CN116736306A - Time sequence radar interference monitoring method based on third high-resolution - Google Patents

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

A time-series radar interference monitoring method based on Gaofen-3

Technical field

The invention relates to the field of radar interference monitoring, and specifically relates to a time-series radar interference monitoring method based on Gaofen-3.

Background technique

Gaofen-3 is my country's first C-band, multi-polarization, high-resolution (up to 1 meter) synthetic aperture radar satellite. It has outstanding advantages such as all-day and all-weather monitoring, high-precision measurement, and multi-mode imaging, and can operate all day and night. And realize the monitoring of global ocean and land information around the clock. Gaofen-3 is used in the field of natural disasters to monitor glacier movements, land subsidence, earthquakes, landslides, debris flows, floods and other disasters.

Currently, in the field of radar interference monitoring, the quality of the Gaofen-3 image interference phase diagram obtained due to orbit errors and baseline errors is not high, making it impossible to fully utilize it for time-series deformation monitoring of the target area.

Contents of the invention

In view of the above-mentioned deficiencies in the existing technology, the present invention provides a time-series radar interference monitoring method based on Gaofen-3, which can improve the quality of Gaofen-3 interference phase diagram by correcting the orbit error and baseline error, thereby achieving target detection. High-precision monitoring of regional surface deformation.

In order to achieve the above-mentioned object of the invention, the technical solutions adopted by the present invention are:

A time-series radar interference monitoring method based on Gaofen-3, including the following steps:

S1. Use Gaofen-3 to obtain the interference phase map of the target area;

S2. Obtain the 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 step S1;

S3. According to the ephemeris data and the winding interference phase map of the target area in step S2, obtain the winding interference phase map of the target area with dense fringes removed;

S4. According to the polynomial fitting, linear regression model and the winding interference phase image of the target area with dense stripes removed in step S3, obtain the corrected winding interference phase image of the target area;

S5. According to the corrected winding interference phase diagram of the target area in step S4, use the time-series radar interferometry method to obtain the time-series deformation rate map of the Gaofen-3 image of the target area to achieve monitoring of the target area.

Further, step S2 includes the following sub-steps:

S21. Perform registration and interference combination on the interference images of the target area in step S1 to generate a single-view winding interference phase map of the target area;

S22. Perform flattening and terrain correction on the single-view winding interference phase map of the target area in step S21 according to the digital elevation model data to obtain the winding interference phase map of the target area.

Further, step S3 includes the following sub-steps:

S31. According to the ephemeris data, use orbital state vector estimation to obtain the first initial baseline of the winding interference phase diagram of the target area;

S32. Obtain the interference fringe frequency data, and obtain the second initial baseline of the winding interference phase diagram of the target area based on the interference fringe frequency data;

S33. According to the first initial baseline in step S31 and the second initial baseline in step S32, obtain the winding interference phase map of the target area with dense fringes removed.

Further, step S31 includes the following sub-steps:

S311. Fit the time position curve of the satellite according to the ephemeris data;

S312. Calculate the unknown parameters of the time position curve of the satellite in step S311 according to the least squares method, and obtain the orbit curve model of the satellite;

S313. According to the orbit curve model of the satellite in step S312, obtain the first initial baseline of the winding interference phase diagram of the target area.

Further, in sub-step S311, the time position curve of the satellite is fitted, which is expressed as:

in: is the center of the antenna/> Axis coordinate value,/> is the center of the antenna/> The constant term coefficient of the axis,/> is the center of the antenna/> The linear term coefficient of the axis,/> is the sampling point time,/> is the center of the antenna/> The coefficient of the quadratic term of the axis,/> is the center of the antenna/> Coefficient of cubic term of axis,/> is the center of the antenna/> Axis coordinate value,/> is the center of the antenna/> The constant term coefficient of the axis,/> is the center of the antenna/> The linear term coefficient of the axis,/> is the center of the antenna/> The coefficient of the quadratic term of the axis,/> is the center of the antenna/> Coefficient of cubic term of axis,/> is the center of the antenna/> Axis coordinate value,/> is the center of the antenna/> The constant term coefficient of the axis,/> is the center of the antenna/> The linear term coefficient of the axis,/> is the center of the antenna/> The coefficient of the quadratic term of the axis,/> is the center of the antenna/> Coefficient of the cubic term of the axis.

