CN105842691A - Automatic adjustment and inlay method of large area InSAR deformation result and device thereof - Google Patents

Abstract

An embodiment of the invention provides an automatic adjustment and inlay method of a large area InSAR deformation result and a device thereof. The method comprises the following steps of automatically identifying a homonymy high coherence point on a large area InSAR adjacent scene SAR image; using the automatically-identified homonymy high coherence point to establish an adjustment model of a large area deformation result and generating an adjustment equation; resolving the adjustment equation and acquiring an adjustment correction amount of a deformation rate of each single scene coverage area in the large area; and using the resolved adjustment correction amounts of the deformation rates of the plurality of single scene coverage areas in the large area to carry out automatic inlay on a large area deformation result. By using the above technical scheme, the scheme can be automatically realized; and large-area coordinated and consistent surface deformation information can be rapidly obtained so that large area surface deformation can be well monitored.

Description

Automatic adjustment and mosaic method and device for large-area InSAR deformation results

technical field

The invention relates to the technical field of InSAR (Synthetic Aperture Radar Interferometry, synthetic aperture radar interferometry), in particular to an automatic adjustment and mosaic method and device for large-area InSAR deformation results.

Background technique

The differential synthetic aperture radar interferometry (D-InSAR, Differential InterferometricSAR) technology based on satellite repeating orbit is a new technology in the field of surface deformation measurement that appeared in the 1980s. It can not only obtain centimeter-level accuracy, but also obtain information on the surface , Compared with layered markers, GPS (Global Positioning System, Global Positioning System) and leveling and other land subsidence technologies, it has great advantages. Traditional D-InSAR is subject to factors such as spatial decoherence, temporal decoherence, and atmospheric interference, making it difficult to guarantee the stability of its application. The time-series InSAR technology that appeared in the late 1990s has completely broken through these limiting factors and is an innovation of D-InSAR technology. The characteristics of time-series InSAR technology are: processing based on time-series SAR images; the object of processing is not all pixels of the entire image, but a subset of pixels that have stable scattering characteristics or maintain high coherence over a long time interval (hereinafter referred to as "high coherence point"). The time-series InSAR technology can generally be summarized into two categories: the single main image time-series InSAR technology represented by permanent scatterer interferometry (Permanent Scatterer or Persistent Scatterer Interferometry or PS-InSAR) and the small baseline subset interferometry technology (Small baseline subset interferometry). , or SBAS InSAR) as the representative multi-primary image time series InSAR technology. Time series InSAR technology has been widely used in deformation monitoring caused by volcanoes, earthquakes, landslides, land subsidence, etc.

Land subsidence is a geological phenomenon in which the regional ground elevation is lowered due to the compression of the crust and surface soil under the action of natural and human factors. It is a special surface deformation and occurs widely in my country. In the early 1990s, the area of land subsidence in 16 provinces (autonomous regions and municipalities) including Shanghai, Tianjin, Beijing, Jiangsu, Zhejiang, and Hebei was about 48,700 km ² . By 2003, it had reached 93,855 km ² . Four severe land subsidence disaster areas including the Delta and the Fenwei Basin. It can be seen that land subsidence has become a regional disaster phenomenon. At present, most of the time-series InSAR deformation monitoring researches that have been carried out at home and abroad are limited to a relatively small area covered by one SAR image. There are few studies on InSAR deformation monitoring for large areas that need to be covered by multi-view SAR images, especially multi-track (track) SAR images.

How to adjust and mosaic the deformation results of multi-scene SAR images based on the extraction of InSAR deformation information of single-scene time series, so as to realize large-area deformation monitoring, is a key problem to be solved urgently by those skilled in the art.

Contents of the invention

Embodiments of the present invention provide an automatic adjustment and mosaic method and device for large-area InSAR deformation results to solve the problem of automatic mosaic of multi-view SAR image deformation results, so as to better realize large-area surface deformation monitoring.

On the one hand, an embodiment of the present invention provides an automatic adjustment and mosaic method for large-area InSAR deformation results, the method comprising:

Automatically identify high-coherence points with the same name on large-area InSAR adjacent scene SAR images;

Using the automatically identified high-coherence points with the same name to establish an adjustment model of the large-area deformation result and generate an adjustment equation;

Solving the adjustment equation to obtain the adjustment correction amount of the deformation rate of each single scene coverage area in the large area;

The deformation results of the large area are automatically mosaicked by using the calculated adjustment corrections of the deformation rates of the multiple single-scene coverage areas in the large area.

