CN110109106A - A kind of InSAR interferometric phase unwrapping method in region with a varied topography - Google Patents
A kind of InSAR interferometric phase unwrapping method in region with a varied topography Download PDFInfo
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Abstract
The present invention relates to a kind of InSAR interferometric phase unwrapping methods in region with a varied topography, comprising: obtains the SAR image data of target area；The complete cycle number sought between adjacent picture elements is poor；Calculate complete cycle number；It obtains solution and twines phase result.The present invention utilizes InSAR technology, improves the precision of interferometry, no matter Topographic Complex Degree, can accurately carry out interferometric phase solution and twine, greatly expand the measurement range of conventional interference radar.
Description
Technical field
The present invention relates to technical field of remote sensing image processing, and in particular to a kind of InSAR region interferometric phase with a varied topography
Unwrapping method.
Background technique
The core of InSAR technical monitoring Ground Deformation is restored by the phase information obtained between radar and ground target
The geometry and deformation characteristics of ground monitoring target have very strong sensibility to earth's surface miniature deformation.Since radar is observed twice
The variation of condition, including radar track deviation, the variation of atural object backscattering characteristic and the influence of noise, so that obtain twice
The radar signal coherence of ground target reduces, it is difficult to complete the phase unwrapping of the radar target of spatial spreading distribution.In addition, thunder
Up to the lubber line error of satellite, the external dem data that introduces is inaccurate and radar satellite observes the shadow of moment atmospheric oscillation twice
Ring etc., these factors can all reduce the precision of InSAR technical monitoring Ground Deformation result.It is current common for this problem
There are two types of solutions: one is conventional synthesis aperture radar differential interferometry technologies (D-InSAR)；One is based on stabilization
The coherent point object time gene sequence analysis of scattering properties.
Due to the periodicity of trigonometric function so that interferometric phase be wrapped in (- π, π] between, can not reflect true
Ground elevation.The process that phase recovery is true phase corresponding with landform altitude will be wound and be known as phase unwrapping.Ideal feelings
Under condition, by extract orientation and distance to phase gradient, then integrated along orientation and distance to gradient, it can reach
To the purpose of phase unwrapping.And real data due to terrain slope lack sampling, it is folded cover, the influence of the factors such as shade, low signal-to-noise ratio,
It will cause the discontinuous of interferometric phase data, so as to cause the error of phase unwrapping.The complexity of interferometric phase makes phase solution
Twine the difficult point always studied and hot spot.
In the InSAR technical system of early stage, phase unwrapping is often based upon single baseline (Single-baseline) expansion,
This kind of technology is established on the hypothesis (phase continuity assumption) of phase continuity.However, in mountain area
The equal biggish region of hypsographies, phase continuity hypothesis is invalid, so the phase unwrapping technology based on early single baseline exists
The biggish region of the hypsographies such as mountain area is easy to produce phase hit, cannot get high-precision true phase result.For this purpose, in recent years
Carry out researcher and developed some phase unwrapping methods based on more baselines, so that phase unwrapping process eliminates the reliance on Phase Continuation
Property is it is assumed that achieve certain effect.However, existing more baseline phase unwrapping methods consider it is new it is assumed that i.e. assume when
Between there is no substantially deformation for earth's surface during sequence SAR image capturing.Obviously, this hypothesis meets under normal circumstances, but
In the region earth's surface deformation frequent occurrence at any time that human activity is more or geological condition is complicated, it is assumed that can not set up, and then lead
Existing method existing defects are caused, precision needs to be further increased.
Summary of the invention
In view of the deficiencies of the prior art, the purpose of the present invention is to propose to a kind of InSAR interferometric phase solutions in region with a varied topography
Method is twined, using InSAR technology, interferometric phase solution is accurately carried out and twines, greatly expand the measurement model of conventional interference radar
Enclose, solution twine it is high-efficient, avoid in traditional algorithm phase continuity assume and earth's surface elevation it is constant assume it is not applicable caused by defect,
Improve phase unwrapping precision.
The purpose of the present invention is adopt the following technical solutions realization:
The present invention provides a kind of InSAR interferometric phase unwrapping method in region with a varied topography, it is improved in that including:
Step 1, the SAR image data of target area is obtained；
Step 2, the complete cycle number sought between adjacent picture elements is poor；
Step 3, complete cycle number is calculated；
Step 4, it obtains solution and twines phase result.
