CN116430384A - Chromatographic SAR three-dimensional imaging method based on multi-primary image processing - Google Patents

Chromatographic SAR three-dimensional imaging method based on multi-primary image processing Download PDF

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CN116430384A
CN116430384A CN202310280865.7A CN202310280865A CN116430384A CN 116430384 A CN116430384 A CN 116430384A CN 202310280865 A CN202310280865 A CN 202310280865A CN 116430384 A CN116430384 A CN 116430384A
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sar
chromatographic
elevation
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丁泽刚
王震
赵健
曾涛
卫扬铠
孙涛
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Beijing Institute of Technology BIT
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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
    • 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
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/414—Discriminating targets with respect to background clutter
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/418—Theoretical aspects

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Abstract

The invention belongs to the technical field of synthetic aperture radars, and provides a chromatographic SAR three-dimensional imaging method based on multi-primary image processing. In the invention, any two SAR images can be subjected to interference processing and a multi-baseline interference image is obtained, and all the interference images can participate in chromatographic processing so as to increase the observed data quantity and inhibit side lobes in the altitude dimension estimation. In addition, in order to further ensure high Cheng Guji precision, optimization processing of the SAR data stack is performed, namely multi-baseline interference phases are screened based on the coherence coefficient, and low-quality interference phases are removed so as to ensure the SAR processing effect.

