CN110749882B - Image domain scallop inhibition method and system based on frequency domain filtering - Google Patents
Image domain scallop inhibition method and system based on frequency domain filtering Download PDFInfo
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Abstract
The invention discloses a method and a system for inhibiting image domain scallops based on frequency domain filtering, wherein the method comprises the following steps: partitioning a sub-band image of a scanning synthetic aperture radar in an image domain; extracting the amplitude of each block image and storing the amplitude as an intensity matrix to obtain an intensity image and converting the intensity image into a logarithmic image; carrying out two-dimensional fast Fourier transform on the logarithmic image; calculating scallop effect harmonic frequency points of the segmented images according to imaging parameters of the radar and by combining the characteristics of two-dimensional fast Fourier transform; extracting an azimuth frequency spectrum at the distance direction 0 frequency in the block image, and performing amplitude filtering on corresponding harmonics by combining a scallop effect harmonic frequency point; and then performing two-dimensional fast Fourier inverse transformation to obtain blocked images after scallop inhibition, splicing the blocked images to obtain sub-band images, and obtaining scallop inhibition results. The image domain scallop inhibition method and the system based on the frequency domain filtering provided by the invention provide a method for carrying out frequency filtering after converting an image into a logarithmic image, thereby simplifying the scallop inhibition processing process.
Description
Technical Field
The invention relates to the field of scanning Synthetic Aperture Radar (ScanSAR) radiation correction, in particular to an improved image domain scallop inhibition method and system based on frequency domain filtering.
Background
The synthetic aperture radar has the working capacity of all-weather all-time operation and is an important microwave remote sensing means; the ScanSAR in the synthetic aperture radar obtains the large range of the distance direction through the periodic switching of the wave beam among a plurality of wave positions in the distance direction, and is an important means for the application of large-area observation, ocean parameter inversion and the like; ScanSAR is one of the necessary working modes of satellite-borne SAR at home and abroad.
The key technology of ScanSAR processing is scallop inhibition, discontinuous observation of the target azimuth direction is caused by periodic switching of beams, and the technology system causes periodic scallop effect in ScanSAR images and seriously influences the image quality.
Scallop suppression puts high requirements on radiation correction of ScanSAR, but due to the influence of satellite attitude measurement accuracy, errors exist in the calculated central frequency, and residual scallop effects exist. Currently, there are two approaches to achieving scallop effect suppression.
1. By accurately estimating the center frequency. In the central frequency estimation link, the echo or the image can be estimated and obtained by an estimation method, in the directional diagram compensation link, the method of directional diagram reciprocal compensation, a BamHer multi-view compensation method and a Shimda compensation method can be adopted for compensation, but the influence of the central frequency estimation error and the antenna directional diagram measurement error still exists, under the condition of low signal-to-noise ratio, the residual scallop effect can still reach more than 0.7dB, and the application of ocean parameter inversion and the like can be greatly influenced;
2. the method is realized by adopting an image domain filtering method. The method for suppressing the scallop through harmonic detection and deconvolution in the image frequency domain is provided in the prior art, but the method needs sea-land segmentation and ship masking at first, and needs iteration processing, has large calculation amount, is not beneficial to automatic realization, and can still have stronger scallops and damage ship targets if the sea-land segmentation is not carried out on the image containing a sea-land junction scene and a ship through simulation experiments.
Disclosure of Invention
The present invention provides a method and a system for image domain scallop suppression based on frequency domain filtering, so as to at least partially solve the above problems.
The key point of the invention is that an improved image domain scallop inhibition method and system based on frequency domain filtering are provided, wherein the image domain scallop inhibition method based on frequency domain filtering comprises the following steps:
partitioning the sub-band image of the scanning synthetic aperture radar in an image domain to obtain a plurality of partitioned images;
in some embodiments, the subband images are complex images;
in still other embodiments, the tiling is performed by overlapping tiles, including adjacent tiles overlapping in a distance direction by a first set value and overlapping in an orientation direction by a second set value.
