CN115015928B - High-efficiency polarization time sequence InSAR method based on total power co-scattering mechanism - Google Patents
High-efficiency polarization time sequence InSAR method based on total power co-scattering mechanism Download PDFInfo
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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
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- 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
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- G01S13/9023—SAR image post-processing techniques combined with interferometric techniques
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- 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
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- 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
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- G01S7/024—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using polarisation effects
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Abstract
The invention discloses a high-efficiency polarized time sequence InSAR method based on a total power same scattering mechanism, which comprises the steps of firstly acquiring a multi-polarized time sequence SAR image of a research monitoring area and preprocessing the SAR image; then, polarization optimization based on scattering mechanisms such as total power and the like is carried out on the interference pattern; finally, the interference phase after optimization of scattering mechanisms such as total power and the like is used for obtaining high-quality pixels as monitoring points according to a point selection criterion, removing track errors, DEM residual errors and atmospheric phases, carrying out three-dimensional phase unwrapping on the high-quality pixel monitoring points to obtain deformation quantity of the monitoring points, and completing deformation monitoring of a research area; the method has the characteristics of reliable monitoring results, high monitoring point density and high calculation efficiency, and can be well applied to quick, accurate and effective inversion of large-area surface deformation.
Description
Technical Field
The invention relates to the field of earth surface deformation monitoring methods, in particular to a high-efficiency polarization time sequence InSAR method based on a total power co-scattering mechanism.
Background
The traditional earth surface monitoring means such as leveling, triangular elevation measurement and GNSS technology have the defects of large working strength, limited measurement range, high monitoring cost and the like. With the rapid development of a synthetic aperture radar (Synthetic Aperture Radar, SAR for short), multi-mode aerospace SAR data with high space, high time resolution, multiple wave bands, multiple polarizations, multiple angles and the like provides rich data sources for earth observation, the continuous improvement of SAR image resolution and the unique advantages of the SAR image resolution all over the day and all weather are widely applied to the field of earth surface or infrastructure displacement monitoring related to urban earth surfaces, mining areas, earthquake deformation fields, volcanoes, landslides, underground coal fires and the like. In a cloudy rain and fog region and a region with difficult mapping, the SAR can solve the continuous monitoring problem which cannot be solved by optical remote sensing, so that the high-resolution SAR image plays an important role in disaster monitoring and evaluation, and the regular ground surface deformation monitoring becomes possible. However, due to the special imaging mechanism of SAR and the complex scattering characteristics of ground objects, the inversion accuracy of partial SAR image surface deformation is not high, and the requirement of processing a large amount of image data cannot be met, so that the application of SAR data is greatly limited.
The existing SAR image ground surface deformation inversion method is mostly based on amplitude data of single-band and single-polarized SAR images. The Polarimetric SAR (PolSAR) image contains abundant information, and the coherent scattering characteristics in different polarization channels contain the scattering mechanism of targets, so that the method has great advantages for accurately monitoring the surface deformation of the SAR image. The existing polarization time sequence InSAR technical method has contradiction between the earth surface deformation monitoring effect and the calculation efficiency. Therefore, the invention provides a high-efficiency polarized time sequence InSAR method based on a total power same scattering mechanism, which carries out phase weighted addition after giving different weights to different polarized interference phases by utilizing the time sequence average intensity of each polarized channel under the Puali base, and optimizes the interference phases. The method greatly reduces the operation time and improves the calculation efficiency while improving the interference phase quality, and can be well applied to monitoring the surface deformation in a large range.
Disclosure of Invention
Aiming at the technical defects, the invention aims to provide a high-efficiency polarization time sequence InSAR method based on a total power and scattering mechanism, which can effectively improve the density of monitoring points and the accuracy of deformation monitoring and provides a novel method for inverting the surface deformation.
