CN116736306B - Time sequence radar interference monitoring method based on third high-resolution - Google Patents
Time sequence radar interference monitoring method based on third high-resolution Download PDFInfo
- Publication number
- CN116736306B CN116736306B CN202311023457.XA CN202311023457A CN116736306B CN 116736306 B CN116736306 B CN 116736306B CN 202311023457 A CN202311023457 A CN 202311023457A CN 116736306 B CN116736306 B CN 116736306B
- Authority
- CN
- China
- Prior art keywords
- target area
- interference
- phase
- phase diagram
- substep
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 50
- 238000012544 monitoring process Methods 0.000 title claims abstract description 35
- 238000010587 phase diagram Methods 0.000 claims abstract description 89
- 238000004804 winding Methods 0.000 claims abstract description 68
- 238000012937 correction Methods 0.000 claims abstract description 18
- 238000012417 linear regression Methods 0.000 claims abstract description 11
- 238000005305 interferometry Methods 0.000 claims abstract description 7
- 238000001914 filtration Methods 0.000 claims description 16
- 238000010586 diagram Methods 0.000 claims description 10
- 238000005070 sampling Methods 0.000 claims description 4
- 238000012876 topography Methods 0.000 claims description 4
- 230000001427 coherent effect Effects 0.000 claims description 3
- 239000006185 dispersion Substances 0.000 claims description 3
- 238000004590 computer program Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000006424 Flood reaction Methods 0.000 description 1
- 238000007476 Maximum Likelihood Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
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
- 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
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- General Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention discloses a time sequence radar interference monitoring method based on a third high-resolution method, which relates to the field of radar interference monitoring, and comprises the following steps: obtaining an interference phase diagram of the target area by using a third high-resolution method; obtaining a winding interference phase diagram of the target area according to the interference phase diagram of the target area and the digital elevation model data; obtaining a winding interference phase diagram of a target area with dense stripes removed; according to polynomial fitting, a linear regression model and a winding interference phase diagram of the target area for removing dense stripes, obtaining a winding interference phase diagram of the target area after correction; and acquiring a time sequence deformation rate chart of the high-resolution third image of the target area by adopting a time sequence radar interferometry method according to the winding interference phase chart corrected by the target area so as to realize the monitoring of the target area. The method can improve the quality of the third interference phase diagram by correcting the track error and the baseline error, thereby realizing high-precision monitoring of the surface deformation of the target area.
Description
Technical Field
The invention relates to the field of radar interference monitoring, in particular to a time sequence radar interference monitoring method based on third high-order.
Background
The third high-resolution satellite is a first C-band, multi-polarization and high-resolution (up to 1 meter) synthetic aperture radar satellite in China, has the outstanding advantages of all-weather monitoring, high-precision measurement, multi-mode imaging and the like in all days, and can realize the monitoring of global ocean and land information in all weather and all days. The third high-pressure sensor is applied to monitoring disasters such as glacier sports, ground subsidence, earthquakes, landslides, debris flows, floods and the like in the field of natural disasters.
At present, the quality of an obtained high-resolution third-order image interference phase diagram is not high due to track errors and baseline errors in the field of radar interference monitoring, and therefore the high-resolution third-order image interference phase diagram cannot be fully utilized for time sequence deformation monitoring of a target area.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a time sequence radar interference monitoring method based on third high-resolution, which can improve the quality of the third high-resolution interference phase diagram by correcting the track error and the base line error, thereby realizing high-precision monitoring of the surface deformation of a target area.
In order to achieve the aim of the invention, the invention adopts the following technical scheme:
a time sequence radar interference monitoring method based on a third high-resolution method comprises the following steps:
s1, acquiring an interference phase diagram of a target area by using a third high-resolution method;
s2, obtaining a winding interference phase diagram of the target area according to the interference phase diagram of the target area and the digital elevation model data in the step S1;
s3, obtaining a winding interference phase diagram of the target area with dense stripes removed according to the ephemeris data and the winding interference phase diagram of the target area in the step S2;
s4, according to polynomial fitting, a linear regression model and the winding interference phase diagram of the target area with dense stripes removed in the step S3, obtaining a winding interference phase diagram after the target area is corrected;
s5, acquiring a time sequence deformation rate chart of the high-resolution third image of the target area by adopting a time sequence radar interferometry method according to the winding interference phase chart corrected by the target area in the step S4 so as to realize the monitoring of the target area.