Extracting the amplitude of each block image as an intensity matrix to obtain an intensity image, extracting the phase of each block image as a phase matrix, and converting the intensity image into a logarithmic image, wherein in some embodiments, the step includes:
wherein x represents the azimuthal pixel number of the image field, r represents the range pixel number of the image field, σ (x, r) is the backscattering coefficient image, I (x, r) is the intensity image, I (x, r) is the azimuth pixel number of the image field, andlog(x, r) is a logarithmic image, γ (x, r) is speckle noise, x is the position of the azimuth pixel, Np is the period of presentation of the scallop in the image domain,
the periodic modulation of the image domain is a scallop effect.
The logarithmic image is subjected to a two-dimensional fast fourier transform.
According to the radar imaging parameters corresponding to the image domain and in combination with the characteristics of the two-dimensional fast Fourier transform, calculating scallop effect harmonic frequency points of the block images, wherein in some embodiments, the steps comprise:
calculating the period Np of the scallop effect of the image domain according to the imaging parameters of the image domain:
wherein, TkThe dwell time of the wave beam in the kth sub-band is shown, Ns is the number of the sub-bands, Vg is the ground speed, and Da is the size of the pixel in the azimuth direction of the image domain;
calculating scallop effect harmonic frequency points Fp of the block images according to the characteristics of two-dimensional fast Fourier transform:
Fp＝i*Nfft/Np，
i＝-floor(Np/2)：1：floor(Np/2)；
wherein N isfftThe number of points for performing a two-dimensional fast fourier transform.
Extracting an azimuth spectrum at 0-distance in the segmented image, and performing amplitude filtering on corresponding harmonics in combination with the scallop effect harmonic frequency points, wherein the steps comprise:
carrying out median filtering or mean filtering on the amplitude of the harmonic component with the frequency of Fp according to the scallop effect harmonic frequency point, and reserving the original phase in the phase;
to pair
And
and filtering the two integer points, and further comprising the following steps:
to pair
And
selecting a filtering range of
Wherein m is 3-8.
And performing two-dimensional fast Fourier inverse transformation and index conversion on the frequency spectrum of the amplitude-filtered block image to obtain the block image after scallop inhibition.
Splicing the blocked images after scallop inhibition to obtain sub-band images, and obtaining scallop inhibition results of the sub-band images;
in some embodiments, the sub-band complex image is regenerated by using the sub-band image obtained by splicing and the phase matrix, and a scallop suppression result of the complex image is obtained.
The image domain scallop suppression system based on frequency domain filtering comprises:
the input module is used for inputting the sub-band image and the imaging parameter of the scanning synthetic aperture radar image domain;
the scallop suppression module is preset with the image domain scallop suppression method based on the frequency domain filtering; and
and the output module outputs the scallop inhibition result of the sub-band image.
The image domain scallop inhibition method and the system based on the frequency domain filtering, which are provided by the invention, are realized aiming at the ScanSAR mode, and have the following beneficial effects:
(1) the intensity image is converted into a logarithmic image to be subjected to Fast Fourier Transform (FFT), so that the frequency spectrums of the scene and the scallop effect are converted into addition from convolution, the deconvolution is simplified into frequency domain filtering, and the scallop suppression processing process is simplified;
(2) calculating the frequency spectrum position of the harmonic component of the scallop effect through the imaging parameters, and accurately realizing the harmonic identification caused by the scallop effect;
(3) because the harmonic component frequency spectrum position caused by the scallop effect can be accurately identified, sea and land segmentation, ship mask and iterative processing are not required, and the processing efficiency is improved;
(4) for the phenomenon of similar scallop effect of images caused by TOPS mode azimuth discrete scanning of the satellite-borne SAR, the method also has applicability by calculating the period of the discrete scanning.