Description

Chromatographic SAR three-dimensional imaging method based on multi-primary image processing
Technical Field
The invention belongs to the technical field of synthetic aperture radars, and particularly relates to a chromatographic SAR three-dimensional imaging method based on multi-primary image processing.
Background
Synthetic aperture radar (Synthetic Aperture Radar, SAR) is a radar system that can acquire the microwave scattering properties of a target area. The chromatographic SAR forms a synthetic aperture in the elevation direction by utilizing SAR data acquired multiple times in space, and can reconstruct the three-dimensional scattering coefficient of a target.
However, for tomographic SAR, it is desirable that the radar platform fly along closely spaced parallel trajectories at different altitude locations. But is typically limited by SAR systems, with fewer heavy rail observations of the same target, and non-uniform track spacing. At this time, the height-wise equivalent aperture is short, the sampling number is small, and the sampling interval is non-uniform, i.e. only sparse and non-uniform synthetic aperture can be obtained.
In this case, the conventional tomographic SAR imaging methods, such as fourier transform, truncated singular value processing, and the like, face problems of low resolution, higher side lobe, and the like. How to use a small amount of non-uniform observation data to achieve high Cheng Xiang high resolution imaging while maintaining azimuth-distance resolution is a challenge facing SAR tomography.
Thus, there is a need for a chromatographic SAR processing method that is suitable for sparse, non-uniform baselines.
Disclosure of Invention
In view of the above, the present invention provides a tomographic SAR three-dimensional imaging method based on multi-primary image processing. In the invention, any two SAR images can be subjected to interference processing and a multi-baseline interference image is obtained, and all the interference images can participate in chromatographic processing so as to increase the observed data quantity and inhibit side lobes in the altitude dimension estimation. In addition, in order to further ensure high Cheng Guji precision, optimization processing of the SAR data stack is performed, namely multi-baseline interference phases are screened based on the coherence coefficient, and low-quality interference phases are removed so as to ensure the SAR processing effect.
The beneficial effects are that:
the invention provides a chromatographic SAR three-dimensional imaging method based on multi-primary image processing, which keeps a long baseline and obtains a large number of short baselines at the same time, thereby improving the average coherence coefficient of a chromatographic SAR data stack, and being equivalent to improving the quality of the data stack. In addition, since the tomographic SAR imaging problem is essentially a spectrum estimation problem, the baseline number corresponds to the sampling number of the spectrum, the increase of the interferogram corresponds to the increase of the sampling number of the spectrum, and the sidelobes in the spectrum estimation are effectively suppressed in combination with the increase of the average image coherence coefficient, so that the three-dimensional imaging effect is further improved.
Drawings
Fig. 1: flow chart of chromatographic SAR processing method based on multi-main image model
Fig. 2: chromatographic SAR observation geometrical structure schematic diagram based on single main image and multi-main image model
Fig. 3: interferometric SAR phase screening process schematic
Fig. 4: and (3) using a truncated singular value method to estimate the section of the elevation of the different elevation targets based on (a) the single main image and (d) the multi-main image model. (b) (e) is the 41 st elevation section under the 0m elevation difference based on the single main image and the multi-main image model, and corresponds to the orange dotted line. (c) (f) 55 th elevation section at 7m elevation difference obtained based on the above method, corresponding to the white dotted line therein
Detailed Description
The present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which embodiments of the invention are shown.
As shown in fig. 1, the tomographic SAR three-dimensional imaging method based on multi-primary image processing includes the following steps:
step one: image registration
The main purpose of image registration is to make the same-name pixel points in the image sequence correspond to the same feature. SAR image registration can be classified into geometric information-based registration and image information-based registration. The geometric registration is to calculate the offset of the secondary image relative to the main image by using the orbit data and the imaging parameters according to the imaging geometric relationship, and has higher efficiency but effective precision, so that the registration operation with higher precision is required to be carried out based on the image information. Since many mature algorithms are available in the SAR image registration field, the invention will not be repeated, and the algorithm adopted here is a real correlation function method.
Step two: multi-primary image processing interferogram generation
Fig. 2 (a) shows a conventional single main image processing method. Based on the idea of the non-stationary main image, this is extended to the multi-main image processing method shown in fig. 2 (b). Under this approach, any image can be used as the primary image and paired with other images, whose generation interferograms can constitute a tomographic SAR data stack for subsequent processing. Assuming N images, at most one can be generated
Figure BDA0004137938050000031
Zhang Ganshe. The traditional SAR chromatographic model is expanded, and the proposed SAR chromatographic model based on multi-main image processing is as follows:
ψ＝Ψ·γ+ε (1)
where ψ is the observation vector with N elements. Psi is one
Figure BDA0004137938050000032
Is used for mapping the matrix. Gamma is a discrete reflection coefficient vector having K elements. Epsilon represents the noise vector. Thus there is
Figure BDA0004137938050000033
Figure BDA0004137938050000041
γ＝[γ(h 1 ),L,γ(h k ),L,γ(h K )] T (4)
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure BDA0004137938050000042
S i representing complex data within the azimuth-range pixel unit in the ith SAR image. S is S j Is the data of the jth SAR image, < +.>
Figure BDA0004137938050000043
Is the flat phase corresponding to the baseline between the ith and jth images. [] * Representing a conjugate operation. Psi and ψ are each composed of several sub-matrices, each corresponding to a different main image,/->
Figure BDA0004137938050000044
Is determined by the baseline parameters.
The normal-slope-range (NSR) is also different for different primary images, which makes even the same target have different heights after projection to different NSRs. Since the elevation of the NSR direction can be obtained from the elevation Cheng Zhuaihuan perpendicular to the reference ground through the viewing angle, the present invention directly estimates the elevation perpendicular to the reference ground. Thus there is
Figure BDA0004137938050000045
Wherein h is k Is the kth elevation value in the discrete reflection coefficient vector,
Figure BDA0004137938050000046
representing an effective baseline between the ith and jth SAR images, r i And theta i Respectively representing the slant distance and the downward viewing angle of the ith image.
Step three: chromatographic SAR data stack optimization
In a tomosynthesis SAR data stack, low quality rejection of the interference phase is an effective method to improve the overall signal-to-noise ratio of the data stack. Since the phase noise level depends on the image coherence, these low quality interference phases can be determined and rejected from the coherence coefficient map of the registered image. In this process, the SAR data stack is optimized pixel by pixel, part of the low quality interferometric phase in the interferogram is deleted, and only the reserved phase is used in the subsequent SAR processing. A schematic of this process is shown in figure 3.
Step four: height dimension imaging process
And performing chromatographic treatment based on the optimized chromatographic SAR data stack to obtain an elevation estimation value. It should be noted that the multi-primary image model proposed by the present invention is only an improvement of the conventional single-primary image model, and is still an essential sparse spectrum estimation problem without any change. Therefore, common algorithms such as truncated singular value methods, compressed sensing type methods, etc. can be used for the elevation dimension imaging process.
Examples of the embodiments
The effects of the present invention will be further described by a point target simulation test.
Simulation conditions: under the parameters of table 1, a chromatographic SAR treatment simulation was performed on the point target. 31 tracks are uniformly distributed in the height range of 150-255m to form a maximum baseline 105m. A long baseline gives a Gao Ruili elevation resolution of about 1.8 m.
Table 1 simulation parameters
Figure BDA0004137938050000051
The simulation used 81 sets of point targets, each set containing two superimposed targets, which were identical in scattering intensity but highly different. The elevation of one target is fixed to be 0m, the elevation of the other target is changed in the range of-20 m, and the fixed step length is 0.5m. And all simulations were performed with a signal-to-noise ratio of 5 dB. For comparison, a truncated singular value method is adopted to estimate the elevation based on two signal models of a single main image and a plurality of main images respectively
Fig. 4 shows a comparison of the estimated heights Cheng Poumian based on different models, (a) and (d) being a set of all elevation profiles, each vertical line representing one height Cheng Poumian, the abscissa representing the target set number (1 to 81) for different elevation differences (from-20 m to 20 m), and the ordinate representing the estimated height. These results have been normalized to the respective maximum peak. The profile peak represents a possible point target, the larger the peak, the greater the likelihood that the elevation is present for the target.
Overall, the main peaks of all sections are almost close to the green line (representing the true elevation of the target). But (d) based on the proposed multi-principal image has more prominent peaks and lower side lobes.
In addition, in order to quantitatively compare the elevation estimation effect, the elevation estimation accuracy was evaluated as shown in table 2. It can be seen by comparison that the multi-primary image model has better elevation estimation accuracy than the single-primary image model.
TABLE 2 accuracy of elevation estimation
Figure BDA0004137938050000061
Of course, the present invention is capable of other various embodiments and its several details are capable of modification and variation in light of the present invention by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (2)

