CN109031301A - Alpine terrain deformation extracting method based on PSInSAR technology - Google Patents
Alpine terrain deformation extracting method based on PSInSAR technology Download PDFInfo
- Publication number
- CN109031301A CN109031301A CN201811123711.2A CN201811123711A CN109031301A CN 109031301 A CN109031301 A CN 109031301A CN 201811123711 A CN201811123711 A CN 201811123711A CN 109031301 A CN109031301 A CN 109031301A
- Authority
- CN
- China
- Prior art keywords
- image
- phase
- coherence factor
- deformation
- point
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Classifications
-
- 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
- G01S13/88—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
-
- 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
- G01S13/88—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
- G01S13/904—SAR modes
Landscapes
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- Radar Systems Or Details Thereof (AREA)
- Image Processing (AREA)
Abstract
The present invention discloses a kind of alpine terrain deformation extracting method based on PSInSAR technology, several High Resolution SAR Images are obtained by piggyback satellite, and choose n width SAR image, using comprehensive coherence factor method selection, wherein a width makees master image, remaining makees auxiliary image, allow again master image respectively with auxiliary image registration and carry out interference processing, obtain coherence factor figure and interferometric phase image；According to coherence factor figure, PS point is chosen using corresponding amplitude deviation and coherence factor dual thresholds method and obtains the PS point triangulation network；Flat filtering is carried out to interferometric phase image, and utilizes external dem data, differential interferometry processing is carried out to interference pattern, obtains differential interferometry figure；It is utilized respectively network adjustment method, puppet 3D phase unwrapping method and three kinds of Lambda algorithm three-dimensional scramble network phase unwrapping methods and phase unwrapping is carried out to differential interferometry figure, obtain Deformation Field to the end.
Description
Technical field
The present invention relates to synthetic aperture radar image-forming technical field more particularly to a kind of mountain areas based on PSInSAR technology
Landform deformation extracting method.
Background technique
Synthetic aperture radar (SAR) has the advantages that round-the-clock, round-the-clock, is widely applied to sees over the ground both at home and abroad
Survey field, interfering synthetic aperture radar (InSAR) application that wherein eighties proposes are even more important.
PSInSAR (Permanent scatterers synthetic aperture radar interferometry) detection Ground Deformation is that (difference is dry in DInSAR
Relate to measurement) on the basis of develop, the differential interferometry phase of PSInSAR is obtained using DInSAR method.DInSAR is visited
Surveying Ground Deformation is to survey on the basis of height to develop from InSAR again, by obtaining the complex pattern pair of ground areal, according to
The geometrical relationship of target and aerial position forms interference line figure, interferes and contain in line figure in complex pattern to upper generation phase difference
The precise information of the difference of the upward point of oblique distance and two aerial positions, utilizes the orbit parameter, system parameter and base of observation platform
Geometrical relationship between line length can measure the three-dimensional position of every bit on image with precise volume, then by redundant observation or outside
Portion's terrain data rejects the influence of topography from interferometric phase, to obtain the phase of Ground Deformation, and then is finally inversed by Ground Deformation.
For the influence of conventional DInSAR phase misalignment correlation and atmosphere delay, Ferretti, which is proposed, only only keeps track thunder in imaging region
The method that those dephasings close serious resolution cell, these target (such as ground are abandoned up to the relatively stable target of scattering properties
The corner or roof of building, it is also possible to exposed rock) influence of noise hardly is closed by dephasing, even if in time many years
The interference at interval still maintains higher interference correlation in, these stable targets are referred to as Permanent scatterers (PS).
Since Permanent scatterers can keep high relevant in some time is spaced, and Space Baseline away from be more than Critical baseline away from feelings
Under condition, be also able to maintain high coherence, can make full use of in this way Long baselines away from interference image to improving number to the maximum extent
According to utilization rate by carrying out time series analysis to these PS points, eliminate atmosphere to find out the PS point in survey region
It influences, just can accurately measure the deformation quantity of PS point, to monitor the movement on ground, and accurately reflect monitored region
Relative displacement.
PSInSAR method is similar to control measurement, it obtains the information of whole region by the authentic communication on point, even if
Interference fringe cannot be formed in entire research area, can also use the deformation of PSInSAR method detection earth's surface.
Summary of the invention
The present invention provides a kind of alpine terrain deformation extracting method based on PSInSAR technology, with solve the prior art without
Method accurately extracts the problem of alpine terrain deformation.