In order to solve the technical problems, the invention adopts the following technical scheme:
the invention provides a high-efficiency polarization time sequence InSAR method based on a total power same scattering mechanism, which comprises the following steps:
s1: acquiring a multi-polarization time sequence SAR image of a research monitoring area, and preprocessing the SAR image;
s2: polarization optimization based on scattering mechanisms such as total power is carried out on the interference pattern, and the method specifically comprises the steps of S21-S24:
s21: constructing a polarized scattering vector under Pauli base according to the polarized scattering matrix;
s22: calculating differential interference phases of different polarizations;
s23: calculating a multi-polarization SAR time sequence average intensity value;
s24: interference pattern polarization optimization based on scattering mechanisms such as total power and the like;
s3: and obtaining high-quality pixels as monitoring points according to a point selection criterion through interference phases optimized by scattering mechanisms such as total power and the like, removing track errors, DEM residual errors and atmospheric phases, and carrying out three-dimensional phase unwrapping on the high-quality pixel monitoring points to obtain deformation amounts of the monitoring points, thereby completing deformation monitoring of a research area.
Preferably, in step S1, the process is performed,
the dual polarized satellite needs to acquire two polarized SAR data of VV and VH;
acquiring three polarized SAR data of HH, VV and cross polarization by the fully polarized satellite;
the multi-polarization sequential SAR image acquisition and preprocessing steps are as follows:
selecting a scene SAR image as a main image, and performing geocoding on different polarization SAR data of the main image; registering the rest SAR data with the main images under the respective polarization channels, wherein the registration precision is in sub-pixel level; and then cutting the registered SAR image data according to the research and monitoring requirements.
Preferably, in step S21, in order to make the elements of the obtained scattering vector closer to the physical characteristics of wave scattering, a Pauli base is selected to develop a scattering matrix S, and the scattering matrix S is constructed as follows:
wherein S represents a scattering matrix, S hh Represents HH poleSingle vision complex SAR image under chemical conversion S vv Represents a single vision complex SAR image under VV polarization, S vh Represents a single vision complex SAR image under VH polarization, S hv Representing single vision complex SAR images under HV polarization;
constructing scattering vector k under Pauli base for ith full-polarization PolSAR image data q，i The following are provided:
wherein q represents full polarization; s is S hh，i Represents the single vision complex SAR image under the ith HH polarization, S vv，i Represents the single vision complex SAR image under the ith VV polarization, S vh，i Represents the single vision complex SAR image under the ith VH polarization, and is based on the reciprocity theorem S vh ＝S hv Thus only using S vh，i Representing cross polarization, and T represents matrix transposition operation;
constructing Pauli-based scattering vector k for dual-polarized SAR image data containing HH and VV polarized channels d，i The following are provided:
construction of Pauli-based scattering vector k for dual polarized SAR image data comprising a co-polarized (HH, VV) and a cross-polarized (VH, HV) polarization channel d，i The following are provided:
k d，i ＝[S xx，i ，2S vh，i ] T
wherein d represents dual polarization; s is S xx，i Representing the single vision complex SAR image under the ith HH or VV polarization.
Preferably, in step S22, a polarization interference vector k is constructed from the polarization scattering vector as follows:
K＝[k 1 ，k 2 ]
k in 1 And k 2 Respectively representing polarization scattering vectors forming main and auxiliary images of the interference pattern;
for the full-polarization SAR image data, three Pauli base polarization channel lower interferograms are obtained through calculation:
I qP3 ＝2·S vh，1 ·S vh，2 *
in which I qP1 、I qP2 And I qP3 An interferogram representing the three polarized channels of full polarization, x being the complex conjugate operator;
and calculating the HH and VV dual-polarized SAR image data to obtain two Pauli base polarization channel lower interferograms:
in which I dP1 、I dP2 Representing an interferogram of two polarized channels of dual polarization;
for dual polarized SAR image data comprising a co-polarization (HH, VV) and a cross polarization (VH, HV), two Pauli base polarization channel lower interferograms are calculated:
I ddP1 ＝S xx，1 ·S xx，2 *
I ddP2 ＝4·S vh，1 ·S vh，2 *
in which I ddP1 、I ddP2 Representing an interference pattern that co-polarizes two polarized channels.
