CN102426360A - Two-dimensional ISRA imaging method of object with micro rotation in air - Google Patents
Two-dimensional ISRA imaging method of object with micro rotation in air Download PDFInfo
- Publication number
- CN102426360A CN102426360A CN201110257606XA CN201110257606A CN102426360A CN 102426360 A CN102426360 A CN 102426360A CN 201110257606X A CN201110257606X A CN 201110257606XA CN 201110257606 A CN201110257606 A CN 201110257606A CN 102426360 A CN102426360 A CN 102426360A
- Authority
- CN
- China
- Prior art keywords
- echo
- frequency
- rotary part
- time
- range unit
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Abstract
The invention discloses a two-dimensional ISRA imaging method of an object with micro rotation in the air. The method comprises the following steps that: (1), a radar matriculates an ISAR echo; (2), translation compensation is carried out; (3), time frequency distribution map is drafted; (4), micro doppler distance units are determined; (5), echo separation of a distance unit; (6), it is determined whether all distance unit have been traversed; (7), a distance-doppler method is used to carry out imaging on a rigid body echo; and (8), imaging is carried out on a rotary part echo. According to the invention, a low frequency modulation rate matched filtering method is employed to carry out echo separation, so that an adaptive chirplet decomposition imaging method's disadvantages including large calculated amount, high time consumption and insufficience of real-time property are overcome; therefore, the method has advantages of simple realization, high efficient and high real-time property. According to the invention, an I-Radon conversion is employed to carry out imaging on a rotary part; therefore, defects of an EHT algorithm are overcome, wherein the defects include high image sidelobe of a rotary object, low precision of estimation position and inaccuracy of object identification; and the method has advantages of good image focusing, high position estimation precision and accurate object identification.
Description
Technical field
The invention belongs to the signal processing technology field, further relate to the two-dimentional ISAR formation method of the aerial fine motion rolling target in the radar imagery field.The present invention can detect aerial fine motion rolling target effectively, and target is accurately located and formed images.
Background technology
When adopting inverse synthetic aperture radar (ISAR) that aerial fine motion target is carried out to picture; Properller, lifting airscrew, turbo type engine blade; Fine motion rotary parts such as the guided missile warhead of precession can be modulated radar waveform in certain attitude angle scope; Thereby produce the radar echo signal that contains the periodic modulation composition, promptly produce little Doppler effect, its rotary part will show as the modulated interferer band along Doppler's direction in the ISAR image; ISAR picture quality to target has caused very big influence, has increased the difficulty of identification.Therefore, be necessary little doppler information is analyzed, on this basis, suppress the modulated interferer band in the image, and utilize little Doppler effect to realize imaging high-speed rotary part.
People such as Li Bin are in its paper " based on the ISAR imaging of fine motion analysis and chirplet decomposition " (" signal Processing " the 29th the 2nd phase of volume; In February, 2009) propose in to adopt self-adaptation chirplet to decompose the formation method that carries out the fine motion target; This method is earlier the Doppler of translation, rotation and the vibration of target to be analyzed; And decompose through chirplet transfer pair echoed signal; In the chirplet parameter field, little Doppler and the little Doppler who decomposes the back signal led discuss, and the Doppler of different motion form is separated.But the deficiency that this method exists is that the set quantity that chirplet decomposes is very huge, causes need consuming great amount of time to the analysis of little doppler information, lacks the real-time to aerial fine motion target imaging.
People such as Qun Zhang are at document " Imaging of a Moving Target With Rotating Parts Based on the Hough Transform " (IEEE trans.on GRS; Vol.46; No.1; Pp.291-299,2008) propose in rigid body, rotary part parameter to be searched for to realize that echo separates and imaging based on the algorithm of Hough conversion and expansion Hough (EHT:Extended-Hough transform) conversion.But the deficiency that this method exists is, because the EHT algorithm receives the influence of point spread function, gained rolling target image has higher secondary lobe, and the positional precision of estimation is not high.
Summary of the invention
The objective of the invention is to overcome the deficiency of prior art, propose a kind of two-dimentional ISAR formation method of aerial fine motion rolling target.This method has remedied the huge imaging shortage real-time that causes target of calculated amount that chirplet decomposes; The influence that the EHT algorithm receives point spread function is prone to produce higher secondary lobe; Therefore can't obtain focusing on the deficiencies such as image of good rigid body and rotary body simultaneously; The rigid body that makes full use of the fine motion target is a linear FM signal at distance-slow time echo; And its frequency modulation rate adopts low frequency modulation matched filtering method that rigid body is separated with the rolling target echo far below the characteristics of the little Doppler's of rotary part frequency modulation rate.For the rigid body echo; Adopt traditional R-D algorithm to be carried out to picture; To high-speed rotary part distance-slow time domain echo envelope characteristics, adopt contrary-Radon (I-Radon) transfer pair rotary part to be carried out to picture, obtain the good ISAR image of focusing of fine motion target rigid body and rotary part simultaneously.
