CN109540095A - Roadbed settlement monitoring method based on satellite navigation and least square - Google Patents
Roadbed settlement monitoring method based on satellite navigation and least square Download PDFInfo
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- CN109540095A CN109540095A CN201811632148.1A CN201811632148A CN109540095A CN 109540095 A CN109540095 A CN 109540095A CN 201811632148 A CN201811632148 A CN 201811632148A CN 109540095 A CN109540095 A CN 109540095A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C5/00—Measuring height; Measuring distances transverse to line of sight; Levelling between separated points; Surveyors' levels
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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
- G01S19/14—Receivers specially adapted for specific applications
-
- 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
- G01S19/33—Multimode operation in different systems which transmit time stamped messages, e.g. GPS/GLONASS
Abstract
The present invention provides a kind of roadbed settlement monitoring method based on satellite navigation and least square, comprising: install monitoring station in the different monitoring points that monitored road bed is easy to happen sedimentation, the reference for installation station outside the certain distance of monitoring station；Monitoring station and base station utilize multifrequency satellite navigation receiving antenna reception Beidou/GPS/GLONASS multifrequency point satellite-signal；Obtain state equation and observational equation；Using least squares filtering, and mean filter, Kalman filter are combined, by denoising the real-time monitoring for obtaining centimetre class precision as a result, and monitoring result is sent to monitoring and early warning platform by network；Continuous N number of hour observation data of base station and monitoring station are resolved, best observed values are obtained by observational equation, it is superimposed by normal equation, parameter is estimated using least square, the post-processing monitoring result of millimeter class precision is obtained finally by denoising, and monitoring result is sent to by monitoring and early warning platform by network.
Description
Technical field
The present invention relates to a kind of satellite navigation application technology, especially a kind of roadbed based on satellite navigation and least square
Monitoring method of the subsidence.
Background technique
Recently as the rapid development of Chinese national economy construction, it is substance that communications and transportation, which is the lifeblood of national economy,
The pillar of production activity and commodity circulation, railway, highway have been China's transportation trade the most main at present, are passed through in its people
Play the role of in Ji and social development highly important.Subgrade engineering occupies important specific gravity, roadbed in railway, highway engineering
It is that solid foundation is stablized on road surface, the roadbed of stable strong is to ensure that the key foundation of railway, highway engineering one's best quality.Roadbed
Fill that unreasonable, filler is not scientific, deficiency compacting can all cause the sedimentation of roadbed without good Soft foundation treatment.It is based on
Cause the diversification factor of subgrade settlement, we only formulate scientific and effective monitoring means (subgrade settlement monitoring analysis), control
Treatment measures processed, applications well construction prevention processing technique could reduce bad loss, control differential settlement phenomenon, be promoted
Highway, the whole construction quality of railway engineering are horizontal, guarantee high-speed rail, the operation of the quick and stable of vehicle.
Traditional deformation monitoring mainly uses common measuring instrument (theodolite, rangefinder, total station, level etc.), this
Kind artificial its repeated work of operation mode is more, and construction precision is not high, the field period is longer, large labor intensity, and production cost occupies
It is high not under.With the development of Satellite Navigation Technique, historic change, satellite navigation skill is had occurred in the operational method of engineering survey
Art measures mainly using network RTK and precise single-point positioning technology, built-in in big region especially with technology of network RTK
Vertical continuous operation base station net system (CORS), realization is round-the-clock to provide high-precision location information for user.Subgrade settlement
Monitoring realizes round-the-clock, high-precision, unattended, automatic operating mode, propulsion information using the advantages of Satellite Navigation Technique
Change the construction process of mapping.