Preferably, in step S23, the step of generating a signal,
for the full-polarization SAR image data, the average intensity value is calculated as follows:
wherein N represents the number of single-view complex SAR images;
for HH and VV dual polarization SAR image data, calculation is neededAnd +.>
For dual polarized SAR image data comprising a co-polarization (HH, VV) and a cross-polarization (VH, HV), calculation is requiredCo-polarization->The calculation is as follows:
preferably, in step S24, different weights are given to different polarized interference phases by using the time sequence average intensity of each channel under the Puali base, and an average equal scattering mechanism is used to avoid introducing artificial time dimension change to the scattering body phase center and mixing the artificial time dimension change into the deformation phase;
for all-polarized SAR image data, total power and the likeThe method for optimizing the interference phase of the injection mechanism comprises the following steps:
in which I TP-ESM An interference pattern obtained by a scattering mechanism method such as total power and the like; phi (phi) qP1 、φ qP2 And phi qP3 Respectively Pauli base in I qP1 、I qP2 And I qP3 An interference phase corresponding to the interference pattern;
the interference optimization method for scattering mechanisms such as HH and VV dual-polarized SAR image data, total power and the like is as follows:
phi in dP1 And phi dP2 Respectively Pauli base in I dP1 And I dP2 An interference phase corresponding to the interference pattern;
for dual polarized SAR image data containing a common polarization (HH, VV) and a cross polarization (VH, HV), the interference optimization method of scattering mechanisms such as total power and the like is as follows:
phi in ddP1 And phi ddP2 Respectively Pauli base in I ddP1 And I ddP2 The interference phase corresponding to the interferogram.
The invention has the beneficial effects that: the method provided by the invention uses the time sequence average amplitude as the optimization weight, avoids the influence of speckle noise and SAR images with lower resolution, has the advantages of low calculation cost, high calculation efficiency, remarkable optimization effect and better optimization performance, and can obtain more monitoring point pixel density than the traditional monitoring method when being practically applied to large-area ground surface deformation monitoring, so as to obtain more reliable and accurate deformation monitoring results through inversion.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of an efficient polarization timing InSAR method based on the total power co-scattering mechanism provided in this embodiment;
FIG. 2 is a diagram A, B showing a comparison of details of differential interference before and after polarization optimization according to the present embodiment;
fig. 3 a and b are graphs showing TPC values before and after polarization optimization provided in this embodiment;
fig. 4 is a graph of TPC statistics before and after optimization provided in this embodiment.
FIG. 5 is a graph showing comparison of the results of monitoring sedimentation in time series before and after polarization optimization according to the present embodiment;
FIG. 6 is a view of a visible image of an Shanghai Pudong airport provided in this embodiment;
FIG. 7 b is a detailed comparison diagram of time-series sedimentation results before and after polarization optimization in region C;
FIG. 7 c is a detailed comparison graph of time-series sedimentation results before and after polarization optimization in the region D;
fig. 7 d is a detailed comparison graph of time-series sedimentation results before and after polarization optimization of the region E.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to verify the true effectiveness of the invention, a Shanghai Pudong airport in the Shanghai is selected as a research example, 34-scene dual-polarized Sentinel-1 data are obtained for experimental verification (33-scene interferograms are obtained by adopting a single main image mode), and the Sentinel-1 satellite SAR data have two polarized channel data of VV and VH. The specific embodiment is as follows:
step one: acquiring dual-polarized SAR image data and preprocessing
The method mainly comprises the following steps: the method comprises the steps of obtaining original VV and VH polarized SAR images, performing preprocessing such as geocoding, registration and clipping, and preparing for subsequent polarization optimization.
Step two: interference phase optimization based on a scattering mechanism such as total power;
according to the VV and VH polarized single vision complex images obtained by the pretreatment in the step one, pauli base is selected to construct a scattering matrix S as follows:
wherein S represents a scattering matrix, S vv Represents a single vision complex SAR image under VV polarization, S vh Representing the single view complex SAR image under VH polarization.
Composition of polarization scattering vector k under Pauli i ：
k i ＝[S vv，i ，2S vh，i ] T
S in vv，i Represents the single vision complex SAR image under the ith VV polarization, S vh，i Representing the single vision complex SAR image under the ith VH polarization, and T represents matrix transposition operation.