On the other hand, an embodiment of the present invention provides an automatic adjustment and mosaic device for large-area InSAR deformation results, and the device includes:

Automatic identification unit, used for automatic identification of high-coherence points with the same name on large-area InSAR adjacent scene SAR images;

The adjustment model establishment unit is used to establish the adjustment model of the large-area deformation result by using the automatically identified high-coherence points with the same name, and generate the adjustment equation;

The adjustment equation solving unit is used to solve the adjustment equation and obtain the adjustment correction amount of the deformation rate of each single scene coverage area in the large area;

The automatic mosaic unit is configured to automatically mosaic the deformation results of the large region by using the calculated adjustment corrections of the deformation rates of the multiple single-scene coverage areas in the large region.

The above-mentioned technical solution has the following beneficial effects: it can be realized automatically, and the large-area coordinated surface deformation information can be quickly obtained, so as to better realize the large-area surface deformation monitoring.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. Those skilled in the art can also obtain other drawings based on these drawings without creative work.

Fig. 1 is a flowchart of an automatic adjustment and mosaic method for large-area InSAR deformation results according to an embodiment of the present invention;

Fig. 2 is a schematic diagram of a large area covered by 4-view SAR images used in the embodiment of the present invention (filling areas such as oblique lines, dots, black, etc. represent the overlapping areas of two-view images, three-view images, and four-view images respectively);

Fig. 3 is the Radarsat-2 image coverage situation and benchmark distribution that the embodiment of the present invention uses;

Fig. 4 is the mosaic diagram of the surface subsidence rate in the Beijing-Tianjin-Hebei region obtained by the embodiment of the present invention;

Figure 5 is the mosaic map of the surface subsidence rate in the Beijing-Tianjin-Hebei region obtained by conventional processing;

Fig. 6 is the histogram of the difference of the sedimentation rate that InSAR and leveling obtain on 142 check points of the application example of the present invention;

FIG. 7 is a schematic structural diagram of an automatic adjustment and mosaic device for large-area InSAR deformation results according to an embodiment of the present invention.

detailed description

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

As shown in Figure 1, it is a flowchart of an automatic adjustment and mosaic method for large-area InSAR deformation results according to an embodiment of the present invention. The method includes:

101. Automatically identify high-coherence points with the same name on large-area InSAR adjacent scene SAR images;

Preferably, before the automatic recognition of the high-coherence points with the same name on the SAR image of the large-area InSAR adjacent scene, the method includes: using the same type of digital elevation model data DEM for the SAR image of the large-area InSAR to perform geographic coding.

The identification of highly coherent points with the same name is the basis of adjustment and mosaic. Although the image matching technology can be used to automatically identify high coherence points with the same name through the matching of adjacent SAR amplitude images, it takes too long. In fact, this problem can be solved quickly by using the principle that high coherence points with the same name have the same geodetic coordinates after geocoding. It must be noted that the geocoding of all SAR images should use the same type of DEM, such as SRTM DEM, so as to ensure that the geocoding of adjacent SAR images has the same planar accuracy. Figure 2 shows a schematic diagram of four scenes of SAR images covering a large area, and the situation of more images covering a larger area can be deduced by analogy. The judging conditions for high coherence points with the same name after geocoding are as follows:

|P1(x, y)-P2(x, y)|<(L _x , L _y ) (1)

Where (x, y) represents the geodetic coordinates after geocoding, P1(x, y), P2(x, y) represents the highly coherent point located at (x, y) on the adjacent SAR image, (x, y) represents The geodetic coordinates after geocoding, L _x , L _y represent the output pixel intervals in the east-west and north-south directions respectively after geocoding. Highly coherent points satisfying condition (1) are considered as homonymous points.

102. Using the automatically identified high-coherence points with the same name to establish an adjustment model of the large-area deformation result, and generate an adjustment equation;

Preferably, the adjustment equation is composed of two types of equations: control point adjustment equation and high coherence point adjustment equation with the same name; when there is no control point in the large area InSAR, the adjustment equation is composed of The point adjustment equation is constructed.