Drawings
FIG. 1 is a flow chart of a frequency domain filtering scallop suppression method incorporating imaging parameters according to an embodiment of the invention;
FIG. 2 is a schematic diagram of image blocking according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating a range of a filtering area selected during filtering according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of image stitching reconstruction performed according to an embodiment of the present invention;
FIG. 5 is a pre-suppression image of a scallop having a sea-land boundary and a complex sea surface, in accordance with an embodiment of the present invention;
FIG. 6 is the image of FIG. 5 after scallop suppression;
FIG. 7 is a self-image two-dimensional spectrum image at a typhoon eye in an embodiment of the invention;
FIG. 8 is a comparison of the front and back of the azimuth spectrum filtering at distance 0 in one embodiment of the present invention;
FIG. 9 is a partial magnification of an image before typhoon eye scallop suppression in an embodiment of the invention;
FIG. 10 is the image of FIG. 9 after scallop suppression;
FIG. 11 is a comparison of the pre-and post-suppression of scalloping at the typhoon eye in accordance with an embodiment of the present invention;
FIG. 12 is a partial magnification of the pre-suppressed image of a scallop at the sea-land boundary;
FIG. 13 is the image of FIG. 12 after scallop suppression;
FIG. 14 is a comparison of the inhibition of scallops at the sea-land boundary in an embodiment of the present invention.
Detailed Description
In order that the objects, technical solutions and advantages of the present invention will become more apparent, the present invention will be further described in detail with reference to the accompanying drawings in conjunction with the following specific embodiments.
With the development of signal processing technology and the intensive research on ScanSAR, it is found that the periodic stripes of the scallop effect presented on the image can be suppressed by a frequency filtering method, and a new solution is provided for the image domain processing of the scallop effect.
Aiming at image domain scallop inhibition of ScanSAR, the invention provides an improved processing method based on the prior art, which comprises image logarithmic conversion, harmonic frequency point calculation, harmonic filtering and the like, so that the suppressed ScanSAR image scallop effect is obviously reduced, and the requirements of ocean parameter inversion and the like are met.
In view of the above, an aspect of the present invention provides a method for image domain scallop suppression based on spectral filtering, please refer to fig. 1, which is a flowchart of a method for frequency domain filtering scallop suppression combined with imaging parameters according to an embodiment of the present invention, the method includes:
1) and partitioning the sub-band image of ScanSAR in the image domain.
And the image of a single sub-band of the ScanSAR is subjected to block parallel processing in the image domain, so that the relatively slow scene change in the image block is ensured, and the processing efficiency can be improved. In some embodiments, the tiling is performed by overlapping tiles, including adjacent tiles with a first setpoint overlapping in the direction of distance and a second setpoint overlapping in the direction of orientation.
Through research and test, aiming at ScanSAR images of common SAR satellites such as GF3 and the like, the images are partitioned by adopting the block sizes of 256 points in the distance direction and 1024 points in the azimuth direction, so that the requirement of FFT on the number of FFT points is met, and a good scallop inhibition effect can be obtained. In order to improve the processing effect of the block edge, in the overlapping and blocking manner adopted in this embodiment, the distance between adjacent blocks overlaps 32 points in the direction and overlaps 64 points in the direction. The block diagram is shown in fig. 2.
2) Intensity image to logarithmic image conversion.
For each block image in step 1, if the input image is a complex image, the amplitude and Phase of the complex image are respectively extracted and stored as an intensity matrix I (x, r) and a Phase matrix Phase (x, r), wherein the intensity matrix is an intensity image.
Converting the intensity image I (x, r) into a logarithmic image Ilog(x, r), the method is as follows:
Ilog(x，r)＝10*log10(I(x，r)) (1)
the reason for converting the intensity image into a logarithmic image is as follows:
for example, the single Burst image domain model is:
I(x)＝W(x)σ(x)γ(x) (2)
wherein, i (x) is a Burst image, w (x) is a two-way antenna directional diagram, σ (x) is a backscattering coefficient, γ (x) is exponentially distributed multiplicative speckle noise, and x is an azimuth pixel position of the Burst image.
