, for the phase/Pseudo-range Observations, the acceleration observation and the auxiliary parameter into
Row pretreatment obtains observation data；
Model determining module, for determining double difference observation model and state model according to the observation data；
Deformation monitoring result determining module is filtered for being based on the double difference observation model and state model using Kalman
Wave method carries out parameter calculation, obtains deformation monitoring result；
Deformation monitoring module, for realizing the deformation monitoring to deformable body according to the deformation monitoring result.
Optionally, the auxiliary parameter includes broadcast ephemeris, survey station coordinate, antenna model, antenna phase center correction text
Part and earth rotation parameter (ERP).
Optionally, the preprocessing module, specifically includes:
First pretreatment unit, for joining to the phase/Pseudo-range Observations, the acceleration observation and the auxiliary
Number carries out data integrity inspection, elimination of rough difference and Detection of Cycle-slip processing；
Second pretreatment unit, for data to carry out the theory of relativity, tide, antenna phase center, troposphere to treated
With the amendment of earth rotation error, observation data are obtained；The observation data include: pretreated double difference phase observation value,
Double difference Pseudo-range Observations, survey station acceleration.
It is optionally, described to determine double difference observation model, specific formula according to the observation data are as follows:
Wherein, footmark b and r is respectively reference station and subscriber station, and k indicates epoch serial number, and i is i-th of satellite, and j-th of j
Satellite,The pretreated double difference Pseudo-range Observations between k epoch i, j satellite b, r survey station,For on k epoch survey station r
I, difference, s between the star of unit rotating vector between the two Satellite ground jr(k) to be displaced reduction on k epoch survey station r,For
Double difference ionospheric error between k epoch i, j satellite b, r survey station,Double difference troposphere is missed between k epoch i, j satellite b, r survey station
Difference,The double difference geometric distance between k epoch i, j satellite b, r survey station, εpIt (k) is k epoch pseudorange observation noise,For k
Pretreated double difference phase observation value between epoch i, j satellite b, r survey station, λ is carrier wavelength,It is defended for k epoch i, j
Double difference fuzziness between star b, r survey station, εφIt (k) is k epoch phase observations noise,For phase observations noise variance,For pseudorange
Observation noise variance.
It is optionally, described to determine state model, specific formula according to the observation data are as follows:
Wherein, s is coordinate basic lineal vector, and v is the speed of survey station, and u is baseline drift error, and amb is all double difference moulds
Paste degree, τ are the sample frequency of GNSS, βkFor the dynamic noise of k-th of epoch, a is pretreated survey station acceleration, QEIt is
State state-noise battle array, qaFor acceleration variance, quFor the variance of baseline drift.
The specific embodiment provided according to the present invention, the invention discloses following technical effects:
The present invention obtains high-precision low-frequency phase/Pseudo-range Observations using GNSS technology, is obtained using accelerometer
High-frequency acceleration observation is taken, by the fusion of the two, high and low frequency message complementary sense can not only be realized, it is also effective
Inhibit GNSS noise, enhancing solves intensity, and then improves and determine deformation monitoring result accuracy and convergence rate.
Detailed description of the invention
It in order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will be to institute in embodiment
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without any creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is deformation data of embodiment of the present invention monitoring method flow chart；
Fig. 2 is that deformation data of the embodiment of the present invention monitors system construction drawing.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The object of the present invention is to provide a kind of deformation data monitoring method and systems, fast and accurately determine shape to realize
Become monitoring result.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, with reference to the accompanying drawing and specific real
Applying mode, the present invention is described in further detail.
Fig. 1 is deformation data of embodiment of the present invention monitoring method flow chart, as shown in Figure 1, the present invention provides a kind of deformation
Data monitoring method, the monitoring method include:
Step S1: phase/Pseudo-range Observations between reference station and subscriber station are obtained using GNSS receiver；Utilize acceleration
Degree obtains the acceleration observation of subscriber station；Obtain auxiliary parameter；
Step S2: the phase/Pseudo-range Observations, the acceleration observation and the auxiliary parameter are located in advance
Reason obtains observation data；
Step S3: double difference observation model and state model are determined according to the observation data；
Step S4: being based on the double difference observation model and state model, carries out parameter calculation using kalman filter method,
Obtain deformation monitoring result；The deformation monitoring result includes displacement, velocity and acceleration；The deformation monitoring result is wideband
With deformation monitoring as a result, the frequency bandwidth of the broadband deformation monitoring result is determining according to actual needs；
Step S5: the deformation monitoring to deformable body is realized according to the deformation monitoring result；Deformable body includes bridge, road
Road, building, disaster.