Further, step S4 includes the following sub-steps:

S41. Perform phase unwrapping on the entangled interference phase image of the target area with dense fringes removed in step S3, and obtain the unwrapped interference phase image of the target area;

S42. Obtain the residual phase of the orbit error according to the phase jump of the unwrapped interference phase diagram of the target area in step S41 of polynomial fitting;

S43. Based on the unwrapped interference phase map of the target area in step S41, use the linear regression model to obtain the atmospheric error;

S44. Obtain the fitting result according to the residual phase of the orbit error in step S42 of polynomial fitting and the atmospheric error in step S43;

S45. Correct the winding interference phase image from which the dense fringes are removed in step S3 according to the fitting result in step S44, and obtain the corrected winding interference phase image of the target area.

Further, in sub-step S42, the phase jump of the unwrapped interference phase diagram of the target area in sub-step S41 is fitted to obtain the residual phase of the orbit error, which is expressed as:

in: is the residual phase of the orbit error in the unwrapped interference phase diagram,/> is/> in the radar coordinate system Axis coordinates,/> is/> in the radar coordinate system 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 step S43, the linear regression model is used to obtain the atmospheric error, which is expressed as:

in: To unwrap the atmospheric errors in the interference phase diagram,/> is/> in the radar coordinate system axis coordinates, is/> in the radar coordinate system Axis coordinates,/> is the first coefficient of atmospheric error,/> is the second coefficient of atmospheric error, To unwrap the elevation information in the interference phase image.

Further, step S5 includes the following sub-steps:

S51. Select candidate points for filtered phase decoherence slow target points based on the amplitude difference dispersion index and the corrected winding interference phase diagram of the target area in step S4;

S52. Determine the phase error according to the candidate points of the filtered phase decoherence slow target point in step S51;

S53. Determine the measurement parameters of the pixel noise level according to the phase error in step S52;

S54. Select the filtered phase decoherent slow target point according to the measurement parameters of the pixel noise level in step S53 and the candidate points of the filtered phase decoherent slow target point in step S51;

S55. According to the filtered phase decoherence slow target point in step S54, the 3D unwrapping method and the corrected unwrapped interference phase diagram of the target area in step S4, obtain the time series deformation rate diagram of the Gaofen-3 image of the target area, To achieve monitoring of target areas.

The invention has the following beneficial effects:

(1) This invention improves the quality of the Gaofen-3 interference phase map by correcting the orbit error and baseline error, thereby achieving high-precision monitoring of surface deformation in the target area;

(2) The present invention obtains the first initial baseline and the second initial baseline of the winding interference phase diagram of the target area by using orbit state vector estimation and interference fringe frequency data. It can make preliminary corrections to the baseline error and orbit error and obtain the target area. Winding interference phase images with dense fringe removal;

(3) By phase unwrapping the preliminary corrected interference phase diagram and using polynomials to fit the residual phase of the orbit error and the atmospheric error, the present invention can further refine the preliminary corrected interference phase diagram and obtain Corrected winding interference phase diagram of the target area;

(4) By using the time-series radar interferometry method, the present invention can perform phase correction and atmospheric correction on the corrected winding interference phase diagram of the target area, and obtain the time-series deformation rate diagram of the Gaofen-3 image of the target area, so as to achieve Effective monitoring of target areas.

Description of drawings

Figure 1 is a schematic flow chart of a time-series radar interference monitoring method based on Gaofen-3.

Detailed ways

The specific embodiments of the present invention are described below to facilitate those skilled in the art to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the technical field, as long as various changes These changes are obvious within the spirit and scope of the invention as defined and determined by the appended claims, and all inventions and creations utilizing the concept of the invention are protected.

As shown in Figure 1, a time-series radar interference monitoring method based on Gaofen-3 includes steps S1-S5, as follows:

S1. Use Gaofen-3 to obtain the interference phase map of the target area.

In an optional embodiment of the present invention, the present invention selects a target area to be monitored, and uses Gaofen-3 to obtain the interference phase map of the target area. The interference phase diagram obtained by the present invention using Gaofen-3 has orbit errors and baseline errors, and only a small number of interference phase diagrams can be applied to the field of time-series radar interference monitoring.

S2. Obtain the 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 step S1.

In an optional embodiment of the present invention, the present invention generates a single-view wrapping interference phase diagram of the target area based on the interference phase diagram of the target area, and performs flattening and summing based on the single-view wrapping interference phase diagram of the target area using digital elevation model data. Terrain correction is performed to obtain the winding interference phase map of the target area.

Step S2 includes the following sub-steps:

S21. Perform registration and interference combination on the interference phase images of the target area in step S1 to generate a single-view winding interference phase image of the target area.

Specifically, the present invention performs registration and interference combination on the interference phase images of the target area to generate a single-view winding interference phase image of the target area.

S22. Perform flattening and terrain correction on the single-view winding interference phase map of the target area in step S21 according to the digital elevation model data to obtain the winding interference phase map of the target area.

