CN102445690B - Three-dimensional imaging QR decomposition method of synthetic aperture radar - Google Patents
Three-dimensional imaging QR decomposition method of synthetic aperture radar Download PDFInfo
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- CN102445690B CN102445690B CN201010513822.1A CN201010513822A CN102445690B CN 102445690 B CN102445690 B CN 102445690B CN 201010513822 A CN201010513822 A CN 201010513822A CN 102445690 B CN102445690 B CN 102445690B
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Abstract
The invention discloses a three-dimensional imaging QR decomposition method of a synthetic aperture radar, relating to the radar three-dimensional imaging technology and comprising the following steps: obtain a binocular-vision complex image of an observed object through two-dimension focusing of original echo data which is obtained through observation of each track, perform registration to a binocular-vision complex image sequence, perform skew symmetric matrix process for phase compensation, and obtain observed sampling data of an object in the height direction; geometrically build an operational matrix which realizes the object elevation imaging according to each observed position and radar observation, obtain a linear equation in a matrix-vector type between the sampling data in the height direction and an object elevation image; perform QR decomposition to the operational matrix, solve the linear equation by utilizing an orthogonal matrix and an upper triangular matrix, which are obtained through decomposition and obtain the object elevation image; finish three-dimension imaging to the object combining the two-dimension object images which are obtained by each two-dimension imaging. The matrix equation inversion technology based on QR decomposition can obtain the object image in the height direction and obtain the three-dimension object image with a high resolution.
Description
Technical field
The present invention relates to radar three-dimensional imaging technical field, is a kind of disposal route for synthetic aperture radar three-dimensional imaging.
Background technology
Synthetic-aperture radar is the repeatedly parallel observation in short transverse by Texas tower, has collected the echo data to target under different visual angles, along the repeatedly sampling of short transverse, has formed height to synthetic aperture; The pulse compression that aperture is synthetic and distance makes progress making progress in conjunction with orientation, has realized the three-dimensional imaging to observed object.2000, the people such as German scholar A.Reigber, in paper < < First Demonstration of Airborne SAR Tomography UsingMultibaseline L-Band Data > >, carry out the research of airborne many baselines SAR three-dimensional imaging, proposed the spectrum estimating processing method of three-dimensional imaging.In follow-up study, F.Lomdardini, the people such as S.Guillaso are respectively at paper < < Adaptive spectral estimation formultibaseline SAR tomography with airborne L-band data > >, in < < Polarimetric SAR Tomography > >, introduced Capon, the methods such as MUSIC are carried out Estimation of Spatial Spectrum, proposition realizes the high-resolution three-D imaging method of many baselines SAR.2003 and 2005, the people such as Italy scholar G.Fornaro have carried out three-dimensional imaging research to spaceborne many baselines SAR respectively in paper and < < Three-Dimensional Focusing with Multipass SAR Data > > and < < Three-Dimensional Multipass SAR Focusing:Experiments WithLong-Term Spaceborne Data > >, by signal modeling, obtained height to the matrix-vector linear equation between observation data and target elevation map picture, and use the methods such as wave beam formation and svd to carry out three-dimensional imaging experiment.First many baselines SAR three-dimensional imaging carries out two-dimensional imaging to the data of every track collection, obtain the two-dimension focusing data vector that target obtains under difference observation visual angle, then utilize height to the sampled data estimation space spectrum of synthetic aperture, or solve linear equation, obtain target along the image of short transverse, thereby the target range-orientation two dimensional image obtaining in conjunction with each observation is realized the three-dimensional imaging to target.
Summary of the invention
The object of the invention is to propose a kind of QR decomposition method of synthetic aperture radar three-dimensional imaging, be that the height gathering according to synthetic-aperture radar is to the linear equation between observation data and target elevation map picture, based on QR, decompose, to obtain high-resolution three-dimensional imaging result.
