CN105842665A - Spectrum weighting-based SAR image sidelobe suppression method - Google Patents
Spectrum weighting-based SAR image sidelobe suppression method Download PDFInfo
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- CN105842665A CN105842665A CN201610165426.1A CN201610165426A CN105842665A CN 105842665 A CN105842665 A CN 105842665A CN 201610165426 A CN201610165426 A CN 201610165426A CN 105842665 A CN105842665 A CN 105842665A
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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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- 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
- G01S7/28—Details of pulse systems
- G01S7/2813—Means providing a modification of the radiation pattern for cancelling noise, clutter or interfering signals, e.g. side lobe suppression, side lobe blanking, null-steering arrays
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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
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- Radar, Positioning & Navigation (AREA)
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- Radar Systems Or Details Thereof (AREA)
Abstract
The invention discloses a spectrum weighting-based SAR image sidelobe suppression method and belongs to the radar remote sensing application technical field. The method of the invention includes the following steps that: Fourier transformation is performed on an SAR image, and then, an spectral image of which the spectral support area is a spectral inscribed maximum rectangle is obtained, namely, a first spectral image is obtained, and weighting processing is performed on the first spectral image according to the features of the spectral support area, so that a second spectral image can be obtained; inverse Fourier transformation and normalization processing are performed on the first spectral image and the second spectral image, so that two new radar images can be obtained; and mathematical logical operation is performed on the two images, so as to obtain a sidelobe suppressed image. Since a spectral weighting method is adopted, the main lobe of the sidelobe suppressed image will not be broadened, and the accuracy and applicability of the radar image can be improved.
Description
Technical field
The present invention relates to radar remote sensing application technology, be specifically related in diameter radar image, utilize image spectrum image
The method that image secondary lobe is suppressed by conversion.
Background technology
The Sidelobe Suppression problem of synthetic aperture radar (Synthetic Aperture Radar, hereinafter referred to as SAR) image is that radar is distant
One of important research content of sense application, is explaining radar observation, is analyzing the aspect tools such as scene characters of ground object, target recognition
Play an important role.The research carrying out SAR image Sidelobe Suppression problem has weight for reducing false-alarm and raising Testing of Feeble Signals ability
Want meaning.
For optical imagery, the subject matter of radar image is to there is strong scattering point and higher secondary lobe, strong mesh in image
The secondary lobe of mark response is easy to interference or covers the main lobe of neighbouring weak signal target.Additionally, secondary lobe interference also can cause in imaging results
Obscuring of image, reduces image resolution ratio, affects the quality of image, be unfavorable for extraction and the identification of characteristics of image target.We
Knowing in radar imagery, in region, the point spread function (PSF) of the impulse response of the scattering point of point-like, i.e. imaging system is one
Complex expression.For same weighting function, PSF is a sinc function, and its secondary lobe maximum is positioned at below main lobe peak value
At 13dB.For the problem of these high secondary lobes, different Sidelobe Suppression ways is successively suggested, traditional distance side lobe suppression side
Method is that it is carried out fast fourier transform (FFT), frequency domain data carries out windowing process, then does inverse fourier transform and obtain thunder
Reach image.The method can effectively reduce secondary lobe, but can cause image main lobe broadening, amplitude reduction so that image divides simultaneously
Resolution reduces, and the quality of image can not be made to get a promotion.It is thus desirable to find more preferable sidelobe level suppression technology.
For suppressed sidelobes, keeping main lobe width, people also been proposed some treating methods and carry out suppressed sidelobes simultaneously the most as far as possible, this
A little methods include apodization filtering, SVA space apodization etc..The cardinal principle of apodization filtering be radar is received backward dissipate
It is emitted back towards wave datum and does Coherent processing.A kind of special image area filter function can be found, by this filter function by apodization filtering
Do process of convolution with image area and can be obtained by a many side lobe response lower than original secondary lobe.Its core finds one exactly
Iteration function, makes initial data after iteration, and main lobe keeps constant, and secondary lobe is inhibited.The quality of its Sidelobe Suppression result
Closely related with apodization filtering device coefficient, the method computing is complex, and iterations is various, and needs to determine in advance the position of main lobe
Putting could preferable suppressed sidelobes.The principle of SVA space apodization is to use an original complex pattern at different weights function
Reason, owing to the impulse response of different weights function is different, therefore weighted results is the most different, then ties in different disposal
In Guo, choose the minima of result so that secondary lobe is inhibited.The method the most more or less can be by different condition
Limit, therefore the suitability is not the strongest.