In each single-scene coverage area, the relative deformation rate relative to a certain point in the scene is obtained by time-series InSAR technology. In the absence of a benchmark point (reference point) for specifying the deformation rate, there is a systematic deviation between the linear deformation rate obtained by using the time series InSAR technique and the true value. This systematic deviation can be obtained in the adjustment process of large-area deformation results. For the above-mentioned situation of covering four scene images, it is assumed that the deformation rate of a single scene image is Vi(x, y), and the adjustment correction amount is Δi, i=1,...,4. The equations in the adjustment model consist of two types, one is the control point adjustment equation, and the other is the high coherence point adjustment equation with the same name. With the support of the measured data of the external ground control points, the variance of the control point adjustment is established, namely:

Vi(x,y)+Δi=GCp_V(x,y) (2)

Among them, GCp_V(x, y) represents the deformation rate value measured by leveling or other means at the control point (x, y). They are the reference data for the deformation rate acquired by InSAR.

For the high coherence points with the same name in adjacent scene images, the adjustment equation for the high coherence points with the same name is established, namely:

Vi(x,y)+Δi=Vj(x,y)+Δj,i,j∈{1,2,3,4} (3)

This equation means that after adjustment, points with the same name on different images should have consistent deformation rates. In Figure 2, the overlapping areas of the two-scene images, three-scene images, and four-scene images are marked with oblique lines, dots, and black patterns, respectively. When the point (x, y) is located in the overlapping area of images of two scenes, three scenes, and four scenes, there are 1, 2, and 3 adjustment equations in the form of (3) respectively.

103. Solve the adjustment equation to obtain the adjustment correction amount of the deformation rate of each single scene coverage area in the large area;

Preferably, the solving of the adjustment equation to obtain the adjustment correction amount of the deformation rate of each single-scene coverage area in the large area includes: performing an adjustment on the adjustment equation according to the principle of least squares Calculate and obtain the adjustment correction amount of the deformation rate of each single-scene coverage area in the large area.

Combining the above two types of equations together constitutes a system of linear equations about 4 unknowns (Δ1, Δ2Δ3, Δ4). Because there are many points with the same name, the number of observation equations is far more than the number of unknowns, and the unknowns can be solved according to the principle of least squares, so that the adjustment and absolute calibration of the deformation rate of each scene coverage area are completed at the same time. The weights of the control points are not considered here. In practical applications, there will be situations where different control points have different credibility. At this time, different weights can be set in formula (2) according to the credibility of the control points, which can be considered in the least squares solution to improve the solution accuracy.

When there is no control point in the monitoring area, there are only equations of the second type. The adjustment at this time can be based on the deformation rate value of any coverage area, and there is one degree of freedom in the unknown, so the number is reduced to three. In this way, there is still a systematic deviation between the deformation rate after the adjustment and the true value.

104. Using the calculated adjustment corrections of the deformation rates of multiple single-scene coverage areas in the large area, automatically mosaic the deformation results of the large area.

Preferably, the automatic mosaic of the deformation results of the large area by using the adjustment corrections of the deformation rates of the multiple single-scene coverage areas in the large area calculated by the solution includes: using the calculated large area According to the adjustment correction amount of the deformation rate of multiple single-scene coverage areas, the deformation results of the large area are automatically mosaiced according to the geodetic coordinates after geocoding and the overlapping times of points with the same name.

After completing the adjustment of the deformation results of multiple single-scene coverage areas, the automatic mosaic of large-area deformation results can be completed according to the geocoded geodetic coordinates. The deformation result at the spatial position (x, y) is

$\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; V</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; Vi</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&Delta;i</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; )</span>$

where N represents the overlapping number of highly coherent points at position (x, y). Corresponding to Figure 2, the values of N are 2, 3, and 4 in the oblique line, dotted, and black areas, respectively. In other regions, there is no overlap, only one measurement, and N takes the value 1. In this way, the deformation rate values at all high coherence points in a large area are obtained.