For achieving the above object, technical solution of the present invention is:
The QR decomposition method of synthetic aperture radar three-dimensional imaging is to use the height of QR decomposition technique Technologies Against Synthetic Aperture Radar collection to carry out target three-dimensional imaging processing to data of multiple angles;
Synthetic-aperture radar is by target is highly upwards being carried out to observation from various visual angles, obtain target along the sampled data of short transverse, it can realize by airborne radar or spaceborne radar in the flight that repeatedly repeats in differing heights position, also can in flight observation, realize by laying array antenna, also can in ground track radar system, move realization by the two dimensional surface of antenna;
Synthetic-aperture radar along orientation to each observation track keeping parallelism, can generate separately the two dimensional image of observation scene, can be positive side-looking, stravismus, strip-type or the imaging of bunching type observation mode; The orientation of each observation track, is to arrange along vertical height direction, or along continuous straight runs arrangement, or along having the direction of an angle to arrange with horizontal direction.
The QR decomposition method of described synthetic aperture radar three-dimensional imaging, it comprises the steps:
Steps A: the target scene original echo data to each observation collection are carried out two-dimensional imaging, generates the haplopia complex pattern of observing scene range-azimuth plane;
Step B: the two-dimensional image sequence that each observation is generated is carried out registration, the image that minimum observation position place obtains of take is master image;
Step C: the oblique solution of every width image being carried out to phase compensation is processed, and phase modulation factor is by the determining positions of each observation;
Step D: the object height obtaining after being processed by oblique solution, to the computing operator matrix of observed samples data and elevation imaging, obtains the linear equation between observation data and target elevation map picture;
Step e: use QR decomposition method to invert to the linear equation of Vector-Matrix Form, obtain target along the image in different resolution of short transverse;
The target scene two dimensional image that step F: integrating step A generates, obtains range-azimuth-height dimensional resolution image of target.
The QR decomposition method of described synthetic aperture radar three-dimensional imaging, described in it, in step D, the structure formula of the computing operator matrix of elevation imaging is:
Wherein, the track number that N is each observation, M be object height to vector length, n=1 ..., N, m=1 ..., M, j is imaginary unit, exp is exponential function, λ is radar wavelength, r ' is target oblique distance value, the reference viewing angle that θ is synthetic-aperture radar,
for the angle of each observation with horizontal direction, l
nbe the n time observation and with reference to the distance between observation position.
The QR decomposition method of described synthetic aperture radar three-dimensional imaging, described in it, in step e, QR decomposition solves linear equation method and obtains target elevation map picture, comprises the steps:
Step e 1: the computing operator matrix to elevation imaging carries out QR decomposition, is decomposed into the product of orthogonal matrix and upper triangular matrix;
Step e 2: invert to decomposing the orthogonal matrix obtaining, its inverse matrix is its associate matrix;
Step e 3: to the linear equation between observed samples data and target elevation map picture, equation both sides are distinguished to the inverse matrix of premultiplication orthogonal matrix by height, obtained the upper triangular matrix equation of inverting target elevation map picture;
Step e 4: solve upper triangular matrix equation, obtain the elevation of target to image.
The beneficial effect of the inventive method is: a kind of method that proposes synthetic aperture radar three-dimensional imaging, according to the observation of synthetic-aperture radar, build height for how much to the linear equation between observation data and target elevation map picture, and use QR decomposition method to solve this linear equation, obtain the elevation image in different resolution of target, thereby realize the high-resolution three-dimensional imaging of target.
Accompanying drawing explanation
Fig. 1 is synthetic aperture radar three-dimensional imaging observation geometric representation;
Fig. 2 is the processing flow chart of synthetic aperture radar three-dimensional imaging QR decomposition method of the present invention;
Fig. 3 is that in the inventive method, elevation imaging linear equation builds process flow diagram;
Fig. 4 is that in the inventive method, QR decomposes the processing flow chart that solves linear equation.
Embodiment
The present invention is the QR decomposition method of synthetic aperture radar three-dimensional imaging, how much of the observations of the SAR three-dimensional imaging of method institute foundation as shown in Figure 1, x be carrier aircraft flight orientation to, y is distance direction, z is vertical height direction.Carrier aircraft has been carried out N time parallel observation in short transverse altogether to target scene, the minimum track of definition height and position is reference position, H is its podium level, the visual angle of reference position beam center is θ, its central beam direction is with reference to oblique distance direction r, and the angle of each survey layout direction and horizontal direction is
definition s is orthogonal to carrier aircraft heading x and with reference to the elevation direction of oblique distance direction r, has set up three-dimensional imaging coordinate system x-r-s, and true origin is positioned at reference to position of platform to be located.