Detailed analysis is carried out to each step below:
Auxiliary parameter of the present invention includes broadcast ephemeris, survey station coordinate, antenna model, antenna phase center amendment file
And earth rotation parameter (ERP)；The earth rotation parameter (ERP) is Ghandler motion and daily change parameter.
Step S2: the phase/Pseudo-range Observations, the acceleration observation and the auxiliary parameter are located in advance
Reason obtains observation data, specifically includes:
Step S21: data are carried out to the phase/Pseudo-range Observations, the acceleration observation and the auxiliary parameter
Integrity checking, elimination of rough difference and Detection of Cycle-slip processing, using guarantee treated data be data type completely, without rough error, nothing
The clean data of cycle slip；
Step S22: to treated, data carry out the theory of relativity, tide, antenna phase center, troposphere and earth rotation mistake
The amendment of difference obtains the observation data after deducting model errors；The observation data include: that pretreated double difference phase is seen
Measured value, double difference Pseudo-range Observations, survey station acceleration.
Step S3: described to determine double difference observation model, specific formula according to the observation data are as follows:
Wherein, footmark b and r is respectively reference station and subscriber station, and k indicates epoch serial number, and i is i-th of satellite, and j-th of j
Satellite,The pretreated double difference Pseudo-range Observations between k epoch i, j satellite b, r survey station,For on k epoch survey station r
I, difference, s between the star of unit rotating vector between the two Satellite ground jr(k) to be displaced reduction on k epoch survey station r,For
Double difference ionospheric error between k epoch i, j satellite b, r survey station,Double difference troposphere is missed between k epoch i, j satellite b, r survey station
Difference,The double difference geometric distance between k epoch i, j satellite b, r survey station, εpIt (k) is k epoch pseudorange observation noise,For k
Pretreated double difference phase observation value between epoch i, j satellite b, r survey station, λ is carrier wavelength,It is defended for k epoch i, j
Double difference fuzziness between star b, r survey station, εφIt (k) is k epoch phase observations noise,For phase observations noise variance,For pseudorange
Observation noise variance.
Step S3: described to determine state model according to the observation data.
Because the effective range of RTK is generally within several kilometers, the ionosphere of double difference and tropospheric error can
To ignore.Therefore, in state equation foundation, only consider displacement, speed, acceleration, baseline drift and carrier phase ginseng
Number.
In the RTK positioning of standard, state equation often uses second order Gauss Markov model, and expression formula is as follows:
Wherein, s is coordinate basic lineal vector, and v is the speed of survey station, and amb is all double difference fuzzinesses, and τ is adopting for GNSS
Sample frequency, a are pretreated survey station acceleration, QSFor dynamic noise battle array, qaFor acceleration variance, αkIt is dynamic for k-th epoch
State noise.
After increasing acceleration observation, because the acceleration after Base-Line Drift Correction can indicate true acceleration, because
This is only needed using single order Gauss Markov model, then determines state model, specific formula according to the observation data are as follows:
Wherein, s is coordinate basic lineal vector, and v is the speed of survey station, and u is baseline drift error, and amb is all double difference moulds
Paste degree, τ are the sample frequency of GNSS, βkFor the dynamic noise of k-th of epoch, a is pretreated survey station acceleration, QEIt is
State state-noise battle array, qaFor acceleration variance, quFor the variance of baseline drift.
The present invention is for data calculation, and according to dynamic noise, epoch is estimated one by one with speed for displacement.Its accelerometer
Baseline drift error as random walk process processing, carrier phase ambiguity in continuous segmental arc as constant processing,
Cycle slip need to be reinitialized when occurring.It should be pointed out that because the sample frequency of GNSS is usually 1Hz, accelerometer
Sample frequency is 100Hz, therefore the filter of data calculation is only predicted on each accelerometer sampled point, is only existed
It is just filtered on GNSS sampled point.