S3. According to the ephemeris data and the winding interference phase map of the target area in step S2, obtain the winding interference phase map of the target area with dense fringes removed.

In an optional embodiment of the present invention, based on the ephemeris data and the winding interference phase diagram of the target area, the present invention adopts a method of combining state vector estimation and interference fringe frequency data to detect the interference phase diagram existing in the Gaofen-3 The orbit error and baseline error are initially corrected, and the winding interference phase map of the target area is obtained with dense fringes removed.

Step S3 includes the following sub-steps:

S31. According to the ephemeris data, use orbital state vector estimation to obtain the first initial baseline of the winding interference phase diagram of the target area.

Step S31 includes the following sub-steps:

S311. Fit the time position curve of the satellite according to the ephemeris data.

The present invention fits the time position curve of the satellite, which is expressed as:

in: is the center of the antenna/> Axis coordinate value,/> is the center of the antenna/> The constant term coefficient of the axis,/> is the center of the antenna/> The linear term coefficient of the axis,/> is the sampling point time,/> is the center of the antenna/> The coefficient of the quadratic term of the axis,/> is the center of the antenna/> Coefficient of cubic term of axis,/> is the center of the antenna/> Axis coordinate value,/> is the center of the antenna/> The constant term coefficient of the axis,/> is the center of the antenna/> The linear term coefficient of the axis,/> is the center of the antenna/> The coefficient of the quadratic term of the axis,/> is the center of the antenna/> Coefficient of cubic term of axis,/> is the center of the antenna/> Axis coordinate value,/> is the center of the antenna/> The constant term coefficient of the axis,/> is the center of the antenna/> The linear term coefficient of the axis,/> is the center of the antenna/> The coefficient of the quadratic term of the axis,/> is the center of the antenna/> Coefficient of the cubic term of the axis.

Specifically, based on the ephemeris data, the present invention can obtain the position of the antenna center and the sampling point time recorded in the Gaofen-3 interference phase diagram during satellite operation, and can use these data to fit the above time position curve.

S312. Calculate the unknown parameters of the time position curve of the satellite in step S311 according to the least squares method, and obtain the orbit curve model of the satellite.

Specifically, the present invention obtains the position point data of the five antenna centers, and can solve the position parameters in the time position curve according to the least squares method, that is, the constant term coefficient, linear term coefficient, quadratic term coefficient and cubic term coefficient corresponding to the coordinate axis. , and then obtain the satellite orbit curve model.

S313. According to the orbit curve model of the satellite in step S312, obtain the first initial baseline of the winding interference phase diagram of the target area.

S32. Obtain the interference fringe frequency data, and obtain the second initial baseline of the winding interference phase diagram of the target area based on the interference fringe frequency data.

Specifically, the present invention can obtain interference fringe frequency data through the maximum likelihood estimation frequency method. This invention uses the fast Fourier transform method to convert the winding interference phase map of the target area from the spatial domain to the frequency domain to calculate the interference fringe frequency, which is expressed as:

in: is the winding interference phase diagram of the target region converted to the frequency domain,/> is an imaginary unit,/> is the track jump phase,/> is the deformation phase,/> is/> in the radar coordinate system Axis coordinates,/> is/> in the radar coordinate system Axis coordinates,/> is the frequency in the distance direction,/> is the frequency in the azimuth direction,/> is the residual phase.

The present invention can deduce the relationship between the second initial baseline and the interference fringe frequency based on the fringe frequency, and then obtain the second initial baseline of the winding interference phase diagram of the target area based on the obtained interference fringe frequency data.

S33. According to the first initial baseline in step S31 and the second initial baseline in step S32, obtain the winding interference phase map of the target area with dense fringes removed.

S4. According to the polynomial fitting, the linear regression model and the winding interference phase image of the target area with dense fringes removed in step S3, obtain the corrected winding interference phase image of the target area.

In an optional embodiment of the present invention, the present invention performs phase unwrapping on the preliminary corrected interference phase diagram, and can fit the entangled interference phase diagram with dense fringes removed based on polynomial fitting, linear regression model and target area. The residual phase of the orbit error and the atmospheric error are eliminated to eliminate the nonlinear error in the orbit error to further refine the preliminary corrected interference phase map and obtain the corrected unwrapped interference phase map of the target area.

Step S4 includes the following sub-steps:

S41. Perform phase unwrapping on the entangled interference phase image of the target area with dense fringes removed in step S3, and obtain the unwrapped interference phase image of the target area.