The target scene original echo that each observation is obtained through range-azimuth to two-dimensional imaging after, obtain haplopia complex pattern data, now to the impact point in three dimensions, the target focus data that the n time observation station obtains is expressed as
Wherein, λ is radar wavelength, γ (s) be target along elevation to scattering function, the elevation that the size of twice a is observation scene is to scope, r
n(x ', r ', s '), n=1 ..., N is the distance between target and the n time observation, according to Fresnel approximation, it can be expressed as
Wherein, l
nbe the n time observation and with reference to the distance between observation position.Therefore the phase bit position of the resulting target focus data of the n time flight observation can be expressed as
According to the phase place of target focus data, the oblique solution phase factor of linear frequency modulation item is removed in definition
After oblique solution is processed, the focus data phase bit position that the n time observation obtains is
Now, the height obtaining to the signal frequency of observation data is
The target two-dimension focusing signal that the n time observation obtains is
Therefore, to the target in each range-azimuth resolution element, obtained its along elevation to scatter distributions function and height to the linear equation relational expression between synthetic aperture sampled data, be expressed as Vector-Matrix Form and be
g＝Φγ
Wherein, the two-dimension focusing data vector that g obtains for each observation, γ be target elevation to scatter distributions function, Φ is the operation matrix between sampled data and elevation map picture, the distance dependent of it and each observation position and target and radar antenna, is expressed as
Wherein, the number that N is each observation, the object height that M is required reconstruction is to vector length, n=1 ..., N, m=1 ..., M, j is imaginary unit, and exp is exponential function, and λ is radar wavelength, and r ' is target oblique distance value, the reference viewing angle that θ is synthetic-aperture radar,
for the angle of each observation with horizontal direction, l
nbe the n time observation and with reference to the distance between observation position.
According to observation data vector sum target elevation, to the linear equation between scattering function, utilize the inversion operation to matrix equation, inverting target elevation to image.
Below in conjunction with accompanying drawing, describe each related detailed problem of QR decomposition method of synthetic aperture radar three-dimensional imaging of the present invention in detail.Be to be noted that described embodiment is only intended to be convenient to the understanding of the present invention, and it is not played to any restriction effect.
The QR decomposition method of synthetic aperture radar three-dimensional imaging of the present invention, its concrete implementation step as shown in Figure 2, mainly contains:
Steps A: the target scene original echo data to each observation collection are carried out two-dimensional imaging, generates the haplopia complex pattern of observing scene range-azimuth plane;
Step B: the two-dimensional image sequence that each observation is generated is carried out registration, the image that minimum observation position place obtains of take is master image;
Step C: the oblique solution of every width image being carried out to phase compensation is processed, and phase modulation factor is by the determining positions of each observation;
Step D: the object height obtaining after being processed by oblique solution, to the computing operator matrix of observed samples data and elevation imaging, obtains the linear equation between observation data and target elevation map picture;
Step e: use QR decomposition method to invert to the linear equation of Vector-Matrix Form, obtain target along the image in different resolution of short transverse;
The target scene two dimensional image that step F: integrating step A generates, obtains range-azimuth-height dimensional resolution image of target.
Structure height in the inventive method is to the linear equation between observation data and target elevation map picture, and the computing operator matrix that calculates elevation imaging is one of core content of the present invention, and concrete implementation step as shown in Figure 3, mainly contains:
Step D1: according to each observation position of synthetic-aperture radar and radar parameter, calculate the computing operator matrix Φ of elevation imaging, computing formula is:
Wherein, the number that N is each observation, M be object height to vector length, n=1 ..., N, m=1 ..., M, j is imaginary unit, exp is exponential function, λ is radar wavelength, r ' is target oblique distance value, the reference viewing angle that θ is synthetic-aperture radar,
for the angle of each observation with horizontal direction, l
nbe the n time observation and with reference to the distance between observation position.
