CN112986949B - SAR high-precision time sequence deformation monitoring method and device for diagonal reflector - Google Patents

SAR high-precision time sequence deformation monitoring method and device for diagonal reflector Download PDF

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CN112986949B
CN112986949B CN202110427354.4A CN202110427354A CN112986949B CN 112986949 B CN112986949 B CN 112986949B CN 202110427354 A CN202110427354 A CN 202110427354A CN 112986949 B CN112986949 B CN 112986949B
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corner reflector
sar image
time
position offset
sar
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CN112986949A (en
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朱茂
葛春青
黄成�
李吉平
王远坚
周海兵
王大伟
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Beijing Vastitude Technology Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B7/00—Measuring arrangements characterised by the use of electric or magnetic techniques
    • G01B7/16—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring the deformation in a solid, e.g. by resistance strain gauge
    • 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
    • G01S13/9004—SAR image acquisition techniques
    • G01S13/9005—SAR image acquisition techniques with optical processing of the SAR signals

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Abstract

The invention relates to a method and a device for monitoring SAR high-precision time sequence deformation aiming at a corner reflector, wherein the method comprises the following steps: extracting accurate position information of each corner reflector from the SAR image at each moment; determining the corresponding total position offset information of each corner reflector in the SAR image pair at different moments according to the accurate position information of each corner reflector; determining first position offset component information corresponding to a spatial baseline according to terrain and satellite orbit data; determining second position offset component information corresponding to system errors and environments according to natural homonymous scattering target signals in the SAR image pair; determining deformation position offset information corresponding to the corner reflector according to the total position offset information, the first position offset component information and the second position offset component information of the SAR image pair; and determining a high-precision deformation sequence of the corner reflector according to the deformation position offset information of the corner reflector. By the technical scheme, the applicability of the SAR deformation monitoring technology based on the corner reflector target is improved.

Description

SAR high-precision time sequence deformation monitoring method and device for diagonal reflector
Technical Field
The disclosure relates to the technical field of synthetic aperture radars, in particular to a method and a device for monitoring SAR high-precision time sequence deformation aiming at a corner reflector.
Background
In recent years, many landslide accidents occur in China every year. Generally, the surface of the slope is slightly displaced before the slope is macroscopically unstable. Therefore, in order to study the triggering mechanism of landslide more deeply and realize the critical-sliding prediction accurately in the first time, the deformation monitoring of slope with full coverage, long time, continuity, real time and high precision is needed. As a remote sensing technical means, the satellite-borne SAR technology has the advantages of wide monitoring coverage range, all-weather observation all the day and the like. The InSAR technology and the Offset Tracking technology based on the spaceborne SAR data have deformation monitoring capability.
In the practical application process, the InSAR technology and the Offset Tracking technology have certain limitations. The deformation measurement precision of the InSAR technology can reach mm magnitude, but the deformation quantity of the InSAR technology cannot be measured due to the influence of decoherence aiming at a large deformation target. Although the Offset Tracking technology can measure rapid deformation, the deformation precision is relatively poor (decimeter magnitude), and high-precision monitoring cannot be carried out. Therefore, for some important targets, the deformation of the important targets needs to be accurately measured by the method of arranging the corner reflector.
The angle reflector has higher signal-to-noise ratio in the SAR image, the positioning precision can reach 1/100 resolution order, and the high-precision deformation inversion capability is realized. However, there are two problems in the process of the actual deformation inversion: (1) the existence of the spatial baseline causes the position of the target to shift in the primary SAR image and the secondary SAR image; (2) systematic errors and atmospheric environmental changes can also cause positional deviations of the target. These two problems affect the deformation monitoring accuracy of the corner reflector.
Disclosure of Invention
In order to overcome the problems in the related art, the invention provides a method and a device for monitoring SAR high-precision time sequence deformation aiming at a corner reflector, which can improve the applicability of the SAR deformation monitoring technology based on the corner reflector target and provide technical support for the engineering application of the technology.
According to a first aspect of the embodiments of the present disclosure, there is provided a method for monitoring SAR high-precision time-series deformation for a corner reflector, the method including:
extracting accurate position information of each corner reflector from the SAR image at each moment;
determining the corresponding total position offset information of each corner reflector in the SAR image pair at different moments according to the accurate position information of each corner reflector;
determining first position offset component information corresponding to a spatial baseline according to terrain and satellite orbit data;
determining second position offset component information corresponding to system errors and environments according to natural homonymous scattering target signals in the SAR image pair;
determining deformation position offset information corresponding to the corner reflector according to the total position offset information, the first position offset component information and the second position offset component information of the SAR image pair;
and determining a high-precision deformation sequence of the corner reflector according to the deformation position offset information of the corner reflector.
In one embodiment, preferably, the determining, according to the precise position information of each corner reflector, total position offset information corresponding to the SAR image pair of each corner reflector at different time includes:
determining the corresponding distance time t according to the accurate position information of each corner reflectorRaAnd azimuth time tAz；
tRa=tRa0+(C-1)ΔtRa
tAz=tAz0+(R-1)ΔtAz
Wherein, tRa0And tAz0Representing the starting sampling time, Δ t, of the distance and azimuth directions, respectivelyRaAnd Δ tAzTime sampling intervals representing a distance direction and an azimuth direction, respectively; [R,C]The exact position of the corner reflector in the SAR image in the azimuth direction and the range direction, respectively.