Further, step S2 includes the following sub-steps:
s21, registering and interference combining the interference images of the target area in the step S1 to generate a single-view winding interference phase diagram of the target area;
s22, carrying out land leveling and topography correction on the single-view winding interference phase diagram of the target area in the bisection step S21 according to the digital elevation model data, and obtaining the winding interference phase diagram of the target area.
Further, step S3 includes the following sub-steps:
s31, according to ephemeris data, acquiring a first initial baseline of a winding interference phase diagram of a target area by using orbit state vector estimation;
s32, obtaining interference fringe frequency data, and obtaining a second initial baseline of a winding interference phase diagram of the target area according to the interference fringe frequency data;
s33, obtaining a winding interference phase diagram of the target area with dense stripes removed according to the first initial baseline in the substep S31 and the second initial baseline in the substep S32.
Further, step S31 includes the following sub-steps:
s311, fitting a time position curve of the satellite according to ephemeris data;
s312, calculating unknown parameters of the time position curve of the satellite in the substep S311 according to a least square method, and obtaining an orbit curve model of the satellite;
s313, acquiring a first initial baseline of a winding interference phase diagram of the target area according to the orbit curve model of the satellite in the substep S312.
Further, in substep S311, a time-position curve of the satellite is fitted, expressed as:
wherein:for the antenna centre +.>Axis coordinate value->For the antenna centre +.>Constant term coefficient of axis,/>For the antenna centre +.>Primary term coefficient of axis,/>For sampling point time, +.>For the antenna centre +.>Quadratic term coefficient of axis,/>For the antenna centre +.>The cubic term coefficient of the axis,/>For the antenna centre +.>Axis coordinate value->For the antenna centre +.>Constant term coefficient of axis,/>For the antenna centre +.>Primary term coefficient of axis,/>For the antenna centre +.>Quadratic term coefficient of axis,/>For the antenna centre +.>The cubic term coefficient of the axis,/>For the antenna centre +.>Axis coordinate value->For the antenna centre +.>Constant term coefficient of axis,/>For the antenna centre +.>Primary term coefficient of axis,/>For the antenna centre +.>Quadratic term coefficient of axis,/>For the antenna centre +.>The cubic term coefficient of the axis.
Further, step S4 includes the following sub-steps:
s41, performing phase unwrapping on the wrapping interference phase map with the dense stripes removed from the target area in the step S3 to obtain an unwrapped interference phase map of the target area;
s42, obtaining the residual phase of the track error according to the phase jump of the unwrapped interference phase diagram of the target area in the polynomial fitting substep S41;
s43, obtaining an atmospheric error by using a linear regression model according to the unwrapped interference phase diagram of the target area in the substep S41;
s44, obtaining a fitting result according to the residual phase of the orbit error in the polynomial fitting substep S42 and the atmospheric error in the substep S43;
s45, correcting the winding interference phase diagram with the dense stripes removed in the step S3 according to the fitting result in the substep S44, and obtaining a winding interference phase diagram corrected by the target area.
Further, in substep S42, the phase jump of the unwrapped interference phase map of the target area in substep S41 is fitted, and the residual phase of the track error is obtained, expressed as:
wherein:to unwrap track errors in the interferometric phase mapResidual phase->Is +.>Axis coordinates->Is +.>Axis coordinates->Is the first coefficient of the residual phase, +.>Is the second coefficient of the residual phase, +.>Is the third coefficient of the residual phase, +.>Is the fourth coefficient of the residual phase, +.>Is the fifth coefficient of the residual phase, +.>Is the sixth coefficient of the residual phase.
Further, in substep S43, the atmospheric error is obtained using a linear regression model, expressed as:
wherein:to unwrap atmospheric errors in the interferogram, +.>Is +.>The axis of the rotation is set to be at the same position,is +.>Axis coordinates->Is the first coefficient of atmospheric error, +.>Is a second coefficient of the atmospheric error,to unwrap elevation information in the interferometric phase map.
Further, step S5 includes the following sub-steps:
s51, selecting candidate points of a filtering phase coherence loss slow target point according to the amplitude difference dispersion index and the winding interference phase diagram corrected by the target area in the step S4;
s52, determining a phase error according to candidate points of the filtering phase loss coherent slow target point in the substep S51;
s53, determining a measure parameter of the pixel noise level according to the phase error in the substep S52;
s54, selecting a filtering phase incoherent slow target point according to the measure parameter of the pixel noise level in the substep S53 and the candidate point of the filtering phase incoherent slow target point in the substep S51;
s55, acquiring a time sequence deformation rate diagram of a high-resolution third image of the target area according to the filtering phase coherence loss slow target point in the substep S54, the 3D unwrapping method and the unwrapped interference phase diagram corrected by the target area in the step S4 so as to realize the monitoring of the target area.