The image domain model after splicing of a plurality of bursts in a single sub-band direction can be obtained as follows:
wherein x is equal to [1, Na ]]Na is the total number of azimuth pixels of the Burst map, r is the distance pixel position of the Burst map, sigma (x, r) is a backscattering coefficient image, gamma (x, r) is speckle noise, Sca (xc) is the representation of the scallop in an image domain, and xc belongs to [1, Np ]]Np is the period of scallop presentation in the image domain,
specifically the periodic modulation of the image domain by the scallop effect.
Therefore, taking logarithms at both ends of equation (3) can convert the multiplied relationship at the right side of the equation into an additive relationship, as follows:
after the conversion to the frequency domain, the frequency spectrums of the right three terms in the formula (4) are in an additive relationship, and if the signals at the two ends of the equal sign in the formula (3) are directly converted to the frequency domain, the right three termsThe relationship of the frequency spectrum is convolution. Thus, after conversion into logarithmic images, the pairs
The corresponding spectral estimate is also transformed by the deconvolution transform in equation (3) to the frequency domain filtering in equation (4).
3) For logarithmic image Ilog(x, r) a 2-dimensional FFT is performed. FFT is common knowledge in the art and will not be described in detail herein.
4) And calculating harmonic frequency points.
I obtained from step 2logThe spectrum of (x, r) is composed of three parts, respectively
The third term is a periodic signal, the frequency spectrum of the periodic signal is formed by a group of harmonic components in the frequency domain, and the frequency points of the harmonic components can be obtained by periodic calculation of the signal. The period Np of the scallop effect of the image domain can be obtained by calculating radar imaging parameters of ScanSAR, and the calculation method comprises the following steps:
wherein, TkThe dwell time of the beam in the kth sub-band, Ns is the number of sub-bands, Vg is the ground speed, and Da is the azimuth pixel size of the image domain.
According to the characteristics of Fourier transform and FFT, the frequency spectrum of a periodic signal with the period Np is embodied as a group of harmonic components with periodic distribution in a frequency domain, and the positions of the harmonic components are as follows:
Fp＝i*Nfft/Np，i＝-floor(Np/2)：1：floor(Np/2) (6)
wherein N isfftThe number of points for performing a two-dimensional fast fourier transform.
5) And (4) amplitude filtering.
Extracting the azimuth frequency spectrum at the position with the distance of 0 frequency in the block image, filtering the amplitude of the harmonic component with the frequency of Fp by adopting methods such as median filtering, mean filtering and the like according to the scallop effect harmonic frequency point obtained by the formula (6), wherein the phase retains the original phase, and the Fp is not an integer generally, so the original phase needs to be filtered
And
and carrying out filtering processing on the two integer points.
And
respectively representing a round-down and a round-up. Both the mean filtering and the median filtering are common image filtering methods, and only the data area for calculating the mean or median will be described here. In the case of mean or median filtering, to eliminate
And
interfere with each other to
For example, the selected filtering range is
As shown in fig. 3, where m is 3-8, in this embodiment, m is 5.
6) And performing two-dimensional Inverse Fast Fourier Transform (IFFT) on the frequency spectrum of the block image after amplitude filtering to obtain a logarithmic image, transforming the logarithmic image into an intensity image through exponential operation, and finally obtaining the block image after scallop inhibition.
7) And (5) image splicing.
The blocked images after the suppression of each scallop are spliced into the original sub-band image, and the splicing method is shown in fig. 4.
8) And (4) regenerating a complex image of the sub-band by using the spliced sub-band image and the Phase matrix Phase (x, r) acquired in the step 1, and acquiring a scallop inhibition result.