Preferably, the step 1 obtains SAR image data, specifically includes:
N scape SAR image is obtained sequentially in time, wherein the 1st scape SAR image is main image, remaining N-1 scape SAR image
For subpictures, N-1 is registrated major-minor image.
Preferably, the step 2, the complete cycle number sought between adjacent picture elements is poor, specifically includes:
Step 2-1, the 1st scape SAR main image and remaining N-1 scape SAR subpictures sequence form N-1 SAR interference image pair；
Step 2-2, due to the 1st scape and the 2nd scape SAR filming image time close proximity, during which Ground Deformation very little gives
To ignore, the image since the 3rd scape to the deformation that earth's surface during the 1st scape SAR image occurs cannot be ignored,
For each interference image pair, the earth's surface elevation shape of the N-1 scape subpictures to the 1st scape main image is established according to timing
Become the first relational model of absolute phase corresponding with s-th of pixel and complete cycle number:
Wherein,Indicate the corresponding absolute phase of i-th of interference image centering, s-th of pixel；
ki(s) (i=1,2 ..., N-1) indicate the corresponding complete cycle number of i-th of interference image centering, s-th of pixel；Bi(i=1,2 ..., N-1)
Indicate that the vertical parallax of i-th of interference image pair is long；Δhm(s) when (m=2,3 ..., N-1) indicates m+1 scape SAR filming image
The earth's surface elevation deformation occurred when relative to the 1st scape SAR filming image；λ indicates wavelength；
Step 2-3 establishes the N-1 scape subpictures to the ground of the 1st scape main image according to timing for each interference image pair
Second relational model of table elevation deformation absolute phase corresponding with the s-1 pixel and complete cycle number, the s-1 pixel
Indicate the adjacent picture elements of s-th of pixel:
Step 2-4 enables depth displacement Δ h (the s)-Δ h of the two since s-1 pixel and s-th of pixel are adjacent picture elements
(s-1)=0 it, is established for each interference image pair according to timing in conjunction with first relational model and second relational model
The third relational model of the absolute phase difference of s-th of pixel and the s-1 pixel and complete cycle number difference:
Wherein,Indicate s-th of i-th of interference image centering
Absolute phase difference between pixel and the s-1 pixel, Δ ki(s, s-1)=ki(s)-ki(s-1) (i=1,2 ..., N-1), table
Show that the complete cycle number between i-th of interference image centering, s-th of pixel and the s-1 pixel is poor；
Step 2-5, to seek Δ kiThird relational model is converted to optimal solution model by (s, s-1):
Wherein, i, j=1,2 ..., N-1 and different；
Step 2-6 seeks the optimal solution of optimal solution model, obtains the complete cycle number difference Δ k between adjacent picture elementsi(s,s-1)。
Preferably, the step 3 calculates complete cycle number k, specifically includes:
Step 3-1 determines coherence factor figure: enabling the major-minor image of i-th of interference image pair, i.e. the 1st scape and i+1 scape SAR
Image is respectively S1And S2, the coherence factor figure of i-th of interference image pair is established, is indicated are as follows:Its
In, E () indicates desired value；* conjugation is indicated；Indicate the conjugate complex number of S2；
Step 3-2, the segmentation of coherence factor figure: marking residue points in coherence factor figure and determines the residue points described
Distribution in coherence factor figure determines the residue points corresponding correlation coefficient value on the coherence factor figure, with all residual
Threshold value of the maximum correlation coefficient value as segmentation data in not good enough, by the coherence factor figure and corresponding winding phase diagram point
It is cut into high quality region and low quality region；
Step 3-3, the phase unwrapping in high quality region；
Step 3-4, the phase unwrapping in low quality region.
Further, the step 3-3, the phase unwrapping in high quality region specifically include:
Step 3-3-1 obtains the GPS information at any point in the high quality region of winding phase diagram；
Step 3-3-2 obtains the corresponding complete cycle number of the point using the GPS information inverting；
Step 3-3-3 carries out complete cycle scalar product point to high quality region, obtains the corresponding complete cycle of each pixel in high quality region
Number.