In order to extract the exact position of the corner reflector in the SAR image (at the level of 1/100 pixels), a method of Sinc interpolation may be employed. Doppler center frequency taking into account SAR satellite dataf dcAnd if not, calculating the Doppler center frequency at the corner reflector based on SAR basic parameters before Sinc interpolation, moving the frequency spectrum to the fundamental frequency, and then performing Sinc interpolation processing.
According to the distance time of the readable reference point in SAR data parameterst RaRefAnd azimuth timet AzRefAnd the distance time of each corner reflectort RaAnd azimuth timet AzIn calculating the Doppler of the corner reflector using the following formulaHeart frequency:
Figure 725501DEST_PATH_IMAGE001
wherein the content of the first and second substances,f dc (R,C) Is the term in the SAR imageR,C]Doppler center frequency at location, tRaRefAnd tAzRefRespectively representing distance time and orientation time, t, of the reference pointRaAnd tAzRespectively representing the distance direction time and the azimuth direction time of each corner reflector; coefAzAnd CoefRaPolynomial coefficients, which are doppler center frequencies, can be read in the SAR data parameters.
In one embodiment, preferably, determining the first position offset component information corresponding to the spatial baseline from the terrain and satellite trajectory data comprises:
acquiring elevation information of each corner reflector at the position of the main SAR image in the SAR image pair based on external DEM data;
calculating the space position coordinates of each corner reflector under the WGS84 based on a Doppler equation, a slope distance equation and an ellipsoid equation, wherein the mathematical expressions of the Doppler equation, the slope distance equation and the ellipsoid equation are as follows:
Figure 718865DEST_PATH_IMAGE002
wherein, tMAzAnd tMRaRespectively representing the corresponding azimuth time and range time, M (t), at the corner reflector position in the main SAR imageMAz) Represents tMAzSatellite position vector, V (t), corresponding to the time master SAR imageMAz) Represents tMAzSatellite velocity vector v corresponding to time master SAR imagelightIs the speed of light, a, b and c are the parameters of the earth's ellipsoid, T represents the position vector of the target, (x)M, yM, zM) Is the component of the target position vector T in the x, y, z directions in the WGS84 coordinate system, TRaThe distance corresponding to the target is the one-way time, and h is the altitude of the target;
according to the space position coordinates, calculating theoretical coordinates of the corner reflector in the auxiliary SAR image by combining satellite orbit data corresponding to the auxiliary SAR image in the SAR image pair;
and determining first position offset component information corresponding to the space baseline according to the theoretical coordinates in the auxiliary SAR image and the elevation information in the main SAR image.
In one embodiment, preferably, the determining second position offset component information corresponding to a system error and an environment according to the natural homonymous scattering target signal in the SAR image pair includes:
respectively searching natural homonymous scattering target signals in a main SAR image and a side SAR image in the SAR image pair;
acquiring the accurate position of the natural homonymous scattering target signal in the primary and secondary SAR images by a Sinc interpolation method based on the natural homonymous scattering target signal;
compensating a position offset component corresponding to a space baseline based on satellite orbit data, and acquiring a residual offset of each natural homonymous scattering target signal;
and determining second position offset component information corresponding to the system error and the environment according to the average value of the residual quantities of all natural homonymous scattering target signals.
In one embodiment, preferably, the searching for natural homonymous scattering target signals in the primary SAR image and the secondary SAR image of the SAR image pair respectively includes:
based on SAR system parameters, acquiring a two-dimensional Sinc signal sig:
Figure 473194DEST_PATH_IMAGE003
wherein sinc is a sinc function identifier, [ R, C ] are pixels in an azimuth direction and a distance direction, RSR is a distance direction sampling frequency, RBW is a distance direction signal bandwidth, PRF is an azimuth direction sampling frequency, and ABW is an azimuth direction signal bandwidth;
respectively carrying out correlation matching on the windows of the two-dimensional Sinc signals in the main SAR image and the auxiliary SAR image so as to respectively obtain strong scattering target signals with correlation coefficients within a preset range in the main SAR image and the auxiliary SAR image;
geocoding strong scattering target signals acquired from the main SAR image and the auxiliary SAR image respectively based on the orbit data and the external DEM data, and calculating spatial three-dimensional position data;
and determining the strong scattering target signals of which the spatial position difference values are within a preset distance range in the main SAR image and the auxiliary SAR image as natural homonymous scattering target signals according to the spatial three-dimensional position data of the strong scattering target signals in the main SAR image and the auxiliary SAR image.
In one embodiment, preferably, the determining a high-precision deformation sequence of the corner reflector according to the deformation position offset information of the corner reflector includes:
according to the deformation position offset information of the corner reflector, combining SAR system parameters, calculating a deformation measurement result of the corner reflector between the time of acquiring the main SAR image and the time of acquiring the auxiliary SAR image;
and carrying out time sequence processing on the deformation measurement results at different moments to determine a high-precision deformation sequence of the corner reflector.
In one embodiment, preferably, the deformation measurement includes a distance deformation and an azimuth deformation, and the distance deformation is calculated by using the following formulad RaAnd the azimuthal deformationd Az；
Figure 210206DEST_PATH_IMAGE004
Wherein v islightRSR is the distance-wise sampling frequency, vSatWhich is the satellite velocity, the PRF is the azimuth sampling frequency,C defofor a shift of the target point in distance towards the image pixel due to deformation,R defothe target point is displaced in azimuth towards the image pixels due to the deformation.