In another aspect, the present invention provides a system for suppressing image domain scallops based on frequency domain filtering, which includes:
the input module is used for inputting the sub-band image and the imaging parameter of the scanning synthetic aperture radar image domain;
the scallop suppression module is preset with the image domain scallop suppression method based on the frequency domain filtering; and
and the output module outputs the scallop inhibition result of the sub-band image.
The theme of the system is scallop suppression processing on the ScanSAR image domain, and the processing process is specifically described in the above embodiments and is not described herein again.
Compared with the prior art, the invention has the advantages that: by adopting the logarithmic domain processing, the relationship between the scene and the scallop modulation is converted from multiplication to addition, and after the relationship is converted into a frequency domain through two-dimensional FFT, the frequency spectrums of the scene and the scallop are converted from convolution to addition, so that the scallop inhibition is converted from deconvolution to frequency domain filtering; the scallop effect harmonic component position is obtained through imaging parameter calculation, and is more stable and not influenced by a scene frequency spectrum compared with the scallop effect harmonic component position obtained through searching in the prior art; according to the invention, sea and land segmentation and ship mask are not required, so that the processing flow is simplified; the invention does not need to carry out iterative processing, thereby improving the processing efficiency.
The effectiveness of the image domain scallop inhibition method and the system based on frequency domain filtering provided by the invention is verified through actually measured data. Fig. 5 is a ScanSAR image No. GF3 containing sea-land boundary scene and typhoon including scallop effect, and it can be seen that there are obvious scallops in the boundary area between the typhoon eye and sea-land. Fig. 6 is an image after scallop suppression is performed on fig. 5, fig. 7 is a two-dimensional spectrum image of the self-image at a typhoon eye, fig. 8 is an azimuth-direction spectrum filtering front-back comparison at a distance of 0 frequency, fig. 9 is a local amplification of an image before scallop effect suppression at the typhoon eye, fig. 10 is a local amplification of an image after scallop effect suppression at the typhoon eye, fig. 11 is a comparison before and after scallop effect suppression at the typhoon eye, fig. 12 is a local amplification of an image before scallop effect suppression at a sea-land boundary, fig. 13 is a local amplification of an image after scallop effect suppression at the sea-land boundary, and fig. 14 is a comparison before and after scallop suppression at the sea-land boundary.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention and are not intended to limit the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. An image domain scallop suppression method based on frequency domain filtering is characterized by comprising the following steps:
partitioning the sub-band image of the scanning synthetic aperture radar in an image domain to obtain a plurality of partitioned images;
extracting the amplitude of each block image to be stored as an intensity matrix to obtain an intensity image, and converting the intensity image into a logarithmic image, wherein the step of converting the intensity image into the logarithmic image is as follows:
wherein x represents an azimuthal pixel number of the image field, r represents a range pixel number of the image field, and σ (x, r) is a backscatter coefficient mapImage, I (x, r) is an intensity image, Ilog(x, r) is a logarithmic image, γ (x, r) is speckle noise, Np is the period of scallop presentation in the image domain,
periodic modulation of the image domain for a scallop effect;
performing two-dimensional fast Fourier transform on the logarithmic image;
calculating scallop effect harmonic frequency points of the block images according to radar imaging parameters corresponding to the image domain and by combining the characteristics of the two-dimensional fast Fourier transform, wherein the calculating the scallop effect harmonic frequency points of the block images comprises the following steps: calculating the cycle Np of the scallop effect of the image domain according to the radar imaging parameters corresponding to the image domain:
wherein, TkCalculating scallop effect harmonic frequency points Fp of the block images according to the characteristics of the two-dimensional fast Fourier transform, wherein the residence time of the wave beam in the kth sub-band is shown as Ns, the number of the sub-bands is shown as Vg, the ground speed is shown as Da, and the pixel size of the image domain direction is shown as Da: fp is Nfft-floor (Np/2): 1: floor (Np/2), where NfftThe number of points for performing the two-dimensional fast Fourier transform;
extracting an azimuth frequency spectrum at the distance direction 0 frequency position in the block image, and carrying out amplitude filtering on corresponding harmonic waves by combining the scallop effect harmonic frequency points;
carrying out two-dimensional fast Fourier inverse transformation and index conversion on the frequency spectrum of the block image after amplitude filtering to obtain a blocked image after scallop inhibition;
and splicing the blocked images after scallop inhibition to obtain sub-band images, and obtaining scallop inhibition results of the sub-band images.