A kind of alpine terrain deformation extracting method based on PSInSAR technology provided by the invention, comprising:
SAR image is chosen, the SAR image includes master image and auxiliary image；
Using the master image and the auxiliary image registration and interference processing is carried out, obtains coherence factor figure and interferometric phase
Figure；
PS point is chosen on the coherence factor figure using amplitude deviation and the dual thresholds method of coherence factor, obtains PS point
The triangulation network；
The interferometric phase image is subjected to flat filtering processing, using dem data to treated the interferometric phase image
Differential interferometry processing is carried out, differential interferometry figure is obtained；
Phase unwrapping processing is carried out to the differential interferometry figure, obtains Deformation Field.
In one embodiment of the invention, SAR image is chosen to specifically include:
N width SAR image is chosen, selects the width in the SAR image as the master map using comprehensive coherence factor method
Picture, remaining n-1 width is as the auxiliary image.
In one embodiment of the invention, phase unwrapping processing is carried out to the differential interferometry figure to specifically include:
It is utilized respectively network adjustment method, puppet 3D phase unwrapping method and Lambda algorithm and phase is carried out to the differential interferometry figure
Solution twines processing.
In one embodiment of the invention, the network adjustment method specifically includes:
The differential mode pattern three times of PS point is established, the coherence factor K in the differential mode pattern three times is calculated1,K2,B⊥, institute
State differential mode pattern three times are as follows:
Plumb line method of loci is introduced, Δ δ ' is chosenHSearch range and step-length with Δ v', by between the adjacent PS point of control
The suitable Δ δ ' of multiple correlation coefficient γ search one by oneHWith Δ v', wherein
It regard linear deformation speed difference corresponding to the maximum value of the coherence factor and elevation amendment difference as parameter Estimation
Value, establishes adjustment function model, and the adjustment function model is,
Solve linear equation:
In one embodiment of the invention, the puppet 3D phase unwrapping method specifically includes:
Delaunay triangulation network connection is done to the PS point and establishes the triangulation network, time dimension is connected by time relationship；
Residue points calculating is carried out along the side of the triangulation network；
The optimization initial value that space 2D phase unwrapping is done using time dimension disentanglement fruit is carried out using minimum Lp norm method
The optimal solution of space dimension.
In one embodiment of the invention, the Lambda algorithm specifically includes:
In n-1 width differential interferometry figure, the phase type of differential interferometry three times of the adjacent PS point of the triangulation network is formed into equation group:
It is denoted as y1=A1·a+B1·b；
In y1=A1·a+B1Imitation observation equation y is added in b2=A2·a+B2B constitutes y=Aa+Bb, wherein A2For 2*m null matrix, B2For 2*2 unit matrix；
It is acquired according to the principle of least square:
C=(A B)
It obtainsComplete cycle float solution, search for obtain the fixed solution of phase complete cycle using fuzziness decorrelation method
By the fixed solutionIt brings solution into and twines phase expression formulaIn reuse minimum two
Multiplication obtains:
After completing phase unwrapping, the Deformation Field is obtained by mutually high conversion and geocoding.
A kind of alpine terrain deformation extracting method based on PSInSAR technology provided by the invention, is obtained by piggyback satellite
Several High Resolution SAR Images are taken, and choose n width SAR image, wherein a width makees master map using comprehensive coherence factor method selection
Picture, remaining makees auxiliary image, then allow master image respectively with auxiliary image registration and carry out interference processing, obtain coherence factor figure and interference
Phase diagram；According to coherence factor figure, PS point is chosen using corresponding amplitude deviation and coherence factor dual thresholds method and obtains PS
The point triangulation network；Flat filtering is carried out to interferometric phase image, and utilizes external dem data, differential interferometry processing is carried out to interference pattern,
Obtain differential interferometry figure；It is utilized respectively three kinds of network adjustment method, puppet 3D phase unwrapping method and Lambda algorithm irregular nets of three-dimensional
Network phase unwrapping method carries out phase unwrapping to differential interferometry figure, obtains Deformation Field to the end.
Detailed description of the invention
Fig. 1 is the flow chart of the alpine terrain deformation extracting method provided in an embodiment of the present invention based on PSInSAR technology；
Fig. 2 is the remote sensing image of the Mao County test block in the embodiment of the present invention；
Fig. 3 is the Mao County triangulation diagram in the embodiment of the present invention；
Fig. 4 is the Erlongshan Mountains differential interferometry figure in the embodiment of the present invention；
Fig. 5 is the Chengdu differential interferometry figure in the embodiment of the present invention.