According to a second aspect of the embodiments of the present disclosure, there is provided a SAR high-precision time-series deformation monitoring device for a corner reflector, the device including:
the extraction module is used for extracting the accurate position information of each corner reflector from the SAR image at each moment;
the first determining module is used for determining the corresponding total position offset information of each corner reflector in the SAR image pair at different moments according to the accurate position information of each corner reflector;
the second determining module is used for determining first position offset component information corresponding to the space baseline according to the terrain and the satellite orbit data;
a third determining module, configured to determine second position offset component information corresponding to a system error and an environment according to a natural homonymous scattering target signal in the SAR image pair;
a fourth determining module, configured to determine deformation position offset information corresponding to the corner reflector according to the total position offset information, the first position offset component information, and the second position offset component information of the SAR image pair;
and the fifth determining module is used for determining the high-precision deformation sequence of the corner reflector according to the deformation position offset information of the corner reflector.
According to a third aspect of the embodiments of the present disclosure, there is provided a SAR high-precision time-series deformation monitoring device for a corner reflector, the device including:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to:
extracting accurate position information of each corner reflector from the SAR image at each moment;
determining the corresponding total position offset information of each corner reflector in the SAR image pair at different moments according to the accurate position information of each corner reflector;
determining first position offset component information corresponding to a spatial baseline according to terrain and satellite orbit data;
determining second position offset component information corresponding to system errors and environments according to natural homonymous scattering target signals in the SAR image pair;
determining deformation position offset information corresponding to the corner reflector according to the total position offset information, the first position offset component information and the second position offset component information of the SAR image pair;
and determining a high-precision deformation sequence of the corner reflector according to the deformation position offset information of the corner reflector.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the steps of the method of any one of the first aspects.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
in the embodiment of the invention, the deformation sequence of the corner reflector is accurately obtained by a signal processing method based on the time-series high-resolution SAR data. In the data processing, the change in the position of the target point due to the baseline is first compensated for based on the satellite orbit data for both problems summarized. Then, natural homonymous targets with stronger signals are searched for in the SAR image, position change caused by atmospheric propagation delay or sensor system errors and the like is compensated through the signals of the homonymous targets, and high-precision deformation of the diagonal reflector of each SAR image is further acquired. And finally, acquiring a deformation sequence of the corner reflector by taking deformation information of the corner reflector of different SAR images as input. The SAR deformation monitoring method based on the corner reflector target can improve the applicability of the SAR deformation monitoring technology based on the corner reflector target and provide technical support for engineering application of the technology.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a flowchart illustrating a SAR high accuracy time-series deformation monitoring method for a corner reflector according to an exemplary embodiment.
Fig. 2 is a flowchart illustrating step S103 in a SAR high-precision time-series deformation monitoring method for a corner reflector according to an exemplary embodiment.
Fig. 3 is a flowchart illustrating step S104 in a SAR high-precision time-series deformation monitoring method for a corner reflector according to an exemplary embodiment.
Fig. 4 is a flowchart illustrating step S104 in a SAR high-precision time-series deformation monitoring method for a corner reflector according to an exemplary embodiment.
Fig. 5 is a flowchart illustrating step S106 in a SAR high-precision time-series deformation monitoring method for a corner reflector according to an exemplary embodiment.
Fig. 6 is a schematic diagram illustrating a corner reflector signal in a SAR image according to an exemplary embodiment.
Fig. 7 is a schematic diagram illustrating a single corner reflector signal prior to interpolation according to an exemplary embodiment.
Fig. 8 is a schematic diagram illustrating an interpolated single corner reflector signal according to an exemplary embodiment.
FIG. 9 is a schematic diagram illustrating the location (20191109) of a strongly scattering target signal according to an exemplary embodiment.
FIG. 10 is a schematic diagram illustrating the location (20191212) of a strongly scattering target signal according to an exemplary embodiment.
FIG. 11 is a diagram illustrating natural homonymous scattering target signals (20191109-20191212), according to an example embodiment.
FIG. 12 is a schematic diagram illustrating the position of a corner reflector according to an exemplary embodiment.
FIG. 13 is a diagram illustrating a sequence of deformations of point A, according to an exemplary embodiment.
FIG. 14 is a diagram illustrating a deformation sequence for B points, according to an exemplary embodiment.
Fig. 15 is a block diagram illustrating an SAR high accuracy time-series deformation monitoring apparatus for a corner reflector according to an exemplary embodiment.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
Fig. 1 is a flowchart illustrating a SAR high-precision time-series deformation monitoring method for a corner reflector according to an exemplary embodiment, where the method includes:
step S101, extracting accurate position information of each corner reflector from the SAR image at each moment;
in general, the corner reflector signal is strong, the signal-to-noise ratio in the SAR image is high, and when the signal-to-noise ratio is higher than 30dB, the positioning accuracy can reach 1/100 resolution. Therefore, the accurate positions of the corner reflectors in different SAR images can be accurately extracted through a Sinc interpolation method, and the position offset of the corner reflectors in different SAR images is calculated.
Step S102, determining corresponding total position offset information of each corner reflector in SAR image pairs at different moments according to the accurate position information of each corner reflector;
bearing-to-center frequency accounting for SAR satellite dataf dc And if not, calculating the central frequency at the corner reflector based on the SAR basic parameters before Sinc interpolation, and moving the frequency spectrum to the fundamental frequency and then performing Sinc interpolation processing.