The polarization interference vector K is constructed from the polarization scattering vectors as follows:
K＝[k 1 ，k 2 ]
k in 1 And k 2 The polarized scattering vectors constituting the primary and secondary images of the interferogram are shown, respectively.
Based on the polarization interference vector K, two polarization channel interference patterns under Pauli base can be calculated respectively as follows:
I ddP1 ＝S vv，1 ·S vv，2 *
I ddP2 ＝4·S vh，1 ·S vh，2 *
in which I ddP1 And I ddP2 Respectively, the interferograms are complex conjugate operators.
The average intensity values under the different polarization channels are calculated as follows:
wherein N represents the number of the single-view complex SAR images, and I represents modulo.
And carrying out total power and other scattering mechanism interference pattern polarization optimization on the dual-polarized SAR data, wherein the formula is as follows:
in which I TP-ESM Representing the interference pattern, phi after optimization ddP1 And phi ddP2 Respectively is I ddP1 And I ddP2 Corresponding to the interference phase.
Finally, obtaining the interference patterns after polarization optimization, thereby obtaining 33 optimized interference patterns in the research area, wherein one interference pattern is shown in figure 2. The interference phase of the edge area of the airport terminal of the original interferogram (VV polarization) is fuzzy, the noise level is reduced after optimization, and the outline of the building is clearer (shown in figure 2A).
Compared with the original interferogram (VV polarization), the deformation fringe noise in the original interferogram is larger, the interference phase quality after polarization optimization is improved, and the deformation fringe is clearer (column of FIG. 2B).
Step three: deformation monitoring based on optimized interferograms
And selecting high-quality time sequence monitoring points based on the optimized time sequence differential interference diagram, removing track errors, DEM residual errors and atmospheric phase correction, then performing three-dimensional phase unwrapping to obtain deformation results of the monitoring points, and completing deformation monitoring of a detection area. In order to compare the monitoring effects of the method of the present invention with those of the conventional PS method (based on the VV polarization data of Sentinel-1) and the weighted average method of the present invention, in this embodiment, the conventional PS method and the optimization method proposed by the present invention are respectively used to process the SAR time-series image.
In order to quantitatively evaluate the polarization optimization effect of the differential interferogram, quantitative comparison analysis is carried out on the interferograms before and after the optimization of the research area by utilizing the interferogram phase quality evaluation index TPC (Temporal Phase Coherence). TPC uses the noise level of the pel in all generated interferograms to evaluate its phase quality, which can be calculated by:
wherein M is the number of interferograms, ψ noise，i Is the i-th interferogram corresponding to the noise phase. Psi phi type noise，i The window (15×15 window is taken in the study in consideration of SAR image resolution and surface coverage of the study area) is estimated based on the interference phase value of the field pixels.
As shown in fig. 3 and 4, the larger the TPC value corresponds to the better the interferogram phase quality. As can be seen from the phase quality evaluation index results, for the Shanghai Pudong airport research area, the phase quality of the interference atlas after optimization is obviously improved.
In the embodiment, the high-quality monitoring point pixel screening is carried out on the original interferogram and the interferogram of the optimization method by setting the TPC threshold value of 0.9. And (5) performing PS time sequence analysis by using open source software StaMPS to obtain a regional surface deformation monitoring result shown in figure 5.