Specific embodiment
Present invention will be further explained below with reference to the attached drawings and examples.
It is the stream of the alpine terrain deformation extracting method provided in an embodiment of the present invention based on PSInSAR technology referring to Fig. 1
Cheng Tu, this method comprises:
S100: SAR image is chosen, the SAR image includes master image and auxiliary image.
SAR image is chosen to specifically include:
N width SAR image is chosen, selects the width in the SAR image as the master map using comprehensive coherence factor method
Picture, remaining n-1 width is as the auxiliary image.
S200: using the master image and the auxiliary image registration and carrying out interference processing, obtains coherence factor figure and does
Relate to phase diagram.
S300: PS point is chosen on the coherence factor figure using amplitude deviation and the dual thresholds method of coherence factor, is obtained
To the PS point triangulation network.
S400: carrying out flat filtering processing for the interferometric phase image, using dem data to treated the interference phase
Bitmap carries out differential interferometry processing, obtains differential interferometry figure.
Dem data is digital elevation model (Digital Elevation Model), is by limited landform altitude number
The factually existing digitized simulation (i.e. the digital expression of topographical surface form) to ground surface or terrain, is with one group of orderly array of values
A kind of actual ground model of form expression ground elevation.In the embodiment of the present invention, using external dem data, to going flat filtering
Treated, and interferometric phase image carries out differential interferometry processing, obtains differential interferometry figure.
S500: phase unwrapping processing is carried out to the differential interferometry figure, obtains Deformation Field.
It is utilized respectively network adjustment method, puppet 3D phase unwrapping method and three kinds of Lambda algorithm three-dimensional scramble network phase solutions
Quick pushing manipulation carries out phase unwrapping to differential interferometry figure, obtains Deformation Field to the end.
Wherein, network adjustment method specifically includes:
The differential mode pattern three times of PS point is established, the coherence factor K in the differential mode pattern three times is calculated1,K2,B⊥, institute
State differential mode pattern three times are as follows:
Plumb line method of loci is introduced, Δ δ ' is chosenHSearch range and step-length with Δ v', by between the adjacent PS point of control
The suitable Δ δ ' of multiple correlation coefficient γ search one by oneHWith Δ v', wherein
It regard linear deformation speed difference corresponding to the maximum value of the coherence factor and elevation amendment difference as parameter Estimation
Value, establishes adjustment function model, and the adjustment function model is,
Solve linear equation:
Pseudo- 3D phase unwrapping method specifically includes:
Delaunay triangulation network connection is done to the PS point and establishes the triangulation network, time dimension is connected by time relationship.
Residue points calculating is carried out along the side of the triangulation network.Residue points necessarily occur in some triangle, corresponding triangle
Certain point in the dual network of net.
The optimization initial value that space 2D phase unwrapping is done using time dimension disentanglement fruit is carried out using minimum Lp norm method
The optimal solution of space dimension.
Lambda algorithm is a kind of searching algorithm based on least-squares estimation adjustment, is currently widely applied be based on
GPS carrier phase is positioned, and the algorithm of appearance and orientation is surveyed.
Lambda algorithm specifically includes:
In n-1 width differential interferometry figure, the phase type of differential interferometry three times of the adjacent PS point of the triangulation network is formed into equation group:
It is denoted as y1=A1·a+B1·b。
Due to Matrix Properties, equation group intangibility, therefore, in y1=A1·a+B1Imitation observation equation y is added in b2=
A2·a+B2B constitutes y=Aa+Bb, whereinA2For 2*m null matrix, B2For
2*2 unit matrix.
It is acquired according to the principle of least square:
C=(A B)
It obtainsComplete cycle float solution, search for obtain the fixed solution of phase complete cycle using fuzziness decorrelation method
By the fixed solutionIt brings solution into and twines phase expression formulaIn reuse minimum two
Multiplication obtains:
After completing phase unwrapping, the Deformation Field is obtained by mutually high conversion and geocoding.
The embodiment of the present invention is described in detail below with reference to Fig. 2, Fig. 3, Fig. 4 and Fig. 5.