Estimating the center doppler frequency based on SAR data parameters will be described belowf dc The method of (3). Knowing the position [ R, C ] of the target point in the SAR image]Then the distance time corresponding to this pointt Ra And azimuth timet Az Respectively as follows:
tRa=tRa0+(C-1)ΔtRa
tAz=tAz0+(R-1)ΔtAz
wherein, tRa0And tAz0Representing the starting sampling time, Δ t, of the distance and azimuth directions, respectivelyRaAnd Δ tAzTime sampling intervals representing a distance direction and an azimuth direction, respectively;
according to the distance time of the readable reference point in SAR data parameterst RaRefAnd azimuth timet AzRefAnd the distance time t of each corner reflectorRaAnd azimuth time tAzCalculating the Doppler center frequency of the corner reflector using the following formula:
Figure 42246DEST_PATH_IMAGE001
estimating the center frequency of each pointf dc The data field can be multiplied by an exponential coefficient
Figure 472090DEST_PATH_IMAGE005
And the Sinc interpolation can be carried out by moving the signal frequency spectrum to the fundamental frequency.
Step S103, determining first position offset component information corresponding to a space baseline according to terrain and satellite orbit data;
due to the existence of the spatial baseline, the satellite orbit positions corresponding to the SAR data at different moments are different. Even if the corner reflector is not deformed, the corner reflector has a position offset in the SAR image. In order to obtain accurate deformation information of the corner reflector, it is necessary to compensate for the position deviation due to the spatial baseline in combination with the terrain and satellite orbit data.
As shown in fig. 2, in one embodiment, preferably, the step S103 includes:
step S201, acquiring elevation information of each corner reflector at the position of a main SAR image in an SAR image pair based on external DEM data;
step S202, calculating the space position coordinates of each corner reflector under the WGS84 based on the Doppler equation, the slope equation and the ellipsoid equation, wherein the mathematical expressions of the Doppler equation, the slope equation and the ellipsoid equation are as follows:
Figure 713716DEST_PATH_IMAGE006
wherein, tMAzAnd tMRaRespectively representing the corresponding azimuth time and range time, M (t), at the corner reflector position in the main SAR imageMAz) Represents tMAzSatellite position vector, V (t), corresponding to the time master SAR imageMAz) Represents tMAzSatellite velocity vector v corresponding to time master SAR imagelightIs the speed of light, a, b and c are the ellipsoidal parameters of the earth;
step S203, calculating theoretical coordinates of the corner reflector in the auxiliary SAR image according to the space position coordinates and by combining satellite orbit data corresponding to the auxiliary SAR image in the SAR image pair;
step S204, determining first position offset component information corresponding to the space baseline according to the theoretical coordinates in the auxiliary SAR image and the elevation information in the main SAR image.
After the space position coordinate T of the corner reflector is calculated, theoretical coordinates [ RS _ T, CS _ T ] of the corner reflector in the auxiliary SAR image can be calculated by combining satellite orbit data corresponding to the auxiliary SAR image]. Azimuthal and distance-wise positional shifts [ Δ R ] of the corner reflector caused by the spatial baselineGeo,ΔCGeo]The calculation formula of (2) is as follows:
ΔRGeo =R S_T -R M
ΔCGeo =C S_T -C M
step S104, determining second position offset component information corresponding to system errors and environments according to natural homonymous scattering target signals in the SAR image pair;
generally, there are differences in atmospheric environment at different SAR image acquisition times, which affect the propagation path of electromagnetic waves. Meanwhile, the SAR may have system errors at different working moments. Therefore, when the position deviation caused by the spatial baseline is compensated, the position deviation caused by the system error and the external environment also needs to be compensated.
Step S105, determining deformation position offset information corresponding to the corner reflector according to the total position offset information, the first position offset component information and the second position offset component information of the SAR image pair;
and step S106, determining a high-precision deformation sequence of the corner reflector according to the deformation position offset information of the corner reflector.
In the embodiment, the deformation sequence of the corner reflector is accurately acquired by a signal processing method based on the time-series high-resolution SAR data. In the data processing, the change in the position of the target point due to the baseline is first compensated for based on the satellite orbit data for both problems summarized. Then, natural homonymous targets with stronger signals are searched for in the SAR image, position change caused by atmospheric propagation delay or sensor system errors and the like is compensated through the signals of the homonymous targets, and high-precision deformation of the diagonal reflector of each SAR image is further acquired. And finally, acquiring a deformation sequence of the corner reflector by taking deformation information of the corner reflector of different SAR images as input. The SAR deformation monitoring method based on the corner reflector target can improve the applicability of the SAR deformation monitoring technology based on the corner reflector target and provide technical support for engineering application of the technology.
Fig. 3 is a flowchart illustrating step S104 in a SAR high-precision time-series deformation monitoring method for a corner reflector according to an exemplary embodiment.
As shown in fig. 3, in one embodiment, preferably, the step S104 includes:
step S301, respectively searching natural homonymous scattering target signals in a main SAR image and a side SAR image in the SAR image pair;
step S302, acquiring the accurate position of the natural homonymous scattering target signal in the primary and secondary SAR images by a Sinc interpolation method based on the natural homonymous scattering target signal;
step S303, compensating the position offset corresponding to the space baseline based on the satellite orbit data, and acquiring the residual offset of each natural homonymous scattering target signal;
and step S304, determining second position offset component information corresponding to the system error and the environment according to the average value of the residual quantities of all natural homonymous scattering target signals.