Realize that basic ideas of the present invention are: the ISAR echo of aerial fine motion target is carried out the translation compensation; After being converted into the target echo under the mount model; Adopt low-key frequency matching filtering method that the rigid body echo is separated with the rotary part echo, respectively rigid body and fine motion rolling target are carried out to picture with R-D algorithm and contrary-Radon conversion respectively again.
Concrete steps of the present invention are following:
(1) radar admission ISAR echo;
(2) translation compensation
The envelope that 2a) adopts adjacent correlation method to carry out the neighbor distance picture to the ISAR echo is aimed at;
2b) adopting many special apparent some self-focusing methods to carry out first phase proofreaies and correct;
(3) draw time frequency distribution map
3a) appoint and get range unit in the target echo;
3b) drawing with time is horizontal ordinate, is the time frequency distribution map of the rigid body and the high-speed rotary part echo of ordinate with the frequency;
(4) confirm little Doppler's range unit;
The echo of (5) range units separates
5a) select original frequency;
5b) the relatively absolute value of original frequency and the size of frequency threshold, as if the absolute value of original frequency less than frequency threshold, execution in step 5c then); Otherwise, execution in step 5d);
5c) that the original frequency place is corresponding echo is recorded as the rigid body echo, upgrades little Doppler's range unit;
5d) judge whether little Doppler's range unit energy is lower than energy threshold, when the energy of little Doppler's range unit is higher than energy threshold, execution in step 5a); Otherwise, execution in step 5e);
5e) from the echo of range unit, deduct 5c) the rigid body echo of record, obtain the echo and the record of rotary part;
(6) judge whether to have traveled through all range units
6a), then search for next range unit, execution in step (5) if do not accomplish;
6b) if completion, then execution in step (7);
(7) use distance-Doppler method to the rigid body echo-wave imaging;
(8) rotary part echo-wave imaging
8a) to step 5e) the middle rotary part echo delivery value that writes down;
8b) draw rotary part echo mould value figure, with the center of crest and wave trough position as the rotation center position;
8c) estimate the rotation angle frequency;
8d) frequency domain filtering;
8e) rear orientation projection obtains the rotary part image of reconstruct.
Compared with prior art, the present invention has the following advantages:
First; The present invention separates with high-speed rotary body rigid body through adopting low-key frequency matching filtering method; Overcome self-adaptation chirplet in the prior art and decomposed big, consuming time many, the shortcoming that lacks real-time of formation method calculated amount, have realize simply, efficient is high, real-time is high advantage.
Second; The present invention forms images with contrary-Radon (I-Radon) transfer pair rotary part; Overcome low, the inaccurate shortcoming of Target Recognition of positional precision that EHT algorithm gained rolling target image secondary lobe is high, estimate, had that image focusing is good, position estimation accuracy is high, a Target Recognition advantage accurately.
Description of drawings
Fig. 1 is a process flow diagram of the present invention;
Fig. 2 is an analogous diagram of the present invention;
Fig. 3 is measured data of the present invention figure as a result.
Embodiment
Below in conjunction with accompanying drawing 1, the specific embodiment of the invention is done further to describe in detail:
2a) adopt adjacent correlation method to carry out envelope and aim at, the distance images convolution that the distance images of ISAR echo is adjacent is measured by way of compensation with the corresponding time delay of its peak value the envelope of echo is aimed at;
2b) adopting many special apparent some self-focusing methods to carry out first phase proofreaies and correct; Envelope is aimed at amplitude change the little range unit that rises and falls as the apparent point of spy; It comprehensively is that a high-quality comprehensive spy shows point that a plurality of spies are shown dot element, and the phase place that shows point with comprehensive spy is carried out the first phase correction as translational movement to all echoes.
Step 3 is drawn time frequency distribution map
3a) appoint a range unit of getting in the target echo;
3b) draw time frequency distribution map; Being drawn with time by the emulation of time frequency analyzing tool case is horizontal ordinate; With the frequency is the time frequency distribution map of the rigid body and the high-speed rotary part echo of ordinate, and the time-frequency distributions of rigid body is a straight line in the distribution plan, and the time-frequency distributions of high-speed rotary part is a sinusoidal curve.
Step 4 is confirmed the residing range unit of little Doppler, and target echo is done Fourier transform along the slow time; With the orientation frequency is transverse axis; With the distance is longitudinal axis drawing image, and it is little Doppler's frequency band that vision intermediate frequency is composed obvious broadening place, chooses the residing range unit of little Doppler's frequency band.
