CN104237887A - SAR remote-sensing image matching method - Google Patents
SAR remote-sensing image matching method Download PDFInfo
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- CN104237887A CN104237887A CN201410513944.9A CN201410513944A CN104237887A CN 104237887 A CN104237887 A CN 104237887A CN 201410513944 A CN201410513944 A CN 201410513944A CN 104237887 A CN104237887 A CN 104237887A
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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
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9021—SAR image post-processing techniques
- G01S13/9023—SAR image post-processing techniques combined with interferometric techniques
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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
- 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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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
- G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
- G06T7/344—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods involving models
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Abstract
The invention provides a method for achieving SAR image indirect matching by using POS and InSAR interference altitude data. Precise geometrical models and Least-square digital surface matching are used to build to-be-matched SAR images, InSAR three-dimensional digital surface models corresponding to the to-be-matched SAR images, InSAR three-dimensional digital surface models corresponding to reference SAR images, and the coordinate conversion relations among reference images, and indirect matching the homonymy points of the to-be-matched SAR images and the reference images is achieved. The method has the advantages that the method is applicable to matching of SAR images with POS and interference data, and matching difficulty caused by geometrical deformation and gray difference of SAR images of complex terrain areas especially airborne interference SAR images is overcome.
Description
Technical field
The invention belongs to the process of SAR remote sensing image information and SAR remote sensing survey field, especially relate to a kind of SAR Remote Sensing Images Matching Method.
Background technology
Synthetic-aperture radar (SAR) is the main sensors of current active microwave imaging, and compared with optical sensor, by day or night, the weather conditions such as weather mist snow are descended all to obtain valid data, all have a wide range of applications at Military and civil fields.The development of SAR sensor and imaging technique, for SAR provides the foundation in the application of different field.The U.S. utilizes space shuttle as the mapping plan (SRTM) of SAR sensor carrier, indicates that radar remote sensing technology enters the New Times of dimensional topography mapping.
Because SAR image can provide texture information and polarization information, InSAR (synthetic aperture radar interferometry technology) can provide terrain information, SAR and InSAR is day by day paid attention in middle-large scale topographic mapping, SAR surveying and mapping technology also achieves impressive progress, but compared with applying with the mapping of optical image, also there is larger gap.The High Precision Automatic coupling of SAR image is the essential condition of SAR image mapping automation application, is also the technical difficult points hindering SAR image to survey and draw application on a large scale at present.At present, the coupling of SAR image mostly inherits optical image matching process.
Because carried SAR easily obtains interference data, InSAR extracting directly DEM is a large advantage of SAR data mapping, but DEM (digital elevation model) affects clearly by local landform, carrier aircraft flight stability degree etc., even if when there being reference mark, the DEM overall precision value that carried SAR obtains still is greater than 1 meter, local maximum error is even larger, has had a strong impact on the application of InSAR in large scale topographical map industrialization.Compared with extracting DEM with InSAR, the precision of the three-dimensional DEM of extraction extracts DEM precision higher than InSAR, is combined with the area adjustment of rare reference mark SAR image, and it is a kind of comparatively sane method of current SAR mapping that three-dimensional mode carries out mapping.But stereoplotting also exists the lower phenomenon of efficiency at present, because the tie point of the same name required by area adjustment is still chosen substantially by hand.Although the Different matching method of airborne SAR image obtains study more widely, but the success ratio of Auto-matching between carried SAR non-interfering image and precision very undesirable, especially between the airborne imagery of reciprocal observation, between image, to make to be matched to power very low for radiation and difference geometrically, and still lacking at present can the airborne SAR image matching technique of widespread use and method.
SAR remote sensing image picpointed coordinate obtains the extensively application of maturation to the SAR data process field that is corrected in of the mutual conversion of topocentric coordinates, InSAR altitude figures, 3-dimensional digital surface model coupling computer vision field application also widely.By these combine with technique to together, realize the coupling of SAR image, also do not have relevant method to occur both at home and abroad.
Summary of the invention
Owing to taking the SAR image greyscale of acquisition and disparity from different perspectives clearly, the coupling of SAR image especially between airborne SAR image is the difficult point in airborne SAR image information processing.The object of the invention is the auxiliary data making full use of the SAR correction of image, set up the mathematics transformational relation between different images picpointed coordinate, realize the coupling between SAR image by indirect mode, overcome the shortcoming being difficult between large baseline SAR image mate.