The present invention is based on can be displaced in real time after this filtering processing, velocity information and baseline drift error, it is original
Acceleration observation deduct baseline drift after obtain true acceleration information.
Fig. 2 is that deformation data of the embodiment of the present invention monitors system construction drawing, as shown in Fig. 2, the present invention also provides a kind of shapes
Become data monitoring system, the monitoring system includes:
Module 1 is obtained, for obtaining phase/Pseudo-range Observations between reference station and subscriber station using GNSS receiver；
The acceleration observation of subscriber station is obtained using acceleration；Obtain auxiliary parameter；
Preprocessing module 2, for the phase/Pseudo-range Observations, the acceleration observation and the auxiliary parameter
It is pre-processed, obtains observation data；
Model determining module 3, for determining double difference observation model and state model according to the observation data；
Deformation monitoring result determining module 4 is filtered for being based on the double difference observation model and state model using Kalman
Wave method carries out parameter calculation, obtains deformation monitoring result；
Deformation monitoring module 5, for realizing the deformation monitoring to deformable body according to the deformation monitoring result.
Auxiliary parameter of the present invention includes broadcast ephemeris, survey station coordinate, antenna model, antenna phase center amendment file
And earth rotation parameter (ERP).
Preprocessing module 2 of the present invention, specifically includes:
First pretreatment unit, for joining to the phase/Pseudo-range Observations, the acceleration observation and the auxiliary
Number carries out data integrity inspection, elimination of rough difference and Detection of Cycle-slip processing；
Second pretreatment unit, for data to carry out the theory of relativity, tide, antenna phase center, troposphere to treated
With the amendment of earth rotation error, observation data are obtained；The observation data include: pretreated double difference phase observation value,
Double difference Pseudo-range Observations, survey station acceleration.
It is of the present invention to determine double difference observation model, specific formula according to the observation data are as follows:
Wherein, footmark b and r is respectively reference station and subscriber station, and k indicates epoch serial number, and i is i-th of satellite, and j-th of j
Satellite,The pretreated double difference Pseudo-range Observations between k epoch i, j satellite b, r survey station,For on k epoch survey station r
I, difference, s between the star of unit rotating vector between the two Satellite ground jr(k) to be displaced reduction on k epoch survey station r,For
Double difference ionospheric error between k epoch i, j satellite b, r survey station,Double difference troposphere is missed between k epoch i, j satellite b, r survey station
Difference,The double difference geometric distance between k epoch i, j satellite b, r survey station, εpIt (k) is k epoch pseudorange observation noise,For k
Pretreated double difference phase observation value between epoch i, j satellite b, r survey station, λ is carrier wavelength,It is defended for k epoch i, j
Double difference fuzziness between star b, r survey station, εφIt (k) is k epoch phase observations noise,For phase observations noise variance,For pseudorange
Observation noise variance.
It is of the present invention to determine state model, specific formula according to the observation data are as follows:
Wherein, s is coordinate basic lineal vector, and v is the speed of survey station, and u is baseline drift error, and amb is all double difference moulds
Paste degree, τ are the sample frequency of GNSS, βkFor the dynamic noise of k-th of epoch, a is pretreated survey station acceleration, QEIt is
State state-noise battle array, qaFor acceleration variance, quFor the variance of baseline drift.
The beneficial effects of the present invention are:
First, high-frequency accelerometer observation is increased, the frequency of result information is improved.
It is hundred times of GNSS sample frequency because the frequency of accelerometer is 100Hz or more, the present invention merges GNSS and height
The observation of frequency acceleration meter carries out fusion resolving, and the defect of low-frequency information can only be obtained by effectively compensating for GNSS, will be mentioned significantly
The frequency of high result information.
Second, by the fusion of two kinds of technologies, mutual supplement with each other's advantages is realized, enriches GNSS deformation monitoring result.
GNSS technology is easily obtained high-precision low frequency displacement information, but there are noise pollution for high-frequency information；Accelerometer
It is easily obtained high-frequency acceleration information, but there are baseline drift errors.The fusion of the two realizes high and low frequency information
Complementation, user can obtain high-precision, wide band displacement, velocity and acceleration deformation data in real time.