Survey region is Mao County, and Erlongshan Mountains is located in river blueness block handover region, under the influence of plate motion and rainfall, mudstone
The geological disasters such as stream take place frequently, and Chengdu surface configuration changes climate and geological conditions influence is smaller, are affected by culture,
The embodiment of the present invention uses the TerraSAR-X image of precision 1m, Mao County, Erlongshan Mountains and Chengdu image information and master map such as 1 institute of table
Show.
1 test block image information of table and master map
| Place | Initial time | Terminal time | Master map | Quantity |
| Mao County | 16/04/23 | 17/12/19 | 16/06/17 | 18 |
| Erlongshan Mountains | 14/04/04 | 15/04/02 | 14/11/21 | 15 |
| Chengdu | 14/05/20 | 16/09/02 | 15/01/17 | 14 |
Fig. 2 and Fig. 3 illustrates the PS point triangular network in Mao County trial zone and Mao County area, includes apparent 7 in region
Electric power pylon, PS point screening technique use amplitude deviation and coherence factor Integrated Selection, obvious striped in the differential interferometry figure of Mao County
Appear in steel tower, rock and ridge region.
Fig. 4 and Fig. 5 illustrates the differential interferometry figure of Erlongshan Mountains and In Chengdu, in the region of Erlongshan Mountains it is affected by noise compared with
Greatly, interference fringe is only present in steel tower part, and Chengdu region is typical Plain urban area, in left side culture's the commercial house
Area, the middle of the road line take out existing obvious interference fringe.
Network adjustment method, puppet 3D phase unwrapping method and Lambda are used to the differential interferometry figure in Mao County, Erlongshan Mountains and Chengdu
Algorithm carries out solution and twines processing, wherein Mao County region linear deformation amount and elevation correction value are as shown in tables 2 and 3.
2 Mao County PS point Linear deformation rate of table is distributed mm/y
| v≤-2 | -2<v≤-1 | -1<v≤0 | 0<v≤1 | 1<v≤2 | v>2 | |
| Network adjustment | 0.0313 | 0.247 | 0.2615 | 0.2206 | 0.2181 | 0.0306 |
| Pseudo- 3D | 0.0218 | 0.2517 | 0.2664 | 0.2254 | 0.2224 | 0.0215 |
| Lambda | 0 | 0.1889 | 0.3510 | 0.2891 | 0.1801 | 0 |
3 Mao County elevation correction value m of table
| h≤-15 | -15<h≤-8 | -8<h≤0 | 0<h≤8 | 8<h≤15 | h>15 | |
| Network adjustment | 0 | 0.0367 | 0.4145 | 0.5073 | 0.0415 | 0 |
| Lambda | 0 | 0.1984 | 0.2653 | 0.3179 | 0.2184 | 0 |
As seen from the table, Mao County rate of deformation is uniformly distributed, and PS point Ground Deformation performance lifting or downward trend are unified, tower
Body region has obvious rise to sink to changing, and elevation correction value deviation trend is unified, and both of which can get trusted elevation knot
Fruit.
Erlongshan Mountains regional deformation rate concentrates in -5~+7mm/y range, and 80% or more is distributed within the scope of ± 5mm/y,
Ascendant trend is presented in PS point more than half, and the PS point in steel tower region is stablized in 0mm/y or so, has stability, wherein 3D phase
Position solution twines algorithm resolving rate and more concentrates relatively.Elevation correction value is distributed within the scope of ± 10m, and Lambda algorithm is more than 80% collection
In in ± 5m.In electric power pylon region, there is network adjustment smaller elevation to correct difference, more confidence level.Chengdu region
The PS dot variable of rate of deformation 90% concentrates within the scope of ± 2.5mm/y, algorithms of different have certain proportion across 2.5~
5mm/y has the point greater than 5mm/y deformation.Horizontal road region all show as it is unified it is stage rise or fall, elevation amendment
Value 85% concentrates within the scope of ± 10m, and network adjustment method calculates the sparse elevation correction value of about 40m or so, this elevation
Amendment may be built by commodity building in region to be formed.
Erlongshan Mountains elevation correction value is minimum, and it is related to be chronically at no developing zone with Erlongshan Mountains.There is artificial trace in Mao County area
Mark and crustal movement combined influence, elevation also has to be changed to a certain degree.The elevation of In Chengdu has discrete sharp point, is built by city
If work causes.
Table 4, table 5 and table 6 illustrate deformation of the earliest auxiliary image with respect to master image in three regions and are distributed.