And acquiring the accurate position of the acquired natural homonymous scattering target in the primary and secondary SAR images by a Sinc interpolation method. Then, the residual offset of each natural homonymous scattering target can be obtained by compensating for the position offset due to the spatial baseline based on the satellite orbit data[R res ,C res ]. Therefore, by calculating the average of the residual offsets of all natural homonymous scattering targets, the position offset caused by the system error and the external environment error can be obtained[R Sys ,C Sys ]。
As shown in fig. 4, in one embodiment, preferably, the step S301 includes:
step S401, acquiring a two-dimensional Sinc signal sig based on SAR system parameters:
Figure 51156DEST_PATH_IMAGE003
wherein [ R, C ] is pixel position coordinates of azimuth and distance directions, RSR is distance direction sampling frequency, RBW is distance direction signal bandwidth, PRF is azimuth direction sampling frequency, and ABW is azimuth direction signal bandwidth;
step S402, respectively carrying out correlation matching on windows of the two-dimensional Sinc signals on the main SAR image and the auxiliary SAR image so as to respectively obtain strong scattering target signals with correlation coefficients within a preset range in the main SAR image and the auxiliary SAR image;
after the two-dimensional Sinc signal is obtained, the correlation matching can be carried out on the window of the two-dimensional Sinc signal and the SAR image, and a larger correlation coefficient can be calculated at the position of the strong scattering point target. By setting a proper correlation coefficient threshold value, the strong scattering point target can be searched in the image.
Step S403, geocoding the strong scattering target signals acquired from the main SAR image and the auxiliary SAR image respectively based on the orbit data and the external DEM data, and calculating spatial three-dimensional position data;
the spatial three-dimensional position data is calculated by the following formula:
calculating the space position coordinate T = [ x ] of each strong scattering target signal under WGS84 based on Doppler equation, slope distance equation and ellipsoid equationM, yM, zM]. The mathematical expressions of the three equations are as follows:
Figure 694627DEST_PATH_IMAGE006
wherein, tMAzAnd tMRaRespectively representing the corresponding azimuth time and distance time, M (t), of the strong scattering target signal position in the main SAR imageMAz)Represents tMAzSatellite position vector, V (t), corresponding to the time master SAR imageMAz) Represents tMAzSatellite velocity vector v corresponding to time master SAR imagelightIs the speed of light, a, b and c are the ellipsoidal parameters of the earth;
step S404, according to the space three-dimensional position data of the strong scattering target signals in the main SAR image and the auxiliary SAR image, determining that the strong scattering target signals of which the space position difference values are within a preset distance range in the main SAR image and the auxiliary SAR image are natural homonymy scattering target signals.
Due to the existence of the spatial baseline in the primary and secondary SAR images, the same target point can appear at different positions in the primary and secondary SAR images. At this time, the strong scattering target points acquired in the primary and secondary SAR images are geocoded based on the orbit data and the external DEM data, respectively, and spatial three-dimensional position data (longitude, latitude, and altitude) thereof are calculated. Meanwhile, a distance threshold value is set, and a strong scattering target point with basically the same spatial position in the primary SAR image and the secondary SAR image is determined as a natural homonymous scattering target.
After the position deviation caused by the space base line and the position deviation caused by the system error and the external environment are compensated, the deformation of the corner reflector can be obtainedResulting in a position shift[R defo ,C defo ]。
As shown in fig. 5, in one embodiment, preferably, the step S106 includes:
step S501, according to deformation position offset information of the corner reflector, combining SAR system parameters, and calculating a deformation measurement result of the corner reflector between the time of acquiring the main SAR image and the time of acquiring the auxiliary SAR image;
step S502, the deformation measurement results at different moments are subjected to time sequence processing to determine a high-precision deformation sequence of the corner reflector.
In one embodiment, preferably, the deformation measurement result includes a distance deformation and an azimuth deformation, and the distance deformation and the azimuth deformation are calculated by the following formulas;
Figure 29793DEST_PATH_IMAGE004
wherein v islightRSR is the distance-wise sampling frequency, vSatFor satellite velocity, PRF is the azimuth sampling frequency.
The embodiments are described below by monitoring corner reflectors on a slope. For more reliable results, the monitoring was performed using COSMO-SkyMed data with 3m resolution. The data parameters are shown in table 1.
TABLE 1 some slope COSMO-SkyMed data parameter
Figure 758715DEST_PATH_IMAGE007
The method comprises the following steps:
as shown in fig. 6, the signal of the corner reflector is strong, so that accurate position information of the corner reflector in the SAR image can be acquired, and further the position offset of the corner reflector in different SAR images can be calculated. In the process of extracting the accurate position of the corner reflector in the image, the center frequency of the corner reflector is calculated based on SAR basic parameters, the frequency spectrum is moved to the fundamental frequency, then Sinc interpolation processing is carried out, and finally the position with the strongest signal amplitude is searched to serve as the accurate position of the corner reflector. The corner reflector target signals before and after interpolation are shown in fig. 7 and 8, respectively.
Step two:
due to the existence of the spatial baseline, the satellite orbit positions corresponding to the SAR data at different moments are different. Even if the corner reflector is not deformed, the corner reflector has a position offset in the SAR image. In order to obtain accurate deformation information of the corner reflector, the position deviation caused by the space base line needs to be compensated by combining terrain and satellite orbit data.