Third is constrained by the acceleration information of high s/n ratio, improves GNSS positioning accuracy and convergence rate.
The acceleration information of high-frequency, high s/n ratio is dissolved into GNSS positioning, can effectively inhibit GNSS noise, increases
Solution intensity is imposed, and then GNSS positioning accuracy and convergence rate can be improved.
Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with other
The difference of embodiment, the same or similar parts in each embodiment may refer to each other.For system disclosed in embodiment
For, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is said referring to method part
It is bright.
Used herein a specific example illustrates the principle and implementation of the invention, and above embodiments are said
It is bright to be merely used to help understand method and its core concept of the invention；At the same time, for those skilled in the art, foundation
Thought of the invention, there will be changes in the specific implementation manner and application range.In conclusion the content of the present specification is not
It is interpreted as limitation of the present invention.
Claims (10)
1. a kind of deformation data monitoring method, which is characterized in that the monitoring method includes:
Phase/Pseudo-range Observations between reference station and subscriber station are obtained using GNSS receiver；User is obtained using acceleration
The acceleration observation stood；Obtain auxiliary parameter；
Phase/the Pseudo-range Observations, the acceleration observation and the auxiliary parameter are pre-processed, observation number is obtained
According to；
Double difference observation model and state model are determined according to the observation data；
Based on the double difference observation model and state model, parameter calculation is carried out using kalman filter method, obtains deformation prison
Survey result；
The deformation monitoring to deformable body is realized according to the deformation monitoring result.
2. deformation data monitoring method according to claim 1, which is characterized in that the auxiliary parameter includes broadcast star
It goes through, survey station coordinate, antenna model, antenna phase center amendment file and earth rotation parameter (ERP).
3. deformation data monitoring method according to claim 1, which is characterized in that described to the phase/pseudorange observation
Value, the acceleration observation and the auxiliary parameter are pre-processed, and are obtained observation data, are specifically included:
To the phase/Pseudo-range Observations, the acceleration observation and the auxiliary parameter progress data integrity inspection, slightly
Difference is rejected and Detection of Cycle-slip processing；
Amendment to treated data carry out the theory of relativity, tide, antenna phase center, troposphere and earth rotation error, is obtained
Data must be observed；The observation data include: pretreated double difference phase observation value, double difference Pseudo-range Observations, survey station acceleration
Degree.
4. deformation data monitoring method according to claim 1, which is characterized in that described to be determined according to the observation data
Double difference observation model, specific formula are as follows:
Wherein, footmark b and r is respectively reference station and subscriber station, and k indicates epoch serial number, and i is i-th of satellite, and j defends for j-th
Star,The pretreated double difference Pseudo-range Observations between k epoch i, j satellite b, r survey station,For i on k epoch survey station r,
Difference, s between the star of unit rotating vector between the two Satellite ground jr(k) to be displaced reduction on k epoch survey station r,For k
Double difference ionospheric error between epoch i, j satellite b, r survey station,Double difference troposphere is missed between k epoch i, j satellite b, r survey station
Difference,The double difference geometric distance between k epoch i, j satellite b, r survey station, εpIt (k) is k epoch pseudorange observation noise,For k
Pretreated double difference phase observation value between epoch i, j satellite b, r survey station, λ is carrier wavelength,It is defended for k epoch i, j
Double difference fuzziness between star b, r survey station, εφIt (k) is k epoch phase observations noise,For phase observations noise variance,For pseudorange
Observation noise variance.
5. deformation data monitoring method according to claim 1, which is characterized in that described to be determined according to the observation data
State model, specific formula are as follows:
Wherein, s is coordinate basic lineal vector, and v is the speed of survey station, and u is baseline drift error, and amb is all double difference fuzzinesses,
τ is the sample frequency of GNSS, βkFor the dynamic noise of k-th of epoch, a is pretreated survey station acceleration, QEFor dynamical state
Noise battle array, qaFor acceleration variance, quFor the variance of baseline drift.