Summary of the invention
The purpose of the present invention is to provide a kind of roadbed settlement monitoring method based on satellite navigation and least square, packet
It includes:
Step 1, monitoring station is installed in the different monitoring points that monitored road bed is easy to happen sedimentation, in monitoring station
The outer reference for installation station of certain distance；
Step 2, monitoring station and base station utilize multifrequency satellite navigation receiving antenna reception Beidou/GPS/GLONASS multifrequency
Point satellite-signal；
Step 3, state equation and observational equation are obtained；
Step 4, using least squares filtering, and mean filter, Kalman filter are combined, Centimeter Level essence is obtained by denoising
The real-time monitoring of degree is as a result, and be sent to monitoring and early warning platform for monitoring result by network；
Step 5, continuous N number of hour observation data of base station and monitoring station are resolved, is obtained most by observational equation
Excellent observation, is superimposed by normal equation, is estimated using least square parameter, obtains a millimeter class precision finally by denoising
Post-processing monitoring result, and monitoring result is sent to by monitoring and early warning platform by network.
The present invention utilizes 2 observation data more than hour, is superimposed by normal equation, is obtained using least square method
The result of subgrade settlement monitoring be more nearly the curve of true roadbed variation, can effectively reflect subgrade settlement deformation
Variation tendency, to provide effective reference frame for departments such as communications and transportation, road equipment maintenances.
The invention will be further described with reference to the accompanying drawings of the specification.
Detailed description of the invention
Fig. 1 is the system block diagram that the present invention uses.
Fig. 2 is method flow schematic diagram of the invention.
Specific embodiment
In conjunction with Fig. 1, a kind of roadbed settlement monitoring equipment based on satellite navigation and least square, including monitoring station, benchmark
It stands, data processing platform (DPP) and monitoring and early warning platform；
Monitoring station for obtaining monitoring data is mounted on the different monitoring points that monitored road bed is easy to happen sedimentation
On, the monitoring station include for real-time reception Beidou/GPS/GLONASS satellite-signal multifrequency satellite navigation receiving antenna,
Beidou/GPS/GLONASS multifrequency point monitoring station receiver, the integrated observation pier for loading receiver and for be receiver
The solar power supply apparatus of power supply is provided；
Base station for providing positioning reference information for monitoring station is mounted on the fixed bit within the 10km of monitoring station
Place is set, the base station includes receiving day for the navigation of real-time reception Beidou/GPS/GLONASS satellite-signal multifrequency satellite
Line, Beidou/GPS/GLONASS multifrequency point reference receiver, the integrated observation pier for loading receiver and for connect
The solar power supply apparatus of receipts machine offer power supply；
The data processing platform (DPP) includes for screening the data preprocessing module of best observed values composition observational equation, using
In the real-time processing module for resolving the real-time settlement monitoring result in monitoring station and for resolving monitoring station secular sinking monitoring knot
Monitoring result is sent to monitoring and warning by network and put down by the post-processing module of fruit, the real-time processing module and post-processing module
Platform；
The monitoring and early warning platform real-time and post-processing settlement monitoring result that processing platform is sent for receiving data is simultaneously
It is shown.
In conjunction with Fig. 2, a kind of roadbed settlement monitoring equipment based on satellite navigation and least square of the present invention is utilized
The monitoring method of implementation, comprising the following steps:
1) monitoring station and base station receive Beidou/GPS/GLONASS multifrequency point using multifrequency satellite navigation receiving antenna and defend
Star signal, and pass through and data are transferred data to by wire/radio network after the signal received is amplified, handled by receiver
Processing platform；
2) data flow that data processing platform (DPP) receives monitoring station and base station is sent, utilizes data preprocessing module, logarithm
According to real-time decoding is carried out, by space-time datum, unified, base station and monitoring station group double difference, eliminate and weaken most of space phase
After the error of closing property, controlled by Detection of Cycle-slip, quality and etc., best observed values are filtered out, effective observational equation is obtained；
3) real-time processing module of data processing platform (DPP) mainly uses least squares filtering, and combine mean filter,
The methods of Kalman filter, by denoising the real-time monitoring for obtaining centimetre class precision as a result, and sending out monitoring result by network
Give monitoring and early warning platform；
4) post-processing module of data processing platform (DPP) using the continuous N number of hour (N >=2) in base station and monitoring station observation number
According to being resolved, best observed values are obtained by observational equation, are superimposed by normal equation, parameter is estimated using least square
Meter obtains the post-processing monitoring result of millimeter class precision finally by denoising, and monitoring result is sent to monitoring by network
Early warning platform；
5) monitoring and early warning platform receives the real-time and post-processing monitoring result that data processing platform (DPP) is sent, and in platform software
It is shown on interface.