Step three:
due to the difference of atmospheric environments at different SAR image acquisition moments, the propagation path of electromagnetic waves is influenced. Meanwhile, the SAR may have system errors at different working moments. In order to compensate for the system error and the position offset caused by the external environment, strong scattering point targets are searched in the primary SAR image and the secondary SAR image respectively, then the strong scattering point targets acquired in the primary SAR image and the secondary SAR image are matched, and finally the position offset caused by the system error and the external environment is obtained through calculation. In the SAR images captured at 20191109 and 20191212, the positions of the detected strong scatterer targets are shown in fig. 9 and 10, respectively, and the positions of the matched natural homonymous scatterer targets are shown in fig. 11.
Step four:
after the position offset caused by the space baseline and the position offset caused by the system error and the external environment are compensated, the position offset caused by the deformation of the corner reflector is obtained, and then the distance deformation of the corner reflector between the acquisition moments of the main SAR image and the auxiliary SAR image can be calculated by combining the relevant parameters of the SAR systemd Ra And azimuthal distortiond Az . And finally, carrying out time sequence processing on the deformation measurement results in different periods, and acquiring the high-precision deformation evolution characteristics of the corner reflector. In this case, the position of the corner reflector on a slope is shown in FIG. 12, where the distance between the corner reflectors A and B is the result of the deformationd Ra As shown in fig. 13 and 14, respectively.
Fig. 15 is a block diagram illustrating an SAR high accuracy time-series deformation monitoring apparatus for a corner reflector according to an exemplary embodiment.
As shown in fig. 15, according to a second aspect of the embodiments of the present disclosure, there is provided a SAR high-precision time-series deformation monitoring device for a corner reflector, the device including:
an extracting module 1501, configured to extract accurate position information of each corner reflector from the SAR image at each time;
a first determining module 1502, configured to determine, according to the accurate position information of each corner reflector, total position offset information corresponding to each corner reflector in the SAR image pair at different times;
a second determination module 1503, configured to determine first position offset component information corresponding to the spatial baseline according to the terrain and the satellite trajectory data;
a third determining module 1504, configured to determine second position offset component information corresponding to a system error and an environment according to a natural homonymous scattering target signal in the SAR image pair;
a fourth determining module 1505, configured to determine deformation position offset information corresponding to the corner reflector according to the total position offset information, the first position offset component information, and the second position offset component information of the SAR image pair;
the fifth determining module 1506 is configured to determine a high-precision deformation sequence of the corner reflector according to the deformation position offset information of the corner reflector.
According to a third aspect of the embodiments of the present disclosure, there is provided a SAR high-precision time-series deformation monitoring device for a corner reflector, the device including:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to:
extracting accurate position information of each corner reflector from the SAR image at each moment;
determining the corresponding total position offset information of each corner reflector in the SAR image pair at different moments according to the accurate position information of each corner reflector;
determining first position offset component information corresponding to a spatial baseline according to terrain and satellite orbit data;
determining second position offset component information corresponding to system errors and environments according to natural homonymous scattering target signals in the SAR image pair;
determining deformation position offset information corresponding to the corner reflector according to the total position offset information, the first position offset component information and the second position offset component information of the SAR image pair;
and determining a high-precision deformation sequence of the corner reflector according to the deformation position offset information of the corner reflector.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the steps of the method of any one of the first aspects.
It is further understood that the use of "a plurality" in this disclosure means two or more, as other terms are analogous. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. The singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It will be further understood that the terms "first," "second," and the like are used to describe various information and that such information should not be limited by these terms. These terms are only used to distinguish one type of information from another and do not denote a particular order or importance. Indeed, the terms "first," "second," and the like are fully interchangeable. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present disclosure.
It is further to be understood that while operations are depicted in the drawings in a particular order, this is not to be understood as requiring that such operations be performed in the particular order shown or in serial order, or that all illustrated operations be performed, to achieve desirable results. In certain environments, multitasking and parallel processing may be advantageous.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims (9)

1. A SAR high-precision time sequence deformation monitoring method for a corner reflector is characterized by comprising the following steps:
extracting accurate position information of each corner reflector from the SAR image at each moment;
determining the corresponding total position offset information of each corner reflector in the SAR image pair at different moments according to the accurate position information of each corner reflector;
determining first position offset component information corresponding to a spatial baseline according to terrain and satellite orbit data;
determining second position offset component information corresponding to system errors and environments according to natural homonymous scattering target signals in the SAR image pair;
determining deformation position offset information corresponding to the corner reflector according to the total position offset information, the first position offset component information and the second position offset component information of the SAR image pair;
determining a high-precision deformation sequence of the corner reflector according to the deformation position offset information of the corner reflector;
the determining, according to the accurate position information of each corner reflector, total position offset information corresponding to each corner reflector in the SAR image pair at different times includes:
determining the corresponding distance direction time t according to the accurate position information of each corner reflectorRaAnd azimuth time tAz；
tRa=tRa0+(C-1)ΔtRa
tAz=tAz0+(R-1)ΔtAz
Wherein, tRa0And tAz0Representing the starting sampling time, Δ t, of the distance and azimuth directions, respectivelyRaAnd Δ tAzTime sampling intervals representing a distance direction and an azimuth direction, respectively; [R,C]Respectively representing the accurate positions of the angular reflector in the azimuth direction and the range direction in the SAR image;
the method comprises the steps that the accurate positions of the corner reflector in the azimuth direction and the distance direction in an SAR image are determined by adopting a Sinc interpolation method, before the Sinc interpolation, the Doppler center frequency at the corner reflector is calculated based on SAR data parameters, the frequency spectrum is moved to the fundamental frequency, and then the Sinc interpolation processing is carried out;
according to the distance of the readable reference point in the SAR data parameter, the time is calculatedt RaRefAnd azimuth timet AzRefAnd the distance of each corner reflector to time tRaAnd azimuth time tAzCalculating the Doppler center frequency of the corner reflector using the following formula:
Figure 216115DEST_PATH_IMAGE001
，
wherein the content of the first and second substances,f dc (R,C) Is the term in the SAR imageR,C]Doppler center frequency at location, tRaRefAnd tAzRefRespectively representing the distance of the reference pointsTime and azimuth time, tRaAnd tAzRespectively representing the distance direction time and the azimuth direction time of each corner reflector; coefAz(0) Coefficient representing an azimuthal polynomial of order 0, CoefAz(1) Coefficient representing an azimuthal polynomial of first order, CoefAz(2) Coefficient representing a second-order azimuthal polynomial, CoefRa(1) Coefficient representing a first order distance polynomial, CoefRa(2) Coefficients representing the second order distance polynomial are read in the SAR data parameters.