6. a kind of deformation data monitors system, which is characterized in that the monitoring system includes:
Module is obtained, for obtaining phase/Pseudo-range Observations between reference station and subscriber station using GNSS receiver；Using adding
The acceleration observation of speed acquisition subscriber station；Obtain auxiliary parameter；
Preprocessing module, it is pre- for being carried out to the phase/Pseudo-range Observations, the acceleration observation and the auxiliary parameter
Processing obtains observation data；
Model determining module, for determining double difference observation model and state model according to the observation data；
Deformation monitoring result determining module, for being based on the double difference observation model and state model, using Kalman filtering side
Method carries out parameter calculation, obtains deformation monitoring result；
Deformation monitoring module, for realizing the deformation monitoring to deformable body according to the deformation monitoring result.
7. deformation data according to claim 6 monitors system, which is characterized in that the auxiliary parameter includes broadcast star
It goes through, survey station coordinate, antenna model, antenna phase center amendment file and earth rotation parameter (ERP).
8. deformation data according to claim 6 monitors system, which is characterized in that the preprocessing module specifically includes:
First pretreatment unit, for the phase/Pseudo-range Observations, the acceleration observation and the auxiliary parameter into
Row data integrity checking, elimination of rough difference and Detection of Cycle-slip processing；
Second pretreatment unit, for data to carry out the theory of relativity, tide, antenna phase center, troposphere and ground to treated
The amendment of revolutions error obtains observation data；The observation data include: pretreated double difference phase observation value, double difference
Pseudo-range Observations, survey station acceleration.
9. deformation data according to claim 6 monitors system, which is characterized in that described to be determined according to the observation data
Double difference observation model, specific formula are as follows:
Wherein, footmark b and r is respectively reference station and subscriber station, and k indicates epoch serial number, and i is i-th of satellite, and j defends for j-th
Star,The pretreated double difference Pseudo-range Observations between k epoch i, j satellite b, r survey station,For i on k epoch survey station r,
Difference, s between the star of unit rotating vector between the two Satellite ground jr(k) to be displaced reduction on k epoch survey station r,For k
Double difference ionospheric error between epoch i, j satellite b, r survey station,Double difference troposphere is missed between k epoch i, j satellite b, r survey station
Difference,The double difference geometric distance between k epoch i, j satellite b, r survey station, εpIt (k) is k epoch pseudorange observation noise,For k
Pretreated double difference phase observation value between epoch i, j satellite b, r survey station, λ is carrier wavelength,It is defended for k epoch i, j
Double difference fuzziness between star b, r survey station, εφIt (k) is k epoch phase observations noise,For phase observations noise variance,For pseudorange
Observation noise variance.
10. deformation data according to claim 6 monitors system, which is characterized in that described true according to the observation data
Determine state model, specific formula are as follows:
Wherein, s is coordinate basic lineal vector, and v is the speed of survey station, and u is baseline drift error, and amb is all double difference fuzzinesses,
τ is the sample frequency of GNSS, βkFor the dynamic noise of k-th of epoch, a is pretreated survey station acceleration, QEFor dynamical state
Noise battle array, qaFor acceleration variance, quFor the variance of baseline drift.
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| CN111443366A (en) * | 2020-04-28 | 2020-07-24 | 武汉大学 | Method and system for detecting abnormal point in GNSS area network |
| CN112525149A (en) * | 2020-11-26 | 2021-03-19 | 广东星舆科技有限公司 | Method and device for monitoring pavement settlement and computer readable medium |
| CN113358017A (en) * | 2021-06-02 | 2021-09-07 | 同济大学 | Multi-station cooperative processing GNSS high-precision deformation monitoring method |
| CN113721445A (en) * | 2021-07-13 | 2021-11-30 | 中国科学院国家授时中心 | Multi-region real-time dynamic time service method and device based on satellite navigation |
| CN114167493A (en) * | 2021-11-23 | 2022-03-11 | 武汉大学 | Earthquake rotation measurement system and method of GNSS double-antenna auxiliary gyroscope |
| CN114912551A (en) * | 2022-07-18 | 2022-08-16 | 中国铁路设计集团有限公司 | GNSS and accelerometer real-time fusion algorithm for bridge deformation monitoring |
| CN115096174A (en) * | 2022-06-14 | 2022-09-23 | 长沙学院 | Method and system for improving GNSS-R deformation detection precision |
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