Further, the step 3-4, the phase unwrapping in low quality region specifically include:
Step 3-4-1 classifies to original SAR image according to the range in low quality region, obtains X kind atural object classification,
The range of X kind atural object classification is marked in interference fringe picture low quality region；
Step 3-4-2 chooses 2 GPS points within the scope of every a kind of atural object, 2X GPS point is chosen altogether, for each
GPS point obtains corresponding complete cycle number using GPS information inverting；
Step 3-4-3 establishes fitting function f (x, y) to be fitted the complete cycle number k of any point:
F (x, y)=a0+a1x+a2y+a3x2+a4xy+a5y2, wherein a0, a1, a2, a3, a4, a5For fitting coefficient,
Step 3-4-4 determines the mean square error E of fitting function f (x, y):
Wherein, ki,jIndicate the corresponding complete cycle number of GPS point of the i-th row, jth column, xi,j
And yi.jIt is the ranks value of the i-th row, jth column pixel respectively；
Step 3-4-5 carries out minimum solution to the mean square error E, obtains the coefficient in fitting function f (x, y)
{ai}；
Step 3-4-6 calculates the corresponding complete cycle number of each pixel in low quality region using fitting function f (x, y).
Further, the step 4 obtains solution and twines phase result, specifically includes:
Step 4-1, according to the corresponding complete cycle number k of each pixel in high quality regionhIt is corresponding with each pixel in low quality region
Complete cycle number kl, obtain the corresponding complete cycle number k of each pixel of whole regioni(s)；
Step 4-2 establishes phase unwrapping model:It calculates solution and twines phase
As a result, whereinIndicate the corresponding absolute phase of i-th of interference image centering, s-th of pixel, ψi(s) indicate that s-th of pixel exists
Interference image twines phase result to the solution in i.
Further, the step 2-6, the optimal solution of optimal solution model is sought using sciagraphy.
Compared with the immediate prior art, the invention has the benefit that
Firstly, the present invention utilizes InSAR technology, the precision of interferometry is improved, interferometric phase solution can be accurately carried out
It twines, greatly expands the measurement range of conventional interference radar.Secondly, being protected the present invention provides a kind of phase unwrapping method
Under the premise of demonstrate,proving phase unwrapping success rate, further increases understanding and twine phase masses, and air transportion when the phase without carrying out complexity
It calculates, solution twines high-efficient.Finally, present invention is particularly suitable for hypsography larger (such as mountain area), Ground Deformations relatively frequently (as manually
Behaviour area) area high-precision phase position solution twine, can to avoid in traditional algorithm phase continuity assume and the constant vacation of earth's surface elevation
It is region if defect caused by not applicable, improves phase unwrapping precision, and then earth's surface elevation deformation inversion accuracy can be improved
Geological disaster provides high-precision monitoring means along transmission line of electricity in range.
Detailed description of the invention
The basic flow chart of Fig. 1 the method for the present invention；
The phase unwrapping exemplary diagram of the low mass region of the present invention Fig. 2；
Fig. 3 phase unwrapping comparative result figure of the present invention.
Specific embodiment
Specific embodiments of the present invention will be described in further detail with reference to the accompanying drawing.
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
All other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
Embodiment
The present invention provides a kind of InSAR interferometric phase unwrapping method in region with a varied topography, as shown in Figure 1, comprising:
Step 1, the SAR image data of target area is obtained；
Step 2, the complete cycle number sought between adjacent picture elements is poor；
Step 3, complete cycle number is calculated；
Step 4, it obtains solution and twines phase result.
Preferably, the step 1 obtains SAR image data, specifically includes:
N scape SAR image is obtained sequentially in time, wherein the 1st scape SAR image is main image, remaining N-1 scape SAR image
For subpictures, N-1 is registrated major-minor image.
