CN115980751A - Power law model InSAR troposphere delay correction method - Google Patents
Power law model InSAR troposphere delay correction method Download PDFInfo
- Publication number
- CN115980751A CN115980751A CN202310070011.6A CN202310070011A CN115980751A CN 115980751 A CN115980751 A CN 115980751A CN 202310070011 A CN202310070011 A CN 202310070011A CN 115980751 A CN115980751 A CN 115980751A
- Authority
- CN
- China
- Prior art keywords
- delay
- troposphere
- phase
- power law
- insar
- 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.)
- Pending
Links
- 239000005436 troposphere Substances 0.000 title claims abstract description 44
- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000012937 correction Methods 0.000 title claims abstract description 28
- 238000012950 reanalysis Methods 0.000 claims abstract description 11
- 238000011160 research Methods 0.000 claims abstract description 9
- 238000012545 processing Methods 0.000 claims abstract description 7
- 230000001427 coherent effect Effects 0.000 claims description 9
- 238000011835 investigation Methods 0.000 claims description 7
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical group O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000012952 Resampling Methods 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 3
- 230000000007 visual effect Effects 0.000 claims description 3
- 238000001914 filtration Methods 0.000 abstract 1
- 230000000694 effects Effects 0.000 description 7
- 238000012544 monitoring process Methods 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 241001420622 Meris Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000001934 delay Effects 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000009440 infrastructure construction Methods 0.000 description 1
- 239000005433 ionosphere Substances 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000013517 stratification Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The invention discloses a troposphere delay correction method of a power law model InSAR, which is added in the process of processing data by a time series InSAR. Calculating the dry delay and the wet delay of the atmosphere in the research area by utilizing a fifth generation atmosphere reanalysis data set of the global climate released by a European middle-term weather forecast center, and then obtaining the total zenith delay of the SAR image; then, power law parameters alpha and reference elevation h are estimated for troposphere delay obtained by calculation of ERA-5 through a fitting method c (ii) a Extracting the surface elevation h of each pixel element in the interference image from the used DEM; then, a space band-pass filtering method is used for estimating partial troposphere delay signals phi tropo Then the reference elevation h is calculated c Making difference with pixel surface elevation h, and adopting robust estimation method to estimate phase and topographic phase relationNumber K φ (ii) a Correlating the coefficient K according to a multiple weighting method φ Calculating into each pixel; and finally, calculating the troposphere delay phase of each interferogram.
Description
Technical Field
The invention belongs to the technical field of InSAR, and particularly relates to a power law model InSAR troposphere delay correction method based on ERA-5 reanalysis data.
Background
The InSAR technology is an interferogram obtained by covering the difference between phase values of two SAR image data obtained by repeated orbit observation at different moments in the same area, and obtained phase difference information is represented as the ground surface deformation condition. Compared with the traditional leveling method, the InSAR technology can measure the deformation of the earth surface in all weather, large range and high precision all day long, is one of the main technical means for monitoring the health of urban infrastructure gradually, is widely used for monitoring the deformation of the earth surface in various places in the world, and successfully identifies and monitors deformation signals which harm urban safety, such as a settlement funnel caused by underground water mining, non-uniform deformation caused by fault activity, earth surface settlement caused by infrastructure construction and the like.
Whether optical or radar remote sensing, atmospheric effects are unavoidable in satellite-to-ground monitoring systems. In radar remote sensing monitoring, when microwave signals emitted by satellites pass through the atmosphere at the time of two times of SAR imaging, delay phases with different degrees, namely atmospheric effects, can be generated under the influence of temperature, humidity, air pressure, wind speed and the like, so that the accuracy of InSAR in surface monitoring is restricted, and the method is one of main error sources.
For urban deformation monitoring in middle and low latitude areas, the ionosphere effect is small, and the troposphere effect in the atmospheric effect is used as one of main error sources for InSAR observation. The troposphere effect can be divided into vertical layering delay and turbulent mixing delay, wherein the vertical layering delay is caused by vertical refraction sections with different acquisition moments of two SAR images, mainly influences areas with large topographic relief, and has strong spatial correlation with the terrain; turbulent mixing delay is caused by the turbulent flow process of atmospheric water vapor, which results in the spatial distribution of the atmospheric refractive index being inconsistent in the horizontal and vertical directions in two observations.