The invention has the following beneficial effects:
(1) According to the method, the quality of the high-resolution third-order interference phase diagram is improved by correcting the track error and the baseline error, so that the high-precision monitoring of the surface deformation of the target area is realized;
(2) According to the invention, the first initial baseline and the second initial baseline of the winding interference phase diagram of the target area are obtained by utilizing the track state vector estimation and the interference fringe frequency data, the baseline error and the track error can be primarily corrected, and the winding interference phase diagram of the target area with dense fringes removed is obtained;
(3) According to the invention, the preliminarily corrected interference phase map is subjected to phase unwrapping, and the residual phase of the track error and the atmospheric error are fitted by utilizing a polynomial, so that the preliminarily corrected interference phase map can be subjected to further refined correction, and a winding interference phase map corrected by a target area is obtained;
(4) According to the invention, by adopting a time sequence radar interferometry method, the phase correction and the atmosphere correction can be carried out on the winding interference phase diagram corrected by the acquired target area, and the time sequence deformation rate diagram of the high-resolution third image of the target area is acquired, so that the effective monitoring of the target area is realized.
Drawings
Fig. 1 is a schematic flow chart of a time sequence radar interference monitoring method based on third high-resolution.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and all the inventions which make use of the inventive concept are protected by the spirit and scope of the present invention as defined and defined in the appended claims to those skilled in the art.
As shown in FIG. 1, a time sequence radar interference monitoring method based on third high-resolution method includes steps S1-S5, specifically as follows:
s1, obtaining an interference phase diagram of the target area by using the third high-resolution method.
In an alternative embodiment of the present invention, the present invention selects a target area to be monitored, and obtains an interference phase map of the target area using the third high score. The invention utilizes the interference phase map obtained by the third high-resolution method to have track errors and baseline errors, and only a small amount of interference phase map can be applied to the field of interference monitoring of the time sequence radar.
S2, obtaining a winding interference phase diagram of the target area according to the interference phase diagram of the target area and the digital elevation model data in the step S1.
In an optional embodiment of the invention, the invention generates a single-view winding interference phase diagram of the target area according to the interference phase diagram of the target area, and performs land leveling and topography correction according to the single-view winding interference phase diagram of the target area of the digital elevation model data to obtain the winding interference phase diagram of the target area.
Step S2 comprises the following sub-steps:
s21, registering and interference combining the interference phase map of the target area in the step S1 to generate a single-view winding interference phase map of the target area.
Specifically, the invention registers and combines interference phase diagrams of the target area to generate a single-view winding interference phase diagram of the target area.
S22, carrying out land leveling and topography correction on the single-view winding interference phase diagram of the target area in the bisection step S21 according to the digital elevation model data, and obtaining the winding interference phase diagram of the target area.
S3, obtaining a winding interference phase diagram of the target area with dense stripes removed according to the ephemeris data and the winding interference phase diagram of the target area in the step S2.
In an optional embodiment of the invention, according to the ephemeris data and the winding interference phase diagram of the target area, a method of combining state vector estimation and interference fringe frequency data is adopted to primarily correct track errors and baseline errors existing in the high-resolution three-number interference phase diagram, and the winding interference phase diagram of the target area with dense fringes removed is obtained.
Step S3 comprises the following sub-steps:
s31, according to ephemeris data, a first initial baseline of a winding interference phase diagram of the target area is obtained through orbit state vector estimation.
Step S31 includes the following sub-steps:
s311, fitting a time position curve of the satellite according to the ephemeris data.
The time position curve of the fitted satellite is expressed as:
wherein:for the antenna centre +.>Axis coordinate value->For the antenna centre +.>Constant term coefficient of axis,/>For the antenna centre +.>Primary term coefficient of axis,/>For sampling point time, +.>For the antenna centre +.>Quadratic term coefficient of axis,/>For the antenna centre +.>The cubic term coefficient of the axis,/>For the antenna centre +.>Axis coordinate value->For the antenna centre +.>Constant term coefficient of axis,/>For the antenna centre +.>Primary term coefficient of axis,/>For the antenna centre +.>Quadratic term coefficient of axis,/>For the antenna centre +.>The cubic term coefficient of the axis,/>For the antenna centre +.>Axis coordinate value->For the antenna centre +.>Constant term coefficient of axis,/>For the antenna centre +.>Primary term coefficient of axis,/>For the antenna centre +.>Quadratic term coefficient of axis,/>For the antenna centre +.>The cubic term coefficient of the axis.