In recent years, people are further through methods such as Experimental comparison, it is proposed that a kind of way by changing target spectrum image realizes
Sidelobe Suppression, the method preferably maintains main lobe width while reducing secondary lobe, and simple to operate, calculates easily.But
Due to the biggest to the change of target spectrum supporting zone, a part of information dropout can be made.
Summary of the invention
The goal of the invention of the present invention is: in order to overcome the weak point that SAR image carries out Sidelobe Suppression, to reach right
After SAR image Sidelobe Suppression, it is thus achieved that the higher image of quality, a kind of SAR image based on the weighting of frequency spectrum supporting zone of special offer
Side lobe suppression method.
The SAR image side lobe suppression method based on frequency spectrum weighting of the present invention, comprises the following steps:
First, SAR image is carried out Fourier transform and obtains spectral image, in determining the frequency spectrum of spectral image, connect maximum rectangle region
Territory；
It is weighted frequency spectrum supporting zone processing, obtains the first Weighted spectral image: in the frequency spectrum of frequency spectrum supporting zone, connect maximum
The weighted value of rectangular area is set to T1, and the weighted value in remaining region is set to 0, wherein T1 >=1, and the value of preferred T1 is
1；
It is weighted the first Weighted spectral image processing, obtains the second Weighted spectral image: based on the first Weighted spectral image
Connecing the midpoint on each limit of maximum rectangular area in frequency spectrum, obtain diamond-shaped area, the weighted value of diamond-shaped area is set to T2, does not includes
The weighted value connecing maximum rectangular area in the frequency spectrum of diamond-shaped area is set to T3, and wherein T2 ＞ T3 >=1, the value of preferred T2 is
The value of 2, T3 is 1.
First Weighted spectral image, the second Weighted spectral image are carried out inverse Fourier transform and do normalized, obtains image
I1, image I2, wherein image I1Corresponding first Weighted spectral image, image I2Corresponding second Weighted spectral image；To image I1、
I2Carry out mathematical logic computing, obtain the SAR image after Sidelobe Suppression, first allow image I1Deduct I2And take absolute value,
To image I3, then use image I2Subtracted image I3And take absolute value, just obtain the SAR image after Sidelobe Suppression.
Owing to have employed technique scheme, the invention has the beneficial effects as follows: after utilizing frequency spectrum weighting, spectral image is carried out Fu
Vertical leaf inverse transformation so that SAR image secondary lobe position changes, and by mathematical logic computing, curbs secondary lobe, and to the greatest extent may be used
The holding main lobe width of energy.Meanwhile, the mode using frequency spectrum weighting makes target spectrum image modification less so that image itself
Information preserve the most intact.
Accompanying drawing explanation
Fig. 1 is the flow chart of the present invention.
Fig. 2 is the analogous diagram carrying out Sidelobe Suppression in embodiment for point target.
Fig. 3 is to carry out the result schematic diagram after Sidelobe Suppression process for real aircraft model SAR image.
Detailed description of the invention
For making the object, technical solutions and advantages of the present invention clearer, below in conjunction with embodiment and accompanying drawing, the present invention is made
Describe in detail further.
See Fig. 1, the side lobe suppression method of the present invention, comprise the following steps:
Step S1: the SAR image that input receiver obtains；
Step S2: SAR image is carried out Fourier transform and obtains the spectral image of SAR image；
Step S3: be weighted frequency spectrum supporting zone processing, obtaining frequency spectrum supporting zone is the frequency spectrum connecing maximum rectangle in frequency spectrum
Image.
In SAR image, often its frequency spectrum supporting zone is not the most a complete rectangle, and at this moment the secondary lobe of image just seems not
Regular, it is unfavorable for extraction and the identification of characteristics of image target, therefore the present invention by being weighted process to frequency spectrum supporting zone
Obtain the frequency spectrum supporting zone in complete rectangular region.I.e. arrange in the frequency spectrum of the spectral image that Fourier transform obtains SAR image
The weighted value connecing maximum rectangle is 1, and the weighted value in remaining region is set to 0, arranges to enter frequency spectrum supporting zone based on above-mentioned weighting
Row weighting processes, it is possible to obtain rectangular spectrum image and now image self loss information minimum, SAR after inverse fourier transform
The secondary lobe of image can seem the most regular, only 4 secondary lobes, and omnidirectional distribution.
If original signal spectrum supporting zone is S (ω, Ω), wherein (ω, Ω) is the coordinate of frequency spectrum supporting zone.Inside connect maximum rectangular window
For W (ω, Ω) and be entered as 1, both carry out dot product, meet the spectral image S of maximum rectangle in obtaining frequency spectrum1(ω, Ω):
S1(ω, Ω)=S (ω, Ω) .*W (ω, Ω) (1)
Step S4: in order to obtain main lobe invariant position further, the spectral image that secondary lobe position changes, it is the most right to need
Spectral image S1(ω, Ω) is weighted processing.