Step 5, the echo of a range unit separates
5a) select original frequency, use
Multiply by the echo that has little Doppler's range unit, wherein k is the frequency modulation rate, and the scope of k is step 3b) time frequency distribution map in rigid body time-frequency distributions slope of a curve scope, t
mBe the slow time. successively the echo after multiplying each other is done Fourier transform and obtain frequency spectrum separately, relatively the size of spectrum amplitude is got the corresponding frequency in maximum spectrum amplitude place as original frequency;
5b) compare the absolute value of original frequency and the size of frequency threshold; Frequency threshold is step 3b) time frequency distribution map in the maximum norm value of frequency values of each rigid body time-frequency distributions curve starting point; If the absolute value of original frequency is less than frequency threshold, execution in step 5c then); Otherwise, execution in step 5d);
5c) that the original frequency place is corresponding echo is recorded as the rigid body echo, and the rigid body echo spectrum of filtering record is transformed into residual spectrum in little Doppler's range unit of time domain from the frequency spectrum of little Doppler's range unit;
5d) judge whether little Doppler's range unit energy is lower than energy threshold, energy threshold be in the step (5) a range unit echo gross energy 20%, when the energy of little Doppler's range unit is higher than energy threshold, execution in step 5a); Otherwise, execution in step 5e);
5e) from the echo of range unit, deduct 5c) in the rigid body echo of record, obtain the echo and the record of rotary part.
Step 6 judges whether to have traveled through all range units
6a), then search for next range unit, execution in step 5 if do not accomplish;
6b) if accomplish, then execution in step 7.
Step 7, with distance-Doppler method to the rigid body echo-wave imaging, with step 5c) after the rigid body echo range-azimuth two dimension decoupling zero of record, adjust the distance respectively and the orientation matched filtering, obtain two-dimentional rigid body echo;
Step 8, the rotary part echo-wave imaging
8a) to step 5e) the middle rotary part echo delivery value that writes down;
8b) draw rotary part echo mould value figure, with the center of crest and wave trough position as the rotation center position;
8c) estimate the rotation angle frequency; Get the maximum range unit echo of amplitude; Calculate its autocorrelation function, the time interval between gained autocorrelation function maximal peak point and the second largest peak value point is the swing circle of rotary part, it is got inverse and multiply by 2 π obtain the rotation angle frequency;
8d) frequency domain filtering is to step 8a) in the mould value of the rotary part echo that obtains by following formula along carrying out Fourier transform apart from frequency domain:
s(ξ，t
m)＝∫|s(r，t
m)|exp(-jξr)dr
Wherein, s (ξ, t
m) for the rotary part echo carries out the result after the Fourier transform along distance domain, ξ is apart from frequency domain, the Support of ξ is [π, π], t
mBe the slow time, | s (r, t
m) | be the mould value of rotary part echo, r is a distance;
With echo s (ξ, the t after the rotary part Fourier transform
m) carry out one-dimensional filtering and inverse Fourier transform by following formula:
Wherein, s ' (r, t
m) be the echo behind the rotary part frequency domain filtering, r is a distance, t
mBe the slow time, | ξ | for ξ being asked mould, s (ξ, t
m) carry out the result after the Fourier transform along distance domain for the rotary part echo.
8e) carry out rear orientation projection, obtain the rotary part image of reconstruct according to following formula:
Wherein, I (x y) is the image of reconstruct after the rear orientation projection, x, y be might the scattering point position horizontal stroke, ordinate, Θ=ω T
aFor rolling target at total observation time T
aIn corner, ω is step 8c) in the rotation angle frequency that obtains, s ' (r ', t
m) for step 8d) and in echo behind the rotary part frequency domain filtering that obtains, r '=xcos (ω t
m)+ysin (ω t
m) be search variables, t
mBe the slow time.
Further specify below in conjunction with 2 pairs of effects of the present invention of accompanying drawing.
Emulation shown in the accompanying drawing 2 is carried out under MATLAB7.0 software, and the parameter of emulated data is following: the radar carrier frequency is f
cBe 10GHz, signal bandwidth B is 800MHz, and PRF is 800Hz.Fig. 2 (a) is the distribution plan of scattering point on imaging plane, wherein, horizontal ordinate represent the orientation to, ordinate represent distance to, unit is rice, ' * ' expression rotation scattering point, ' o ' expression rigid body scattering point.4 rotation scattering points are rotation center with the target imaging center, and radius of turn is 1.5m, rotational frequency f
RotBe 6.67Hz.Two rigid body scattering points are positioned at the same distance unit, and one of them is positioned at the target imaging center, and another and its spacing are 0.75m, rotational frequency f
0Be 0.04Hz, the reflection coefficient of high speed rotating scattering point is 8 times of rigid body scattering point.The emulated data distance samples is 500 unit, and number of echoes is 512 times.