Technical scheme of the present invention is the auxiliary data utilizing the SAR correction of image, comprise POS data and InSAR oblique distance altitude figures, by tight model realization InSAR oblique distance altitude figures to the conversion of 3-dimensional digital surface model and 3-dimensional digital surface model to the conversion of image, the conversion parameter realized between 3-dimensional digital surface model corresponding to different images is mated by least square digital watch face, and then the transformational relation set up between different images picpointed coordinate, realize the coordinate conversion between SAR image corresponding image points, and realize the coupling between SAR image by following steps:
(1) POS data and SAR rigorous geometric model is utilized, altitude figures is interfered with reference to image and InSAR corresponding to image to be matched, namely utilize POS data and SAR rigorous geometric model to carry out three-dimensional reconstruction to reference to image and InSAR oblique distance elevation corresponding to image to be matched, convert to reference to InSAR 3-dimensional digital surface model corresponding to image and InSAR 3-dimensional digital surface model corresponding to image to be matched respectively;
(2) in two kinds of digital surface models, choose and significantly carry out least square 3D surface matching in same comparatively zonule containing elevation features, obtain two and comprise translation parameters dX, dY, dZ compared with conversion 7 parameter of zonule digital surface model, rotation parameter ω,
κ and zooming parameter s;
(3) according to any picture point p coordinate (R of image to be matched in territory, respective cell
p, C
p), utilize POS data and interfere altitude figures to calculate the coordinate (X of this picpointed coordinate in the InSAR 3-dimensional digital surface model that image to be matched is corresponding with the InSAR of this picture point
p, Y
p, Z
p);
(4) according to conversion 7 parameter of two kinds of digital surface models, utilize 3-dimensional digital surface transformation model, calculate this three-dimensional point (X
p, Y
p, Z
p) position (X of conjugate points in the InSAR 3-dimensional digital surface model corresponding with reference to image
q, Y
q, Z
q);
(5) according to the POS data with reference to image, utilize the inverse location of tight geometric model by this conjugate points three-dimensional coordinate (X
q, Y
q, Z
q) be transformed into reference on image, obtain the picture point q coordinate (R with reference to image
q, C
q), realize the coordinate (R of image picture point p to be matched
p, C
p) with the coordinate (R with reference to image picture point q
q, C
q) coupling.
Step (3) is to (5), briefly, it is exactly the picpointed coordinate according to image to be matched, POS and InSAR altitude figures is utilized to calculate the coordinate position of this picpointed coordinate in the 3-dimensional digital surface model that image to be matched is corresponding, and according to the conversion parameter of two kinds of digital surface models, calculate the conjugate points position of this three-dimensional point on the digital surface model corresponding with reference to image, the POS data of reference image and tight geometric model is utilized by this conjugate points three-dimensional coordinate to be transformed into reference on image, obtain the corresponding image points coordinate with reference to image, realize the indirect matching of SAR picture point.
Described SAR image is oblique distance image, and InSAR interferes altitude figures to be that InSAR oblique distance interferes altitude figures, and SAR rigorous geometric model is Range-Doppler model.
Described POS data is sensing station, speed and attitude data after the motion compensation of SAR video imaging.
The method can be used for the coupling of SAR image especially between airborne interference SAR image with POS and interference data, can overcome geometry deformation between the SAR image of region with a varied topography and gray difference and the coupling difficulty that causes.
Accompanying drawing explanation
Fig. 1 is the schematic diagram of the SAR image indirect matching method flow under POS data of the present invention and the support of InSAR altitude figures;
Fig. 2 is operation steps schematic diagram of the present invention.
Embodiment
The present invention is by strict geometric transformation model and least square 3D surface matching model, and realize the conversion between different SAR image between picpointed coordinate and the coupling between corresponding image points, implementing procedure, see accompanying drawing 1, is realized by following steps:
Step 1: obtain in the same way with reference to SAR image and InSAR 3-dimensional digital surface model corresponding to SAR image to be matched.Namely by the sensing station in POS data and speed parameter are transformed in tangent plane rectangular coordinate system, utilize the POS data of image, InSAR to interfere altitude figures and tight geometric model node-by-node algorithm with reference to three-dimensional coordinate corresponding to SAR image picture point, obtain the 3-dimensional digital surface model of image.In its midsagittal plane rectangular coordinate system, the computing method of each object space point coordinate are: according to the position of this moment sensor of imaging moment interpolation of picture point, speed, attitude and Doppler parameter; From InSAR altitude figures, altitude figures corresponding to this picture point is extracted according to picpointed coordinate; Height value corresponding to sensing station value, velocity amplitude, imaging doppler parameter value, picture point is used as given value, utilizes the dimensionally areal coordinate value (X, Y, Z) that distance-Doppler tight equation solution picture point is corresponding.