Take spectral image S respectively1The midpoint of each rectangular edges in (ω, Ω), constitutes a rhombus, obtains diamond-shaped area, and arrange Pedicellus et Pericarpium Trapae
The weighted value of the view data in shape region is 2, and the weighted value of the view data of the rectangular area beyond diamond-shaped area is 1, remaining
The weighted value of the view data in region is 0, arranges spectral image S based on above-mentioned1(ω, Ω) is weighted processing, and obtains spectrogram
As S2(ω,Ω).To spectral image S2(ω, Ω) carries out inverse fourier transform and can be obtained by main lobe invariant position and main lobe is not opened up
Width, secondary lobe position and the image of amplitude conversion.
If W1(ω, Ω) is weighting two-dimensional function, and its diamond-shaped area is entered as 2, and the rectangular area beyond rhombus is entered as 1, its
Its area assignment is 0.I.e.
Take spectral image S1(ω, Ω) and W1(ω, Ω) dot product, obtains rectangular spectrum figure S2(ω, Ω):
S2(ω, Ω)=S1(ω,Ω).*W1(ω,Ω) (3)
Because rectangular spectrum figure S2(ω, Ω) is based on spectral image S1(ω, Ω) obtains, if when the weighting of step S3 processes, if
Put weighting two-dimensional functionAnd S1(ω, Ω)=S (ω, Ω) .*W ' (ω, Ω), the most in step s 4,
Weighting two-dimensional function
Step S5: to spectral image S1(ω,Ω)、S2(ω, Ω) does inverse fourier transform, obtains image I1(ω, Ω), I2(ω, Ω),
Wherein I1(ω, Ω) corresponding spectral image S1(ω,Ω)。
Step S6: to image I1(ω, Ω), I2After (ω, Ω) is normalized, carries out mathematical logic computing, obtain secondary lobe
The SAR image of suppression.
First I is allowed1(ω, Ω) deducts I2(ω, Ω) also takes absolute value, and obtains I3(ω, Ω), image I3(ω, Ω) does not has main lobe, only
There are 8 secondary lobes, and the amplitude of 8 secondary lobes is I1The half of (ω, Ω), concrete operation such as following formula:
I3(ω, Ω)=| I1(ω,Ω)-I2(ω,Ω)| (4)
Use I again2(ω, Ω) deducts I3(ω, Ω) also takes absolute value, and has just obtained SAR image I of Sidelobe Suppression4(ω, Ω), specifically
Computing is as follows:
I4(ω, Ω)=| I2(ω,Ω)-I3(ω,Ω)| (5)
Embodiment
The present embodiment uses point target to emulate, and simulation result is shown in Fig. 2.Point target is multiplied by two one-dimensional sinc functions and obtains,
Three point targets are obtained by translation transformation.It can be seen that three point targets and secondary lobe thereof in Fig. 2-a, and secondary lobe crosses at secondary lobe
Place defines decoy.First image 2-a is carried out Fourier transform and obtain spectral image, as shown in Fig. 2-b, due to this frequency spectrum
Image is exactly rectangle, it is possible to (being weighted frequency spectrum supporting zone processing, obtaining frequency spectrum supporting zone is to omit step S3
The spectral image of maximum rectangle is connect in frequency spectrum.) it follows that be weighted rectangular spectrum image processing, obtain weighting rectangular spectrum
Image, as shown in fig. 2-c.In Fig. 2-c, diamond-shaped area weighted value is 2, other regions of rectangle (except the rectangular area of diamond-shaped area)
Weighted value is 1.Respectively rectangular spectrum image and weighting rectangular spectrum image are done inverse fourier transform and obtain image J1, J2, as
Shown in Fig. 2-d, 2-e.Finally to doing mathematics logical operations after J1, J2 normalization, obtain the image J3 of Sidelobe Suppression, such as figure
Shown in 2-f.
By emulation it will be seen that image J2 after inverse fourier transform, its main lobe width does not has broadening, secondary lobe position substantially
Put and change, and secondary lobe quantity becomes 8.After normalization and mathematical logic computing, the image of the Sidelobe Suppression obtained
J3, it can be seen that the secondary lobe of J3 is almost suppressed clean, and main lobe does not has broadening, and aliasing does not occur, and is exactly the most a bit,
Comparing with original image Fig. 2-a, the decoy in Fig. 2-a is wholly absent, and this has the biggest side to the identification degree promoting image
Help, so that the characteristic effect extracting image is more preferable, eliminate the false target impact on image.