In measurement adjustment, least squares filtering is exactly to ask that determine parameter best using the observation for containing error (noise)
The method of valuation.Least squares filtering is using all parameters to be estimated as random parameter, in its known priori statistics
Under the premise of, the optimum evaluation for determining parameter is sought according to general least square principle.Least square method (also known as least squares method) is one
Kind mathematical optimization techniques.It finds the optimal function matching of data by minimizing the quadratic sum of error.Utilize least square method
The quadratic sum of error is most between the data and real data that unknown data can easily be acquired, and these are acquired
It is small.
In satellite navigation data processing, least squares filtering and the application of least square method are as follows respectively:
(1) application of least squares filtering
By General Surveying Adjustment principle it is found that setting L as normal state random observation vector, X is system status parameters (or letter
Number, Normal Distribution) vector.Parameter X and observation L has following priori statistical property:
In formula, ux、uLRespectively represent system status parameters and observation vector tests preceding expectation；Dxx、DLLThen indicate system shape
State parameter and observation vector test preceding variance matrix.Observational equation between L and X meets
L=BX+ φ (2)
In formula: B is observation coefficient matrix；φ is random error.And the covariance between random error and unknown parameter
For Cov (φ, X)=0 (3)
Current LxIndicate the experienced expectation u of Xx, that is, it is regarded as dummy observation, regards parameter X to be asked as nonrandom
Parameter, if the random error corresponding to it is φx, there is observational equation between three at this time:
Lx=X+ φx (4)
Due to parameter to be asked at this timeIt is nonrandom parameter, formula (2) is merged with formula (4) and considers that observation is true
Be worth it is unknown, practical adjustment with most or valueInstead of when, have error equation:
In formula: V and VxRespectively correspond actual observed value L and dummy observation LxCorrection.
Formula (5) is the function model of indirect adjustment.According to general least square principle:
As V and VxMeetWhen minimum, even if the valuation of unknown parameter X is optimal, wherein PxIt is respectively void with P
The Posterior weight battle array of quasi-observation and observation.It is to obtain optimal estimation and the corresponding variance of unknown parameter X
In formula,ForVariance.Formula (6) is to ask the calculating of unknown parameter public under general least square principle
Formula or least squares filtering formula.
In the real-time RTK positioning of GNSS, usually using the three-dimensional coordinate of rover station and three-dimensional velocity as unknown parameter, work as sight
When containing rough error in direction finding amount, then the state equation and observational equation of system respectively indicate are as follows:
In formula, XkThe state vector to be estimated of etching system, L when for kkThe observation vector of etching system, Φ when for kk,k-1When for k-1
It is carved into the state-transition matrix at k moment, generally unit matrix；BkThe coefficient matrix of etching system, Γ when for kk,k-1For system noise
Matrix, Ωk-1For the system noise at k-1 moment, VkFor the observation noise at k moment.The stochastic model of standard Kalman filtering are as follows:
Wherein, DΩIt (k) is system dynamic noise variance matrix, DVIt (k) is observation noise variance matrix, δkjFor Kronecker letter
Number.Standard Kalman filtering equations are as follows:
Wherein,
At this point, if in observation vector contain rough error when, the measurement equation of system are as follows:
In formula, HkFor the rough error interference matrix at k moment, it is made of element 0 and 1；ΔkFor rough error vector.If according to standard card
Kalman Filtering model is filtered, and prediction residual is
Ek=Lk-BkX [k/ (k-1)]=Ek+HkΔk (12)
It can be seen that reflection degree of the rough error in prediction residual, depend primarily on the reliability of location parameter initial value, root
The characteristics of according to Kalman filter model, actually depends on the original state of dynamical system.
At this point, State-Vector Equation are as follows:
Rough error i.e. in observation vector passes through state gain matrix JkInfluence state vector filter value.When known quantity direction finding
Measure LkIn when containing t rough error, then influence of the rough error to state vector is (omits the subscript k) of gain matrix below.