Preferably, the step 2, the complete cycle number sought between adjacent picture elements is poor, specifically includes:
Step 2-1, the 1st scape SAR main image and remaining N-1 scape SAR subpictures sequence form N-1 SAR interference image pair；
Step 2-2, due to the 1st scape and the 2nd scape SAR filming image time close proximity, during which Ground Deformation very little gives
To ignore, the image since the 3rd scape to the deformation that earth's surface during the 1st scape SAR image occurs cannot be ignored,
For each interference image pair, the earth's surface elevation shape of the N-1 scape subpictures to the 1st scape main image is established according to timing
Become the first relational model of absolute phase corresponding with s-th of pixel and complete cycle number:
Wherein,Indicate the corresponding absolute phase of i-th of interference image centering, s-th of pixel；ki
(s) (i=1,2 ..., N-1) indicate the corresponding complete cycle number of i-th of interference image centering, s-th of pixel；Bi(i=1,2 ..., N-1)
Indicate that the vertical parallax of i-th of interference image pair is long；Δhm(s) when (m=2,3 ..., N-1) indicates m+1 scape SAR filming image
The earth's surface elevation deformation occurred when relative to the 1st scape SAR filming image；λ indicates wavelength；
Step 2-3 establishes the N-1 scape subpictures to the ground of the 1st scape main image according to timing for each interference image pair
Second relational model of table elevation deformation absolute phase corresponding with the s-1 pixel and complete cycle number, the s-1 pixel
Indicate the adjacent picture elements of s-th of pixel:
Step 2-4 enables depth displacement Δ h (the s)-Δ h of the two since s-1 pixel and s-th of pixel are adjacent picture elements
(s-1)=0 it, is established for each interference image pair according to timing in conjunction with first relational model and second relational model
The third relational model of the absolute phase difference of s-th of pixel and the s-1 pixel and complete cycle number difference:
Wherein,Indicate i-th of interference image centering, s-th of pixel
With the absolute phase difference between the s-1 pixel, Δ ki(s, s-1)=ki(s)-ki(s-1) (i=1,2 ..., N-1) indicates the
Complete cycle number between s-th of pixel of i interference image centering and the s-1 pixel is poor；
Step 2-5, to seek Δ kiThird relational model is converted to optimal solution model by (s, s-1):
Wherein, i, j=1,2 ..., N-1 and different；
Step 2-6 seeks the optimal solution of optimal solution model, obtains the complete cycle number difference Δ k between adjacent picture elementsi(s,s-1)。
Preferably, the step 3 calculates complete cycle number k, specifically includes:
Step 3-1 determines coherence factor figure: enabling the major-minor image of i-th of interference image pair, i.e. the 1st scape and i+1 scape SAR
Image is respectively S1And S2, the coherence factor figure of i-th of interference image pair is established, is indicated are as follows:Its
In, E () indicates desired value；* conjugation is indicated；Indicate the conjugate complex number of S2；
Step 3-2, the segmentation of coherence factor figure: marking residue points in coherence factor figure and determines the residue points described
Distribution in coherence factor figure determines the residue points corresponding correlation coefficient value on the coherence factor figure, with all residual
Threshold value of the maximum correlation coefficient value as segmentation data in not good enough, by the coherence factor figure and corresponding winding phase diagram point
It is cut into high quality region and low quality region；
Step 3-3, the phase unwrapping in high quality region；
Step 3-4, the phase unwrapping in low quality region.
Specifically, the step 3-3, the phase unwrapping in high quality region specifically include:
Step 3-3-1 obtains the GPS information at any point in the high quality region of winding phase diagram；
Step 3-3-2 obtains the corresponding complete cycle number of the point using the GPS information inverting；
Step 3-3-3 carries out complete cycle scalar product point to high quality region, obtains the corresponding complete cycle of each pixel in high quality region
Number.
Specifically, the step 3-4, the phase unwrapping in low quality region specifically include:
Step 3-4-1 classifies to original SAR image according to the range in low quality region, obtains X kind atural object classification,
The range of X kind atural object classification is marked in interference fringe picture low quality region；
Step 3-4-2 chooses 2 GPS points within the scope of every a kind of atural object, 2X GPS point is chosen altogether, for each
GPS point obtains corresponding complete cycle number using GPS information inverting；
Step 3-4-3 establishes fitting function f (x, y) to be fitted the complete cycle number k of any point:
F (x, y)=a0+a1x+a2y+a3x2+a4xy+a5y2, wherein a0, a1, a2, a3, a4, a5For fitting coefficient,
Step 3-4-4 determines the mean square error E of fitting function f (x, y):
Wherein, ki,jIndicate the corresponding complete cycle number of GPS point of the i-th row, jth column, xi,jWith
yi.jIt is the ranks value of the i-th row, jth column pixel respectively；
Step 3-4-5 carries out minimum solution to the mean square error E, obtains the coefficient in fitting function f (x, y)
{ai}；
Step 3-4-6 calculates the corresponding complete cycle number of each pixel in low quality region using fitting function f (x, y).