As can be seen from fig. 5, the overall sedimentation trend monitored by both methods is consistent, laterally illustrating the reliability of the monitoring in accordance with aspects of the present invention. The monitoring points of the two monitoring methods are 29323 and 35790 respectively, the method of the invention improves the original interference result by 22%, the density of the monitoring points is greatly improved, and the earth surface deformation details of the example area can be better reflected. The monitoring results of partial local surface deformation are shown in fig. 6-7, and the density of the monitoring points can be obviously improved in the C, D area and the E area.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (2)
1. The high-efficiency polarization time sequence InSAR method based on the total power co-scattering mechanism is characterized by comprising the following steps of:
s1: acquiring a multi-polarization time sequence SAR image of a research monitoring area, and preprocessing the SAR image;
the dual polarized satellite needs to acquire two polarized SAR data of VV and VH;
acquiring three polarized SAR data of HH, VV and cross polarization by the fully polarized satellite;
s2: polarization optimization based on total power co-scattering mechanism is carried out on the interference pattern, and the method specifically comprises the following steps:
s21: constructing a polarized scattering vector under Pauli base according to the polarized scattering matrix;
in order to make the elements of the obtained scattering vector closer to the physical characteristics of wave scattering, pauli base is selected to spread a scattering matrix S, and the scattering matrix S is constructed as follows:
wherein S represents a scattering matrix, S hh Represents a single vision complex SAR image under HH polarization, S vv Represents a single vision complex SAR image under VV polarization, S vh Represents a single vision complex SAR image under VH polarization, S hv Representing single vision complex SAR images under HV polarization;
constructing scattering vector k under Pauli base for ith full-polarization PolSAR image data q，i The following are provided:
wherein q represents full polarization; s is S hh，i Represents the single vision complex SAR image under the ith HH polarization, S vv，i Represents the single vision complex SAR image under the ith VV polarization, S vh，i Represents the single vision complex SAR image under the ith VH polarization, and is based on the reciprocity theorem S vh ＝S hv Thus only using S vh，i Representing cross polarization, and T represents matrix transposition operation;
constructing Pauli-based scattering vector k for dual-polarized SAR image data containing HH and VV polarized channels d，i The following are provided:
construction of Pauli-based scattering vector k for dual polarized SAR image data containing a co-polarization, HH, VV, and a cross-polarization, VH, HV polarization channel d，i The following are provided:
k d，i ＝[S xx，i ，2S vh，i ] T
wherein d represents dual polarization; s is S xx，i Representing the single vision complex SAR image under the ith HH or VV polarization;
s22: calculating differential interference phases of different polarizations;
the polarization interference vector K is constructed from the polarization scattering vectors as follows:
K＝[k 1 ，k 2 ]
k in 1 And k 2 Respectively representing polarization scattering vectors forming main and auxiliary images of the interference pattern;
for the full-polarization SAR image data, three Pauli base polarization channel lower interferograms are obtained through calculation:
I qP3 ＝2·S vh，1 ·S vh，2 *
in which I qP1 、I qP2 And I qP3 An interferogram representing the three polarized channels of full polarization, x being the complex conjugate operator;
and calculating the HH and VV dual-polarized SAR image data to obtain two Pauli base polarization channel lower interferograms:
in which I dP1 、I dP2 Representing an interferogram of two polarized channels of dual polarization;
for dual polarized SAR image data containing one co-polarization, i.e. HH and VV, and one cross polarization, i.e. VH and HV, the following interference patterns of two Pauli base polarization channels are obtained by calculation:
I ddP1 ＝S xx，1 ·S xx，2 *
I ddP2 ＝4·S vh，1 ·S vh，2 *
in which I ddP1 、I ddP2 An interferogram representing co-polarized two polarized channels;
s23: calculating a multi-polarization SAR time sequence average intensity value;
for the full-polarization SAR image data, the average intensity value is calculated as follows:
wherein N represents the number of single-view complex SAR images;
for HH and VV dual polarization SAR image data, calculation is neededAnd +.>
For dual polarized SAR image data containing a co-polarization, i.e., HH, VV, and a cross polarization, i.e., VH, HV, calculation is neededCo-polarization-> The calculation is as follows:
s24: interference diagram polarization optimization based on total power and scattering mechanism;
the average intensity of each channel time sequence under the Puali base is utilized to endow different weight values to different polarized interference phases, and an average same scattering mechanism is used to avoid introducing artificial time dimension change to the scattering body phase center so as to be confused into a deformation phase;
for the full polarization SAR image data, the interference phase optimization method of the total power same scattering mechanism is as follows:
in which I TP-ESM An interference pattern obtained by a total power same scattering mechanism method; phi (phi) qP1 、φ qP2 And phi qP3 Respectively Pauli base in I qP1 、I qP2 And I qP3 An interference phase corresponding to the interference pattern;
for HH and VV dual polarization SAR image data, the total power same scattering mechanism interference optimization method comprises the following steps:
phi in dP1 And phi dP2 Respectively Pauli base in I dP1 And I dP2 An interference phase corresponding to the interference pattern;
for dual polarized SAR image data containing a common polarization, namely HH and VV, and a cross polarization, namely VH and HV, the total power co-scattering mechanism interference optimization method is as follows:
phi in ddP1 And phi ddP2 Respectively Pauli base in I ddP1 And I ddP2 An interference phase corresponding to the interference pattern;
s3: and obtaining high-quality pixels as monitoring points according to a point selection criterion through the interference phase after the total power and scattering mechanism are optimized, removing track errors, DEM residual errors and atmospheric phases, and carrying out three-dimensional phase unwrapping on the high-quality pixel monitoring points to obtain deformation quantity of the monitoring points, thereby completing deformation monitoring of a research area.
