CN104407332B - A kind of ground SAR updates DEM bearing calibration - Google Patents
A kind of ground SAR updates DEM bearing calibration Download PDFInfo
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Abstract
The present invention relates to the bearing calibration that a kind of ground SAR updates DEM, according to the ground SAR complex field echo datas received, SAR magnitude image is calculated；Extract ground SAR image corner reflector point；Ground SAR image is registering with optical imagery progress；Obtain the ground SAR image data that two antenna sensors are received；Phasing is carried out to two images respectively；Coherence calculation is carried out to the interference pattern of two antennas；Phase unwrapping；The oblique distance signal path calculated after correction is poor, reduces baseline component B in sensorhAnd BvMeasure inaccurate error；Final elevation calibration is completed with ground vertical control point；DEM after ground SAR image and optical imagery, with renewal is carried out into three-dimensional overlay to show.Processing procedure of the present invention does not have approximate, can realize that optics is registering with ground SAR, and DEM can be updated in trimming process, therefore can realize that multi-source data is accurately corrected, with more preferable Three-dimensional Display result.
Description
Technical Field
The invention relates to a DEM updating and correcting technology, in particular to a correcting method for updating a DEM by a ground-based SAR.
Background
The method can update DEM (Digital Elevation Model) by using deformation quantity of Ground-Based SAR interferometry, and can realize accurate correction of Ground-Based SAR amplitude diagram, deformation quantity diagram and optical image in real three-dimensional coordinate system, and the correction method for updating DEM by using deformation quantity of SAR can use deformation quantity of SAR to obtain image before and after deformation by repeatedly observing target area, and can obtain deformation information of target after interference treatment to implement deformation monitoring in short distance, but can not obtain terrain information from echo signal due to orbital invariance, and can not make DEM, for example, Ground-Based SAR interferometry monitors disasters such as mountain landslide, glacier movement and others, monitoring the deformation field, deformation rate and the like of high-rise buildings, dams and the like.
Correspondingly, a method for acquiring the DEM by ground-based InSAR measurement is provided. Noferini et al propose a method of generating a DEM from SAR interference images. (see: L.Noferini, M.Pieraccini, D.Mecatti, G.Macaluso, G.Luziand C.Atzeni, "DEM by group-Based SARIntermetric," IEEE Geoscience and remote Sensing Letters, vol.4, pp.659-663, October 2007.). Noferini et al also propose a method for reducing the influence of the atmosphere on SAR data and generating DEM through SAR interference images. (see: L.Noferini, M.Pieraccini, D.Mecatti, G.Macaluso, G.Luzi and C.Atzeni, "DEM by group-based SAR interaction," IEEE Geoscience and Remote Sensing Letters, vol.4, pp.659-663, October 2007). Since this method mainly describes the influence of atmospheric propagation on SAR data, a method of eliminating the influence of atmospheric is described, and there is no specific description on how to generate DEM by deformation.
Although the deformation generated DEM considers the influence of various factors, the deformation generated DEM has approximation, the optical and ground-based SAR cannot be registered, and the DEM cannot be updated.
Disclosure of Invention
Aiming at the defects that the prior art cannot acquire topographic information from echo signals, cannot make a DEM and the like, the invention aims to provide a correction method for updating the DEM by a ground-based SAR, which can realize the registration of optics and the ground-based SAR and has no approximation in the processing process.
In order to solve the technical problems, the invention adopts the technical scheme that:
the invention relates to a correction method for updating DEM by a ground-based SAR, which comprises the following steps:
step S1: calculating an amplitude image of the SAR according to the received complex-domain echo data of the ground SAR;
step S2: extracting a foundation SAR image corner reflector point from the amplitude image;
step S3: taking corner reflector points in the two images as control points, and registering the ground-based SAR image with the optical image;
step S4: acquiring ground-based SAR image data received by two antenna sensors;
step S5: the first antenna is imaged as an image I at any time1,nThe second antenna is imaged as image I at the corresponding time2,n；
Step S6: respectively carrying out phase correction on the two images;
step S7: performing coherence calculation on interference patterns of the two antennas;
step S8: performing phase unwrapping by using a weighted least square method;
step S9: after phase unwrapping, calculating the corrected path difference of the slant-distance signal, and reducing the baseline component B in the sensorhAnd BvMeasuring an imprecision error;
step S10: finishing the final elevation calibration work by using the surface elevation control points, and calculating a new elevation h value;
step S11: performing three-dimensional superposition display on the ground-based SAR image and the optical image which are registered in the step S3 and the DEM updated in the step S10;
in the step S2, an elliptic paraboloid model is adopted to extract corner reflector points of the ground-based SAR image, and the expression of the elliptic paraboloid model is as follows:
i.e. F ═ q (x-x)0)2+p(y-y0)2-2pq(z+z0)
In the formula, p and q are the sizes of transverse and longitudinal openings of the ellipse, namely the diffusion ranges of the azimuth direction and the distance upwards; x, y are the positions of the pixel values; x is the number of0,y0The coordinate value of the highest point of the model; z is the actual pixel value; z is a radical of0The pixel value of the model up-shift, namely the brightest pixel value of the corner reflector point; if the opening is downward, p, q and z0Both are negative values and F is the solving function constructed by the model.
Solving for p, q, X using the model0,Y0,Z0Five parameters, which are converted to a linear problem, i.e. solved by the following formula:
the ground-based SAR image and the optical image are registered as follows: actually measuring the coordinates of the corner reflector points, taking the corner reflector points in the two images as control points, resolving parameters by adopting a polynomial model, wherein the polynomial correction algorithm is as follows:
wherein (X, Y) is the coordinate in the original image coordinate system, (X, Y) is the coordinate in the corrected coordinate system, a0....ai，b0....biThe parameters are solved for the model and,
and (4) resampling the ground SAR image by adopting a nearest neighbor method to obtain a registered image.
The imaging principle adopts a time domain back propagation algorithm TDBA:
wherein G is the position of a point G (rho, theta) relative to the radar under a cylindrical coordinate system, rho is the distance from the antenna to any point on the ground, theta is the antenna irradiation depression angle, Gt(t,xa,n) Is the image data reflected in the time domain, t is the time, c is the propagation velocity, N is the total number of echo points in the image, xa,nIs a linear array of antenna positions, pnIs the distance from the antenna of the nth figure to any point on the ground.
The two images are phase corrected to: according to the formulaTo determine the phase difference, wherein,for the purpose of reference point phase,representing the phase of the received image in the image over time,the phase difference between each pixel point and a reference point in the complex number image is shown, and n is a natural number which is gradually increased.
The coherence model is:
wherein,<，>is the spatial averaging operator.v1,v2Is a pair of complex pixel values, gamma is coherent and the coherence range is 0 to 1.
And (3) performing phase unwrapping by adopting a weighted least square method, and solving an equation by using a preconditioned conjugate gradient PCG method, wherein the weight function is determined by the average absolute value of the correlation degree of the observed value.
Calculating a corrected slope signal path difference to reduce the horizontal component B of the baseline component in the sensor by the following equationhAnd the perpendicular component B of the base linevMeasurement of inaccuracy error:
ΔrCAL＝Δr-Δr(pREF)+ΔrREF
wherein, Δ rCALFor the corrected slope signal path difference, Δ r is the actual measured slope signal path difference, Δ r (p)REF) For the skew signal path difference at the control point, Δ rREFIs the skew signal path difference except for the control point.
The correction is in calculating the theoretical differential path Δ r corresponding to the control pointREFIn (c) pREF＝(xr,yr,hr):
Then the differential path of each pixel of the whole image is converted so as to be the same as that of the control point; wherein x isrAs the x-coordinate, y, of the control pointrAs y-coordinate of the control point, hrIs a high of the control point, r1Distance, r, from antenna Rx1 to the control point2Distance from antenna Rx2 to the control point, H is the raw elevation. B is the baseline and τ is time.
The new elevation h values are:
wherein, BvAnd BhThe horizontal and vertical components B, H being the original elevation, H being the calibrated elevation, r1Is the distance from the antenna to any point on the ground.
The invention has the following beneficial effects and advantages:
1. the processing process of the method is not approximate, the registration of the optics and the ground SAR can be realized, and the DEM can be updated in the correction process, so that the accurate correction of multi-source data can be realized, and a better three-dimensional display processing result is obtained.
2. The method can realize the correction of the ground SAR and the optical image and the three-dimensional display with the DEM.
Drawings
FIG. 1A is a three-dimensional view of an elliptic paraboloid model of the present invention;
FIG. 1B is a distance diagram of the elliptic paraboloid model of the present invention;
FIG. 1C is an azimuthal view of the elliptic paraboloid model of the present invention;
FIG. 2 is a schematic diagram illustrating steps of a new method for updating DEM based on SAR;
FIG. 3A is a three-dimensional view of a corner reflector point pixel fit shape window in an image;
FIG. 3B is a graph of a corner reflector point pixel fit morphology window distance in an image;
FIG. 3C is a view of the corner reflector point pixel fitting morphology window orientation in an image.
Fig. 4 is a schematic diagram of three-dimensional spatial distribution of simulated DEM and simulated deformation data included in the simulation according to the embodiment of the method of the present invention.
Detailed Description
The invention is further elucidated with reference to the accompanying drawings.
As shown in fig. 2, the method for correcting the updated DEM based on the ground SAR of the present invention includes the following steps:
step S1: calculating an amplitude image of the SAR according to the received complex-domain echo data of the ground SAR;
step S2: in the amplitude image, an elliptic paraboloid model is adopted to accurately extract corner reflector points of the ground-based SAR image, and the expression of the elliptic paraboloid model is as follows:
i.e. F ═ q (x-x)0)2+p(y-y0)2-2pq(z+z0)
Wherein p and q are the sizes of the openings in the transverse and longitudinal directions of the ellipse, i.e. the directions and distances are upwardA scatter range; x, y are the positions of the pixel values; x is the number of0,y0The coordinate value of the highest point of the model; z is the actual pixel value; z is a radical of0The pixel value of the model up-shift, namely the brightest pixel value of the corner reflector point; if the opening is downward, p, q and z0All are negative values, F is a solving function constructed by the model;
step S3: and taking the corner reflector points in the two images as control points, and registering the ground-based SAR image and the optical image. The coordinates of the corner reflector points are actually measured by the field. And (4) taking corner reflector points in the two images as control points, and resolving parameters by adopting a polynomial model. Resampling the ground SAR image by adopting a nearest neighbor method, setting a background value, determining the size range of an output image, and finally evaluating the precision;
the polynomial correction algorithm is as follows:
wherein (X, Y) is the coordinate in the original image coordinate system, (X, Y) is the coordinate in the corrected coordinate system, a0....ai，b0....biSolving parameters for the model;
step S4: obtaining ground-based SAR image data received by two antennas Rx1 and Rx2 sensors, wherein n is the number of images received over time;
step S5: the first antenna is imaged as an image I at any time1,nThe second antenna is imaged as image I at the corresponding time2,n(ii) a The imaging principle adopts a time domain back propagation algorithm TDBA
(Time-Domain Back-propagation Algorithm)；
The imaging principle adopts a time domain back propagation algorithm TDBA:
wherein G is the position of a point G (rho, theta) relative to the radar under a cylindrical coordinate system, rho is the distance from the antenna to any point on the ground, theta is the antenna irradiation depression angle, Gt(t,xa,n) Is the image data reflected in the time domain, t is the time, c is the propagation velocity, N is the total number of echo points in the image, xa,nIs a linear array of antenna positions, pnIs the distance from the antenna of the nth figure to any point on the ground.
Step S6: the two images are phase corrected separately. According to the formulaTo determine a phase difference;for the purpose of reference point phase,representing the phase of the received image in the image over time,representing the phase difference of each pixel point in the complex image and a reference point; n is a natural number which becomes gradually larger.
Step S7: performing coherence calculation on interference patterns of the two antennas; the coherence model is:
wherein,<，>is the spatial averaging operator.v1,v2Is a pair of complex pixel values, gamma is coherent and the coherence range is 0 to 1.
Step S8: and performing phase unwrapping by adopting a weighted least square method. Solving an equation by using a Preconditioned Conjugate Gradient (PCG) method, wherein a weight function is determined by the mean absolute value of the correlation degree of an observed value;
step S9: after phase unwrapping, a corrected slope signal path difference is calculated to reduce the horizontal component B of the baseline in the sensorhAnd the perpendicular component B of the base linevMeasurement of inaccuracy error:
ΔrCAL＝Δr-Δr(pREF)+ΔrREF
Bhis the horizontal component of the baseline, BvPerpendicular component of base line, Δ rCALFor the corrected slope signal path difference, Δ r is the actual measured slope signal path difference, Δ r (p)REF) For the skew signal path difference at the control point, Δ rREFIs the skew signal path difference except the control point;
step S10: finishing the final elevation calibration work by using the surface elevation control points, and calculating a new elevation h value; the correction is in calculating the theoretical differential path Δ r corresponding to the control pointREFIn (c) pREF＝(xr,yr,hr):
Then the differential path of each pixel of the whole image is converted so as to be the same as that of the control point; wherein x isrAs the x-coordinate, y, of the control pointrAs y-coordinate of the control point, hrIs a high of the control point, r1Distance from Rx1 to the control point, r2Distance from Rx2 to the control point, H is the raw elevation, B is the baseline, and τ is time.
The new values of elevation h are:
wherein B is a baseline, H is an original elevation value, H is a calibrated elevation value, r1Is the distance from the antenna to any point on the ground.
Step S11: and displaying the ground SAR image and the optical image which are registered in the step S3 in a three-dimensional superposition mode with the DEM updated in the step S10.
As shown in fig. 1A to 1C, the elliptic paraboloid model simulates a three-dimensional display image of a corner reflector point echo form, and is a three-dimensional image, a distance map and an orientation map in this order.
The method of the present invention is further explained by a simulation test, in which an elliptic paraboloid model is used to accurately extract an angular reflection point in an SAR image. Firstly, roughly determining a large window of the position of a corner reflector point in an SAR amplitude image, fitting by using a 3-by-3 range in the large window, meeting the requirement that the pixel distribution of an elliptic paraboloid model is the position of the corner reflector point, and accurately extracting the position of the point. The model is shown in FIGS. 3A to 3C.
The DEM is updated and overlaid with the distortion map correction as shown in fig. 4.
First, steps S1 to S3 are performed, and then the following formula is followed
The elliptic paraboloid parameters are solved, the corner reflector points are fitted, and the results obtained in step S3 are registered.
The subsequent steps S4 to S11 are sequentially performed, the echo data are acquired, the phase shift is calculated, the deformation amount image is obtained after the interference, and the updated elevation value result is obtained according to the deformation amount, as shown in fig. 4. It can be seen that the DEM obtained by the method can be displayed by being superposed with the deformation quantity diagram, and the spatial layout of the target can be distinguished.
The invention relates to a DEM updating and correcting technology, which accurately extracts a corner reflector point of a ground SAR image through an elliptic paraboloid model, registers the corner reflector point with an optical image, updates the DEM by using the deformation of the ground SAR, finally realizes the correction of the ground SAR and the optical image, and displays the correction and the DEM in three dimensions. The processing process of the method is not approximate, the registration of the optics and the ground SAR can be realized, and the DEM can be updated in the correction process, so that the accurate correction of multi-source data can be realized, and the processing result can be displayed in a better three-dimensional mode.
The above description is only an embodiment of the present invention, and the scope of the present invention is not limited thereto, and any person skilled in the art can understand that the modifications or substitutions should be included in the scope of the present invention disclosed in the present invention, so the scope of the present invention should be subject to the protection scope of the claims.
Claims (10)
1. A correction method for updating DEM based on ground SAR is characterized by comprising the following steps:
step S1: calculating an amplitude image of the SAR according to the received complex-domain echo data of the ground SAR;
step S2: extracting a foundation SAR image corner reflector point from the amplitude image;
step S3: taking corner reflector points in the two images as control points, and registering the ground-based SAR image with the optical image;
step S4: acquiring ground-based SAR image data received by two antenna sensors;
step S5: the first antenna is imaged as an image I at any time1,nThe second antenna is imaged as image I at the corresponding time2,n；
Step S6: respectively carrying out phase correction on the two images;
step S7: performing coherence calculation on interference patterns of the two antennas;
step S8: performing phase unwrapping by using a weighted least square method;
step S9: after phase unwrapping, calculating the corrected path difference of the slant-distance signal, and reducing the baseline component B in the sensorhAnd BvMeasuring an imprecision error;
step S10: finishing the final elevation calibration work by using the surface elevation control points, and calculating a new elevation h value;
step S11: and displaying the ground SAR image and the optical image which are registered in the step S3 in a three-dimensional superposition mode with the DEM updated in the step S10.
2. The method for correcting DEM updated by ground-based SAR according to claim 1, characterized in that: in the step S2, an elliptic paraboloid model is adopted to extract corner reflector points of the ground-based SAR image, and the expression of the elliptic paraboloid model is as follows:
i.e. F ═ q (x-x)0)2+p(y-y0)2-2pq(z+z0)
In the formula, p and q are the sizes of transverse and longitudinal openings of the ellipse, namely the diffusion ranges of the azimuth direction and the distance upwards; x, y are the positions of the pixel values; x is the number of0,y0The coordinate value of the highest point of the model; z is the actual pixel value; z is a radical of0The pixel value of the model up-shift, namely the brightest pixel value of the corner reflector point; if the opening is downward, p, q and z0Both are negative values and F is the solving function constructed by the model.
3. The method for correcting DEM updated by ground-based SAR according to claim 1, characterized in that:
the ground-based SAR image and the optical image are registered as follows: actually measuring the coordinates of the corner reflector points, taking the corner reflector points in the two images as control points, resolving parameters by adopting a polynomial model, wherein the polynomial correction algorithm is as follows:
wherein (X, Y) is the coordinate in the original image coordinate system, (X, Y) is the coordinate in the corrected coordinate system, a0....ai，b0....biThe parameters are solved for the model and,
and (4) resampling the ground SAR image by adopting a nearest neighbor method to obtain a registered image.
4. The method for correcting DEM updated by SAR on ground as claimed in claim 1, characterized in that the imaging principle adopts the time domain back propagation algorithm TDBA:
wherein G is the position of a point G (rho, theta) relative to the radar under a cylindrical coordinate system, rho is the distance from the antenna to any point on the ground, theta is the antenna irradiation depression angle, Gt(t,xa,n) Is the image data reflected in the time domain, t is the time, c is the propagation velocity, N is the total number of echo points in the image, xa,nIs a linear array of antenna positions, pnIs the distance from the antenna of the nth figure to any point on the ground.
5. The method for correcting DEM updated by ground-based SAR according to claim 1, characterized in that: the two images are phase corrected to: according to the formulaDetermining a phase difference by i {1,2}, j {0,1,2.. n }, wherein,for the purpose of reference point phase,representing the phase of the received image in the image over time,the phase difference between each pixel point and a reference point in the complex image is represented, j is {0,1,2.. n }, and n is a natural number which gradually increases.
6. The method for correcting DEM updated by ground-based SAR according to claim 1, characterized in that: the coherence model is:
wherein,<，>is the spatial averaging operator, v1,v2Is a pair of complex pixel values, gamma is coherent and the coherence range is 0 to 1.
7. The method for correcting DEM updated by ground-based SAR according to claim 1, characterized in that:
and (3) performing phase unwrapping by adopting a weighted least square method, and solving an equation by using a preconditioned conjugate gradient PCG method, wherein the weight function is determined by the average absolute value of the correlation degree of the observed value.
8. The method for correcting DEM updated by ground-based SAR according to claim 1, characterized in that:
calculating a corrected slope signal path difference to reduce the horizontal component B of the baseline component in the sensor by the following equationhAnd the perpendicular component B of the base linevMeasurement of inaccuracy error:
ΔrCAL＝Δr-Δr(pREF)+ΔrREF
wherein, Δ rCALFor the corrected slope signal path difference, Δ r is the actual measured slope signal path difference, Δ r (p)REF) For the skew signal path difference at the control point, Δ rREFIs the skew signal path difference except for the control point.
9. The method for calibrating a DEM updated based on SAR of claim 8, wherein: slope signal path difference Δ r except for control pointREFComprises the following steps:
then the differential path of each pixel of the whole image is converted so as to be the same as that of the control point; wherein x isrAs the x-coordinate, y, of the control pointrAs y-coordinate of the control point, hrIs a high of the control point, r1Distance, r, from antenna Rx1 to the control point2The distance from the antenna Rx2 to the control point is shown, and H is an original elevation value; b is the baseline and τ is time.
10. Method for updating DEM on ground SAR according to claim 1, characterized in that said new elevation h has the value:
wherein, BvAnd BhThe horizontal and vertical components B, H being the original elevation, H being the calibrated elevation, r1The distance from the antenna to any point on the ground; Δ rCALIs the corrected skew signal path difference.
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| CN116184402A (en) * | 2022-10-19 | 2023-05-30 | 四川航天燎原科技有限公司 | Airborne real-time three-dimensional imaging radar and aircraft |
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| CN103487809B (en) * | 2013-09-23 | 2016-01-20 | 中国科学院电子学研究所 | A kind of based on BP algorithm and time become the airborne InSAR data disposal route of baseline |
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| CN108562900A (en) * | 2018-05-04 | 2018-09-21 | 中国人民解放军国防科技大学 | SAR image geometric registration method based on elevation correction |
| CN108562900B (en) * | 2018-05-04 | 2020-09-08 | 中国人民解放军国防科技大学 | SAR image geometric registration method based on elevation correction |
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