At present, models based on spectrometer (MERIS, MODIS) atmospheric correction models, meteorological research and prediction models (WRF) and the like in the InSAR troposphere delay correction method can effectively correct turbulent mixing delay. In areas with large topographic relief, although the vertical layering delay can be corrected by the conventional linear model and the power law model, the conventional linear model and the power law model have the disadvantages. The traditional linear model correction method is based on a single interferogram, a simple relationship between a phase and an elevation is assumed, and a scale factor is a constant, so that the tropospheric delay of spatial variation cannot be estimated; the power law model correction method is a method for correcting vertical layering delay after estimating power law parameters by utilizing sounding balloon data, but the power law model atmospheric correction method cannot be used in areas without sounding balloon data.
Therefore, the power law model InSAR troposphere delay correction method based on the ERA-5 is provided.
Disclosure of Invention
In order to solve the problem that a power law model method cannot be used due to lack of sounding balloon data, the invention provides a power law model InSAR troposphere delay correction method based on ERA-5 reanalysis data;
in order to achieve the technical purpose, the invention is realized by the following technical scheme:
an ERA-5 reanalysis data-based power law model InSAR troposphere delay correction method is realized by the following steps:
s1: collecting data sets of N SAR single-view complex images, selecting one of the images as a main image, and taking the rest N-1 images as auxiliary images;
s2: carrying out image registration and resampling on the N-1 auxiliary images and the main image, and generating N interferograms after preprocessing; after processing is carried out by utilizing an external DEM, removing a terrain phase, and finally generating a differential interference pattern;
s3: selecting coherent points, and screening out high-coherence target points;
s4: carrying out phase unwrapping on the selected coherent point target to obtain a differential interference phase after unwrapping each coherent point;
s5: performing troposphere delay correction by using an ERA-5 meteorological reanalysis data dataset, and calculating dry delay and wet delay of a troposphere in a research area;
s6: analyzing the relationship between the tropospheric delay phase corrected by the ERA-5 re-analysis data set and the terrain elevation, and fitting the required power law parameter alpha and the reference elevation h by using the obtained relationship between the tropospheric delay phase and the elevation c Finally, troposphere delay correction is carried out by utilizing a power law model;
s7: after the vertical layering delay is corrected, an InSAR time sequence result is generated.
Preferably, the specific technical method in S5 is as follows:
adopting an expression:
the refractive index of the atmosphere due to dry retardation in the investigation region was calculated,
it is calculated that the refractive index of the atmosphere, -based on the wet delay in the investigation region>
Calculating the atmospheric refractive index N of the troposphere; wherein, K 1 ＝0.776Kpa -1 ，K 2 ＝0.716Kpa -1 ，K 3 ＝3.75*10 5 K 2 pa -1 P is total pressure, T is temperature, and e is water vapor partial pressure;
the tropospheric dry and wet retardations are obtained by integrating the refractive indices:
adopting an expression:
calculating the delay of the radar visual line to the troposphere in the research area,
the total delay of the radar visual line to the troposphere in the research area is calculated,
calculating tropospheric delay of the interferogram; wherein it is present>
Conversion factor for pseudo range to add to phase delay, θ is angle of incidence, h top Is troposphere zenith, and h is surface elevation;
preferably, an expression is adopted in S6:
h<h c (ii) a K is a scale factor between the estimated tropospheric delay phase and the reference elevation; />
Is a constant deviation term, is the height h c The delay phase of time.
The beneficial effects of the invention are:
according to the InSAR troposphere delay correction method provided by the invention, by utilizing the advantage that EAR-5 re-analysis data set data is acquired without charge globally, the power law model can be applied in different time periods and under different atmospheric conditions, the vertical layering delay caused by large topographic relief is effectively corrected, and the accuracy of surface deformation detection is improved.
Drawings
Fig. 1 is a processing flow chart of the time series InSAR technique method of the present invention.
Fig. 2 is a flow chart of the power law model InSAR troposphere delay correction method based on ERA-5 provided by the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides an ERA-5-based power law model InSAR troposphere correction method, which is an atmospheric delay correction method used when the topographic relief is large and the troposphere delay and the elevation show high correlation. Adding a troposphere delay correction method in the process of processing time series InSAR data, and removing vertical stratification delay according to the relationship between troposphere delay and elevation; wherein, ERA-5 meteorological reanalysis data set is adopted to estimate the troposphere phase of the researched area, if the estimated troposphere delay and the elevation have a power law relation, then parameters alpha and h in the power law model are estimated by utilizing the troposphere delay c And finally, correcting the vertical layered atmosphere delay by adopting a power law model correction method.