2. The image domain scallop suppression method based on frequency domain filtering of claim 1, further comprising:
the sub-band image is a complex image, and the complex image is blocked to obtain a plurality of block images;
extracting the amplitude of each block image to be stored as an intensity matrix, and extracting the phase of each block image to be stored as a phase matrix;
carrying out the same scallop inhibition processing on each block image and splicing to obtain sub-band images;
and regenerating a sub-band complex image by using the sub-band image obtained by splicing and the phase matrix to obtain a scallop inhibition result of the complex image.
3. The method for image domain scallop suppression based on frequency domain filtering according to claim 1, wherein the amplitude filtering comprises:
carrying out median filtering or mean filtering on the amplitude of the harmonic component with the frequency of Fp according to the scallop effect harmonic frequency point, and reserving an original phase for the phase;
to pair
And
and carrying out filtering processing on the two integer points.
4. The method of claim 3, wherein the pair of image domain scallops is based on frequency domain filtering
And
the filtering processing of the two integer points comprises the following steps:
to pair
And
selecting a filtering range of
Wherein m is 3-8.
5. The method of claim 1 or 2, wherein the blocks are overlapped by a first setting in a distance direction and a second setting in an orientation direction.
6. An image domain scallop suppression system based on frequency domain filtering, the system comprising:
the input module is used for inputting the sub-band image and the imaging parameter of the scanning synthetic aperture radar image domain;
a scallop suppression module, in which the image domain scallop suppression method based on frequency domain filtering of any one of claims 1 to 5 is preset; and
and the output module outputs the scallop inhibition result of the sub-band image.
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| CN117348011A (en) * | 2023-09-26 | 2024-01-05 | 宁波大学 | Method for rapidly correcting SAR radial flow velocity and inverting sea surface flow field |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0202320A1 (en) * | 1984-11-28 | 1986-11-26 | Hans Hellsten | A method for radar mapping an area and a radar equipment to carry out the method. |
| GB9507472D0 (en) * | 1995-04-11 | 1996-04-24 | Commw Of Australia | Improved target detection |
| US7376688B1 (en) * | 2001-01-09 | 2008-05-20 | Urbain A. von der Embse | Wavelet multi-resolution waveforms |
| CN101609147A (en) * | 2008-06-18 | 2009-12-23 | 中国科学院电子学研究所 | A kind of center frequency estimation method based on the time-frequency domain pre-filtering |
| CN101833094A (en) * | 2010-04-06 | 2010-09-15 | 北京航空航天大学 | Imaging processing device of satellite-borne TOPSAR (Terrain Observation by Progressive Scans Synthetic Aperture Radar) data and processing method thereof |
| JP2011208974A (en) * | 2010-03-29 | 2011-10-20 | Mitsubishi Electric Corp | Radar image processing device |
| CN102346249A (en) * | 2010-07-28 | 2012-02-08 | 中国科学院电子学研究所 | Implementation method for wide swath earth observation step scanning mode of synthetic aperture radar |
| CN104977582A (en) * | 2015-06-10 | 2015-10-14 | 电子科技大学 | Deconvolution method for realizing scanning radar azimuth super-resolution imaging |
| CN105548981A (en) * | 2015-12-31 | 2016-05-04 | 中国科学院电子学研究所 | Method and apparatus for correcting synthetic aperture radar (SAR) echo data |
| CN107092933A (en) * | 2017-04-24 | 2017-08-25 | 中国科学院遥感与数字地球研究所 | A kind of synthetic aperture radar scan pattern image sea ice sorting technique |
| CN108132465A (en) * | 2017-12-13 | 2018-06-08 | 西安电子科技大学 | Terahertz radar foresight imaging method based on reflecting antenna |
-
2019
- 2019-10-24 CN CN201911020140.4A patent/CN110749882B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0202320A1 (en) * | 1984-11-28 | 1986-11-26 | Hans Hellsten | A method for radar mapping an area and a radar equipment to carry out the method. |
| GB9507472D0 (en) * | 1995-04-11 | 1996-04-24 | Commw Of Australia | Improved target detection |
| GB2299910A (en) * | 1995-04-11 | 1996-10-16 | Commw Of Australia | Target detection |
| US7376688B1 (en) * | 2001-01-09 | 2008-05-20 | Urbain A. von der Embse | Wavelet multi-resolution waveforms |
| CN101609147A (en) * | 2008-06-18 | 2009-12-23 | 中国科学院电子学研究所 | A kind of center frequency estimation method based on the time-frequency domain pre-filtering |
| JP2011208974A (en) * | 2010-03-29 | 2011-10-20 | Mitsubishi Electric Corp | Radar image processing device |
| CN101833094A (en) * | 2010-04-06 | 2010-09-15 | 北京航空航天大学 | Imaging processing device of satellite-borne TOPSAR (Terrain Observation by Progressive Scans Synthetic Aperture Radar) data and processing method thereof |
| CN102346249A (en) * | 2010-07-28 | 2012-02-08 | 中国科学院电子学研究所 | Implementation method for wide swath earth observation step scanning mode of synthetic aperture radar |
| CN104977582A (en) * | 2015-06-10 | 2015-10-14 | 电子科技大学 | Deconvolution method for realizing scanning radar azimuth super-resolution imaging |
| CN105548981A (en) * | 2015-12-31 | 2016-05-04 | 中国科学院电子学研究所 | Method and apparatus for correcting synthetic aperture radar (SAR) echo data |
| CN107092933A (en) * | 2017-04-24 | 2017-08-25 | 中国科学院遥感与数字地球研究所 | A kind of synthetic aperture radar scan pattern image sea ice sorting technique |
| CN108132465A (en) * | 2017-12-13 | 2018-06-08 | 西安电子科技大学 | Terahertz radar foresight imaging method based on reflecting antenna |
Non-Patent Citations (8)
| Title |
|---|
| A Descalloping Postprocessor for ScanSAR Images of Ocean Scenes;Roland Romeiser 等;《IEEE Transactions on Geoscience and Remote Sensing》;20121210;第3259-3272页 * |
| Adapting precision standard SAR processors to ScanSAR;R. Bamler;《1995 International Geoscience and Remote Sensing Symposium》;20020806;第2051-2053页 * |
| DESNET: DEEP RESIDUAL NETWORKS FOR DESCALLOPING OF SCANSAR IMAGES;Shangliang Xu 等;《38th IEEE IGARSS》;20181231;第8929-8932页 * |
| 偏微分方程和非局部处理框架下的SAR滤波研究;马晓双;《中国博士学位论文全文数据库 基础科学辑》;20170815;第1-132页 * |
| 基于IMU的机载TOPSAR目标定位方法;范怀涛 等;《航空学报》;20151025;第37卷(第5期);第1587-1594页 * |
| 基于系统噪声抑制的ScanSAR辐射校正方法;张晓 等;《国外电子测量技术》;20150630;第34卷(第6期);第40-44页 * |
| 基于频域扩展和SPECAN的全孔径TOPSAR成像算法;陈祺 等;《电子与信息学报》;20121031;第34卷(第10期);第2445-2450页 * |
| 海陆交界非平稳场景星载ScanSAR扇贝效应抑制方法;谷昕炜 等;《海军航空工程学院学报》;20180228;第33卷(第1期);第125-129、134页 * |
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