4 Mao County deformation quantity of table counts mm
| d≤-2.4 | -2.4<d≤-1.2 | -1.2<d≤0 | 0<d≤1.2 | 1.2<d≤2.4 | d>2.4 | |
| Network adjustment | 0.098 | 0.275 | 0.164 | 0.147 | 0.214 | 0.099 |
| Pseudo- 3D | 0.083 | 0.225 | 0.156 | 0.170 | 0.283 | 0.082 |
| Lambda | 0.004 | 0.319 | 0.220 | 0.180 | 0.273 | 0.002 |
5 Erlongshan Mountains deformation quantity of table counts mm
| d≤-4.5 | -4.5<d≤-3 | -3<d≤0 | 0<d≤3 | 3<d≤4.5 | d>4.5 | |
| Network adjustment | 0 | 0 | 0.4845 | 0.515 | 0 | 0 |
| Pseudo- 3D | 0 | 0 | 0.545 | 0.455 | 0 | 0 |
| Lambda | 0.005 | 0.035 | 0.416 | 0.504 | 0.037 | 0.003 |
6 Chengdu deformation quantity of table counts cm
| d≤-6 | -6<d≤-3 | -3<d≤0 | 0<d≤3 | 3<d≤6 | d>6 | |
| Network adjustment | 0 | 0.0865 | 0.4930 | 0.3301 | 0.0904 | 0 |
| Pseudo- 3D | 0 | 05230 | 0.5097 | 0.4553 | 0 | 0 |
| Lambda | 0 | 0.001 | 0.4368 | 0.5581 | 0.0040 | 0 |
In each research area, PS point in SAR image maximum imaging time interval have total deformation distribution, trend with
Linear deformation rate is related to time interval.The deformation of maximum ± 30mm occurs for Mao County, and nearly 60% PS point deformation is in ± 12mm
In deformation range.- 30~24mm deformation occurs for Erlongshan Mountains, and 70% deformation concentrates between ± 12mm.Chengdu occurs maximum
The deformation of 120mm, most of PS dot changes are distributed within the scope of 30m.By Sichuan Electric Power Network artificial line walking record show Mao County and
An iron rake with three to six teeth periphery is transmitted electricity in image imaging time as occurrence of large-area geological disaster in Erlongshan Mountains, does not also have collapse of iron tower case, says
Bright deformation, which is extracted, has confidence level, and steel tower is not threatened by deformation safely.
The specific embodiment of invention described above is not intended to limit the scope of the present invention..
Claims (6)
1. a kind of alpine terrain deformation extracting method based on PSInSAR technology characterized by comprising
SAR image is chosen, the SAR image includes master image and auxiliary image；
Using the master image and the auxiliary image registration and interference processing is carried out, obtains coherence factor figure and interferometric phase image；
PS point is chosen on the coherence factor figure using amplitude deviation and the dual thresholds method of coherence factor, obtains PS point triangle
Net；
The interferometric phase image is subjected to flat filtering processing, the interferometric phase image carries out to treated using dem data
Differential interferometry processing, obtains differential interferometry figure；
Phase unwrapping processing is carried out to the differential interferometry figure, obtains Deformation Field.
2. the alpine terrain deformation extracting method according to claim 1 based on PSInSAR technology, which is characterized in that choosing
SAR image is taken to specifically include:
N width SAR image is chosen, selects the width in the SAR image as the master image using comprehensive coherence factor method,
Remaining n-1 width is as the auxiliary image.
3. the alpine terrain deformation extracting method according to claim 2 based on PSInSAR technology, which is characterized in that right
The differential interferometry figure carries out phase unwrapping processing and specifically includes:
It is utilized respectively network adjustment method, puppet 3D phase unwrapping method and Lambda algorithm and phase unwrapping is carried out to the differential interferometry figure
Processing.