S42. Obtain the residual phase of the orbit error according to the phase transition of the unwrapped interference phase diagram of the target area in step S41 of polynomial fitting.

The present invention fits the phase jump of the unwrapped interference phase diagram of the target area in step S41, and obtains the residual phase of the orbit error, which is expressed as:

in: is the residual phase of the orbit error in the unwrapped interference phase diagram,/> is/> in the radar coordinate system Axis coordinates,/> is/> in the radar coordinate system 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. According to the unwrapped interference phase diagram of the target area in step S41, use the linear regression model to obtain the atmospheric error.

This invention uses a linear regression model to obtain the atmospheric error, which is expressed as:

in: To unwrap the atmospheric errors in the interference phase diagram,/> is/> in the radar coordinate system axis coordinates, is/> in the radar coordinate system Axis coordinates,/> is the first coefficient of atmospheric error,/> is the second coefficient of atmospheric error, To unwrap the elevation information in the interference phase image.

S44. Obtain the fitting result according to the residual phase of the orbit error in step S42 and the atmospheric error in step S43 of polynomial fitting.

S45. Correct the winding interference phase image from which the dense fringes are removed in step S3 according to the fitting result in step S44, and obtain the corrected winding interference phase image of the target area.

S5. According to the corrected winding interference phase diagram of the target area in step S4, use the time-series radar interferometry method to obtain the time-series deformation rate map of the Gaofen-3 image of the target area to achieve monitoring of the target area.

In an optional embodiment of the present invention, based on the corrected winding interference phase diagram of the target area, the present invention uses a time-series radar interferometry method to perform phase correction and atmospheric correction on the corrected winding interference phase diagram of the target area to obtain the target. The time series deformation rate diagram of the Gaofen-3 image in the area is used to monitor the target area.

Step S5 includes the following sub-steps:

S51. Select the candidate point of the filtered phase decoherence slow target point according to the amplitude difference dispersion index and the corrected winding interference phase diagram of the target area in step S4.

S52. Determine the phase error according to the candidate points of the filtered phase decoherence slow target point in step S51.

S53. Determine the measurement parameter of the pixel noise level according to the phase error in step S52.

S54. Select the filtered phase decoherence slow target point according to the measurement parameters of the pixel noise level in step S53 and the candidate points of the filtered phase decoherence slow target point in step S51.

S55. According to the filtered phase decoherence slow target point in step S54, the 3D unwrapping method and the corrected unwrapped interference phase diagram of the target area in step S4, obtain the time series deformation rate diagram of the Gaofen-3 image of the target area, To achieve monitoring of target areas.

Specifically, the present invention can perform phase correction on the corrected unwrapped interference phase diagram of the target area according to the filtered phase decoherence slow target point in step S54, and perform phase correction on the phase-corrected interference phase diagram according to the 3D unwrapping method. Unwrapping, and using the spatial correlation error correction method to perform atmospheric correction on the unwrapped interference phase map to obtain the time-series deformation rate map of the Gaofen-3 image in the target area, thereby achieving accurate monitoring of the target area.

The 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 process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes 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 device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce a use A device for realizing the functions specified in one process or multiple processes of the flowchart and/or one block or multiple blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory that causes a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction means, the instructions The device implements the functions specified in a process or processes of the flowchart and/or a block or blocks of the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device, causing a series of operating steps to be performed on the computer or other programmable device to produce computer-implemented processing, thereby executing on the computer or other programmable device. Instructions provide steps for implementing the functions specified in a process or processes of a flowchart diagram and/or a block or blocks of a block diagram.

The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those of ordinary skill in the art, based on this The idea of the invention will be subject to change in the specific implementation and scope of application. In summary, the contents of this description should not be understood as limiting the invention.

Those of ordinary skill in the art will appreciate that the embodiments described here are provided to help readers understand the principles of the present invention, and it should be understood that the scope of the present 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 based on the technical teachings disclosed in the present invention without departing from the essence of the present invention, and these modifications and combinations are still within the protection scope of the present invention.

Claims (9)

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;

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.

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 sequence radar based on third high score according to claim 1, wherein the 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;

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.

4. A method of time-series radar interferometry based on third-order high score according to claim 3, wherein step S31 comprises the sub-steps of:

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.

5. The method for interference monitoring of time-series radar based on third-order high score according to claim 4, 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.

6. The method for interference monitoring of time sequence radar based on third high score according to claim 1, wherein the 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.

7. The method for monitoring interference of time-series radar based on third high-resolution method according to claim 6, 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->First to be residual phaseCoefficient of->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.

8. The method for interference monitoring of time-series radar based on third-order high score according to claim 6, 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.

9. 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.