In order to better illustrate the effectiveness and superiority of the technical solution of the present invention, the application examples of the present invention and conventional processing methods are now compared and analyzed as follows: as shown in Figure 3, it is the Radarsat-2 image coverage and Distribution map of benchmarking points. The monitoring area is the Beijing-Tianjin-Hebei region, covering an area of about 100,000 square kilometers. A total of 8 Radarsat-2 wide-mode images are covered. The coverage area of a single image is about 150km*150km. Table 1 shows the number of time-series SAR images and the initial acquisition time of the eight single-scene coverage areas. While using InSAR to monitor the surface subsidence, some leveling data were obtained from the surveying and mapping departments of Beijing and Tianjin. The leveling survey work in Beijing and Tianjin is completed from the beginning of October to the end of November every year, and the three phases of leveling data from 2012 to 2014 have been obtained. Please note that the effective period of the benchmarking point does not completely coincide with the effective period of the SAR image. The positions of these benchmarking points are marked in Figure 3 with solid circles, of which 1/3 of the points represent the benchmarking points involved in the adjustment calculation, a total of 70, and 2/3 of the points represent the benchmarking points used for accuracy verification, a total of 142 indivual.

Table 1 Radarsat-2 image information used in Beijing-Tianjin-Hebei land subsidence monitoring

The average deformation rate in the radar line-of-sight direction of each scene coverage area is obtained by using the time series InSAR technology, and then converted into the vertical surface subsidence rate. Negative values indicate subsidence of the surface and positive values indicate uplift of the surface. Then process according to the adjustment method, obtain the average subsidence rate figure of the large-area mosaic after calibration, as shown in Figure 4, the subsidence rate between different single scene coverage areas has good consistency, this shows that the present invention The method is efficient and reliable.

Figure 5 is a mosaic of deformation rates in the Beijing-Tianjin-Hebei region obtained by conventional processing methods. Since there are only leveling data in Beijing and Tianjin, only the deformation rates of the three scenes labeled 1, 2, 3, and 4 in Figure 3 can be calculated. For direct calibration, the deformation rates of the remaining four scenes can only be indirectly calibrated by transferring the points of the same name with the calibrated data. Finally, when the mosaic of a large area is generated, there will be obvious "stitching seams" due to the inconsistent calibration accuracy of different scenes. It can be seen that there are obvious errors between the results in Figure 5 and Figure 4.

The accuracy of the large-area subsidence rate results shown in Fig. 3 was verified by using 142 benchmarks. The histogram of the difference between the two is shown in Figure 6. The mean square error of the difference is 4.5 mm per year, the maximum value of the difference is 12.1 mm per year, and the minimum value is -11.2 mm per year. Among them, the difference of the subsidence rate on 90 points is located at [-3mm/year, 3mm/year], which also shows that the result of the subsidence rate in the Beijing-Tianjin-Hebei region obtained by the application example of the present invention has very high accuracy. Of course, the starting time of the SAR image and the benchmarking point do not completely coincide, which will also have a certain impact on the difference in the settlement rate calculated by the two.

To sum up, it can be seen that the automatic adjustment and mosaic method of large-area InSAR deformation results of the application example of the present invention has two major advantages. Points and external control points are jointly considered, and the adjustment and absolute calibration of InSAR deformation monitoring results are realized simultaneously. This method has important application value in large-scale surface deformation monitoring.

As shown in Figure 7, it is a schematic structural diagram of an automatic adjustment and mosaic device for large-area InSAR deformation results according to an embodiment of the present invention. The device includes:

Automatic identification unit 71, used for automatic identification of high coherence points with the same name on large-area InSAR adjacent scene SAR images;

The adjustment model establishment unit 72 is used to establish the adjustment model of the large-area deformation result by using the automatically identified high-coherence points with the same name, and generate an adjustment equation;

The adjustment equation solving unit 73 is used to solve the adjustment equation to obtain the adjustment correction amount of the deformation rate of each single scene coverage area in the large area;

The automatic mosaic unit 74 is configured to automatically mosaic the deformation results of the large region by using the calculated adjustment corrections of the deformation rates of the multiple single-scene coverage areas in the large region.

Preferably, the device further includes: a geocoding unit 70, configured to geocode the large-area InSAR SAR images using the same type of digital elevation model data DEM.

Preferably, the adjustment equation is composed of two types of equations: control point adjustment equation and high coherence point adjustment equation with the same name; when there is no control point in the large area InSAR, the adjustment equation is composed of The point adjustment equation is constructed.

Preferably, the adjustment equation solving unit 73 is further specifically configured to solve the adjustment equation according to the principle of least squares, and obtain the adjustment of the deformation rate of each single scene coverage area in the large area correction amount.