Example 1
Referring to fig. 1, the invention provides a time series InSAR technical method processing flow chart of an ERA-5-based power law model troposphere delay correction method, which comprises the following steps:
s1: collecting data sets of N SAR single-view complex images, selecting one image as a main image, and taking the rest N-1 images as auxiliary images;
s2: carrying out image registration and resampling on the N-1 auxiliary images and the main image, and generating N interferograms after preprocessing; after processing is carried out by utilizing an external DEM, removing a terrain phase, and finally generating a differential interference pattern;
s3: selecting coherent points, and screening out high-coherence target points;
s4: carrying out phase unwrapping on the selected coherent point target to obtain a differential interference phase after unwrapping each coherent point;
s5: tropospheric delay correction is performed using the ERA-5 meteorological reanalysis data dataset to calculate dry and wet delays for the troposphere in the study area, including:
adopting an expression:
the refractive index of the atmosphere due to dry retardation in the investigation region was calculated,
it is calculated that the refractive index of the atmosphere, -based on the wet delay in the investigation region>
Calculating the atmospheric refractive index N of the troposphere; wherein, K 1 ＝0.776Kpa -1 ，K 2 ＝0.716Kpa -1 ，K 3 ＝3.75*10 5 K 2 pa -1 P is total pressure, T is temperature, and e is water vapor partial pressure;
the tropospheric dry and wet retardations are obtained by integrating the refractive indices:
adopting an expression:
calculating the tropospheric stem delay,. Or `, in the investigation region>
the total tropospheric delay within the study volume is calculated,
tropospheric delay of the interferogram is calculated. Wherein the content of the first and second substances,
a conversion factor for pseudo-range to phase delay, theta is the angle of incidence, h top The troposphere zenith and the earth surface elevation.
S6: analyzing the relation between the tropospheric delay phase corrected by the ERA-5 re-analysis data set and the terrain elevation, and fitting the required power law parameter alpha and the reference elevation h by using the obtained relation between the tropospheric delay phase and the elevation c Finally, troposphere delay correction is carried out by utilizing a power law model;
adopting an expression: delta phi tropo ＝K(h c -h) α +Φ c ,h<h c (ii) a K is a scale factor, phi, between the estimated tropospheric delay phase and the reference elevation c Is a constant deviation term (height h) c Delayed phase of time).
S7: and generating an InSAR time sequence result after correcting the vertical layering delay.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (3)
1. A power law model InSAR troposphere delay correction method based on ERA-5 reanalysis data is characterized by comprising the following steps:
s1: collecting data sets of N SAR single-view complex images, selecting one image as a main image, and taking the rest N-1 images as auxiliary images;
s2: carrying out image registration and resampling on the N-1 auxiliary images and the main image, and generating N interferograms after preprocessing; after processing is carried out by utilizing an external DEM, removing a terrain phase, and finally generating a differential interference pattern;
s3: selecting coherent points, and screening out high-coherence target points;
s4: phase unwrapping is carried out on the selected coherent point target, and a differential interference phase after unwrapping of each coherent point is obtained;
s5: performing troposphere delay correction by using an ERA-5 meteorological reanalysis data dataset, and calculating dry delay and wet delay of a troposphere in a research area;
s6: analyzing the relation between the tropospheric delay phase corrected by the ERA-5 re-analysis data set and the terrain elevation, and fitting the required power law parameter alpha and the reference elevation h by using the obtained relation between the tropospheric delay phase and the elevation c Finally, troposphere delay correction is carried out by utilizing a power law model;
s7: and generating an InSAR time sequence result after correcting the vertical layering delay.
2. The method for power law model InSAR troposphere delay correction based on ERA-5 reanalysis data as claimed in claim 1, wherein the specific technical method in S5 is as follows:
adopting an expression:
the refractive index of the atmosphere due to dry retardation in the investigation region was calculated,
it is calculated that the refractive index of the atmosphere, -based on the wet delay in the investigation region>
Calculating the atmospheric refractive index N of the troposphere; wherein, K 1 ＝0.776Kpa -1 ，K 2 ＝0.716Kpa -1 ，K 3 ＝3.75*10 5 K 2 pa -1 P is total pressure, T is temperature, and e is water vapor partial pressure;
the tropospheric dry and wet retardations are obtained by integrating the refractive indices:
adopting an expression:
calculating the delay of the radar sight line to the troposphere in the research area,
the total delay of the radar visual line to the troposphere in the research area is calculated,
calculating tropospheric delay of the interferogram; wherein it is present>
Conversion factor for pseudo range to add to phase delay, θ is angle of incidence, h top Is the troposphere zenith and h is the earth's surfaceAnd (4) elevation.