If above formula is become:
As long as then according to ΔjSize select suitable constant cij, can eliminate or weaken rough error to state vector
It influences.At this point, the calculation formula of state vector can be changed to:
Variable constant cijDepending on two kinds of factors.One is the prediction residual E of vector measuring valuek；The second is gain matrix
Jk.Due to gain matrix JkIt is the prediction variance matrix D by state vectorX[k/ (k-1)], observation noise variance matrix DV(k) it and measures
Matrix BkDetermining, and DX[k/ (k-1)] is unrelated with the observation vector of kth phase, therefore JkMainly by DV(k) and BkDetermine, i.e., by
The graphic structure and accuracy of observation of GPS monitoring net determine.According to error reliability theory, graphic structure and accuracy of observation can use net
Redundant obser ration part this index indicate.So gain matrix JkIt is mainly determined by the redundant obser ration part r of monitoring net, i.e.,
cijRedundant obser ration part r is depended on againj.If the structure and observation program of monitoring net, extra sight have been determined in the design phase
Survey component rjIt can calculate.If the rough error contained in prediction residual is in different ranges, cijValue it is different.
When rough error is greater than a certain limit value, the measurement vector should be rejected；When rough error is smaller, that is, think to measure in vector only containing accidental
When error, then it should retain the measurement vector；Otherwise influence of the reduction amount direction finding amount to state vector.This region, with parameter k0
And k1To indicate.At this point,
Construct equivalent gain matrix:
In formula, k0And k1For robust parameter.k0Referred to as quartile parameter, takes 2.5-3.5；k1Point is referred to as eliminated, 3.5-4.5 is taken；
Kalman filter exactly can be according to the relative size of status predication covariance matrix and measurement error covariance, certainly
It moves, immediately adjust yield value, to reach the optimal estimation to system mode.
(2) application of least square method
When we study the correlation between two variables (x, y), it is commonly available a series of pairs of data
(x1, y1.x2, y2...xm, ym)；These data are depicted in x-y rectangular coordinate system, if finding these points in straight line
Near, this linear equation such as (formula 1-1) can be enabled.
yi=a0+a1X (formula 1-1)
Wherein: a0, a1 are any real numbers, will determine a0 and a1 to establish this linear equation, using " least square method is former
Reason ", by the quadratic sum ∑ (Yi- of measured value Yi and the deviation (Yi-Yj) using calculated value Yj (Yj=a0+a1Xi) (formula 1-1)
Yj)2Minimum " optimized criterion ".It enables:
(formula 1-1) is substituted into (formula 1-2) and is obtained:
As ∑ (Yi-Yj)2When minimum, available functionsPartial derivative is asked to a0, a1, the two partial derivatives is enabled to be equal to zero.
∑ 2 (a0+a1*Xi-Yi)=0 (formula 1-4)
∑ 2Xi (a0+a1*Xi-Yi)=0 (formula 1-5)
That is:
Na0+ (∑ Xi) a1=∑ Yi (formula 1-6)
(∑ Xi) a0+ (∑ Xi^2) a1=∑ (Xi*Yi) (formula 1-7)
Two obtained are two equation groups of unknown number about a0, a1, solve the two equation groups and obtain:
A0=(∑ Yi)/n-a1 (∑ Xi)/n (formula 1-8)
A1=[n ∑ (XiYi)-(∑ Xi ∑ Yi)]/(n ∑ Xi^2- ∑ Xi ∑ Xi) (formula 1-9)
At this moment a0, a1 substitute into (formula 1-1) in, (formula 1-1) at this time be exactly we return a linear equation i.e.: number
Learn model.In regression process, the correlation of recurrence can not all by each regression data point (x1, y1.x2,
Y2...xm, ym), it, can be by related coefficient " R ", statistic " F ", remaining standard deviation " S " in order to judge the quality of correlation
Judged；" R " is 1 better more leveling off to；The absolute value of " F " is the bigger the better；" S " is 0 better more leveling off to.