Preferably, the automatic mosaic unit 74 is further specifically configured to use the calculated adjustment corrections of the deformation rates of multiple single-scene coverage areas in the large area, according to the geocoded geodetic coordinates and the points of the same name Overlapping times, automatic mosaicking is performed on the large-area deformation results.

The above-mentioned technical solution has the following beneficial effects: it can be realized automatically, and the large-area coordinated surface deformation information can be quickly obtained, so as to better realize the large-area surface deformation monitoring.

It is understood that the specific order or hierarchy of steps in the processes disclosed is an example of exemplary approaches. Based upon design preferences, it is understood that the specific order or hierarchy of steps in the processes may be rearranged without departing from the scope of the present disclosure. The accompanying method claims present elements of the various steps in a sample order, and are not meant to be limited to the specific order or hierarchy described.

In the foregoing Detailed Description, various features are grouped together in a single embodiment to simplify the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments of the subject matter require more features than are expressly recited in each claim. Rather, as the following claims reflect, the invention lies in less than all features of a single disclosed embodiment. Thus the following claims are hereby expressly incorporated into the Detailed Description, with each claim standing on its own as a separate preferred embodiment of this invention.

The foregoing description of the disclosed embodiments was provided to enable any person skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may also be applied to other embodiments without departing from the spirit and scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments presented herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

The foregoing description includes illustrations of one or more embodiments. Of course, it is impossible to describe all possible combinations of components or methods to describe the above-mentioned embodiments, but those skilled in the art should recognize that various embodiments can be further combined and permuted. Accordingly, the embodiments described herein are intended to embrace all such alterations, modifications and variations that fall within the scope of the appended claims. Furthermore, to the extent that the term "comprises" is used in the specification or claims, the word is encompassed in a manner similar to the term "comprises" as interpreted when "comprises" is used as a link in the claims. Furthermore, any use of the term "or" in the specification of the claims is intended to mean a "non-exclusive or".

Those skilled in the art can also understand that various illustrative logical blocks (illustrativelogical blocks), units, and steps listed in the embodiments of the present invention can be implemented by electronic hardware, computer software, or a combination of the two. To clearly demonstrate the interchangeability of hardware and software, the various illustrative components, units and steps above have generally described their functions. Whether such functions are implemented by hardware or software depends on the specific application and overall system design requirements. Those skilled in the art may use various methods to implement the described functions for each specific application, but such implementation should not be understood as exceeding the protection scope of the embodiments of the present invention.

Various illustrative logic blocks or units described in the embodiments of the present invention can be discretely processed by a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field programmable gate array or other programmable logic devices. Gate or transistor logic, discrete hardware components, or any combination of the above designed to implement or operate the described functions. The general-purpose processor may be a microprocessor, and optionally, the general-purpose processor may also be any conventional processor, controller, microcontroller or state machine. A processor may also be implemented by a combination of computing devices, such as a digital signal processor and a microprocessor, multiple microprocessors, one or more microprocessors combined with a digital signal processor core, or any other similar configuration to accomplish.

The steps of the method or algorithm described in the embodiments of the present invention may be directly embedded in hardware, a software module executed by a processor, or a combination of both. The software modules may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM or any other storage medium in the art. Exemplarily, the storage medium can be connected to the processor, so that the processor can read information from the storage medium, and can write information to the storage medium. Optionally, the storage medium can also be integrated into the processor. The processor and the storage medium can be set in the ASIC, and the ASIC can be set in the user terminal. Optionally, the processor and the storage medium may also be set in different components in the user terminal.

In one or more exemplary designs, the above functions described in the embodiments of the present invention may be implemented in hardware, software, firmware or any combination of the three. If implemented in software, the functions can be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes computer storage media and communication media that facilitate transfer of a computer program from one place to another. Storage media may be any available media that can be accessed by a general purpose or special computer. For example, such computer-readable media may include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other device that can be used to carry or store instructions or data structures and Other medium of program code in a form readable by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. In addition, any connection is properly defined as a computer-readable medium, for example, if the software is transmitted from a website site, server, or other remote source via a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL) Or transmitted by wireless means such as infrared, wireless and microwave are also included in the definition of computer readable media. Disks and discs include compact discs, laser discs, optical discs, DVDs, floppy discs, and Blu-ray discs. Disks usually reproduce data magnetically, while discs usually reproduce data optically with lasers. Combinations of the above can also be contained on a computer readable medium.