4. the alpine terrain deformation extracting method according to claim 3 based on PSInSAR technology, which is characterized in that institute
Network adjustment method is stated to specifically include:
The differential mode pattern three times of PS point is established, the coherence factor K in the differential mode pattern three times is calculated1,K2,B⊥, described three
Secondary differential mode pattern are as follows:
Plumb line method of loci is introduced, Δ δ ' is chosenHSearch range and step-length with Δ v' pass through answering between the adjacent PS point of control
The suitable Δ δ ' of related coefficient γ search one by oneHWith Δ v', wherein
It regard linear deformation speed difference corresponding to the maximum value of the coherence factor and elevation amendment difference as estimates of parameters, builds
Vertical adjustment function model, the adjustment function model be,
Solve linear equation:
5. the alpine terrain deformation extracting method according to claim 4 based on PSInSAR technology, which is characterized in that institute
Pseudo- 3D phase unwrapping method is stated to specifically include:
Delaunay triangulation network connection is done to the PS point and establishes the triangulation network, time dimension is connected by time relationship；
Residue points calculating is carried out along the side of the triangulation network；
The optimization initial value that space 2D phase unwrapping is done using time dimension disentanglement fruit carries out space using minimum Lp norm method
Tie up optimal solution.
6. the alpine terrain deformation extracting method according to claim 5 based on PSInSAR technology, which is characterized in that institute
Lambda algorithm is stated to specifically include:
In n-1 width differential interferometry figure, the phase type of differential interferometry three times of the adjacent PS point of the triangulation network is formed into equation group:
It is denoted as y1=A1·a+B1·b；
In y1=A1·a+B1Imitation observation equation y is added in b2=A2·a+B2B constitutes y=Aa+Bb, wherein A2For 2*m null matrix, B2For 2*2 unit matrix；
It is acquired according to the principle of least square:
It obtainsComplete cycle float solution, search for obtain the fixed solution of phase complete cycle using fuzziness decorrelation method
By the fixed solutionIt brings solution into and twines phase expression formula In reuse least square method and obtain
It arrives:
After completing phase unwrapping, the Deformation Field is obtained by mutually high conversion and geocoding.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811123711.2A CN109031301A (en) | 2018-09-26 | 2018-09-26 | Alpine terrain deformation extracting method based on PSInSAR technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811123711.2A CN109031301A (en) | 2018-09-26 | 2018-09-26 | Alpine terrain deformation extracting method based on PSInSAR technology |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109031301A true CN109031301A (en) | 2018-12-18 |
Family
ID=64618086
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811123711.2A Withdrawn CN109031301A (en) | 2018-09-26 | 2018-09-26 | Alpine terrain deformation extracting method based on PSInSAR technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109031301A (en) |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109489625A (en) * | 2018-12-20 | 2019-03-19 | 国家测绘地理信息局第六地形测量队 | A kind of urban area Ground Deformation monitoring method |
| CN110568440A (en) * | 2019-09-10 | 2019-12-13 | 四川省地质工程勘察院集团有限公司 | method for monitoring deformation of complex mountain area based on DS-InSAR technology |
| CN111059998A (en) * | 2019-12-31 | 2020-04-24 | 中国地质大学（北京） | High-resolution-based time sequence InSAR deformation monitoring method and system |
| CN111308468A (en) * | 2019-11-27 | 2020-06-19 | 北京东方至远科技股份有限公司 | Method for automatically identifying deformation risk area based on In SAR technology |
| CN111537999A (en) * | 2020-03-04 | 2020-08-14 | 云南电网有限责任公司电力科学研究院 | Robust and efficient decomposition projection automatic focusing method |
| CN111598929A (en) * | 2020-04-26 | 2020-08-28 | 云南电网有限责任公司电力科学研究院 | Two-dimensional unwrapping method based on time sequence differential interference synthetic aperture radar data |
| CN112213723A (en) * | 2020-09-11 | 2021-01-12 | 速度时空信息科技股份有限公司 | Method for monitoring landslide in real time by using SBAS technology |