Fig. 2 (b) adopts the figure as a result of distance-Doppler method imaging for adopting the isolated rigid body echo of low-key frequency matching filter method, and wherein, horizontal ordinate is the Doppler unit, and ordinate is a range unit.Two rigid body scattering points among the figure are arranged in same range unit, and are consistent with the position distribution of two rigid body scattering points among Fig. 2 (a).
4 high speed rotating scattering points that Fig. 2 (c) obtains for the EHF method that adopts background technology and mention wait merchant's line chart, wherein, horizontal ordinate be the orientation to, ordinate be apart to, unit is rice.By finding out among the figure; Though the distribution of four rotation scattering points is consistent with the distribution of rotation scattering point among Fig. 2 (a); But around each scattering point, all produced wave; Explain that the scattering point image all has higher secondary lobe, visible in view of the above bad to the imaging effect of high-speed rotary part by the EHF method.
Fig. 2 (d) is the contour map of 4 high speed rotating scattering points adopting I-Radon converter technique of the present invention and obtain, wherein, horizontal ordinate be the orientation to, ordinate be apart to, unit is rice.Consistent by the distribution that can find out four rotation scattering points among the figure with the distribution of rotation scattering point among Fig. 2 (a), and do not have wave around each scattering point, explain that the secondary lobe of each scattering point is lower.Can know that with Fig. 2 (c) contrast the secondary lobe that the I-Radon mapping algorithm produces is far fewer than the secondary lobe of EHF conversion.It is thus clear that the present invention is good to the focusing effect of rotary part imaging.
Through to measured data of the present invention, the practicality of the present invention in engineering practice is described below in conjunction with accompanying drawing 3.
Adopt the measured data of An-26 aircraft that the present invention is carried out method validation, the measured data parameter is following: aircraft is the twin screw transporter, and airscrew diameter is about 3.9m.The imaging radar bandwidth is 400MHz, and PRF is 400Hz.The data matrix size is 256 * 512.
Fig. 3 (a) does not adopt method of the present invention for echo is directly carried out after the translation compensation, and directly adopts the figure as a result of distance of the prior art-Doppler method imaging, and wherein, horizontal ordinate is the Doppler unit, and ordinate is a range unit.By finding out among the figure; Near the interference fringe that the 130th range unit, exists significantly, produces by two high speed rotating screw propellers; Explain directly and adopt the imaging of distance-Doppler method can produce interference fringe, reduce the quality of image, increased difficulty Target Recognition to mixing echo.
Fig. 3 (b) is for after low-key frequency matching filtering method carries out the echo separation among employing the present invention, and to the figure as a result that gained rigid body echo adopts distance-Doppler method to form images, wherein, horizontal ordinate is the Doppler unit, and ordinate is a range unit.By finding out among the figure, only comprise the echo of rigid body among the figure, removed interference stripes, explain that low-key frequency matching filtering method of the present invention can realize effectively that echo separates.
Fig. 3 (c) is for after low-key frequency matching filtering method carries out the separation of rigid body echo among employing the present invention; Adopt I-Radon method to be carried out to the figure as a result of picture to one of them propeller echo of gained, wherein, horizontal ordinate be the orientation to; Ordinate be the distance to, unit is rice.Four strong scattering points around image center among the figure are represented 4 propeller blades, and the airscrew diameter that therefrom estimates is about 1.4m, and less than physical size, this is to be caused by the angle between screw propeller rotating shaft and radar line of sight.Explain that I-Radon method of the present invention can obtain An-26 aircaft configuration and the more complete description of motion feature.
Fig. 3 (d) is for after low-key frequency matching filtering method carries out the separation of rigid body echo among employing the present invention; Adopt the I-Radon method to be carried out to the figure as a result of picture to the another one propeller echo of gained, wherein, horizontal ordinate be the orientation to; Ordinate be the distance to, unit is rice.Four strong scattering points among the figure are represented 4 propeller blades, and the airscrew diameter that therefrom estimates is about 1.4m, and less than physical size, this is to be caused by the angle between screw propeller rotating shaft and radar line of sight.Explain that I-Radon method of the present invention can obtain An-26 aircaft configuration and the more complete description of motion feature.