1. A chromatography SAR three-dimensional imaging method based on multi-main image processing is characterized by comprising the following steps:
step one, registering images;
step two, generating an interference pattern based on multi-main image processing;
step three, chromatographic SAR data stack optimization;
and step four, high-dimensional imaging processing.
2. The method for three-dimensional imaging of a chromatographic SAR based on multi-primary image processing as set forth in claim 1, wherein in the step two, expansion is performed based on a traditional chromatographic SAR model, and the proposed chromatographic SAR model based on multi-primary image processing is as follows:
ψ＝Ψ·γ+ε
where ψ is the observation vector with N elements. Psi is one
Figure FDA0004137938040000011
Is used for mapping the matrix. Gamma is a discrete reflection coefficient vector having K elements. Epsilon represents noiseVector. Thus there is
Figure FDA0004137938040000012
Figure FDA0004137938040000013
γ＝[γ(h 1 ),L,γ(h k ),L,γ(h K )] T
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure FDA0004137938040000014
S i representing complex data within the azimuth-range pixel unit in the ith SAR image. S is S j Is the data of the jth SAR image, < +.>
Figure FDA0004137938040000015
Is the flat phase corresponding to the baseline between the ith and jth images. [] * Representing a conjugate operation. Psi and ψ are each composed of several sub-matrices, each corresponding to a different main image,/->
Figure FDA0004137938040000016
Is determined by the baseline parameters.
The normal-slope-range (NSR) is also different for different primary images, which makes even the same target have different heights after projection to different NSRs. Since the elevation of the NSR direction can be obtained from the elevation Cheng Zhuaihuan perpendicular to the reference ground through the viewing angle, the present invention directly estimates the elevation perpendicular to the reference ground. Thus there is
Figure FDA0004137938040000021
Wherein h is k Is the kth elevation value in the discrete reflection coefficient vector,
Figure FDA0004137938040000022
representing an effective baseline between the ith and jth SAR images, r i And theta i Respectively representing the slant distance and the downward viewing angle of the ith image.
CN202310280865.7A 2023-03-22 2023-03-22 Chromatographic SAR three-dimensional imaging method based on multi-primary image processing Pending CN116430384A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117554962A (en) * 2024-01-12 2024-02-13 中国科学院空天信息创新研究院 Chromatographic SAR gridless three-dimensional inversion method based on weighted least square

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117554962A (en) * 2024-01-12 2024-02-13 中国科学院空天信息创新研究院 Chromatographic SAR gridless three-dimensional inversion method based on weighted least square
CN117554962B (en) * 2024-01-12 2024-03-22 中国科学院空天信息创新研究院 Chromatographic SAR gridless three-dimensional inversion method based on weighted least square

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