The present invention utilizes the principle of least square, carries out grade unknown point Three-dimensional color power angio, utilizes Big Dipper satellite signal
B1And B2Or the L of GPS satellite signal1And L2On pseudorange double difference observation, set up following error equation:
In (formula 1-10), R1, R2, RWLFor corresponding L1, L2, LWLThe wide lane observation of pseudorange；ν is residual vector；B is by connecing
For receipts machine to the direction cosines Construction designing matrix of satellite, I is unit matrix；For basic lineal vector to be estimated；For wide lane ambiguity
Degree；lRAnd lWLRespectively indicate OMC (ObservationMinusCalculation) constant of pseudorange and WL carrier phase observable to
Amount.
Combine Data processing with GPS in Beidou, for each epoch, error equation be may be expressed as:
In (formula 1-11), the weight proportion of GPS and Beidou observation is 1.5:1, L OMC.In composition double difference observation
When, dipper system and GPS should select reference star of the highest satellite of elevation angle as the system respectively, then by each satellite
The contribution of double difference observation is added in normal equation
If current single epoch processing result residual error is less than setting value, epoch contribution is added most by normal equation superposition
Whole equation, is shown below
In, n is total epoch number.Using the formula, the optimum evaluation of unknown parameter X can be estimated, to acquire optimal solution.
Claims (2)
1. a kind of roadbed settlement monitoring method based on satellite navigation and least square characterized by comprising
Step 1, monitoring station is installed in the different monitoring points that monitored road bed is easy to happen sedimentation, in the certain of monitoring station
Apart from outer reference for installation station；
Step 2, monitoring station and base station receive Beidou/GPS/GLONASS multifrequency point using multifrequency satellite navigation receiving antenna and defend
Star signal；
Step 3, state equation and observational equation are obtained；
Step 4, using least squares filtering, and mean filter, Kalman filter are combined, centimetre class precision is obtained by denoising
Real-time monitoring is as a result, and be sent to monitoring and early warning platform for monitoring result by network；
Step 5, continuous N number of hour observation data of base station and monitoring station are resolved, optimal sight is obtained by observational equation
Measured value is superimposed by normal equation, is estimated using least square parameter, after obtaining millimeter class precision finally by denoising
Monitoring result is handled, and monitoring result is sent to by monitoring and early warning platform by network.
2. the method according to claim 1, wherein the state equation and observational equation of step 3 are respectively as follows:
Wherein, XkThe state vector to be estimated of etching system, L when for kkThe observation vector of etching system, Φ when for kk,k-1For the k-1 moment to k
The state-transition matrix at moment, generally unit matrix；BkThe coefficient matrix of etching system, Γ when for kk,k-1For system noise matrix,
Ωk-1For the system noise at k-1 moment, VkFor the observation noise at k moment.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110055945A (en) * | 2019-05-22 | 2019-07-26 | 马培峰 | A kind of monitoring method, device and the relevant device of soil solidifying sedimentation |
| CN110308465A (en) * | 2019-06-06 | 2019-10-08 | 重庆工商大学融智学院 | Geography information polymerization based on surface subsidence |
| CN111595293A (en) * | 2020-05-29 | 2020-08-28 | 山东交通学院 | Surface deformation monitoring method and system based on multi-source monitoring data fusion |
| CN111929711A (en) * | 2020-07-31 | 2020-11-13 | 苏州迭慧智能科技有限公司 | Multiple landslide and settlement monitoring network system based on satellite navigation accurate coherent measurement |
| CN112114339A (en) * | 2020-11-20 | 2020-12-22 | 四川中科川信科技有限公司 | GNSS data differential iterative filtering resolving method |