Fig. 2 gives the phase unwrapping example of low mass region, and left figure is original SAR image terrain classification, and right figure is to correspond to
The calibration of interference fringe picture low mass region range.In right figure, it may be seen that if the region of speckle noise is low quality region.Root
According to the range in low quality region, classify to original SAR image, it is other to obtain differently species, and mainly water body is (left herein
Figure).Then, 2 GPS points are chosen within the scope of the water body in interference fringe picture.On this basis, for each GPS point inverting
Corresponding complete cycle number is obtained, and carries out subsequent fitting.
Preferably, the step 4 obtains solution and twines phase result, specifically includes:
Step 4-1, according to the corresponding complete cycle number k of each pixel in high quality regionhIt is corresponding with each pixel in low quality region
Complete cycle number kl, obtain the corresponding complete cycle number k of each pixel of whole regioni(s)；
Step 4-2 establishes phase unwrapping model:It calculates solution and twines phase
As a result, whereinIndicate the corresponding absolute phase of i-th of interference image centering, s-th of pixel, ψi(s) indicate that s-th of pixel exists
Interference image twines phase result to the solution in i.
The phase unwrapping result figure an of Mountainous Regions is given in Fig. 3.Left figure be obtained using traditional algorithm as a result,
Right figure is the result obtained using the method for the present invention.It can be seen that there are apparent phase hits in white edge in left figure；And right figure
In corresponding region it is smoother, error significantly reduces.
Specifically, the step 2-6, the optimal solution of optimal solution model is sought using sciagraphy.
It should be understood by those skilled in the art that, embodiments herein can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the application, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Finally it should be noted that: the above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof, to the greatest extent
Invention is explained in detail referring to above-described embodiment for pipe, it should be understood by those ordinary skilled in the art that: still
It can be with modifications or equivalent substitutions are made to specific embodiments of the invention, and without departing from any of spirit and scope of the invention
Modification or equivalent replacement, should all cover within the scope of the claims of the present invention.
Claims (8)
1. a kind of InSAR interferometric phase unwrapping method in region with a varied topography characterized by comprising
Step 1, the SAR image data of target area is obtained；
Step 2, the complete cycle number sought between adjacent picture elements is poor；
Step 3, complete cycle number is calculated；
Step 4, it obtains solution and twines phase result.
2. according to the method described in claim 1, wherein, the step 1 obtains SAR image data, specifically includes:
N scape SAR image is obtained sequentially in time, wherein the 1st scape SAR image is main image, remaining N-1 scape SAR image is pair
Image is registrated N-1 to major-minor image.
3. according to the method described in claim 1, wherein, the step 2, the complete cycle number sought between adjacent picture elements is poor, specifically
Include:
Step 2-1, the 1st scape SAR main image and remaining N-1 scape SAR subpictures sequence form N-1 SAR interference image pair；
Step 2-2, due to the 1st scape and the 2nd scape SAR filming image time close proximity, during which Ground Deformation very little is omitted,
Image to the deformation that earth's surface during the 1st scape SAR image occurs since the 3rd scape cannot be ignored,
For each interference image pair, according to timing establish the N-1 scape subpictures to the 1st scape main image the deformation of earth's surface elevation with
First relational model of the corresponding absolute phase of s-th of pixel and complete cycle number:
Wherein,Indicate the corresponding absolute phase of i-th of interference image centering, s-th of pixel；ki(s)
(i=1,2 ..., N-1) indicate the corresponding complete cycle number of i-th of interference image centering, s-th of pixel；Bi(i=1,2 ..., N-1) it indicates
The vertical parallax of i-th of interference image pair is long；Δhm(s) (m=2,3 ..., N-1) indicate opposite when m+1 scape SAR filming image
The earth's surface elevation deformation occurred when the 1st scape SAR filming image；λ indicates wavelength；
Step 2-3, for each interference image pair, the earth's surface for establishing the N-1 scape subpictures to the 1st scape main image according to timing is high
Second relational model of journey deformation absolute phase corresponding with the s-1 pixel and complete cycle number, the s-1 pixel indicate