| CN112268517A (en) * | 2020-10-13 | 2021-01-26 | 内蒙古电力(集团)有限责任公司乌海超高压供电局 | Method for monitoring deformation of power transmission tower equipment by PSInSAR |
| CN112363166A (en) * | 2020-12-10 | 2021-02-12 | 长安大学 | InSAR phase unwrapping method and system based on reliable redundant network |
| CN112698328A (en) * | 2020-11-30 | 2021-04-23 | 四川大学 | Phase unwrapping method and system for monitoring dam and landslide deformation GB-SAR |
| CN113191374A (en) * | 2021-05-19 | 2021-07-30 | 甘肃省地震局（中国地震局兰州地震研究所） | PolSAR image ridge line extraction method based on pyramid attention network |
| CN113311433A (en) * | 2021-05-28 | 2021-08-27 | 北京航空航天大学 | InSAR interferometric phase two-step unwrapping method combining quality map and minimum cost flow |
| CN113866765A (en) * | 2021-09-24 | 2021-12-31 | 中国科学院精密测量科学与技术创新研究院 | PS-InSAR measurement method based on multi-component time coherent model |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102608601A (en) * | 2012-03-08 | 2012-07-25 | 北京北科安地科技发展有限公司 | Method for recognizing artificial corner reflector in SAR (synthetic aperture radar) image |
| CN105425236A (en) * | 2015-11-24 | 2016-03-23 | 中清能绿洲科技股份有限公司 | Automatic topographic surveying apparatus based on synthetic aperture radar imaging |
| CN106023157A (en) * | 2016-05-10 | 2016-10-12 | 电子科技大学 | Mountain area surface micro deformation information extraction method based on SAR images |
| CA3012551A1 (en) * | 2016-02-03 | 2017-08-10 | Deutsches Zentrum Fur Luft - Und Raumfahrt E.V. | Method for calibrating an active sensor system |
| CN107132539A (en) * | 2017-05-03 | 2017-09-05 | 中国地质科学院探矿工艺研究所 | Landslide early-stage identification method of time sequence InSAR (interferometric synthetic Aperture Radar) based on small baseline set |
-
2018
- 2018-09-26 CN CN201811123711.2A patent/CN109031301A/en not_active Withdrawn
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102608601A (en) * | 2012-03-08 | 2012-07-25 | 北京北科安地科技发展有限公司 | Method for recognizing artificial corner reflector in SAR (synthetic aperture radar) image |
| CN105425236A (en) * | 2015-11-24 | 2016-03-23 | 中清能绿洲科技股份有限公司 | Automatic topographic surveying apparatus based on synthetic aperture radar imaging |
| CA3012551A1 (en) * | 2016-02-03 | 2017-08-10 | Deutsches Zentrum Fur Luft - Und Raumfahrt E.V. | Method for calibrating an active sensor system |
| CN106023157A (en) * | 2016-05-10 | 2016-10-12 | 电子科技大学 | Mountain area surface micro deformation information extraction method based on SAR images |
| CN107132539A (en) * | 2017-05-03 | 2017-09-05 | 中国地质科学院探矿工艺研究所 | Landslide early-stage identification method of time sequence InSAR (interferometric synthetic Aperture Radar) based on small baseline set |
Non-Patent Citations (1)
| Title |
|---|
| 唐李: ""基于InSAR的输电通道地形形变提取研究"", 《中国优秀博硕士学位论文全文数据库（硕士） 工程科技Ⅱ辑》 * |
Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109489625A (en) * | 2018-12-20 | 2019-03-19 | 国家测绘地理信息局第六地形测量队 | A kind of urban area Ground Deformation monitoring method |
| CN110568440A (en) * | 2019-09-10 | 2019-12-13 | 四川省地质工程勘察院集团有限公司 | method for monitoring deformation of complex mountain area based on DS-InSAR technology |
| CN111308468A (en) * | 2019-11-27 | 2020-06-19 | 北京东方至远科技股份有限公司 | Method for automatically identifying deformation risk area based on In SAR technology |
| CN111059998A (en) * | 2019-12-31 | 2020-04-24 | 中国地质大学（北京） | High-resolution-based time sequence InSAR deformation monitoring method and system |
| CN111537999A (en) * | 2020-03-04 | 2020-08-14 | 云南电网有限责任公司电力科学研究院 | Robust and efficient decomposition projection automatic focusing method |
| CN111537999B (en) * | 2020-03-04 | 2023-06-30 | 云南电网有限责任公司电力科学研究院 | Robust and efficient decomposition projection automatic focusing method |
| CN111598929B (en) * | 2020-04-26 | 2023-02-17 | 云南电网有限责任公司电力科学研究院 | Two-dimensional unwrapping method based on time sequence differential interference synthetic aperture radar data |
| CN111598929A (en) * | 2020-04-26 | 2020-08-28 | 云南电网有限责任公司电力科学研究院 | Two-dimensional unwrapping method based on time sequence differential interference synthetic aperture radar data |
| CN112213723A (en) * | 2020-09-11 | 2021-01-12 | 速度时空信息科技股份有限公司 | Method for monitoring landslide in real time by using SBAS technology |
| CN112268517A (en) * | 2020-10-13 | 2021-01-26 | 内蒙古电力(集团)有限责任公司乌海超高压供电局 | Method for monitoring deformation of power transmission tower equipment by PSInSAR |