Claims (10)
1. the two-dimentional ISAR formation method of aerial fine motion rolling target comprises the steps:
(1) radar admission ISAR echo;
(2) translation compensation
The envelope that 2a) adopts adjacent correlation method to carry out the neighbor distance picture to the ISAR echo is aimed at;
2b) adopting many special apparent some self-focusing methods to carry out first phase proofreaies and correct;
(3) draw time frequency distribution map
3a) appoint and get range unit in the target echo;
3b) drawing with time is horizontal ordinate, is the time frequency distribution map of the rigid body and the high-speed rotary part echo of ordinate with the frequency;
(4) confirm little Doppler's range unit;
The echo of (5) range units separates
5a) select original frequency;
5b) the relatively absolute value of original frequency and the size of frequency threshold, as if the absolute value of original frequency less than frequency threshold, execution in step 5c then); Otherwise, execution in step 5d);
5c) that the original frequency place is corresponding echo is recorded as the rigid body echo, upgrades little Doppler's range unit;
5d) judge whether little Doppler's range unit energy is lower than energy threshold, when the energy of little Doppler's range unit is higher than energy threshold, execution in step 5a); Otherwise, execution in step 5e);
5e) from the echo of range unit, deduct 5c) the rigid body echo of record, obtain the echo and the record of rotary part;
(6) judge whether to have traveled through all range units
6a), then search for next range unit, execution in step (5) if do not accomplish;
6b) if completion, then execution in step (7);
(7) use distance-Doppler method to the rigid body echo-wave imaging;
(8) rotary part echo-wave imaging
8a) to step 5e) the middle rotary part echo delivery value that writes down;
8b) draw rotary part echo mould value figure, with the center of crest and wave trough position as the rotation center position;
8c) estimate the rotation angle frequency;
8d) frequency domain filtering;
8e) rear orientation projection obtains the rotary part image of reconstruct.
2. the two-dimentional ISAR formation method of aerial fine motion rolling target according to claim 1; It is characterized in that; Step 3b) time frequency distribution map described in is obtained by the emulation of time frequency analyzing tool case, and the time-frequency distributions of rigid body is a straight line among the figure, and the time-frequency distributions of high-speed rotary part is a sinusoidal curve.
3. the two-dimentional ISAR formation method of aerial fine motion rolling target according to claim 1; It is characterized in that; The method of definite little Doppler's range unit is described in the step (4), and target echo is done Fourier transform along the slow time, is transverse axis with the orientation frequency; With the distance is longitudinal axis drawing image, determines the residing range unit of little Doppler.
4. the two-dimentional ISAR formation method of aerial fine motion rolling target according to claim 1 is characterized in that step 5a) described in the method for selection original frequency be to use
Multiply by the echo that has little Doppler's range unit, wherein k is the frequency modulation rate, and the scope of k is step 3b) time frequency distribution map in rigid body time-frequency distributions slope of a curve scope, t
mBe the slow time, successively the echo after multiplying each other done Fourier transform and obtain frequency spectrum separately that relatively the size of spectrum amplitude is got the corresponding frequency in maximum spectrum amplitude place as original frequency.
5. the two-dimentional ISAR formation method of aerial fine motion rolling target according to claim 1 is characterized in that step 5b) described in frequency threshold be step 3b) time frequency distribution map in the maximum norm value of frequency values of each rigid body time-frequency distributions curve starting point.
6. the two-dimentional ISAR formation method of aerial fine motion rolling target according to claim 1; It is characterized in that; The method of the little Doppler's range unit of the renewal step 5c) is; The rigid body echo spectrum of filtering record is transformed into residual spectrum in little Doppler's range unit of time domain from the frequency spectrum of little Doppler's range unit.
7. the two-dimentional ISAR formation method of aerial fine motion rolling target according to claim 1 is characterized in that step 5d) described in energy threshold be in the step (5) a range unit echo gross energy 20%.
8. the two-dimentional ISAR formation method of aerial fine motion rolling target according to claim 1; It is characterized in that; The method of the estimation rotation angle frequency step 8c) is, gets the maximum range unit echo of amplitude, calculates its autocorrelation function; The time interval between gained autocorrelation function maximal peak point and the second largest peak value point is the swing circle of rotary part, it is got inverse and multiply by 2 π obtain the rotation angle frequency.
9. the two-dimentional ISAR formation method of aerial fine motion rolling target according to claim 1; It is characterized in that; The method of frequency domain filtering step 8d) is, to step 8a) in the mould value of the rotary part echo that obtains by following formula along carrying out Fourier transform apart from frequency domain:
s(ξ，t
m)＝∫|s(r，t
m)|exp(-jξr)dr
Wherein, s (ξ, t
m) for the rotary part echo carries out the result after the Fourier transform along distance domain, ξ is apart from frequency domain, the Support of ξ is [π, π], t
mBe the slow time, | s (r, t
m) | be the mould value of rotary part echo, r is a distance;
With echo s (ξ, the t after the rotary part Fourier transform
m) carry out one-dimensional filtering and inverse Fourier transform by following formula:
Wherein, s ' (r, t
m) be the echo behind the rotary part frequency domain filtering, r is a distance, t
mBe the slow time, | ξ | for ξ being asked mould, s (ξ, t
m) carry out the result after the Fourier transform along distance domain for the rotary part echo.