The adjacent picture elements of s-th of pixel:
Step 2-4 enables depth displacement Δ h (the s)-Δ h (s- of the two since s-1 pixel and s-th of pixel are adjacent picture elements
1)=0, in conjunction with first relational model and second relational model, for each interference image pair, s is established according to timing
The third relational model of the absolute phase difference of a pixel and the s-1 pixel and complete cycle number difference:
Wherein,Indicate i-th of interference image centering, s-th of pixel
With the absolute phase difference between the s-1 pixel, Δ ki(s, s-1)=ki(s)-ki(s-1) (i=1,2 ..., N-1) indicates the
Complete cycle number between s-th of pixel of i interference image centering and the s-1 pixel is poor；
Step 2-5, to seek Δ kiThird relational model is converted to optimal solution model by (s, s-1):
Wherein, i, j=1,2 ..., N-1 and different；
Step 2-6 seeks the optimal solution of optimal solution model, obtains the complete cycle number difference Δ k between adjacent picture elementsi(s,s-1)。
4. according to the method described in claim 1, wherein, the step 3 calculates complete cycle number k, specifically includes:
Step 3-1 determines coherence factor figure: enabling the major-minor image of i-th of interference image pair, i.e. the 1st scape and i+1 scape SAR image
Respectively S1And S2, the coherence factor figure of i-th of interference image pair is established, is indicated are as follows:Wherein, E
() indicates desired value；* conjugation is indicated；Indicate the conjugate complex number of S2；
Step 3-2, the segmentation of coherence factor figure: marking residue points in coherence factor figure and determines the residue points described relevant
Distribution in coefficient figure determines the residue points corresponding correlation coefficient value on the coherence factor figure, with all residue points
In maximum correlation coefficient value as segmentation data threshold value, the coherence factor figure and corresponding winding phase diagram are divided into
High quality region and low quality region；
Step 3-3, the phase unwrapping in high quality region；
Step 3-4, the phase unwrapping in low quality region.
5. according to the method described in claim 4, wherein, the step 3-3, the phase unwrapping in high quality region specifically includes:
Step 3-3-1 obtains the GPS information at any point in the high quality region of winding phase diagram；
Step 3-3-2 obtains the corresponding complete cycle number of the point using the GPS information inverting；
Step 3-3-3 carries out complete cycle scalar product point to high quality region, obtains the corresponding complete cycle number of each pixel in high quality region.
6. according to the method described in claim 4, wherein, the step 3-4, the phase unwrapping in low quality region specifically includes:
Step 3-4-1 classifies to original SAR image according to the range in low quality region, X kind atural object classification is obtained, by X
The range of kind atural object classification marks in interference fringe picture low quality region；
Step 3-4-2 chooses 2 GPS points within the scope of every a kind of atural object, chooses 2X GPS point altogether, for each GPS point,
Corresponding complete cycle number is obtained using GPS information inverting；
Step 3-4-3 establishes fitting function f (x, y) to be fitted the complete cycle number k of any point:
F (x, y)=a0+a1x+a2y+a3x2+a4xy+a5y2, wherein a0, a1, a2, a3, a4, a5For fitting coefficient,
Step 3-4-4 determines the mean square error E of fitting function f (x, y):
Wherein, ki,jIndicate the corresponding complete cycle number of GPS point of the i-th row, jth column, xi,jAnd yi.j
It is the ranks value of the i-th row, jth column pixel respectively；
Step 3-4-5 carries out minimum solution to the mean square error E, obtains the coefficient { a in fitting function f (x, y)i}；
Step 3-4-6 calculates the corresponding complete cycle number of each pixel in low quality region using fitting function f (x, y).
7. according to the method described in claim 1, wherein, the step 4 obtains solution and twines phase result, specifically includes:
Step 4-1, according to the corresponding complete cycle number k of each pixel in high quality regionhComplete cycle corresponding with each pixel in low quality region
Number kl, obtain the corresponding complete cycle number k of each pixel of whole regioni(s)；
Step 4-2 establishes phase unwrapping model:It calculates solution and twines phase knot
Fruit, whereinIndicate the corresponding absolute phase of i-th of interference image centering, s-th of pixel, ψi(s) indicate s-th of pixel dry
It relates to as twining phase result to the solution in i.
8. according to the method described in claim 3, wherein, the step 2-6 seeks the optimal of optimal solution model using sciagraphy
Solution.
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