Specifically, the method can obtain the position of the center of the antenna and the time of the sampling point in the satellite operation process recorded in the high-resolution three-number interference phase diagram according to ephemeris data, and can use the data to simulate the time position curve.
S312, calculating unknown parameters of the time position curve of the satellite in the substep S311 according to a least square method, and obtaining an orbit curve model of the satellite.
Specifically, the method acquires position point data of the centers of five antennas, and can solve position parameters in a time position curve, namely constant term coefficients, primary term coefficients, secondary term coefficients and tertiary term coefficients corresponding to coordinate axes according to a least square method, so as to acquire a satellite orbit curve model.
S313, acquiring a first initial baseline of a winding interference phase diagram of the target area according to the orbit curve model of the satellite in the substep S312.
S32, obtaining interference fringe frequency data, and obtaining a second initial baseline of a winding interference phase diagram of the target area according to the interference fringe frequency data.
Specifically, the invention can obtain interference fringe frequency data by a maximum likelihood estimation frequency method. The invention converts the winding interference phase diagram of the target area from a space domain to a frequency domain through a fast Fourier transform method to calculate interference fringe frequency, which is expressed as:
wherein:for the transformation of the winding interference phase diagram of the target area in the frequency domain +.>Is imaginary unit, ++>For track jump phase +.>For deformation phase +.>Is +.>Axis coordinates->Is +.>Axis coordinates->For distance frequency, ++>For the frequency of azimuth +.>Is the residual phase.
The invention can deduce the relation between the second initial baseline and the interference fringe frequency according to the fringe frequency, and further acquire the second initial baseline of the winding interference phase diagram of the target area according to the obtained interference fringe frequency data.
S33, obtaining a winding interference phase diagram of the target area with dense stripes removed according to the first initial baseline in the substep S31 and the second initial baseline in the substep S32.
S4, obtaining a winding interference phase diagram after the target area correction according to polynomial fitting, the linear regression model and the winding interference phase diagram of the target area with the dense stripes removed in the step S3.
In an alternative embodiment of the invention, the invention carries out phase unwrapping on the interference phase map after preliminary correction, and the unwrapped interference phase map after the correction of the target area is obtained according to polynomial fitting, linear regression model and the wrapping interference phase map with the dense stripes removed, which can fit the residual phase and atmospheric error of the orbit error and eliminate the nonlinear error in the orbit error, so as to carry out further refined correction on the interference phase map after the preliminary correction.
Step S4 comprises the following sub-steps:
s41, performing phase unwrapping on the wrapping interference phase map with the dense stripes removed from the target area in the step S3, and obtaining an unwrapped interference phase map of the target area.
S42, obtaining the residual phase of the track error according to the phase jump of the unwrapped interference phase diagram of the target area in the polynomial fitting substep S41.
The invention fits the phase jump of the unwrapped interference phase diagram of the target area in the substep S41, obtains the residual phase of the track error, and is expressed as:
wherein:for unwrapping the residual phase of the track error in the interferometric phase map,/for example>Is +.>Axis coordinates->Is +.>Axis coordinates->Is the first coefficient of the residual phase, +.>Is the second coefficient of the residual phase, +.>Is the third coefficient of the residual phase, +.>Is the fourth coefficient of the residual phase, +.>Is the fifth coefficient of the residual phase, +.>Is the sixth coefficient of the residual phase.
S43, obtaining the atmospheric error by using a linear regression model according to the unwrapped interference phase diagram of the target area in the substep S41.
The invention utilizes a linear regression model to obtain the atmospheric error, which is expressed as:
wherein:to unwind and dryAtmospheric errors in the phase diagram, +.>Is +.>The axis of the rotation is set to be at the same position,is +.>Axis coordinates->Is the first coefficient of atmospheric error, +.>Is a second coefficient of the atmospheric error,to unwrap elevation information in the interferometric phase map.
S44, obtaining a fitting result according to the residual phase of the orbit error in the polynomial fitting substep S42 and the atmospheric error in the substep S43.