10. the two-dimentional ISAR formation method of aerial fine motion rolling target according to claim 1 is characterized in that step 8e) described in the formula of rear orientation projection be:
Wherein, I (x y) is the image of reconstruct after the rear orientation projection, x, y be might the scattering point position horizontal stroke, ordinate, Θ=ω T
aFor rolling target at total observation time T
aIn corner, ω is step 8c) in the rotation angle frequency that obtains, s ' (r ', t
m) for step 8d) and in echo behind the rotary part frequency domain filtering that obtains, r '=xcos (ω t
m)+ysin (ω t
m) be search variables, t
mBe the slow time.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201110257606 CN102426360B (en) | 2011-09-01 | 2011-09-01 | Two-dimensional ISRA imaging method of object with micro rotation in air |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201110257606 CN102426360B (en) | 2011-09-01 | 2011-09-01 | Two-dimensional ISRA imaging method of object with micro rotation in air |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102426360A true CN102426360A (en) | 2012-04-25 |
| CN102426360B CN102426360B (en) | 2013-09-25 |
Family
ID=45960364
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 201110257606 Active CN102426360B (en) | 2011-09-01 | 2011-09-01 | Two-dimensional ISRA imaging method of object with micro rotation in air |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102426360B (en) |
Cited By (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103424741A (en) * | 2013-08-29 | 2013-12-04 | 西安电子科技大学 | Smooth procession cone parameter estimation method based on high-resolution ISAR imaging |
| CN103698765A (en) * | 2013-12-27 | 2014-04-02 | 西安电子科技大学 | ISAR (inverse synthetic aperture radar) imaging orientation calibration method |
| CN105510916A (en) * | 2015-11-30 | 2016-04-20 | 中国科学院电子学研究所 | InISAR (Interferometric Inverse Synthetic Aperture Radar) system-based moving target detection method |
| CN105919625A (en) * | 2016-05-26 | 2016-09-07 | 飞依诺科技(苏州)有限公司 | Pulse Doppler wall filtering processing method and processing system |
| CN106950554A (en) * | 2017-03-21 | 2017-07-14 | 中国人民解放军国防科学技术大学 | The method for realizing rolling target parameter Estimation under the conditions of vibration interference |
| CN106990398A (en) * | 2016-01-21 | 2017-07-28 | 中国人民解放军空军工程大学 | A kind of body of revolution fine motion feature awareness extracting method |
| CN107064889A (en) * | 2017-03-10 | 2017-08-18 | 北京环境特性研究所 | A kind of high-resolution fine motion target imaging system integration testing platform |
| CN107526079A (en) * | 2016-06-22 | 2017-12-29 | 中国解放军空军工程大学 | A kind of spatial spin target wideband radar three-D imaging method based on L-type triantennary interference treatment |
| CN107843894A (en) * | 2017-09-30 | 2018-03-27 | 中国人民解放军战略支援部队航天工程大学 | A kind of ISAR imaging methods of compound movement target |
| CN109633641A (en) * | 2018-11-30 | 2019-04-16 | 上海无线电设备研究所 | A kind of rotor blade inverse synthetic aperture radar imaging algorithm of Terahertz frequency range |
| CN110441753A (en) * | 2019-09-19 | 2019-11-12 | 森思泰克河北科技有限公司 | Radar occlusion detection method and radar |
| CN110554378A (en) * | 2019-09-10 | 2019-12-10 | 深圳锐越微技术有限公司 | Single-channel Doppler radar radial motion direction identification method and device |
| CN110716201A (en) * | 2019-09-10 | 2020-01-21 | 中国人民解放军空军工程大学 | Space rotation target video ISAR imaging method based on transmitted pulse period delay design |
| CN111427039A (en) * | 2020-04-21 | 2020-07-17 | 北京航天长征飞行器研究所 | ISAR imaging deception jamming method and device based on micro-motion characteristic modulation |
| CN111830505A (en) * | 2020-07-30 | 2020-10-27 | 北京环境特性研究所 | Radar rapid imaging method and device based on micro-motion periodic mask |
| CN112034460A (en) * | 2020-08-17 | 2020-12-04 | 宋千 | Circular-arc aperture radar imaging method based on antenna phase directional diagram compensation and radar |
| CN112710996A (en) * | 2020-12-08 | 2021-04-27 | 中国人民解放军海军航空大学 | Data set expansion method and system for radar micro-motion target identification |
| CN113156430A (en) * | 2021-04-29 | 2021-07-23 | 中国人民解放军空军工程大学 | Human body target gait fine recognition method based on vortex electromagnetic wave radar |
| CN113376633A (en) * | 2021-05-20 | 2021-09-10 | 西安电子科技大学 | ISAR echo vibration compensation and integral focusing imaging method for airplane wing |
| CN117437270A (en) * | 2023-12-21 | 2024-01-23 | 江苏恒力化纤股份有限公司 | Fabric texture regularity calculation method based on Fourier transform |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006275569A (en) * | 2005-03-28 | 2006-10-12 | Mitsubishi Electric Corp | Simulator system for radar imaging |
| JP2008026106A (en) * | 2006-07-20 | 2008-02-07 | Mitsubishi Electric Corp | Inverse synthetic aperture radar apparatus |
-
2011
- 2011-09-01 CN CN 201110257606 patent/CN102426360B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006275569A (en) * | 2005-03-28 | 2006-10-12 | Mitsubishi Electric Corp | Simulator system for radar imaging |
| JP2008026106A (en) * | 2006-07-20 | 2008-02-07 | Mitsubishi Electric Corp | Inverse synthetic aperture radar apparatus |
Non-Patent Citations (2)
| Title |
|---|
| 白雪茹等: "空中微动旋转目标的二维ISAR成像算法", 《电子学报》 * |
| 郑义明: "SAR/ISAR运动补偿新方法研究", 《中国优秀博士学位论文全文数据库》 * |
Cited By (33)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103424741A (en) * | 2013-08-29 | 2013-12-04 | 西安电子科技大学 | Smooth procession cone parameter estimation method based on high-resolution ISAR imaging |
| CN103424741B (en) * | 2013-08-29 | 2015-06-03 | 西安电子科技大学 | Smooth procession cone parameter estimation method based on high-resolution ISAR imaging |
| CN103698765A (en) * | 2013-12-27 | 2014-04-02 | 西安电子科技大学 | ISAR (inverse synthetic aperture radar) imaging orientation calibration method |
| CN105510916A (en) * | 2015-11-30 | 2016-04-20 | 中国科学院电子学研究所 | InISAR (Interferometric Inverse Synthetic Aperture Radar) system-based moving target detection method |
| CN106990398B (en) * | 2016-01-21 | 2019-10-15 | 中国人民解放军空军工程大学 | A kind of body of revolution fine motion feature awareness extracting method |
| CN106990398A (en) * | 2016-01-21 | 2017-07-28 | 中国人民解放军空军工程大学 | A kind of body of revolution fine motion feature awareness extracting method |
| CN105919625A (en) * | 2016-05-26 | 2016-09-07 | 飞依诺科技(苏州)有限公司 | Pulse Doppler wall filtering processing method and processing system |
| CN105919625B (en) * | 2016-05-26 | 2019-01-01 | 飞依诺科技(苏州)有限公司 | Pulse Doppler wall filtering processing method and processing system |
| CN107526079A (en) * | 2016-06-22 | 2017-12-29 | 中国解放军空军工程大学 | A kind of spatial spin target wideband radar three-D imaging method based on L-type triantennary interference treatment |
| CN107526079B (en) * | 2016-06-22 | 2020-07-31 | 中国解放军空军工程大学 | Space spin target broadband radar three-dimensional imaging method based on L type three-antenna interference processing |
| CN107064889A (en) * | 2017-03-10 | 2017-08-18 | 北京环境特性研究所 | A kind of high-resolution fine motion target imaging system integration testing platform |
| CN107064889B (en) * | 2017-03-10 | 2019-06-18 | 北京环境特性研究所 | A kind of high-resolution fine motion target imaging system integration testing platform |
| CN106950554A (en) * | 2017-03-21 | 2017-07-14 | 中国人民解放军国防科学技术大学 | The method for realizing rolling target parameter Estimation under the conditions of vibration interference |
| CN107843894A (en) * | 2017-09-30 | 2018-03-27 | 中国人民解放军战略支援部队航天工程大学 | A kind of ISAR imaging methods of compound movement target |
| CN109633641A (en) * | 2018-11-30 | 2019-04-16 | 上海无线电设备研究所 | A kind of rotor blade inverse synthetic aperture radar imaging algorithm of Terahertz frequency range |
| CN109633641B (en) * | 2018-11-30 | 2020-11-03 | 上海无线电设备研究所 | Terahertz frequency band rotor blade inverse synthetic aperture radar imaging algorithm |
| CN110716201A (en) * | 2019-09-10 | 2020-01-21 | 中国人民解放军空军工程大学 | Space rotation target video ISAR imaging method based on transmitted pulse period delay design |
| CN110554378A (en) * | 2019-09-10 | 2019-12-10 | 深圳锐越微技术有限公司 | Single-channel Doppler radar radial motion direction identification method and device |
| CN110554378B (en) * | 2019-09-10 | 2021-05-11 | 深圳锐越微技术有限公司 | Single-channel Doppler radar radial motion direction identification method and device |
| CN110716201B (en) * | 2019-09-10 | 2024-01-26 | 中国人民解放军空军工程大学 | Space rotation target video ISAR imaging method based on emission pulse period delay design |
| CN110441753A (en) * | 2019-09-19 | 2019-11-12 | 森思泰克河北科技有限公司 | Radar occlusion detection method and radar |
| CN110441753B (en) * | 2019-09-19 | 2021-03-30 | 森思泰克河北科技有限公司 | Radar occlusion detection method and radar |
| CN111427039A (en) * | 2020-04-21 | 2020-07-17 | 北京航天长征飞行器研究所 | ISAR imaging deception jamming method and device based on micro-motion characteristic modulation |
| CN111830505B (en) * | 2020-07-30 | 2022-02-22 | 北京环境特性研究所 | Radar rapid imaging method and device based on micro-motion periodic mask |
| CN111830505A (en) * | 2020-07-30 | 2020-10-27 | 北京环境特性研究所 | Radar rapid imaging method and device based on micro-motion periodic mask |
| CN112034460A (en) * | 2020-08-17 | 2020-12-04 | 宋千 | Circular-arc aperture radar imaging method based on antenna phase directional diagram compensation and radar |
| CN112710996A (en) * | 2020-12-08 | 2021-04-27 | 中国人民解放军海军航空大学 | Data set expansion method and system for radar micro-motion target identification |
| CN113156430A (en) * | 2021-04-29 | 2021-07-23 | 中国人民解放军空军工程大学 | Human body target gait fine recognition method based on vortex electromagnetic wave radar |
| CN113156430B (en) * | 2021-04-29 | 2023-07-28 | 中国人民解放军空军工程大学 | Human body target gait fine recognition method based on vortex electromagnetic wave radar |
| CN113376633B (en) * | 2021-05-20 | 2023-04-18 | 西安电子科技大学 | ISAR echo vibration compensation and integral focusing imaging method for airplane wing |
| CN113376633A (en) * | 2021-05-20 | 2021-09-10 | 西安电子科技大学 | ISAR echo vibration compensation and integral focusing imaging method for airplane wing |
| CN117437270A (en) * | 2023-12-21 | 2024-01-23 | 江苏恒力化纤股份有限公司 | Fabric texture regularity calculation method based on Fourier transform |
| CN117437270B (en) * | 2023-12-21 | 2024-03-19 | 江苏恒力化纤股份有限公司 | Fabric texture regularity calculation method based on Fourier transform |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102426360B (en) | 2013-09-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102426360B (en) | Two-dimensional ISRA imaging method of object with micro rotation in air | |
| CN102288963B (en) | Bistatic inverse synthetic aperture radar (ISAR) image fusion method based on sub aperture parameter estimation | |
| CN105301590B (en) | A kind of maneuvering target frequency modulation stepping inverse synthetic aperture imaging method | |
| CN111142105B (en) | ISAR imaging method for complex moving target | |
| CN102393518B (en) | Airborne SAR (synthetic aperture radar) imaging method suitable for large squint angle | |
| CN104898119B (en) | A kind of moving target parameter estimation method based on correlation function | |
| CN110346798B (en) | Bistatic synthetic aperture radar wavenumber domain efficient imaging processing method | |
| CN110146886A (en) | The method for quick estimating of non-homogeneous rotating target motion parameter | |
| CN102914773B (en) | Multi-pass circumference SAR three-dimensional imaging method | |
| CN102540189A (en) | Spinning target three-dimensional imaging method based on plural backward projection | |
| CN109444882B (en) | Double-station SAR imaging method based on variable squint elliptical beam synchronous model | |
| CN103885051A (en) | Simple scattering point cone target parameter estimation method based on time-frequency imaging | |
| CN103424741A (en) | Smooth procession cone parameter estimation method based on high-resolution ISAR imaging | |
| CN110133648B (en) | Method for selecting ship imaging time window of inverse synthetic aperture radar | |
| CN110161503B (en) | Short-range and wide-range SAR high-resolution imaging method based on three-dimensional equidistant circle model | |
| CN104833974A (en) | SAR imaging quick backward projection method based on image spectrum compression | |
| CN106054187B (en) | Based on the big Squint SAR curvilinear path wave-number domain imaging method under oblique distance model | |
| CN110146889A (en) | Large-rotation-angle ISAR imaging method based on optimal echo sub-region selection | |
| CN108710111A (en) | A kind of two-dimentional space-variant bearing calibration of airborne biradical Forward-looking SAR orientation phase | |
| CN103630899B (en) | Method for high-resolution radar compressed sensing imaging of moving object on ground | |
| CN102608576B (en) | Geometric correction method for large rake forward synthetic aperture radar return image | |
| CN110244300B (en) | Missile-borne SAR (synthetic Aperture Radar) level flight section high-resolution imaging method based on sphere model and FENLCS (finite Impulse noise correction) algorithm | |
| CN103149554A (en) | Scaling inverse Fourier transformation imaging method of bistatic synthetic aperture radar (SAR) | |
| CN111208514A (en) | Chebyshev slant range model of curved motion trajectory SAR and Chirp Scaling imaging method | |
| CN102012510A (en) | Inverse synthetic aperture radar imaging method based on time-phase derivative distribution |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |