CN116659429A - Multi-source data high-precision time sequence earth surface three-dimensional deformation resolving method and system - Google Patents
Multi-source data high-precision time sequence earth surface three-dimensional deformation resolving method and system Download PDFInfo
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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
- G01B15/00—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons
- G01B15/06—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons for measuring the deformation in a solid
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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
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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
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
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- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9021—SAR image post-processing techniques
- G01S13/9023—SAR image post-processing techniques combined with interferometric techniques
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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
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Abstract
A multi-source data high-precision time sequence earth surface three-dimensional deformation resolving method and system comprise the following steps: step S100, preprocessing GNSS data; step S200, preprocessing InSAR data; step S300, a motion equation and an observation equation for monitoring the three-dimensional deformation of the region are established; and step S400, filtering fusion solution. When the three-dimensional deformation of the earth surface is calculated based on the multisource deformation monitoring data, the state quantity of the last moment and the observed quantity of the current moment can be utilized to obtain the three-dimensional deformation field of the earth surface at the current data acquisition moment, so that the dynamic three-dimensional deformation monitoring is realized; when only a single InSAR view line is used for observing data at the current moment, the three-dimensional deformation information of the earth surface at the moment can be obtained.
Description
Technical Field
The invention relates to the technical field of three-dimensional dynamic monitoring and tracking of earth surface deformation, in particular to a high-precision time sequence earth surface three-dimensional deformation resolving method and system for multi-source data.
Background
With the development and progress of the space geodetic technology, the application of global navigation satellite system GNSS (Global Navigation Satellite System, GNSS) and synthetic aperture radar interferometry (Interferometric Synthetic Aperture Radar, inSAR) as two novel earth observation technologies in the aspects of earth movement, geological disaster early warning and prevention and control is more and more prominent.
In the prior art, the three-dimensional deformation research of the GNSS and InSAR multisource data fusion earth surface is mainly concentrated at two points, namely, the reconstruction of a post-disaster three-dimensional deformation field and the calculation of a three-dimensional deformation rate field. The method comprises the steps of directly fusing InSAR and GNSS deformation observation values obtained by various technologies to obtain an instantaneous three-dimensional deformation field; the latter is to calculate average speed of various deformation observation values and then fuse them to obtain three-dimensional deformation speed field. In either case, when only a single InSAR line of sight is used for data, three-dimensional deformation information cannot be acquired, and the time resolution of the InSAR data is greatly sacrificed; and the relation between the time before and after the surface deformation cannot be obtained, and the dynamic process of the surface deformation cannot be reflected.
Disclosure of Invention
In order to overcome the problems in the prior art, the invention aims to provide a multi-source data high-precision time sequence earth surface three-dimensional deformation resolving method and system, in particular to a Kalman filtering GNSS-InSAR high-precision time sequence earth surface three-dimensional deformation resolving method.
Aiming at the problem that the general multisource data fusion model can only acquire instantaneous deformation at a certain moment or average three-dimensional deformation In a certain period of time, but cannot reflect the dynamic process of the surface deformation and sacrifice the time resolution of an observed value, the invention provides a high-precision time sequence surface three-dimensional deformation resolving method based on Kalman filtering GNSS-InSAR.
The invention is realized by the following technical scheme:
the first aspect of the invention relates to a multi-source data high-precision time sequence earth surface three-dimensional deformation resolving method, which comprises the following steps:
step S100, preprocessing GNSS data;
step S200, preprocessing InSAR data;
step S300, a motion equation and an observation equation for monitoring the three-dimensional deformation of the region are established;
and step S400, filtering fusion solution.
Further, in step S100, the GNSS monitoring values are processed to obtain a GNSS point deformation monitoring result, and the deformation monitoring result is interpolated to obtain GNSS data conforming to the spatial resolution.
Further, in step S200, spatial correlation error processing is removed from the InSAR data to obtain a line-of-sight deformation time sequence, and downsampling processing is performed on the deformation monitoring result, so that the spatial resolution of the deformation monitoring result is consistent with that of the GNSS interpolation result.
Further, in step S300, a discrete kalman filter equation of motion is established based on the deformation displacement value, the instantaneous velocity and the instantaneous acceleration rate to be calculated by the monitoring point; and establishing an observation equation according to the relation between the InSAR line-of-sight deformation and the projection of the InSAR line-of-sight deformation in the three-dimensional direction of the earth surface.
Further, step S400 includes:
step S410, determining a filtering initial value;
step S420, performing filter recurrence estimation under the criterion of minimum mean square error estimation according to the state equation and the observation equation.
Further, step S420 includes:
step S421, predicting the deformation state value at the current moment in one step: obtaining a state one-step prediction by using the state quantity of the previous moment and by means of a state transition matrix;
step S422, predicting the deformation state value variance at the current moment in one step: solving a one-step prediction error variance matrix by using the state vector covariance of the last moment and the dynamic model noise vector;
step S423, calculating a filtering gain matrix: solving a filtering gain matrix by using the observation vector and the observation matrix;
in step S424, a filtered updated state vector and a corresponding covariance matrix are obtained.
Filtering and resolving are carried out by using InSAR or GNSS observation values acquired at different moments, three-dimensional deformation state vector estimation values at each data acquisition moment are obtained, and three-dimensional deformation of a monitoring area is dynamically monitored.
The invention also relates to a multi-source data high-precision time sequence earth surface three-dimensional deformation resolving system, which comprises:
the GNSS data preprocessing module is used for preprocessing GNSS data;
the InSAR data preprocessing module is used for preprocessing the InSAR data;
the equation building module is used for building a motion equation and an observation equation for monitoring the three-dimensional deformation of the region;
and the filtering fusion resolving module is used for filtering fusion resolving.
The invention also relates to an electronic device comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method.
The invention also relates to a non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method.
The technical scheme of the invention can realize the following beneficial technical effects:
according to the Kalman filtering GNSS-InSAR-based high-precision time sequence earth surface three-dimensional deformation calculation algorithm, three-dimensional deformation information at any data acquisition time can be calculated, real-time dynamic estimation of earth surface three-dimensional deformation of a monitoring area can be realized, a high-precision time sequence three-dimensional deformation field and a three-dimensional deformation rate field can be acquired, and time and spatial resolution of earth surface three-dimensional deformation monitoring can be improved.
Drawings
FIG. 1 is a flow chart of a multi-source data high-precision time sequence earth surface three-dimensional deformation resolving method;
FIG. 2 is a flow chart of a multi-source data high-precision time sequence earth surface three-dimensional deformation resolving method.
Detailed Description
The objects, technical solutions and advantages of the present invention will become more apparent by the following detailed description of the present invention with reference to the accompanying drawings. It should be understood that the description is only illustrative and is not intended to limit the scope of the invention. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the present invention.
The present invention will be described in detail with reference to the accompanying drawings and examples.
The invention provides a multi-source data high-precision time sequence earth surface three-dimensional deformation resolving method, which is a method for supporting earth surface three-dimensional deformation dynamic resolving.
Specifically, the method comprises the following steps:
in step S100, GNSS data is preprocessed.
GNSS data are acquired through continuous GNSS monitoring points, the GNSS monitoring values are processed through baseline resolving, net adjustment processing and the like to obtain GNSS point deformation monitoring results, and the deformation monitoring results are subjected to Kriging interpolation to obtain GNSS data conforming to spatial resolution.
And step S200, preprocessing InSAR data.
InSAR data are unwrapped by a master-slave image registration method, a time sequence coherence factor solving method, a high coherence point selecting method, a phase unwrapping method, a band-pass filtering method for removing space related errors such as atmosphere and orbit, and the like, and then the line-of-sight deformation time sequence is obtained. And carrying out downsampling treatment on the deformation monitoring result to ensure that the deformation monitoring result is consistent with the spatial resolution of the GNSS interpolation result.
And step S300, establishing a motion equation and an observation equation for monitoring the three-dimensional deformation of the region.
Set the deformation displacement value to be calculated of the monitoring pointThe instantaneous rate is +.>Instantaneous acceleration rate->Considered as a random disturbance, the equation of motion of the discrete kalman filter can be expressed as:
（1）
（2）
in the above-mentioned method, the step of,and->Is->And->Displacement of time monitoring point->And->Is->And->Instantaneous rate of time monitoring point, +.>，/>Is->The acceleration rate of time of day, in matrix form, can be expressed as:
（3）
wherein,,for the state vector to be solved +.>For state transition matrix>Is a system dynamic noise vector.