2. The method of claim 1, wherein determining first position offset component information corresponding to the spatial baseline from the terrain and satellite trajectory data comprises:
acquiring elevation information of each corner reflector at the position of the main SAR image in the SAR image pair based on external DEM data;
calculating the space position coordinates of each corner reflector under the WGS84 based on a Doppler equation, a slope distance equation and an ellipsoid equation, wherein the mathematical expressions of the Doppler equation, the slope distance equation and the ellipsoid equation are as follows:
Figure 673641DEST_PATH_IMAGE002
wherein, tMAzRepresenting the corresponding azimuthal time at the corner reflector position in the main SAR image, M (t)MAz) Represents tMAzA satellite position vector corresponding to the time main SAR image, T represents a position vector of a target, (x)M, yM, zM) Is the component of the target position vector T in the x, y, z directions in the WGS84 coordinate system, V (T)MAz) Represents tMAzSatellite velocity vector v corresponding to time master SAR imagelightIs the speed of light, tRaDistance direction time of the corner reflector, a, b and c are ellipsoid parameters of the earth, and h is the altitude of the target;
according to the space position coordinates, calculating theoretical coordinates of the corner reflector in the auxiliary SAR image by combining satellite orbit data corresponding to the auxiliary SAR image in the SAR image pair;
and determining first position offset component information corresponding to the space baseline according to the theoretical coordinates in the auxiliary SAR image and the elevation information in the main SAR image.
3. The method of claim 1, wherein determining second position offset component information corresponding to a system error and an environment from the natural homonymous scattering target signals in the pair of SAR images comprises:
respectively searching natural homonymous scattering target signals in a main SAR image and a side SAR image in the SAR image pair;
acquiring the accurate position of the natural homonymous scattering target signal in the primary and secondary SAR images by a Sinc interpolation method based on the natural homonymous scattering target signal;
compensating the position offset corresponding to the space baseline based on the satellite orbit data, and acquiring the residual offset of each natural homonymous scattering target signal;
and determining second position offset component information corresponding to the system error and the environment according to the average value of the residual quantities of all natural homonymous scattering target signals.
4. The method of claim 3, wherein the searching for natural homonymous scattering target signals in the primary SAR image and the secondary SAR image of the SAR image pair, respectively, comprises:
based on SAR system parameters, acquiring a two-dimensional Sinc signal, and defining the signal as sig:
Figure 488014DEST_PATH_IMAGE003
wherein [ R, C ] are pixels of azimuth and distance directions, RSR is distance direction sampling frequency, RBW is distance direction signal bandwidth, PRF is azimuth direction sampling frequency, ABW is azimuth direction signal bandwidth, and sinc is sinc function identification;
respectively carrying out correlation matching on the windows of the two-dimensional Sinc signals in the main SAR image and the auxiliary SAR image so as to respectively obtain strong scattering target signals with correlation coefficients within a preset range in the main SAR image and the auxiliary SAR image;
geocoding strong scattering target signals acquired from the main SAR image and the auxiliary SAR image respectively based on the orbit data and the external DEM data, and calculating spatial three-dimensional position data;
and determining the strong scattering target signals of which the spatial position difference values are within a preset distance range in the main SAR image and the auxiliary SAR image as natural homonymous scattering target signals according to the spatial three-dimensional position data of the strong scattering target signals in the main SAR image and the auxiliary SAR image.
5. The method of claim 1, wherein determining a high-precision deformation sequence of the corner reflector according to the deformation position offset information of the corner reflector comprises:
according to the deformation position offset information of the corner reflector, combining SAR system parameters, calculating a deformation measurement result of the corner reflector between the time of acquiring the main SAR image and the time of acquiring the auxiliary SAR image;
and carrying out time sequence processing on the deformation measurement results at different moments to determine a high-precision deformation sequence of the corner reflector.
6. The method of claim 5, wherein the deformation measurements include a distance deformation and an azimuth deformation, and the distance deformation is calculated using the following formulad RaAnd the azimuthal deformationd Az；
Figure 310476DEST_PATH_IMAGE004
Wherein v islightRSR is the distance-wise sampling frequency, vSatWhich is the satellite velocity, the PRF is the azimuth sampling frequency,C defofor a shift of the target point in distance towards the image pixel due to deformation,R defothe target point is displaced in azimuth towards the image pixels due to the deformation.