S45, correcting the winding interference phase diagram with the dense stripes removed in the step S3 according to the fitting result in the substep S44, and obtaining a winding interference phase diagram corrected by the target area.
S5, acquiring a time sequence deformation rate chart of the high-resolution third image of the target area by adopting a time sequence radar interferometry method according to the winding interference phase chart corrected by the target area in the step S4 so as to realize the monitoring of the target area.
In an optional embodiment of the invention, according to the winding interference phase map corrected by the target area, the phase correction and the atmosphere correction are carried out on the winding interference phase map corrected by the acquired target area by adopting a time sequence radar interferometry method, and the time sequence deformation rate map of the high-resolution third image of the target area is acquired so as to realize the monitoring of the target area.
Step S5 comprises the following sub-steps:
s51, selecting candidate points of the filtering phase coherence loss slow target point according to the amplitude difference dispersion index and the winding interference phase diagram corrected by the target area in the step S4.
S52, determining a phase error according to the candidate points of the filtering phase loss coherent slow target point in the substep S51.
S53, determining a measure parameter of the pixel noise level according to the phase error in the substep S52.
S54, selecting a filtering phase coherence-losing slow target point according to the measure parameter of the pixel noise level in the substep S53 and the candidate point of the filtering phase coherence-losing slow target point in the substep S51.
S55, acquiring a time sequence deformation rate diagram of a high-resolution third image of the target area according to the filtering phase coherence loss slow target point in the substep S54, the 3D unwrapping method and the unwrapped interference phase diagram corrected by the target area in the step S4 so as to realize the monitoring of the target area.
Specifically, according to the filtering phase coherence loss slow target point in the substep S54, the phase correction can be performed on the unwrapped interference phase map corrected by the target area, the phase unwrapped interference phase map is performed according to the 3D unwrapped method, and the unwrapped interference phase map is subjected to atmosphere correction by the space correlation error correction method, so that the time sequence deformation rate map of the high-resolution third image of the target area is obtained, and further accurate monitoring of the target area is realized.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principles and embodiments of the present invention have been described in detail with reference to specific examples, which are provided to facilitate understanding of the method and core ideas of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Those of ordinary skill in the art will recognize that the embodiments described herein are for the purpose of aiding the reader in understanding the principles of the present invention and should be understood that the scope of the invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific modifications and combinations from the teachings of the present disclosure without departing from the spirit thereof, and such modifications and combinations remain within the scope of the present disclosure.
Claims (6)
1. A time sequence radar interference monitoring method based on a third high-resolution method is characterized by comprising the following steps:
s1, acquiring an interference phase diagram of a target area by using a third high-resolution method;
s2, obtaining a winding interference phase diagram of the target area according to the interference phase diagram of the target area and the digital elevation model data in the step S1;
s3, obtaining a winding interference phase diagram of the target area with dense stripes removed according to the ephemeris data and the winding interference phase diagram of the target area in the step S2;
step S3 comprises the following sub-steps:
s31, according to ephemeris data, acquiring a first initial baseline of a winding interference phase diagram of a target area by using orbit state vector estimation;
step S31 includes the following sub-steps:
s311, fitting a time position curve of the satellite according to ephemeris data;
s312, calculating unknown parameters of the time position curve of the satellite in the substep S311 according to a least square method, and obtaining an orbit curve model of the satellite;
s313, acquiring a first initial baseline of a winding interference phase diagram of the target area according to the orbit curve model of the satellite in the substep S312;
s32, obtaining interference fringe frequency data, and obtaining a second initial baseline of a winding interference phase diagram of the target area according to the interference fringe frequency data;
s33, obtaining a winding interference phase diagram of the target area with dense stripes removed according to the first initial baseline in the substep S31 and the second initial baseline in the substep S32;
s4, according to polynomial fitting, a linear regression model and the winding interference phase diagram of the target area with dense stripes removed in the step S3, obtaining a winding interference phase diagram after the target area is corrected;
step S4 comprises the following sub-steps:
s41, performing phase unwrapping on the wrapping interference phase map with the dense stripes removed from the target area in the step S3 to obtain an unwrapped interference phase map of the target area;
s42, obtaining the residual phase of the track error according to the phase jump of the unwrapped interference phase diagram of the target area in the polynomial fitting substep S41;
s43, obtaining an atmospheric error by using a linear regression model according to the unwrapped interference phase diagram of the target area in the substep S41;
s44, obtaining a fitting result according to the residual phase of the orbit error in the polynomial fitting substep S42 and the atmospheric error in the substep S43;
s45, correcting the winding interference phase diagram with the dense stripes removed in the step S3 according to the fitting result in the substep S44, and obtaining a winding interference phase diagram corrected by the target area;
s5, acquiring a time sequence deformation rate chart of the high-resolution third image of the target area by adopting a time sequence radar interferometry method according to the winding interference phase chart corrected by the target area in the step S4 so as to realize the monitoring of the target area.