In particular, the deformation is based on InSAR line of sightThe relation with the projection of the three-dimensional direction of the earth surface establishes an observation equation:
（4）
in the method, in the process of the invention,the obtained vision line for the InSAR data of different orbits is changed into projection vectors in east-west direction, north-south direction and vertical direction of the earth surface. When the monitoring point has GNSS observation data, an observation equation can be established:
（5）
in the method, in the process of the invention,the ground deformation observation value obtained by GNSS or the ground deformation observation value obtained by interpolation of discrete GNSS observation points. The above-mentioned various observational equations can be expressed as follows:
（6）
in the method, in the process of the invention,representing observation values acquired by various monitoring technologies at k moment, < >>For the state vector to be solved at time k, +.>Is of various kinds of viewObservation equation design matrix of measured value at k moment, < >>Observed noise vector for monitoring point at time k, its variance matrix ++>。
And step S400, filtering fusion solution.
Step S410, determining a filtering initial value;
taking outThe three-dimensional deformation and variance of the earth's surface at the moment are zero, using +.>The InSAR deformation observed value and the GNSS deformation observed value at moment are subjected to least square calculation to obtain an initial three-dimensional displacement value +.>Corresponding variance matrix->Initial three-dimensional deformation Rate>Inter-average deformation rate->The corresponding variance matrix is->. Observation noise variance matrix->The variance of the InSAR observations is determined by a conventional moving window estimation method, and the variance of the GNSS observations is determined by a common Kriging interpolation variance calculation.
Step S420, performing filtering recursive estimation according to a state equation and an observation equation under a criterion of minimum mean square error estimation;
step S421, predicting the deformation state value at the moment in one step: using state quantity of last momentBy means of state transition matrix->Obtaining a one-step prediction of the state +.>；
(66)
Step S422, predicting the deformation state value variance at the moment in one step: using last moment state vector covarianceAnd dynamic model noise vector->Solving a one-step prediction error variance matrix>；
(77)
Step S423, calculating a filtering gain matrix: using observation vectorsAnd observation matrix->Filtering gain matrix；
(88)
Step S424, filtering and updating the state vectorAnd corresponding covariance matrix->；
(99)
(100)
After the initial filtering value is determined, filtering and resolving can be carried out according to the obtained initial state estimated value and the corresponding covariance matrix by utilizing InSAR or GNSS observed values obtained at different moments according to the formulas (66) to (100) to obtain three-dimensional deformation state vector estimated values at each data acquisition moment, so that the three-dimensional deformation dynamic monitoring of the monitoring area is realized.
Starting from a function model and a random model in a ground surface three-dimensional deformation calculation model, the invention establishes a ground surface three-dimensional deformation dynamic calculation model based on Kalman Filtering (Kalman Filtering), establishes an observation model and a motion model for regional ground surface three-dimensional deformation monitoring by utilizing the space-time correlation of GNSS and InSAR data, and realizes real-time dynamic estimation of ground surface three-dimensional deformation of a monitoring region by sequentially fusing GNSS and InSAR deformation monitoring data obtained by multiple technologies, thereby obtaining a high-precision time sequence three-dimensional deformation field and improving the time resolution of a ground surface three-dimensional deformation monitoring result.
The invention also relates to a multi-source data high-precision time sequence earth surface three-dimensional deformation resolving system, which comprises:
the GNSS data preprocessing module is used for preprocessing GNSS data;
the InSAR data preprocessing module is used for preprocessing the InSAR data;
the equation building module is used for building a motion equation and an observation equation for monitoring the three-dimensional deformation of the region;
and the filtering fusion resolving module is used for filtering fusion resolving.
The invention also relates to an electronic device comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method.
The invention also relates to a non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method.
In summary, the invention provides a multi-source data high-precision time sequence earth surface three-dimensional deformation resolving method, which comprises the following steps: step S100, preprocessing GNSS data; step S200, preprocessing InSAR data; step S300, a motion equation and an observation equation for monitoring the three-dimensional deformation of the region are established; and step S400, filtering fusion solution. When the three-dimensional deformation of the earth surface is calculated based on the multisource deformation monitoring data, the state quantity of the last moment and the observed quantity of the current moment can be utilized to obtain the three-dimensional deformation field of the earth surface at the current data acquisition moment, so that the dynamic three-dimensional deformation monitoring is realized; when only a single InSAR view line is used for observing data at the current moment, the three-dimensional deformation information of the earth surface at the moment can be obtained.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explanation of the principles of the present invention and are in no way limiting of the invention. Accordingly, any modification, equivalent replacement, improvement, etc. made without departing from the spirit and scope of the present invention should be included in the scope of the present invention. Furthermore, the appended claims are intended to cover all such changes and modifications that fall within the scope and boundary of the appended claims, or equivalents of such scope and boundary.
Claims (6)
1. A multi-source data high-precision time sequence earth surface three-dimensional deformation resolving method is characterized by comprising the following steps:
step S100, preprocessing GNSS data: processing the GNSS monitoring value to obtain a GNSS point deformation monitoring result, and interpolating the deformation monitoring result to obtain GNSS data conforming to the spatial resolution;
step S200, preprocessing the InSAR data: removing spatial correlation errors from InSAR data to obtain a line-of-sight deformation time sequence, and performing downsampling on deformation monitoring results to enable the deformation monitoring results to be consistent with the spatial resolution of GNSS interpolation results;
step S300, a motion equation and an observation equation for monitoring the three-dimensional deformation of the region are established: establishing a discrete Kalman filtering equation of motion based on the deformation displacement value to be solved by the monitoring point, the instantaneous speed and the instantaneous acceleration rate; establishing an observation equation according to the relation between InSAR-LOS line-of-sight deformation, GNSS three-dimensional deformation and projection of the earth surface E, N, U in the three-dimensional direction;
and step S400, filtering fusion solution.
2. The method for resolving high-precision time-series earth surface three-dimensional deformation of multi-source data according to claim 1, wherein step S400 comprises:
step S410, determining a filtering initial value;
step S420, performing filter recurrence estimation under the criterion of minimum mean square error estimation according to the state equation and the observation equation.
3. The method of high-precision time-series earth surface three-dimensional deformation resolution of multi-source data according to claim 1, wherein step S420 comprises:
step S421, predicting the deformation state value at the current moment in one step: obtaining a state one-step prediction by using the state quantity of the previous moment and by means of a state transition matrix;
step S422, predicting the deformation state value variance at the current moment in one step: solving a one-step prediction error variance matrix by using the state vector covariance of the last moment and the dynamic model noise vector;
step S423, calculating a filtering gain matrix: solving a filtering gain matrix by using the observation vector and the observation matrix;
step S424, obtaining a filtering update state vector and a corresponding covariance matrix;
filtering and resolving are carried out by using InSAR or GNSS observation values acquired at different moments, three-dimensional deformation state vector estimation values at each data acquisition moment are obtained, and three-dimensional deformation of a monitoring area is dynamically monitored.
4. A multi-source data high-precision time sequence earth surface three-dimensional deformation resolving system is characterized by comprising:
the GNSS data preprocessing module is used for preprocessing GNSS data: processing the GNSS monitoring value to obtain a GNSS point deformation monitoring result, and interpolating the deformation monitoring result to obtain GNSS data conforming to the spatial resolution;
the InSAR data preprocessing module is used for preprocessing the InSAR data: removing spatial correlation errors from InSAR data to obtain a line-of-sight deformation time sequence, and performing downsampling on deformation monitoring results to enable the deformation monitoring results to be consistent with the spatial resolution of GNSS interpolation results;
the equation building module is used for building a motion equation and an observation equation for monitoring the three-dimensional deformation of the region: establishing a discrete Kalman filtering equation of motion based on the deformation displacement value to be solved by the monitoring point, the instantaneous speed and the instantaneous acceleration rate; establishing an observation equation according to the relation between InSAR-LOS line-of-sight deformation, GNSS three-dimensional deformation and projection of the earth surface E, N, U in the three-dimensional direction;
and the filtering fusion resolving module is used for filtering fusion resolving.
5. An electronic device, the electronic device comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of the preceding claims 1 to 3.
6. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of the preceding claims 1 to 3.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117331078A (en) * | 2023-10-26 | 2024-01-02 | 内蒙古至远创新科技有限公司 | Method and system for calculating differential deformation rate based on InSAR data |
| CN118259280A (en) * | 2024-05-28 | 2024-06-28 | 深圳大学 | Sea-filling airport deformation evaluation method, system and terminal combining InSAR and GNSS |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104699966A (en) * | 2015-03-09 | 2015-06-10 | 中南大学 | Method for obtaining deformation sequence of high temporal-spatial resolution by fusing GNSS and InSAR data |
| WO2019066698A1 (en) * | 2017-09-29 | 2019-04-04 | Saab Ab | A method for determining the base line for a synthetic aperture of a sar using gnss |
| CN110058236A (en) * | 2019-05-21 | 2019-07-26 | 中南大学 | It is a kind of towards three-dimensional Ground Deformation estimation InSAR and GNSS determine Quan Fangfa |
| CN111522006A (en) * | 2020-06-29 | 2020-08-11 | 航天宏图信息技术股份有限公司 | Earth surface settlement monitoring method and device fusing Beidou and InSAR data |
| CN111721241A (en) * | 2020-05-08 | 2020-09-29 | 北京理工大学 | GNSS-InBSAR and GB-InSAR cross-system fusion three-dimensional deformation measurement method |
| CN112540370A (en) * | 2020-12-08 | 2021-03-23 | 鞍钢集团矿业有限公司 | InSAR and GNSS fused strip mine slope deformation measurement method |
| CN112540369A (en) * | 2020-11-27 | 2021-03-23 | 武汉大学 | Landslide three-dimensional deformation resolving method and system integrating GNSS and lifting rail time sequence InSAR |
| EP3866105A1 (en) * | 2020-02-17 | 2021-08-18 | Paris Sciences et Lettres - Quartier Latin | Method for processing insar images to extract ground deformation signals |
| CN113405447A (en) * | 2020-05-19 | 2021-09-17 | 湖南北斗微芯产业发展有限公司 | Track traffic deformation monitoring method, device and equipment integrating InSAR and GNSS |
| CN116052009A (en) * | 2022-11-01 | 2023-05-02 | 中南大学 | GNSS station measurement layout method based on InSAR deformation and application thereof |
-
2023
- 2023-08-01 CN CN202310954510.1A patent/CN116659429A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104699966A (en) * | 2015-03-09 | 2015-06-10 | 中南大学 | Method for obtaining deformation sequence of high temporal-spatial resolution by fusing GNSS and InSAR data |
| WO2019066698A1 (en) * | 2017-09-29 | 2019-04-04 | Saab Ab | A method for determining the base line for a synthetic aperture of a sar using gnss |
| CN110058236A (en) * | 2019-05-21 | 2019-07-26 | 中南大学 | It is a kind of towards three-dimensional Ground Deformation estimation InSAR and GNSS determine Quan Fangfa |
| EP3866105A1 (en) * | 2020-02-17 | 2021-08-18 | Paris Sciences et Lettres - Quartier Latin | Method for processing insar images to extract ground deformation signals |
| CN111721241A (en) * | 2020-05-08 | 2020-09-29 | 北京理工大学 | GNSS-InBSAR and GB-InSAR cross-system fusion three-dimensional deformation measurement method |
| CN113405447A (en) * | 2020-05-19 | 2021-09-17 | 湖南北斗微芯产业发展有限公司 | Track traffic deformation monitoring method, device and equipment integrating InSAR and GNSS |
| CN111522006A (en) * | 2020-06-29 | 2020-08-11 | 航天宏图信息技术股份有限公司 | Earth surface settlement monitoring method and device fusing Beidou and InSAR data |
| CN112540369A (en) * | 2020-11-27 | 2021-03-23 | 武汉大学 | Landslide three-dimensional deformation resolving method and system integrating GNSS and lifting rail time sequence InSAR |
| CN112540370A (en) * | 2020-12-08 | 2021-03-23 | 鞍钢集团矿业有限公司 | InSAR and GNSS fused strip mine slope deformation measurement method |
| CN116052009A (en) * | 2022-11-01 | 2023-05-02 | 中南大学 | GNSS station measurement layout method based on InSAR deformation and application thereof |
Non-Patent Citations (4)
| Title |
|---|
| 周文韬: "融合 GNSS 与 InSAR的矿区地表三维形变监测", 《中国优秀硕士学位论文全文 数据库工程科技Ⅰ辑》, no. 08, pages 2 - 7 * |
| 周文韬: "融合GNSS与InSAR的矿区地表三维形变监测", 中国优秀硕士学位论文全文数据库工程科技Ⅰ辑, pages 2 - 7 * |
| 杨雪艳: "InSAR 高精度时序地表三维形变模型研究", 《中国优秀硕士学位论文全 文数据库基础科学辑 》, no. 06, pages 21 - 22 * |
| 焦明连;: "GPS与InSAR数据融合方法及其应用", 全球定位系统, no. 03 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117331078A (en) * | 2023-10-26 | 2024-01-02 | 内蒙古至远创新科技有限公司 | Method and system for calculating differential deformation rate based on InSAR data |
| CN118259280A (en) * | 2024-05-28 | 2024-06-28 | 深圳大学 | Sea-filling airport deformation evaluation method, system and terminal combining InSAR and GNSS |
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