Step D2: the object height obtaining after being processed by oblique solution, to observed samples data, obtains the linear equation between observation data and target elevation map picture, is expressed as g=Φ γ; Wherein, g be object height to observed samples data, γ be target elevation to scatter distributions function.
It is one of core content of the present invention that QR decomposition method in the inventive method solves linear equation, and concrete implementation step as shown in Figure 4, mainly contains:
Step e 1: the computing operator matrix to elevation imaging carries out QR decomposition, is decomposed into the product of orthogonal matrix Q and upper triangular matrix R, is expressed as Φ=QR;
Step e 2: invert to decomposing the orthogonal matrix obtaining, its inverse matrix is its associate matrix Q
-1=Q
h;
Step e 3: to the linear equation between observed samples data and target elevation map picture, equation both sides are distinguished to the inverse matrix of premultiplication orthogonal matrix by height, obtained the upper triangular matrix equation of inverting target elevation map picture, be expressed as R γ=Q
hg;
Step e 4: solve upper triangular matrix equation, obtain the elevation of target to image.
The method that the present invention is above-mentioned, has applied on computers MATLAB software and has been verified, and Technologies Against Synthetic Aperture Radar emulated data and ground rail system image data carried out three-dimensional imaging processing, and the validity of method has obtained checking.
The above; it is only the embodiment in the present invention; but protection scope of the present invention is not limited to this; any people who is familiar with this technology is in the disclosed technical scope of the present invention; can understand conversion or the replacement expected; all should be encompassed in of the present invention comprise scope within, therefore, protection scope of the present invention should be as the criterion with the protection domain of claims.
Claims (2)
1. a QR decomposition method for synthetic aperture radar three-dimensional imaging, is to use QR decomposition technique Technologies Against Synthetic Aperture Radar to carry out target three-dimensional imaging processing along the data of multiple angles of short transverse collection, it is characterized in that:
Synthetic-aperture radar is by target being carried out in short transverse to the observation of various visual angles, obtain target along the sampled data of short transverse, by airborne radar or spaceborne radar, the flight that repeatedly repeats in differing heights position realizes for it, or by laying array antenna, in flight observation, realize, or the two dimensional surface of antenna moves realization in ground track radar system;
Synthetic-aperture radar along orientation to each observation track keeping parallelism, can generate separately the two dimensional image of observation scene, be positive side-looking, stravismus, strip-type or the imaging of bunching type observation mode; The orientation of each observation track, is to arrange along vertical height direction, or along continuous straight runs arrangement, or along having the direction of an angle to arrange with horizontal direction;
The QR decomposition method of this synthetic aperture radar three-dimensional imaging comprises the steps:
Steps A: the target scene original echo data to each observation collection are carried out two-dimensional imaging, generates the haplopia complex pattern of observing scene range-azimuth plane;
Step B: the two-dimensional image sequence that each observation is generated is carried out registration, the image that minimum observation position place obtains of take is master image;
Step C: the oblique solution of every width image being carried out to phase compensation is processed, and phase modulation factor is by the determining positions of each observation;
Step D: the object height obtaining after being processed by oblique solution, to the computing operator matrix of observed samples data and elevation imaging, obtains the linear equation between observation data and target elevation map picture;
Step e: use QR decomposition method to invert to the matrix of coefficients of the linear equation of Vector-Matrix Form, obtain target along the image in different resolution of short transverse;
The target scene two dimensional image that step F: integrating step A generates, obtains range-azimuth-height dimensional resolution image of target;
The structure formula of the computing operator matrix of elevation imaging in described step D is:
Wherein, N is observation track number, M be object height to vector length, n=1 ..., N, m=1 ..., M, j is imaginary unit, exp is exponential function, λ is radar wavelength, r ' is target oblique distance value, the reference viewing angle that θ is synthetic-aperture radar,
for the angle of each observation with horizontal direction, l
nbe the n time observation and with reference to the distance between observation position.