2. The method of high-efficiency polarized sequential InSAR based on total power co-scattering mechanism as claimed in claim 1, wherein in step S1, the steps of multi-polarized sequential SAR image acquisition and preprocessing are as follows:
selecting a scene SAR image as a main image, and performing geocoding on different polarization SAR data of the main image; registering the rest SAR data with the main images under the respective polarization channels, wherein the registration precision is in sub-pixel level; and then cutting the registered SAR image data according to the research and monitoring requirements.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0587919A (en) * | 1991-09-26 | 1993-04-09 | Nec Corp | Polarimetric synthetic aperture radar apparatus |
| US5489907A (en) * | 1993-09-24 | 1996-02-06 | Deutsche Forschungsanstalt Fur Luft- Und Raumfahrt E.V. | Airborne SAR system for determining the topography of a terrain |
| CN103870841A (en) * | 2014-03-11 | 2014-06-18 | 西安电子科技大学 | Polarization SAR (synthetic aperture radar) image classification method based on Freeman decomposition and PSO (particle swarm optimization) |
| CN107329139A (en) * | 2017-07-26 | 2017-11-07 | 邓少平 | A kind of pair of phase dual polarization interference SAR image water area extraction method |
| CN113091596A (en) * | 2021-03-31 | 2021-07-09 | 中国矿业大学 | Surface deformation monitoring method based on multi-polarization time sequence SAR data |
| CN114200450A (en) * | 2021-12-06 | 2022-03-18 | 国网湖南省电力有限公司 | Method for identifying landslide near power transmission channel based on dual-polarization time sequence SAR technology |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP6349938B2 (en) * | 2014-05-09 | 2018-07-04 | 日本電気株式会社 | Measuring point information providing apparatus, fluctuation detecting apparatus, method and program |
-
2022
- 2022-05-30 CN CN202210599229.6A patent/CN115015928B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0587919A (en) * | 1991-09-26 | 1993-04-09 | Nec Corp | Polarimetric synthetic aperture radar apparatus |
| US5489907A (en) * | 1993-09-24 | 1996-02-06 | Deutsche Forschungsanstalt Fur Luft- Und Raumfahrt E.V. | Airborne SAR system for determining the topography of a terrain |
| CN103870841A (en) * | 2014-03-11 | 2014-06-18 | 西安电子科技大学 | Polarization SAR (synthetic aperture radar) image classification method based on Freeman decomposition and PSO (particle swarm optimization) |
| CN107329139A (en) * | 2017-07-26 | 2017-11-07 | 邓少平 | A kind of pair of phase dual polarization interference SAR image water area extraction method |
| CN113091596A (en) * | 2021-03-31 | 2021-07-09 | 中国矿业大学 | Surface deformation monitoring method based on multi-polarization time sequence SAR data |
| CN114200450A (en) * | 2021-12-06 | 2022-03-18 | 国网湖南省电力有限公司 | Method for identifying landslide near power transmission channel based on dual-polarization time sequence SAR technology |
Non-Patent Citations (1)
| Title |
|---|
| "Phase Quality Optimization in Polarimetric Differential SAR Interferometry";Rubén Iglesias等;《IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,》;第52卷(第5期);2875-2888 * |
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| CN115015928A (en) | 2022-09-06 |
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