Range-Doppler equations expression formula is as follows:
Wherein (Xs, Ys, Zs, V
x, V
y, V
z) be topocentric coordinates and SAR center of antenna state vector, λ, f
d, R
jfor SAR wavelength, Doppler frequency and radar wave measured distance, these parameters can be extracted from POS data and sensor imaging parameters, Z is elevation parameter, can extract from InSAR altitude figures, solve the X in above-mentioned equation and Y parameter, dimensionally areal coordinate value (X, Y, Z) can be obtained.
Step 2: carry out Least squares matching to reference to image and 3-dimensional digital surface model corresponding to image to be matched, namely according to reference number surface model with treat the principle that distance between digital surface model conjugate points is minimum, solve the Conformal transformation parameter vector T of transformational relation between two kinds of digital surface models, comprise three translation t vectors: [dX, dY, dZ]
t, three rotation angle parameter ω,
a κ and zooming parameter s.Make the some P on the digital surface model to be matched and conjugate points Q on reference number surface model meet: Q=t+sRP, and according to transformed error vector e objective function e
te is minimum solves conversion parameter vector T:[dX, dY, dZ, ω,
κ, s]
t, wherein R be angle parameter ω,
the rotation matrix that κ is corresponding, P is the three-dimensional coordinate (X of image picture point to be joined correspondence in InSARDSM
p, Y
p, Z
p).
Step 3: according to the picture point p coordinate (R of image to be matched
p, C
p), picture point imaging moment is extracted and the position of this moment sensor of interpolation, speed, attitude and Doppler parameter from POS, from the altitude figures that InSAR extracting data picture point is corresponding, solve the three-dimensional point P coordinate figure (X of picture point in the InSAR digital surface model that image to be matched is corresponding according to Range-Doppler equations
p, Y
p, Z
p), and according to conversion 7 parameter obtained in step 2, this point is transformed in InSAR 3-dimensional digital surface model corresponding to reference image, namely according to formula:
Obtain the three-dimensional coordinate (X of the conjugate points Q of P
q, Y
q, Z
q), wherein R (ω,
κ) in step 2 obtain angle parameter ω,
the rotation matrix that κ is corresponding, dX, dY, dZ are the translation parameters obtained in step 2, and s is the zooming parameter obtained in step 2.
Utilize the three-dimensional coordinate of Q and the POS data with reference to image, utilize Range-Doppler equations to calculate the picture point q coordinate (R of Q point on reference image by the mode of iteration
q, C
q), the homonymy matching point of image p point to be matched is with reference to the q point on image; According to the three-dimensional coordinate (X of Q
q, Y
q, Z
q) iterative computation is with reference to the picture point q coordinate (R on image
q, C
q) method be:
1. given initial row x
0, and by initial row assignment to current line and x
n=x
0;
2. according to the current line xn photography corresponding moment sensing station of interpolation and attitude, and according to sensing station Xs, Ys, Zs, speed V
x, V
y, V
z, topocentric coordinates X, Y, Z and Space-Based Radar be to impact point space length R
j, in conjunction with wavelength X parameter, calculate side-looking RADOP calculated value: f
d counts=2 [(X-Xs) V
x+ (Y-Ys) V
y+ (Z-Zs) V
z]/λ R
j;
The discrepancy delta f of the doppler values 3. calculated according to the actual doppler values of imaging and above-mentioned steps
d=f
d counts-f
dif, | Δ f
d| when being less than given threshold value, stop iterative search, current line x
nbe correspondingly millet cake image row-coordinate to be asked, i.e. R
q=x
n, jump to and 6. walk, otherwise carry out and 4. walk;
4. according to Doppler difference △ f
dand image direction is to resolution M
areappraise the capable x of picture point place image that ground point is corresponding
n+1:
5. according to xth
n+1the corresponding track profile value of row image moment interpolation, repeats the operation operation that 2. beginning the walks.
6. according to topocentric coordinates and the capable photography moment sensing station (Xs, Ys, Zs) of corresponding image, topocentric coordinates (X, Y, Z), initial oblique distance and distance to image resolution Mr, calculate picture point theoretical row coordinate C
q
Value (the R of the corresponding picpointed coordinate of ground point is solved by the method for above-mentioned iteration
q, C
q), namely obtain q point at the image space coordinate with reference to image.
Utilize step 3, the conversion in available acquisition matching area between any picture point, the conversion of all picture points and coupling in feasible region.
The present invention mainly comprises the following steps as seen in Figure 2: (1) realizes interfering elevation to the conversion with reference to InSAR 3-dimensional digital surface model with reference to the InSAR that image is corresponding by tight geometric manipulations, and InSAR interference elevation corresponding to image to be matched is to the conversion of INSAR 3-dimensional digital surface model to be matched; (2) obtain with reference to conversion 7 parameter between InSAR 3-dimensional digital surface model corresponding to image and InSAR 3-dimensional digital surface model corresponding to image to be matched by least square 3D surface matching; (3), interfere the support of elevation at image POS and InSAR to be joined under, the conversion of image picture point p to be joined to corresponding ground three-dimensional point P is realized by tight location model; (4) according to 7 parameters that (2) obtain, three-dimensional coordinate transformational relation is utilized to obtain the conjugate points Q of P point on the 3-dimensional digital surface model corresponding with reference to image; (5) under supporting with reference to image POS, according to the inverse location of tight geometry, realize Q point to the coordinate conversion with reference to image picture point q, and then realize the coupling of p and q.
Claims (7)
1. a method for SAR Remote Sensing Images Matching, is characterized in that, comprises the following steps:
(1) POS data and SAR rigorous geometric model is utilized, altitude figures is interfered with reference to image and InSAR corresponding to image to be matched, convert to reference to InSAR 3-dimensional digital surface model (3DDigitalSurfaceModel, DSM) corresponding to image and InSAR 3-dimensional digital surface model corresponding to image to be matched respectively;
(2) in two kinds of digital surface models, choose and significantly carry out least square 3D surface matching in same comparatively zonule containing elevation features, obtain two and comprise translation parameters dX, dY, dZ compared with the conversion 7 parameter vector T of zonule digital surface model, rotation parameter ω,
κ and zooming parameter s;
(3) according to any picture point p image coordinate (R of image to be matched corresponding in matching area
p, C
p), utilize POS data and interfere altitude figures to calculate the three-dimensional point coordinate (X of this picture point in the InSAR 3-dimensional digital surface model that image to be matched is corresponding with the InSAR of this picture point
p, Y
p, Z
p);
(4) utilize two kinds of digital surface models to mate conversion 7 parameter obtained, calculate this three-dimensional point (X
p, Y
p, Z
p) position (X of conjugate points in the 3-dimensional digital surface model corresponding with reference to image
q, Y
q, Z
q);
(5) according to the POS data with reference to image, tight geometric model is utilized against location algorithm by this conjugate points three-dimensional coordinate (X
q, Y
q, Z
q) be transformed into reference on image, obtain the image coordinate (R of the picture point q with reference to image
q, C
q), realize the coordinate (R of image picture point p to be matched
p, C
p) with the coordinate (R with reference to image picture point q
q, C
q) coupling.
2. the method for SAR Remote Sensing Images Matching according to claim 1, is characterized in that: described SAR image is oblique distance image, and InSAR interferes altitude figures to be that InSAR oblique distance interferes altitude figures, and SAR rigorous geometric model is Range-Doppler model.
3. the method for SAR Remote Sensing Images Matching according to claim 1, is characterized in that: described POS data is sensing station, speed and attitude data after the motion compensation of SAR video imaging.
4. the method for SAR Remote Sensing Images Matching according to claim 1, is characterized in that: the acquisition methods with reference to InSAR 3-dimensional digital surface model corresponding to image and InSAR 3-dimensional digital surface model corresponding to image to be matched described in step (1) is as described below:
Sensing station in POS data and speed parameter are transformed in tangent plane rectangular coordinate system, utilize the POS data of image and tight geometric model node-by-node algorithm with reference to three-dimensional coordinate corresponding to SAR image picture point, obtain the InSAR 3-dimensional digital surface model that image is corresponding;
The computing method of each point coordinate of InSAR 3-dimensional digital surface model that described image is corresponding are: according to the position of sensor in this moment tangent plane rectangular coordinate system of imaging moment interpolation of picture point, speed, attitude and Doppler parameter; From InSAR altitude figures, altitude figures corresponding to this picture point is extracted according to picpointed coordinate; Elevation corresponding to sensing station, speed, imaging doppler parameter, picture point is used as given value, utilizes Range-Doppler equations to solve dimensionally areal coordinate value (X, Y, Z) corresponding to picture point;
Range-Doppler equations expression formula is as follows:
Wherein, (Xs, Ys, Zs, VX, VY, VZ) be SAR center of antenna position and speed parameter, (λ, f
d, R
j) be SAR wavelength, Doppler frequency and radar value impact point distance, Z is elevation parameter, extracting directly from InSAR oblique distance altitude figures, solve the X in above-mentioned equation and Y parameter, the 3D point coordinate value (X, Y, Z) of 3-dimensional digital surface model can be obtained.
5. the method for SAR Remote Sensing Images Matching according to claim 1, it is characterized in that: in step (2), Least squares matching is carried out to reference to image and 3-dimensional digital surface model corresponding to image to be matched, namely according to reference to the minimum principle of the distance between the digital surface model of image and the digital surface model conjugate points of image to be matched, solve the Conformal transformation parameter T collection of transformational relation between two kinds of digital surface models, comprise three translation parameters: dX, dY, dZ, three independent rotation angle parameter ω,
κ, and a zooming parameter s; Point P on the InSAR digital surface model making image to be matched corresponding meets with reference to the conjugate points Q on InSAR digital surface model corresponding to image: Q=t+sRP, and according to the objective function e of transformed error vector e
te is minimum solves conversion parameter set T:(dX, dY, dZ, ω,
κ, s), wherein R represent rotation matrix R that three angle parameters form (ω,
κ), P is vector [X
p, Y
p, Z
p]
t, Q is vector [X
q, Y
q, Z
q]
t, t is vector [dX, dY, dZ]
t.
6. the method for SAR Remote Sensing Images Matching according to claim 1, is characterized in that: in step (3) and step (4), according to the picture point p coordinate (R of image to be matched
p, C
p), picture point imaging moment is extracted and the position of this moment sensor of interpolation, speed, attitude and Doppler parameter from POS, from the altitude figures that InSAR extracting data picture point is corresponding, solve the three-dimensional point P coordinate figure (X of picture point in the InSAR digital surface model that image to be matched is corresponding according to Range-Doppler equations
p, Y
p, Z
p), and according to conversion 7 parameter obtained in step (2), this point is transformed in 3-dimensional digital surface model corresponding to reference image, namely according to formula:
Obtain the three-dimensional coordinate (X of the conjugate points Q of P
q, Y
q, Z
q), wherein R (ω,
angle parameter ω κ) obtained for step (2) is middle,
the rotation matrix that κ is corresponding, dX, dY, dZ are the translation parameters obtained in step (2), and s is the zooming parameter obtained in step (2).
7. the method for SAR Remote Sensing Images Matching according to claim 1, it is characterized in that: in step (5), utilize the three-dimensional coordinate of Q and the POS data with reference to image, utilize Range-Doppler equations to calculate the picture point q coordinate (R of Q point on reference image by the mode of iteration
q, C
q), the homonymy matching point of image p point to be matched is with reference to the q point on image; According to the three-dimensional coordinate (X of Q
q, Y
q, Z
q) iterative computation is with reference to the picture point q coordinate (R on image
q, C
q) method be:
1. the capable valuation x of given initial image
0, and make current line x
n=x
0;
2. according to current line x
nthe photography corresponding moment sensing station of interpolation and attitude, and according to sensing station (Xs, Ys, Zs), speed (V
x, V
y, V
z), topocentric coordinates (X, Y, Z) and radar be to the space length R of impact point
j, in conjunction with wavelength X parameter, calculate side-looking RADOP calculated value: f
d counts=2 [(X-Xs) V
x+ (Y-Ys) V
y+ (Z-Zs) V
z]/λ R
j;
The discrepancy delta f of the doppler values 3. calculated according to the actual doppler values of imaging and above-mentioned steps
d=f
d counts-f
d, when | Δ f
d| when being less than given threshold value, current line x
nbe correspondingly millet cake image row-coordinate to be asked, i.e. R
q=x
n, jump to and 6. walk, otherwise enter step 4.;
4. according to △ f
dand image direction reappraises picture point place image behavior x corresponding to ground point to resolution Ma
n+1:
In formula, V is the velocity magnitude of SAR sensor;
5. by current line x
nagain assignment, i.e. x
n=x
n+1, repeat the operation that 2. beginning walks;
6. according to topocentric coordinates and the capable photography moment sensing station (Xs, Ys, Zs) of corresponding image, terrain object point coordinate (X, Y, Z), initial oblique distance R
0, and slant range resolution M
r, calculate picture point theoretical row coordinate C
q
Value (the R of the corresponding picpointed coordinate of ground point is solved by the method for above-mentioned iteration
q, C
q), namely obtain q point at the image space coordinate with reference to image;
Utilize step 3, the conversion in available acquisition matching area between any picture point, the conversion of all picture points and coupling in feasible region.
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