2. The method for interference monitoring of time sequence radar based on third high score according to claim 1, wherein the step S2 comprises the following sub-steps:
s21, registering and interference combining the interference images of the target area in the step S1 to generate a single-view winding interference phase diagram of the target area;
s22, carrying out land leveling and topography correction on the single-view winding interference phase diagram of the target area in the bisection step S21 according to the digital elevation model data, and obtaining the winding interference phase diagram of the target area.
3. The method for interference monitoring of time-series radar based on the third high score according to claim 1, wherein in the substep S311, a time-position curve of the satellite is fitted, expressed as:
wherein:for the antenna centre +.>Axis coordinate value->For the antenna centre +.>Constant term coefficient of axis,/>For the antenna centre +.>Primary term coefficient of axis,/>For sampling point time, +.>For the antenna centre +.>Quadratic term coefficient of axis,/>For the antenna centre +.>The cubic term coefficient of the axis,/>For the antenna centre +.>Axis coordinate value->For the antenna centre +.>Constant term coefficient of axis,/>For the antenna centre +.>Primary term coefficient of axis,/>For the antenna centre +.>Quadratic term coefficient of axis,/>For the antenna centre +.>The cubic term coefficient of the axis,/>For the antenna centre +.>Axis coordinate value->For the antenna centre +.>Constant term coefficient of axis,/>For the antenna centre +.>Primary term coefficient of axis,/>For the antenna centre +.>Quadratic term coefficient of axis,/>For the antenna centre +.>The cubic term coefficient of the axis.
4. The method for monitoring time-series radar interferometry based on the third high-resolution method according to claim 1, wherein in the substep S42, phase jumps of unwrapped interference phase diagrams of the target area in the substep S41 are fitted, and residual phases of track errors are obtained, which are expressed as:
wherein:for unwrapping the residual phase of the track error in the interferometric phase map,/for example>Is +.>Axis coordinates->Is +.>Axis coordinates->Is the first coefficient of the residual phase, +.>As a second coefficient of the residual phase,is the third coefficient of the residual phase, +.>Is the fourth coefficient of the residual phase, +.>Is the fifth coefficient of the residual phase, +.>Is the sixth coefficient of the residual phase.
5. The method for interference monitoring of time-series radar based on the third high score according to claim 1, wherein in the substep S43, the atmospheric error is obtained by using a linear regression model, expressed as:
wherein:to unwrap atmospheric errors in the interferogram, +.>Is +.>Axis coordinates->Is +.>Axis coordinates->Is the first coefficient of atmospheric error, +.>Is a second coefficient of the atmospheric error,to unwrap elevation information in the interferometric phase map.
6. The method for interference monitoring of time sequence radar based on third high score according to claim 1, wherein the step S5 comprises the following sub-steps:
s51, selecting candidate points of a filtering phase coherence loss slow target point according to the amplitude difference dispersion index and the winding interference phase diagram corrected by the target area in the step S4;
s52, determining a phase error according to candidate points of the filtering phase loss coherent slow target point in the substep S51;
s53, determining a measure parameter of the pixel noise level according to the phase error in the substep S52;
s54, selecting a filtering phase incoherent slow target point according to the measure parameter of the pixel noise level in the substep S53 and the candidate point of the filtering phase incoherent slow target point in the substep S51;
s55, acquiring a time sequence deformation rate diagram of a high-resolution third image of the target area according to the filtering phase coherence loss slow target point in the substep S54, the 3D unwrapping method and the unwrapped interference phase diagram corrected by the target area in the step S4 so as to realize the monitoring of the target area.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311023457.XA CN116736306B (en) | 2023-08-15 | 2023-08-15 | Time sequence radar interference monitoring method based on third high-resolution |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311023457.XA CN116736306B (en) | 2023-08-15 | 2023-08-15 | Time sequence radar interference monitoring method based on third high-resolution |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116736306A CN116736306A (en) | 2023-09-12 |