| CN112698328A (en) * | 2020-11-30 | 2021-04-23 | 四川大学 | Phase unwrapping method and system for monitoring dam and landslide deformation GB-SAR |
| CN112363166A (en) * | 2020-12-10 | 2021-02-12 | 长安大学 | InSAR phase unwrapping method and system based on reliable redundant network |
| CN112363166B (en) * | 2020-12-10 | 2023-08-22 | 长安大学 | InSAR phase unwrapping method and system based on reliable redundant network |
| CN113191374A (en) * | 2021-05-19 | 2021-07-30 | 甘肃省地震局（中国地震局兰州地震研究所） | PolSAR image ridge line extraction method based on pyramid attention network |
| CN113311433B (en) * | 2021-05-28 | 2022-08-02 | 北京航空航天大学 | InSAR interferometric phase two-step unwrapping method combining quality map and minimum cost flow |
| CN113311433A (en) * | 2021-05-28 | 2021-08-27 | 北京航空航天大学 | InSAR interferometric phase two-step unwrapping method combining quality map and minimum cost flow |
| CN113866765A (en) * | 2021-09-24 | 2021-12-31 | 中国科学院精密测量科学与技术创新研究院 | PS-InSAR measurement method based on multi-component time coherent model |
| CN113866765B (en) * | 2021-09-24 | 2022-12-13 | 中国科学院精密测量科学与技术创新研究院 | PS-InSAR measurement method based on multi-component time coherent model |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109031301A (en) | Alpine terrain deformation extracting method based on PSInSAR technology | |
| Dawei et al. | Unmanned aerial vehicle (UAV) photogrammetry technology for dynamic mining subsidence monitoring and parameter inversion: A case study in China | |
| CN106772377A (en) | A kind of building deformation monitoring method based on InSAR | |
| Barbarella et al. | Monitoring of large landslides by Terrestrial Laser Scanning techniques: field data collection and processing | |
| CN101551455B (en) | 3D terrain imaging system of interferometric synthetic aperture radar and elevation mapping method thereof | |
| Bovenga et al. | Application of multi-temporal differential interferometry to slope instability detection in urban/peri-urban areas | |
| Catalão et al. | Merging GPS and atmospherically corrected InSAR data to map 3-D terrain displacement velocity | |
| CN110456346A (en) | A kind of electric power pylon inclination monitoring method based on InSAR technology | |
| CN105954747A (en) | Tower foundation stability analyzing method based on three-dimensional deformation monitoring of unfavorable geologic body of power grid | |
| CN109212522B (en) | High-precision DEM inversion method and device based on double-base satellite-borne SAR | |
| CN101770027A (en) | Ground surface three-dimensional deformation monitoring method based on InSAR and GPS data fusion | |
| Liu et al. | Surface displacement and topographic change analysis of the Changhe landslide on September 14, 2019, China | |
| Zeybek et al. | Accurate determination of the Taşkent (Konya, Turkey) landslide using a long-range terrestrial laser scanner | |
| CN105824022A (en) | Method for monitoring three-dimensional deformation of unfavorable geologic body under power grid | |
| Herzog et al. | Least-cost kernel density estimation and interpolation-based density analysis applied to survey data | |
| CN107180448A (en) | A kind of mining area DEM change detecting methods based on earth's surface invariant features | |
| Abdulrahman | Determination of the local geoid model in Duhok Region, University of Duhok Campus as a Case study | |
| CN114674277B (en) | Deep mining earth surface subsidence monitoring method by combining full-field survey lines | |
| CN113238228A (en) | Level constraint-based InSAR three-dimensional surface deformation acquisition method, system and device | |
| CN109166084A (en) | A kind of SAR geometric distortion quantitative simulation method based on neighbor point gradient relation | |
| CN110310370A (en) | A method of realizing that GPS is merged with SRTM point face based on integral adjustment | |
| CN113008202B (en) | Ground settlement monitoring method integrating different synthetic aperture radar interferometry | |
| CN111398958B (en) | Method for determining correlation between ground settlement and building height of loess excavation area | |
| Pérez-Falls et al. | Land subsidence in Villahermosa Tabasco Mexico, using radar interferometry | |
| He et al. | Integration of InSAR and GPS for hydraulic engineering |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20181218 |