Fig. 3 is that real aircraft model image uses the inventive method to carry out the result of Sidelobe Suppression.Wherein Fig. 3-a is original image,
Fig. 3-b is the image after Sidelobe Suppression.Can significantly find out, after the inventive method processes, the secondary lobe of original image obtains
Arrive suppression, and main lobe do not had broadening so that be originally in the point of aliasing state due to side lobe effect, can efficiently separate out,
Enhance the resolution of image.Also eliminate the decoy much formed due to secondary lobe superposition simultaneously.
SAR image side lobe suppression method according to the present invention, implements Sidelobe Suppression to SAR image and makes again image main lobe simultaneously
Broadening keeps constant, and ensure that image information is not lost.Formed due to secondary lobe superposition even if image exists
False target, after the present invention carries out Sidelobe Suppression, it is also possible to effectively removed, and the restrictive condition of this invention is very
Few, the suitability is the strongest.
The above, the only detailed description of the invention of the present invention, any feature disclosed in this specification, unless specifically stated otherwise,
All can be by other equivalences or there is the alternative features of similar purpose replaced；Disclosed all features or all methods or mistake
Step in journey, in addition to mutually exclusive feature and/or step, all can be combined in any way.
Claims (4)
1. a SAR image side lobe suppression method based on frequency spectrum weighting, it is characterised in that comprise the following steps:
SAR image is carried out Fourier transform and obtains spectral image, in determining the frequency spectrum of spectral image, connect maximum rectangular area；
It is weighted frequency spectrum supporting zone processing, obtains the first Weighted spectral image: in the frequency spectrum of frequency spectrum supporting zone, connect maximum
The weighted value of rectangular area is set to T1, and the weighted value in remaining region is set to 0, wherein T1 >=1；
It is weighted the first Weighted spectral image processing, obtains the second Weighted spectral image: based on the first Weighted spectral image
Connecing the midpoint on each limit of maximum rectangular area in frequency spectrum, obtain diamond-shaped area, the weighted value of diamond-shaped area is set to T2, does not includes
The weighted value connecing maximum rectangular area in the frequency spectrum of diamond-shaped area is set to T3, wherein T2 ＞ T3 >=1；
First Weighted spectral image, the second Weighted spectral image are carried out inverse Fourier transform and do normalized, obtains image
I1, image I2, wherein image I1Corresponding first Weighted spectral image, image I2Corresponding second Weighted spectral image；
Take | I2-|I1-I2| | as the SAR image after Sidelobe Suppression.
2. the method for claim 1, it is characterised in that SAR image is carried out Fourier transform and obtains spectral image
After, if the frequency spectrum supporting zone of spectral image is complete rectangle, then directly using spectral image as the first Weighted spectral image；
First Weighted spectral image is being weighted process, when obtaining the second Weighted spectral image, each based on frequency spectrum supporting zone
The midpoint on limit, obtains diamond-shaped area, and the weighted value of diamond-shaped area is set to T2, does not include the frequency spectrum supporting zone of diamond-shaped area
Weighted value is set to T3, wherein T2 ＞ T3 >=1.
3. method as claimed in claim 1 or 2, it is characterised in that the value of weights T1 is 1.
4. method as claimed in claim 1 or 2, it is characterised in that the value of weights T2 is 2, and the value of weights T3 is 1.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106680785A (en) * | 2017-03-06 | 2017-05-17 | 浙江工业大学 | Method for suppressing SAR image sidelobe based on wavelet space apodization |
| CN108008381A (en) * | 2017-06-09 | 2018-05-08 | 北京航空航天大学 | A kind of target bearing side lobe suppression method and device based on angles of azimuth SAR image |
| CN110780272A (en) * | 2019-10-29 | 2020-02-11 | 西安电子科技大学 | Unparameterized paired echo suppression method for bump platform SAR |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106680785A (en) * | 2017-03-06 | 2017-05-17 | 浙江工业大学 | Method for suppressing SAR image sidelobe based on wavelet space apodization |
| CN106680785B (en) * | 2017-03-06 | 2019-03-12 | 浙江工业大学 | SAR image side lobe suppression method based on wavelet transformation space apodization |
| CN108008381A (en) * | 2017-06-09 | 2018-05-08 | 北京航空航天大学 | A kind of target bearing side lobe suppression method and device based on angles of azimuth SAR image |
| CN110780272A (en) * | 2019-10-29 | 2020-02-11 | 西安电子科技大学 | Unparameterized paired echo suppression method for bump platform SAR |
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