The specific embodiments described above have further described the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above descriptions are only specific embodiments of the present invention and are not intended to limit the scope of the present invention. Protection scope, within the spirit and principles of the present invention, any modification, equivalent replacement, improvement, etc., shall be included in the protection scope of the present invention.

Claims (10)

1. an automatic adjustment and mosaic method of large-area InSAR deformation results, characterized in that, the method comprises: Automatically identify high-coherence points with the same name on large-area InSAR adjacent scene SAR images; Using the automatically identified high-coherence points with the same name to establish an adjustment model of the large-area deformation result and generate an adjustment equation; Solving the adjustment equation to obtain the adjustment correction amount of the deformation rate of each single scene coverage area in the large area; The deformation results of the large area are automatically mosaicked by using the calculated adjustment corrections of the deformation rates of the multiple single-scene coverage areas in the large area. 2. The automatic adjustment and mosaic method of large-area InSAR deformation results as claimed in claim 1, characterized in that, before the automatic identification of the same-named high-coherence points on the large-area InSAR adjacent scene SAR images, the method includes : The same type of digital elevation model data DEM is used to geocode the InSAR SAR image of the large area. 3. The automatic adjustment and mosaic method of large-area InSAR deformation results as claimed in claim 1, is characterized in that, described adjustment equation is made of two types of equations: control point adjustment equation and high coherence point adjustment equation of the same name; When there is no control point in the large area InSAR, the adjustment equation is composed of the same-named high-coherence point adjustment equation. 4. the automatic adjustment and mosaic method of large-area InSAR deformation results as claimed in claim 1, is characterized in that, described adjustment equation is solved, obtains the coverage area of each single scene in the described large area Adjustment corrections for deformation rates, including: The adjustment equation is solved according to the principle of least squares, and the adjustment correction amount of the deformation rate of each single-scene coverage area in the large area is obtained. 5. the automatic adjustment and mosaic method of large-area InSAR deformation result as claimed in claim 1, it is characterized in that, the adjustment correction amount of the deformation rate of a plurality of single-view coverage areas in the described large-area calculated by using solution , to automatically mosaic the deformation results of the large area, including: Using the calculated adjustment corrections of the deformation rates of multiple single-scene coverage areas in the large area, the deformation results of the large area are automatically mosaiced according to the geocoded geodetic coordinates and the overlapping times of points with the same name. 6. An automatic adjustment and mosaic device for large-area InSAR deformation results, characterized in that the device includes: Automatic identification unit, used for automatic identification of high-coherence points with the same name on large-area InSAR adjacent scene SAR images; The adjustment model establishment unit is used to establish the adjustment model of the large-area deformation result by using the automatically identified high-coherence points with the same name, and generate the adjustment equation; The adjustment equation solving unit is used to solve the adjustment equation and obtain the adjustment correction amount of the deformation rate of each single scene coverage area in the large area; The automatic mosaic unit is configured to automatically mosaic the deformation results of the large region by using the calculated adjustment corrections of the deformation rates of the multiple single-scene coverage areas in the large region. 7. The automatic adjustment and mosaic device of large-area InSAR deformation results as claimed in claim 6, wherein said device further comprises: The geocoding unit is configured to geocode the large-area InSAR SAR images using the same type of digital elevation model data DEM. 8. The automatic adjustment and mosaic device of large-area InSAR deformation results as claimed in claim 6, wherein the adjustment equation is composed of two types of equations: control point adjustment equation and homonymic high coherence point adjustment equation; When there is no control point in the large area InSAR, the adjustment equation is composed of the same-named high-coherence point adjustment equation. 9. The automatic adjustment and mosaic device of large-area InSAR deformation results as claimed in claim 6, characterized in that, The adjustment equation solving unit is further specifically configured to solve the adjustment equation according to the principle of least squares, and obtain the adjustment correction amount of the deformation rate of each single-scene coverage area in the large area. 10. The automatic adjustment and mosaic device of large-area InSAR deformation results as claimed in claim 6, characterized in that, The automatic mosaic unit is further specifically configured to use the adjustment correction amount of the deformation rate of multiple single-scene coverage areas in the large area calculated by the solution, according to the geodetic coordinates after geocoding and the overlapping times of points with the same name, to The large-area deformation results are automatically mosaicked.