| CN116736306B true CN116736306B (en) | 2023-10-24 |
Family
ID=87919047
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311023457.XA Active CN116736306B (en) | 2023-08-15 | 2023-08-15 | Time sequence radar interference monitoring method based on third high-resolution |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116736306B (en) |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103675790A (en) * | 2013-12-23 | 2014-03-26 | 中国国土资源航空物探遥感中心 | Method for improving earth surface shape change monitoring precision of InSAR (Interferometric Synthetic Aperture Radar) technology based on high-precision DEM (Digital Elevation Model) |
| CN105487065A (en) * | 2016-01-08 | 2016-04-13 | 香港理工大学深圳研究院 | Time sequence satellite borne radar data processing method and device |
| CN109031300A (en) * | 2018-09-03 | 2018-12-18 | 中科卫星应用德清研究院 | Synthetic aperture radar monitors Dangerous Rock Body deformation method and system |
| CN109242872A (en) * | 2018-08-27 | 2019-01-18 | 西安电子科技大学 | Interference baseline estimation method based on SRTM DEM |
| CN110109106A (en) * | 2019-04-23 | 2019-08-09 | 中国电力科学研究院有限公司 | A kind of InSAR interferometric phase unwrapping method in region with a varied topography |
| CN110109112A (en) * | 2019-04-30 | 2019-08-09 | 成都理工大学 | A kind of sea-filling region airport deformation monitoring method based on InSAR |
| CN111239736A (en) * | 2020-03-19 | 2020-06-05 | 中南大学 | Single-baseline-based surface elevation correction method, device, equipment and storage medium |
| CN111965646A (en) * | 2020-10-20 | 2020-11-20 | 航天宏图信息技术股份有限公司 | Satellite-borne radar data processing method, device, equipment and storage medium |
| CN111998766A (en) * | 2020-08-31 | 2020-11-27 | 同济大学 | Surface deformation inversion method based on time sequence InSAR technology |
| CN115856889A (en) * | 2023-02-03 | 2023-03-28 | 北京数慧时空信息技术有限公司 | InSAR time sequence deformation monitoring method capable of automatically correcting errors |
| CN116222412A (en) * | 2023-05-10 | 2023-06-06 | 北京中舆达信息科技有限公司 | Surface deformation monitoring method and system |
| CN116381680A (en) * | 2022-11-21 | 2023-07-04 | 中交基础设施养护集团有限公司 | Urban earth surface deformation monitoring method based on time sequence radar interferometry technology |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB201709525D0 (en) * | 2017-06-15 | 2017-08-02 | Univ Nottingham | Land deformation measurement |
-
2023
- 2023-08-15 CN CN202311023457.XA patent/CN116736306B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103675790A (en) * | 2013-12-23 | 2014-03-26 | 中国国土资源航空物探遥感中心 | Method for improving earth surface shape change monitoring precision of InSAR (Interferometric Synthetic Aperture Radar) technology based on high-precision DEM (Digital Elevation Model) |
| CN105487065A (en) * | 2016-01-08 | 2016-04-13 | 香港理工大学深圳研究院 | Time sequence satellite borne radar data processing method and device |
| CN109242872A (en) * | 2018-08-27 | 2019-01-18 | 西安电子科技大学 | Interference baseline estimation method based on SRTM DEM |
| CN109031300A (en) * | 2018-09-03 | 2018-12-18 | 中科卫星应用德清研究院 | Synthetic aperture radar monitors Dangerous Rock Body deformation method and system |
| CN110109106A (en) * | 2019-04-23 | 2019-08-09 | 中国电力科学研究院有限公司 | A kind of InSAR interferometric phase unwrapping method in region with a varied topography |
| CN110109112A (en) * | 2019-04-30 | 2019-08-09 | 成都理工大学 | A kind of sea-filling region airport deformation monitoring method based on InSAR |
| CN111239736A (en) * | 2020-03-19 | 2020-06-05 | 中南大学 | Single-baseline-based surface elevation correction method, device, equipment and storage medium |
| CN111998766A (en) * | 2020-08-31 | 2020-11-27 | 同济大学 | Surface deformation inversion method based on time sequence InSAR technology |
| CN111965646A (en) * | 2020-10-20 | 2020-11-20 | 航天宏图信息技术股份有限公司 | Satellite-borne radar data processing method, device, equipment and storage medium |
| CN116381680A (en) * | 2022-11-21 | 2023-07-04 | 中交基础设施养护集团有限公司 | Urban earth surface deformation monitoring method based on time sequence radar interferometry technology |
| CN115856889A (en) * | 2023-02-03 | 2023-03-28 | 北京数慧时空信息技术有限公司 | InSAR time sequence deformation monitoring method capable of automatically correcting errors |
| CN116222412A (en) * | 2023-05-10 | 2023-06-06 | 北京中舆达信息科技有限公司 | Surface deformation monitoring method and system |
Non-Patent Citations (7)
| Title |
|---|
| Evaluating and Analyzing the Potential of the Gaofen-3 SAR Satellite for Landslide Monitoring;Ningling Wen等;《Remote Sensing》;1-17 * |
| Image-Based Baseline Correction Method for Spaceborne InSAR With External DEM;Qingyue Yang等;《IEEE Transactions on Geoscience and Remote Sensing》;全文 * |
| 利用高分辨率TerraSAR-X数据监测武汉地区2013～2015年地面沉降;白林等;《大地测量与地球动力学》(第8期);832-836 * |
| 基于InSAR技术的长宁地区地表形变监测研究;李世云;《中国优秀硕士学位论文全文数据库 基础科学辑》(第4期);A008-122 * |
| 多分辨率分析的InSAR轨道误差去除算法;何永红等;《测绘科学》(第7期);128-136 * |
| 系统噪声对InSAR相位解缠影响的模拟分析;李立中等;《测绘》(第6期);243-246 * |
| 高分辨率星载InSAR技术在DEM生成及更新中的应用研究;蒋厚军;《中国博士学位论文全文数据库 基础科学辑》(第1期);A008-9 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116736306A (en) | 2023-09-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106772342B (en) | Time sequence differential radar interference method suitable for large-gradient ground surface settlement monitoring | |
| CN107102333B (en) | Satellite-borne InSAR long and short baseline fusion unwrapping method | |
| CN109917356B (en) | Airborne laser scanning system error calibration method | |
| CN101770027B (en) | Ground surface three-dimensional deformation monitoring method based on InSAR and GPS data fusion | |
| CN105487065B (en) | A kind of sequential spaceborne radar data processing method and device | |
| CN103364766B (en) | External calibration method of satellite-borne interferometric synthetic aperture radar (InSAR) system | |
| CN112051571A (en) | LOS (line of sight) deformation variable estimation method of novel differential InSAR (interferometric synthetic Aperture Radar) | |
| CN115201825B (en) | Atmospheric delay correction method in InSAR (interferometric synthetic aperture radar) inter-seismic deformation monitoring | |
| CN116338607B (en) | Time domain and space domain two-step InSAR troposphere delay correction method | |
| CN112711021B (en) | Multi-resolution InSAR (interferometric synthetic Aperture Radar) interactive interference time sequence analysis method | |
| WO2009055320A2 (en) | Method and apparatus for determining parameters for a parametric expression characterizing the phase of an acquired signal | |
| CN110109105A (en) | A method of the InSAR technical monitoring Ground Deformation based on timing | |
| CN117406221A (en) | InSAR deformation monitoring method for high-resolution DEM of corner reflector | |
| Mao et al. | Estimation and compensation of ionospheric phase delay for multi-aperture InSAR: An azimuth split-spectrum interferometry approach | |
| CN118191841A (en) | Method, device, equipment and medium for measuring and correcting earth surface subsidence deformation based on correlation analysis | |
| CN116736306B (en) | Time sequence radar interference monitoring method based on third high-resolution | |
| Mao et al. | Ionospheric phase delay correction for time series multiple-aperture InSAR constrained by polynomial deformation model | |
| CN113341410B (en) | Large-range under-forest terrain estimation method, device, equipment and medium | |
| CN115980317B (en) | Foundation GNSS-R data soil moisture estimation method based on corrected phase | |
| Pahlevi et al. | Determination of gravimetric geoid model in Sulawesi–Indonesia | |
| Yamashita et al. | Mitigation of ionospheric noise in azimuth offset based on the split-spectrum method | |
| CN110657742A (en) | Aquifer deformation signal separation method, aquifer deformation signal separation device, aquifer deformation signal separation equipment and readable storage medium | |
| CN110658521A (en) | Winding phase-based GBInSAR atmospheric correction method and system | |
| CN109839635B (en) | Method for extracting elevation of height measurement foot points through Cryosat-2 SARIn mode L1 b-level waveform data | |
| CN113138388B (en) | Ground subsidence monitoring method integrating precise level and InSAR reliable subsidence value |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |