CN106646470A - Chromatographic SAR three-dimensional point cloud generation method based on generalized orthogonal matching pursuit - Google Patents
Chromatographic SAR three-dimensional point cloud generation method based on generalized orthogonal matching pursuit Download PDFInfo
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- CN106646470A CN106646470A CN201611199283.2A CN201611199283A CN106646470A CN 106646470 A CN106646470 A CN 106646470A CN 201611199283 A CN201611199283 A CN 201611199283A CN 106646470 A CN106646470 A CN 106646470A
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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
- G01S13/9027—Pattern recognition for feature extraction
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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
- 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
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Abstract
The invention discloses a chromatographic SAR three-dimensional point cloud generation method based on generalized orthogonal matching pursuit, and the method comprises the following steps: S1, obtaining multi-temporal SAR image data of a target building; S2, carrying out the high-dimensional (slant-range vertical) focusing through a compressed sensing algorithm based on the generalized orthogonal matching pursuit; S3, obtaining the target elevation information, encrypting point cloud through an interpolation method, and expressing and outputting a reconstructed target. The method obtains the high-dimensional information of the target building through the compressed sensing algorithm based on the generalized orthogonal matching pursuit. During iterative operation, N atoms is selected at each time from optimal atoms at most, thereby guaranteeing the robustness of the algorithm while simplifying the calculation complexity of an orthogonal matching pursuit algorithm, and overcoming the constraint that can a signal be restored only if a conventional chromatographic SAR imaging method has to meet the Nyquist sampling law.
Description
Technical field
The present invention relates to electronic signal process technical field, more particularly, to a kind of generalized orthogonal match tracing is based on
Chromatography SAR three-dimensional point cloud generation methods.
Background technology
Current chromatography SAR City Building three-dimensional point clouds generation method be mostly using Fourier transformation focusing algorithm and
The super-resolution tomography algorithm (MUSIC, APES etc.) of Estimation of Spatial Spectrum, MUSIC is calculated in Estimation of Spatial Spectrum tomography algorithm
Method (International Geoscience and Remote Sensing Symposium) is by the association to observation signal
Variance matrix carries out Eigenvalues Decomposition, obtains the estimation of noise subspace, then using signal subspace and noise subspace just
Hand over feature to carry out detection signal, in the angle of arrival (Direction of Arrival, DOA) of target echo super-resolution can be obtained
Rate effect, then can just estimate DOA to be converted into Height Estimation, so as to realize chromatographing SAR urban architectures by geometric transformation
Thing three-dimensional point cloud is generated.
Using Fourier transformation focusing algorithm and the super-resolution tomography algorithm of Estimation of Spatial Spectrum carry out chromatograph SAR into
Picture, it is necessary to which meeting nyquist sampling theorem can just recover signal, and by flight path limited amount and limit pockety
System, it is difficult to effectively imaging.
The content of the invention
The present invention provide it is a kind of overcome the problems referred to above or solve the above problems at least in part based on generalized orthogonal
With the chromatography SAR three-dimensional point cloud generation methods followed the trail of, the restriction of nyquist sampling law is overcome, while can quickly, accurately
Go out the three-dimensional information of City Building using chromatography SAR technology reengineerings.
According to an aspect of the present invention, there is provided a kind of method that chromatography SAR three-dimensional point clouds are generated, to city single building
Thing carries out three-dimensional imaging, comprises the following steps：
S1, the SAR image data for obtaining target structures thing multidate；
S2, by carrying out height dimension focusing based on the compressed sensing algorithm of generalized orthogonal match tracing；
S3, target elevation information is obtained, with interpolation method pass point cloud, the object representation of reconstruct out and is exported.
Used as preferred, step S1 is specifically included：By sensor in different time, Different Flight position to same
Target Acquisition two-dimensional SAR image data.
Used as preferred, the two-dimensional SAR image data includes orbit altitude, revisiting period, ranges of incidence angles, orientation point
Resolution, range resolution ratio, single channel scene size, maximum acquisition length.
Used as preferred, step S2 is specifically included：
S21, by the SAR bidimensional image data of multidate, build a seasonal effect in time series 3-D data set；
S22, the time series signal to each scattering unit are reconstructed, to obtain height dimension information.
Used as preferred, step S21 is specifically included：Determine respectively be intercepted the orientation and distance of target image to
Beginning and end, by two-dimensional SAR plural number image data preserve into two-dimensional complex number array form, by the image ordered series of numbers structure of multidate
Into the third dimension of a time dimension.
Used as preferred, step S22 is specifically included：Three-dimensional array is processed, is obtained for generalized orthogonal
Signal degree of rarefication K, calculation matrix Ф with tracing algorithm and observation signal y, and be input in generalized orthogonal matching pursuit algorithm
Carry out height dimension focusing, with obtain chromatograph to backscattering coefficient.
Used as preferred, the generalized orthogonal matching pursuit algorithm is specifically included：
A, initialization, residual error initialization r0=y, signal supported collection Λ0=Φ, reconstruction signalInitialization iteration time
Number t=1, selects courtyard number N；
B, by residual error, select associated N number of atom, and add in signal supported collection：
Λi=Λi-1∪Γi
C, screening indexed set：
D, renewal residual error：
E, i=i+1, if meeting i >=K, algorithm stops and exports reconstruction signalOtherwise repeat step b to d.
As preferred, in step b, by calculating the inner product of residual error and a certain row of sparse matrix, and inner product is found out
N number of atom of maximum absolute value, pair atom related to residual error is selected.
Used as preferred, step S1 also includes carrying out SAR image data registration, goes tiltedly process, phase error to mend
Repay.
Compared with prior art, the beneficial effects of the present invention is：The present invention is using based on generalized orthogonal match tracing
The compressed sensing algorithm of (Generalized Orthogonal Matching Pursuit, GOMP) obtains subject monomers building
The vertical information of oblique distance, when computing is iterated, select optimal atom number to be maximum N number of every time, simplify orthogonal
Computation complexity with tracing algorithm, overcomes the feelings that tradition chromatography SAR imaging methods must are fulfilled for nyquist sampling law
The restriction of signal could be recovered under condition；Reduce to number of times and the requirement to course line precise control of navigating；Ensureing reconstruction steady
While property, the complexity of computing is reduced, therefore in terms of operational efficiency than orthogonal matching pursuit algorithm advantageously.
Description of the drawings
Fig. 1 is the chromatography SAR three-D imaging method FB(flow block)s of the embodiment of the present invention 1；
Fig. 2 is the idiographic flow schematic diagram of Fig. 1 in the embodiment of the present invention 1；
Fig. 3 is the generalized orthogonal matching pursuit algorithm flow chart of the embodiment of the present invention 1；
Fig. 4 is the SAR imaging results schematic diagrames of the embodiment of the present invention 2.
Fig. 5 is the schematic diagram after the SAR imaging results interpolation encryption of the embodiment of the present invention 2.
Specific embodiment
With reference to the accompanying drawings and examples, the specific embodiment of the present invention is described in further detail.Hereinafter implement
Example is not limited to the scope of the present invention for illustrating the present invention.
Finally, the present processes are only preferably embodiment, are not intended to limit protection scope of the present invention.It is all
Within the spirit and principles in the present invention, any modification, equivalent substitution and improvements made etc. should be included in the protection of the present invention
Within the scope of.
Embodiment 1
A kind of chromatography SAR City Building three-dimensional point cloud generation methods are figures 1 and 2 show that, is comprised the following steps：
S1, the SAR image data for obtaining target structures thing multidate；
S2, by based on generalized orthogonal match tracing compressed sensing algorithm carry out height dimension (oblique distance is vertical) focus on；
S3, target elevation information is obtained, with interpolation method pass point cloud, the object representation of reconstruct out and is exported.
Used as preferred, step S1 is specifically included：By sensor in different time, Different Flight position to same
Target Acquisition N scape two-dimensional SAR image datas.
Used as preferred, the two-dimensional SAR image data includes orbit altitude, revisiting period, ranges of incidence angles, orientation point
Resolution, range resolution ratio, single channel scene size, maximum acquisition length.
Used as preferred, step S2 is specifically included：
S21, by two-dimensional SAR image data constitute a three-dimensional array；
S22, three-dimensional array is compressed perception process, obtain target structures in the vertical information of oblique distance.
Used as preferred, step S21 is specifically included：Determine respectively be intercepted the orientation and distance of target image to
Beginning and end, two-dimensional SAR image data is represented in the form of two-dimensional array, then by 2-D data constitute three dimensions
Group, determines object effects region.
In the present embodiment, the method for three-dimensional array being built using two-dimensional array.Specifically such as：
One two-dimensional array D1=[1 23；4 5 6；78 9],
Three-dimensional array D is built,
Ground floor D (；,；, 1)=D1,
Second layer D (；,；, 2)=2*D1,
Third layer D (；,；, 3)=3*D1 just can obtain three-dimensional array D, determine target image region in order to right
Image data parameter initialization, including light velocity c, carrier frequency f, wavelength, incidence angle, low coverage, centre-to-centre spacing, long distance, orientation point
Resolution, range resolution, oblique distance, horizontal range, basic lineal vector, elevation reference value etc..
From compressive sensing theory, if signal is sparse or compressible in certain transform domain, it is possible to use the Kui less than how
The observation data of this special sample rate are to the signal reconstruction.Due to the image-forming principle of SAR, the vertical signal of oblique distance of SAR image capturings
As sparse signal, therefore compressed sensing can be applied in chromatography SAR three-dimensional imagings, obtain Target scalar in oblique distance
Vertical information, so as to extract the elevation information of atural object.Step S22 is specifically included：Three-dimensional array is processed, is obtained
To signal degree of rarefication K, calculation matrix Ф and observation signal y for generalized orthogonal matching pursuit algorithm, and it is input to broad sense just
Handing in matching pursuit algorithm carries out the vertical signal reconstruct of oblique distance.
As preferred, as shown in figure 3, the generalized orthogonal matching pursuit algorithm is specifically included：
A, the signal sequence obtained in resolution cell, set up sparse base restructuring matrix, initialize, residual error initialization r0=y,
Signal supported collection Λ0=Φ, reconstruction signalInitialization iterations t=1, selects atom number N；
B, by residual error, select associated N number of atom, that is, calculate the inner product of residual error and sparse basis array, find out in
N number of atom of product maximum absolute value, and add in signal supported collection, update Increment Matrix：
Λi=Λi-1∪Γi
C, screening indexed set：
D, signal is carried out according to Increment Matrix least square difference estimate, update residual error：
E, i=i+1, if meeting i >=K, algorithm stops and exports reconstruction signalOtherwise repeat step b to d.
The mode chosen using iteration from calculation matrix selects the N number of column vector maximum with signal correlation, then,
Every time in iterative process, find to vectorial maximally related N column vectors are participated in that (most related is exactly calculation matrix by calculation matrix
A certain column vector is maximum with the inner product of remaining vector), and record this N column vector.Index value is updated in index set, and is remembered
The reconstruct atom set that searches of record, then relevant portion is deducted in observing matrix updating residual vector.When iterations i reaches
During degree of rarefication K, stop iteration.Generalized orthogonal match tracing (Generalized Orthogonal Matching Pursuit,
GOMP) be one kind in OMP innovatory algorithms, when computing is iterated, select every time optimal atom number be it is maximum N number of,
While algorithm robustness is ensured, the computation complexity of orthogonal matching pursuit algorithm is simplified.
Step S1 also includes carrying out SAR image data registration, removes tiltedly process, phase error compensation.
Compared with prior art, the beneficial effects of the present invention is：The present invention is obtained using the compressed sensing algorithm of GOMP
The vertical information of oblique distance of subject monomers building, when computing is iterated, selects every time optimal atom number to be the N number of of maximum,
The computation complexity of orthogonal matching pursuit algorithm is simplified, tradition chromatography SAR imaging methods is overcome and must is fulfilled for Nyquist
The restriction of signal could be recovered in the case of Sampling Theorem；Reduce to number of times and the requirement to course line precise control of navigating；
While ensureing reconstruction steady, the complexity of computing is reduced, therefore compare orthogonal matching pursuit algorithm in terms of operational efficiency
Advantageously.
Embodiment 2
The 14 scape rail lift images chosen under " TerraSAR-X " HH polarization modes between -2013 years 2011 of Beijing area are
Experimental data, slant range resolution is 1.2m, and ground range resolution is 2.15m, and azimuth resolution is 3.3m, and with Beijing Pan Gu seven
Star hotel is used as instance objects.With the image in December, 2011 as main image, other images are from image to example.Through SAR shadows
The registration of picture, the selection and cutting of single building, image go tiltedly with the data prediction such as phase error compensation after, according to upper
State the three-dimensional imaging for realizing example building the step of the 5th part illustrates based on generalized orthogonal matching pursuit algorithm, its result
As shown in Figure 4, the point cloud after interpolation encryption is as shown in Figure 5.
Finally, the present processes are only preferably embodiment, are not intended to limit protection scope of the present invention.It is all
Within the spirit and principles in the present invention, any modification, equivalent substitution and improvements made etc. should be included in the protection of the present invention
Within the scope of.
Claims (9)
1. a kind of method that chromatography SAR three-dimensional point clouds are generated, it is characterised in that comprise the following steps：
S1, the SAR image data for obtaining target structures thing multidate；
S2, by carrying out height dimension focusing based on the compressed sensing algorithm of generalized orthogonal match tracing；
S3, target elevation information is obtained, with interpolation method pass point cloud, the object representation of reconstruct out and is exported.
2. chromatography SAR three-dimensional point cloud generation methods according to claim 1, it is characterised in that step S1 is specifically wrapped
Include：The two-dimensional SAR image number of multidate is obtained to same target structures thing in different time, Different Flight position by sensor
According to.
3. chromatography SAR three-dimensional point cloud generation methods according to claim 2, it is characterised in that the two-dimensional SAR image number
According to including orbit altitude, revisiting period, ranges of incidence angles, azimuth resolution, range resolution ratio, single channel scene size, maximum
Obtain length.
4. chromatography SAR three-dimensional point cloud generation methods according to claim 2, it is characterised in that step S2 is specifically wrapped
Include：
S21, by the SAR bidimensional image data of multidate, build a seasonal effect in time series 3-D data set；
S22, the time series signal to each scattering unit are reconstructed, to obtain height dimension information.
5. chromatography SAR three-dimensional point cloud generation methods according to claim 4, it is characterised in that step S21 is specifically wrapped
Include：Determine respectively be intercepted the orientation and distance of target image to beginning and end, two-dimensional SAR plural number image data is protected
Two-dimensional complex number array form is saved as, the image ordered series of numbers of multidate is constituted into the third dimension of a time dimension.
6. chromatography SAR three-dimensional point cloud generation methods according to claim 4, it is characterised in that step S22 is specifically wrapped
Include：The time series signal of each scattering unit is processed, is obtained for the signal of generalized orthogonal matching pursuit algorithm
Degree of rarefication K, calculation matrix Ф and observation signal y, and be input in generalized orthogonal matching pursuit algorithm and carry out height dimension focusing, with
Obtain chromatography to backscattering coefficient.
7. chromatography SAR three-dimensional point cloud generation methods according to claim 6, it is characterised in that the generalized orthogonal matching
Tracing algorithm is specifically included：
A, initialization, residual error initialization r0=y, signal supported collection Λ0=Φ, reconstruction signalInitialization iterations t=
1, select atom number N；
B, by residual error, select associated N number of atom, and add in signal supported collection：
Λi=Λi-1∪Γi
C, screening indexed set：
D, renewal residual error：
E, i=i+1, if meeting i >=K, algorithm stops and exports reconstruction signalOtherwise repeat step b to d.
8. chromatography SAR three-dimensional point cloud generation methods according to claim 6, it is characterised in that in step b, pass through
The inner product of calculating residual error and a certain row of sparse matrix, and find out N number of atom of inner product maximum absolute value, pair original related to residual error
Son is selected.
9. chromatography SAR three-dimensional point cloud generation methods according to claim 1, it is characterised in that step S1 also includes
Registration is carried out to SAR image data, tiltedly process, phase error compensation is removed.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107133999A (en) * | 2017-05-12 | 2017-09-05 | 天津大学 | Using the tomographic reconstruction method of match tracing |
| CN107942315A (en) * | 2017-11-24 | 2018-04-20 | 中船重工（武汉）凌久电子有限责任公司 | A kind of radar background return based on satellite elevation data produces algorithm |
| CN112734812A (en) * | 2020-12-24 | 2021-04-30 | 北京建筑大学 | Method and device for determining number of scatterers, electronic equipment and storage medium |
| CN116449369A (en) * | 2023-06-16 | 2023-07-18 | 四川杰诺创科技有限公司 | Inverse synthetic aperture radar imaging method based on multi-norm constraint |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107133999A (en) * | 2017-05-12 | 2017-09-05 | 天津大学 | Using the tomographic reconstruction method of match tracing |
| CN107133999B (en) * | 2017-05-12 | 2019-12-06 | 天津大学 | Tomography reconstruction method applying matching pursuit |
| CN107942315A (en) * | 2017-11-24 | 2018-04-20 | 中船重工（武汉）凌久电子有限责任公司 | A kind of radar background return based on satellite elevation data produces algorithm |
| CN107942315B (en) * | 2017-11-24 | 2019-08-27 | 中船重工（武汉）凌久电子有限责任公司 | A kind of radar background return generation algorithm based on satellite elevation data |
| CN112734812A (en) * | 2020-12-24 | 2021-04-30 | 北京建筑大学 | Method and device for determining number of scatterers, electronic equipment and storage medium |
| CN112734812B (en) * | 2020-12-24 | 2023-07-11 | 北京建筑大学 | Method, device, electronic equipment and storage medium for determining number of scatterers |
| CN116449369A (en) * | 2023-06-16 | 2023-07-18 | 四川杰诺创科技有限公司 | Inverse synthetic aperture radar imaging method based on multi-norm constraint |
| CN116449369B (en) * | 2023-06-16 | 2023-08-15 | 四川杰诺创科技有限公司 | Inverse synthetic aperture radar imaging method based on multi-norm constraint |
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