7. A SAR high accuracy time series deformation monitoring device for corner reflector, characterized in that the device comprises:
the extraction module is used for extracting the accurate position information of each corner reflector from the SAR image at each moment;
the first determining module is used for determining the corresponding total position offset information of each corner reflector in the SAR image pair at different moments according to the accurate position information of each corner reflector;
the second determining module is used for determining first position offset component information corresponding to the space baseline according to the terrain and the satellite orbit data;
a third determining module, configured to determine second position offset component information corresponding to a system error and an environment according to a natural homonymous scattering target signal in the SAR image pair;
a fourth determining module, configured to determine deformation position offset information corresponding to the corner reflector according to the total position offset information, the first position offset component information, and the second position offset component information of the SAR image pair;
the fifth determining module is used for determining a high-precision deformation sequence of the corner reflector according to the deformation position offset information of the corner reflector;
the first determination module is to:
determining the corresponding distance direction time t according to the accurate position information of each corner reflectorRaAnd azimuth time tAz；
tRa=tRa0+(C-1)ΔtRa
tAz=tAz0+(R-1)ΔtAz
Wherein, tRa0And tAz0Representing the starting sampling time, Δ t, of the distance and azimuth directions, respectivelyRaAnd Δ tAzTime sampling intervals representing a distance direction and an azimuth direction, respectively; [R,C]Respectively representing the accurate positions of the angular reflector in the azimuth direction and the range direction in the SAR image;
the method comprises the steps that the accurate positions of the corner reflector in the azimuth direction and the distance direction in an SAR image are determined by adopting a Sinc interpolation method, before the Sinc interpolation, the Doppler center frequency at the corner reflector is calculated based on SAR basic parameters, and after the frequency spectrum is moved to the fundamental frequency, the Sinc interpolation processing is carried out;
according to the distance of the readable reference point in the SAR basic parameter, the time is calculatedt RaRefAnd azimuth timet AzRefAnd the distance of each corner reflector to time tRaAnd azimuth time tAzCalculating the Doppler center frequency of the corner reflector using the following formula:
Figure 577509DEST_PATH_IMAGE001
，
wherein the content of the first and second substances,f dc (R,C) Is the term in the SAR imageR,C]Doppler center frequency at location, tRaRefAnd tAzRefRespectively representing the distance-wise time and the azimuth-wise time, t, of the reference pointRaAnd tAzRespectively representing the distance direction time and the azimuth direction time of each corner reflector; coefAz(0) Coefficient representing an azimuthal polynomial of order 0, CoefAz(1) Coefficient representing an azimuthal polynomial of first order, CoefAz(2) Coefficient representing a second-order azimuthal polynomial, CoefRa(1) Coefficient representing a first order distance polynomial, CoefRa(2) Coefficients representing the second order distance polynomial are read in the SAR data parameters.
8. A SAR high accuracy time series deformation monitoring device for corner reflector, characterized in that the device comprises:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to:
extracting accurate position information of each corner reflector from the SAR image at each moment;
determining the corresponding total position offset information of each corner reflector in the SAR image pair at different moments according to the accurate position information of each corner reflector;
determining first position offset component information corresponding to a spatial baseline according to terrain and satellite orbit data;
determining second position offset component information corresponding to system errors and environments according to natural homonymous scattering target signals in the SAR image pair;
determining deformation position offset information corresponding to the corner reflector according to the total position offset information, the first position offset component information and the second position offset component information of the SAR image pair;
determining a high-precision deformation sequence of the corner reflector according to the deformation position offset information of the corner reflector;
the determining, according to the accurate position information of each corner reflector, total position offset information corresponding to each corner reflector in the SAR image pair at different times includes:
determining the corresponding distance direction time t according to the accurate position information of each corner reflectorRaAnd azimuth time tAz；
tRa=tRa0+(C-1)ΔtRa
tAz=tAz0+(R-1)ΔtAz
Wherein, tRa0And tAz0Representing the starting sampling time, Δ t, of the distance and azimuth directions, respectivelyRaAnd Δ tAzTime sampling intervals representing a distance direction and an azimuth direction, respectively; [R,C]Respectively representing the accurate positions of the angular reflector in the azimuth direction and the range direction in the SAR image;
the method comprises the steps that the accurate positions of the corner reflector in the azimuth direction and the distance direction in an SAR image are determined by adopting a Sinc interpolation method, before the Sinc interpolation, the Doppler center frequency at the corner reflector is calculated based on SAR basic parameters, and after the frequency spectrum is moved to the fundamental frequency, the Sinc interpolation processing is carried out;
according to the distance of the readable reference point in the SAR basic parameter, the time is calculatedt RaRefAnd orientationTo timet AzRefAnd the distance of each corner reflector to time tRaAnd azimuth time tAzCalculating the Doppler center frequency of the corner reflector using the following formula:
Figure 838727DEST_PATH_IMAGE001
，
wherein the content of the first and second substances,f dc (R,C) Is the term in the SAR imageR,C]Doppler center frequency at location, tRaRefAnd tAzRefRespectively representing the distance-wise time and the azimuth-wise time, t, of the reference pointRaAnd tAzRespectively representing the distance direction time and the azimuth direction time of each corner reflector; coefAz(0) Coefficient representing an azimuthal polynomial of order 0, CoefAz(1) Coefficient representing an azimuthal polynomial of first order, CoefAz(2) Coefficient representing a second-order azimuthal polynomial, CoefRa(1) Coefficient representing a first order distance polynomial, CoefRa(2) Coefficients representing the second order distance polynomial are read in the SAR data parameters.
9. A computer-readable storage medium having stored thereon computer instructions, which, when executed by a processor, carry out the steps of the method according to any one of claims 1 to 6.
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