2. the QR decomposition method of synthetic aperture radar three-dimensional imaging as claimed in claim 1, is characterized in that: in described step e, QR decomposition solves linear equation method and obtains target elevation map picture, comprises the steps:
Step e 1: the computing operator matrix to elevation imaging carries out QR decomposition, is decomposed into the product of orthogonal matrix and upper triangular matrix;
Step e 2: invert to decomposing the orthogonal matrix obtaining, its inverse matrix is its associate matrix;
Step e 3: to the linear equation between observed samples data and target elevation map picture, equation both sides are distinguished to the inverse matrix of premultiplication orthogonal matrix by height, obtained the upper triangular matrix equation of inverting target elevation map picture;
Step e 4: solve upper triangular matrix equation, obtain the elevation of target to image.
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| CN106526592B (en) * | 2016-12-09 | 2019-03-26 | 中国科学院电子学研究所 | The estimation method of the low scattering region scattering value of SAR image based on frequency spectrum |
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| US10318822B2 (en) * | 2017-04-06 | 2019-06-11 | GM Global Technology Operations LLC | Object tracking |
| CN109946697A (en) * | 2019-04-01 | 2019-06-28 | 中国科学院电子学研究所 | A kind of reconstructing device and method for reconstructing of digital elevation model |
| CN110823191B (en) * | 2019-10-08 | 2021-12-07 | 北京空间飞行器总体设计部 | Method and system for determining ocean current measurement performance of mixed baseline dual-antenna squint interference SAR |
| CN112799064B (en) * | 2020-12-30 | 2023-05-26 | 内蒙古工业大学 | Cylindrical aperture nonlinear progressive phase iterative imaging method and device |
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| CN117630936B (en) * | 2024-01-23 | 2024-04-09 | 中国科学院空天信息创新研究院 | Synthetic aperture radar observation angle analysis method and device, electronic equipment and medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101561504A (en) * | 2008-04-16 | 2009-10-21 | 中国科学院电子学研究所 | Height direction dimension reduction processing method for three-dimensional imaging of circumferential synthetic aperture radar |
| CN101581780A (en) * | 2008-05-14 | 2009-11-18 | 中国科学院电子学研究所 | Three-dimensional focus imaging method of side-looking chromatography synthetic aperture radar |
| CN101614810A (en) * | 2008-06-25 | 2009-12-30 | 电子科技大学 | A kind of method for merging resolutions of linear array three-dimensional imaging synthetic aperture radars |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2009137528A1 (en) * | 2008-05-05 | 2009-11-12 | The Advantage Network, Llc | Microwave imaging system and method |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101561504A (en) * | 2008-04-16 | 2009-10-21 | 中国科学院电子学研究所 | Height direction dimension reduction processing method for three-dimensional imaging of circumferential synthetic aperture radar |
| CN101581780A (en) * | 2008-05-14 | 2009-11-18 | 中国科学院电子学研究所 | Three-dimensional focus imaging method of side-looking chromatography synthetic aperture radar |
| CN101614810A (en) * | 2008-06-25 | 2009-12-30 | 电子科技大学 | A kind of method for merging resolutions of linear array three-dimensional imaging synthetic aperture radars |
Non-Patent Citations (7)
| Title |
|---|
| Gianfranco Fornaro et al..Three-dimensional focusing with multipass SAR data.《IEEE Transactions on Geoscience and Remote Sensing》.2003,第41卷(第3期), |
| Gianfranco Fornaro et al..Three-dimensional multipass SAR focusing experiments with long-term spaceborne data.《IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING》.2005,第43卷(第4期), |
| Three-dimensional focusing with multipass SAR data;Gianfranco Fornaro et al.;《IEEE Transactions on Geoscience and Remote Sensing》;20030331;第41卷(第3期);全文 * |
| Three-dimensional multipass SAR focusing experiments with long-term spaceborne data;Gianfranco Fornaro et al.;《IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING》;20050430;第43卷(第4期);全文 * |
| WANG Bin et al..Studies on MB-SAR 3D imaging algorithm using Yule-Walker method.《SCIENCE CHINA:Information Sciences》.2010,第53卷(第9期), * |
| 多基线SAR三维成像的QR分解算法;王斌 等;《中国科学院研究生院学报》;20110131;第28卷(第1期);全文 * |
| 王斌 等.多基线SAR三维成像的QR分解算法.《中国科学院研究生院学报》.2011,第28卷(第1期), |
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