| 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 |
| CN113311460A (en) * | 2021-07-28 | 2021-08-27 | 湖南联智科技股份有限公司 | Beidou-based early warning method and system |
| CN113777642A (en) * | 2020-06-10 | 2021-12-10 | 千寻位置网络有限公司 | Method and device for processing parameters to be estimated of geodetic survey result |
| CN113819863A (en) * | 2021-10-08 | 2021-12-21 | 中国科学院国家授时中心 | Deformation monitoring method and system |
| CN114234911A (en) * | 2021-12-09 | 2022-03-25 | 南京苏逸实业有限公司 | Ultrasonic sedimentation and horizontal displacement measuring device and measuring method utilizing Beidou for positioning |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104296721A (en) * | 2014-11-01 | 2015-01-21 | 机械工业勘察设计研究院 | Satellite positioning and static leveling-based layered settlement monitoring system and method |
| CN104915534A (en) * | 2014-11-25 | 2015-09-16 | 国家电网公司 | Deformation analysis and decision-making method of electric power tower based on sequence learning |
| CN107421434A (en) * | 2017-08-08 | 2017-12-01 | 千寻位置网络有限公司 | More base station Multi GNSS Long baselines near real-time deformation monitoring methods |
| CN108508469A (en) * | 2018-04-17 | 2018-09-07 | 安徽继远软件有限公司 | A kind of electric power tower deformation monitoring system and its monitoring method based on the preposition resolving of the Big Dipper |
-
2018
- 2018-12-29 CN CN201811632148.1A patent/CN109540095A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104296721A (en) * | 2014-11-01 | 2015-01-21 | 机械工业勘察设计研究院 | Satellite positioning and static leveling-based layered settlement monitoring system and method |
| CN104915534A (en) * | 2014-11-25 | 2015-09-16 | 国家电网公司 | Deformation analysis and decision-making method of electric power tower based on sequence learning |
| CN107421434A (en) * | 2017-08-08 | 2017-12-01 | 千寻位置网络有限公司 | More base station Multi GNSS Long baselines near real-time deformation monitoring methods |
| CN108508469A (en) * | 2018-04-17 | 2018-09-07 | 安徽继远软件有限公司 | A kind of electric power tower deformation monitoring system and its monitoring method based on the preposition resolving of the Big Dipper |
Non-Patent Citations (5)
| Title |
|---|
| 刘伟平等: "《北斗卫星导航系统精密轨道确定》", 30 June 2016 * |
| 刘国林等: "《近代测量平差理论与方法》", 31 August 2012 * |
| 崔希璋等: "《广义测量平差（第二版）》", 30 June 1982 * |
| 胡圣武等: "《现代测量数据处理理论与应用》", 31 January 2016 * |
| 韩静: "BDS/GPS相对定位算法研究及其在滑坡监测中的应用", 《中国优秀硕士学位论文全文数据库 基础科学辑》 * |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110055945A (en) * | 2019-05-22 | 2019-07-26 | 马培峰 | A kind of monitoring method, device and the relevant device of soil solidifying sedimentation |
| CN110055945B (en) * | 2019-05-22 | 2021-05-25 | 马培峰 | Method and device for monitoring soil consolidation settlement and related equipment |
| CN110308465A (en) * | 2019-06-06 | 2019-10-08 | 重庆工商大学融智学院 | Geography information polymerization based on surface subsidence |
| CN111595293A (en) * | 2020-05-29 | 2020-08-28 | 山东交通学院 | Surface deformation monitoring method and system based on multi-source monitoring data fusion |
| CN113777642A (en) * | 2020-06-10 | 2021-12-10 | 千寻位置网络有限公司 | Method and device for processing parameters to be estimated of geodetic survey result |
| CN111929711A (en) * | 2020-07-31 | 2020-11-13 | 苏州迭慧智能科技有限公司 | Multiple landslide and settlement monitoring network system based on satellite navigation accurate coherent measurement |
| CN112114339A (en) * | 2020-11-20 | 2020-12-22 | 四川中科川信科技有限公司 | GNSS data differential iterative filtering resolving method |
| 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 |
| CN113311460A (en) * | 2021-07-28 | 2021-08-27 | 湖南联智科技股份有限公司 | Beidou-based early warning method and system |
| CN113311460B (en) * | 2021-07-28 | 2021-10-26 | 湖南联智科技股份有限公司 | Beidou-based early warning method and system |
| CN113819863A (en) * | 2021-10-08 | 2021-12-21 | 中国科学院国家授时中心 | Deformation monitoring method and system |
| CN114234911A (en) * | 2021-12-09 | 2022-03-25 | 南京苏逸实业有限公司 | Ultrasonic sedimentation and horizontal displacement measuring device and measuring method utilizing Beidou for positioning |
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