3. The method for power law model InSAR tropospheric delay correction based on ERA-5 reanalysis data as claimed in claim 1, wherein the S6 adopts the expression:
k is a scale factor between the estimated tropospheric delay phase and the reference elevation; />
Is a constant deviation term, is the height h c The delay phase of time. />
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310070011.6A CN115980751A (en) | 2023-02-07 | 2023-02-07 | Power law model InSAR troposphere delay correction method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310070011.6A CN115980751A (en) | 2023-02-07 | 2023-02-07 | Power law model InSAR troposphere delay correction method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115980751A true CN115980751A (en) | 2023-04-18 |
Family
ID=85972404
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310070011.6A Pending CN115980751A (en) | 2023-02-07 | 2023-02-07 | Power law model InSAR troposphere delay correction method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115980751A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116338607A (en) * | 2023-05-19 | 2023-06-27 | 中国科学院空天信息创新研究院 | Time domain and space domain two-step InSAR troposphere delay correction method |
-
2023
- 2023-02-07 CN CN202310070011.6A patent/CN115980751A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116338607A (en) * | 2023-05-19 | 2023-06-27 | 中国科学院空天信息创新研究院 | Time domain and space domain two-step InSAR troposphere delay correction method |
| CN116338607B (en) * | 2023-05-19 | 2023-07-25 | 中国科学院空天信息创新研究院 | Time domain and space domain two-step InSAR troposphere delay correction method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Chen et al. | A new downscaling-integration framework for high-resolution monthly precipitation estimates: Combining rain gauge observations, satellite-derived precipitation data and geographical ancillary data | |
| CN109782282B (en) | Time series InSAR analysis method integrating troposphere atmospheric delay correction | |
| CN111078678B (en) | Satellite precipitation data correction method based on multi-source information fusion and scale reduction | |
| CN113205475B (en) | Forest height inversion method based on multi-source satellite remote sensing data | |
| Hunink et al. | A High-resolution Precipitation 2-step mapping Procedure (HiP2P): Development and application to a tropical mountainous area | |
| CN111125609A (en) | Ionized layer three-dimensional electron density reconstruction method based on double-exponential driving | |
| Löfgren et al. | Tropospheric correction for InSAR using interpolated ECMWF data and GPS zenith total delay from the Southern California integrated GPS network | |
| CN112444188B (en) | Multi-view InSAR sea wall high-precision three-dimensional deformation measurement method | |
| CN107037428A (en) | It is a kind of to improve the method that spaceborne dual station difference InSAR extracts deformation precision | |
| CN111856459A (en) | Improved DEM maximum likelihood constraint multi-baseline InSAR phase unwrapping method | |
| CN115980751A (en) | Power law model InSAR troposphere delay correction method | |
| CN117523404B (en) | Method, device, terminal and storage medium for monitoring dynamic change of storage yard | |
| CN115079172A (en) | MTInSAR landslide monitoring method, equipment and storage medium | |
| CN112711022B (en) | GNSS chromatography-assisted InSAR (interferometric synthetic aperture radar) atmospheric delay correction method | |
| Nitti et al. | On the use of COSMO/SkyMed data and Weather Models for interferometric DEM generation | |
| Zhang et al. | A new method for tropospheric tomography using GNSS and Fengyun-4A data | |
| Tang et al. | High-spatial-resolution mapping of precipitable water vapour using SAR interferograms, GPS observations and ERA-Interim reanalysis | |
| CN116029162B (en) | Flood disaster inundation range monitoring method and system by using satellite-borne GNSS-R data | |
| Wu et al. | Rice yield estimation based on spaceborne SAR: A review from 1988 to 2018 | |
| Miao et al. | Wet Tropospheric Correction Methods for Wide-Swath Altimeters | |
| CN115563582A (en) | Multi-scale evaluation method, device and system for geological risk along oil and gas pipeline | |
| Li | Production of Regional 1 km× 1 km Water Vapor Fields through the Integration of GPS and MODIS Data | |
| Chang et al. | InSAR atmospheric distortions mitigation: GPS observations and NCEP FNL data | |
| Fu et al. | Study on accuracy assessment of DEM in the marsh using with interferometric Palsar, SENTINEL-1A and Terrasar-X images | |
| Lombardi et al. | Accuracy of high resolution CSK interferometric Digital Elevation Models |
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 |