CN103235298A - Microwave related imaging system and imaging method based on thinned array - Google Patents
Microwave related imaging system and imaging method based on thinned array Download PDFInfo
- Publication number
- CN103235298A CN103235298A CN2013101673606A CN201310167360A CN103235298A CN 103235298 A CN103235298 A CN 103235298A CN 2013101673606 A CN2013101673606 A CN 2013101673606A CN 201310167360 A CN201310167360 A CN 201310167360A CN 103235298 A CN103235298 A CN 103235298A
- Authority
- CN
- China
- Prior art keywords
- target
- microwave
- radiation field
- array
- vector
- 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 microwave related imaging system and a microwave related imaging method based on a thinned array, which mainly aim to solve the problems of poor imaging effect and low resolution when non-radial relative movement does not exist between a radar antenna and a target in the prior art. The system comprises a transmitting antenna (1), a target (2), a receiver (3) and a signal processor (5), wherein the transmitting antenna (1) is formed by a thinned array antenna; different microwave coded signals are transmitted by all array elements, so as to form a microwave radiation field in space through incoherent superposition; the target (2) is irradiated through the microwave radiation field, so as to generate target scattering echoes; the microwave radiation field (4) on the surface of the target (2) is stored; the target scattering echoes are received by the receiver (3) through a single antenna and a single channel; and the target scattering echoes received by the receiver (3) and the pre-stored microwave radiation field (4) are processed by the signal processor (5), so as to obtain the imaging of the target. By using the system and the method, super-resolution imaging of the target without ambiguity can be realized when the non-radial relative movement does not exist between the radar antenna and the target, and the system and the method can be used for super-resolution imaging of the target by an airborne forward-looking radar and a ball-borne radar.
Description
Technical field
The invention belongs to the Radar Technology field, relate to microwave relevance imaging system and formation method, the acquisition process and the optimization algorithm that can be used for thinned array antenna structure, signal are used.
Technical background
Utilizing entangled photons is that Soviet Union scholar David Nikolaevich Klyshko proposed first in theory in 1988 to the scheme that realizes the quantum relevance imaging.People such as the Shi Yanhua of Univ Maryland-Coll Park USA, T.B.Pittman utilize the entangled photons that conversion SPDC process produces under the spontaneous parameter right in nineteen ninety-five, in conjunction with the coincidence measurement technology, have realized a kind of quantum relevance imaging and interference.2004, gondola Lugiato group proposed to utilize common classical thermal light source also can realize relevance imaging theoretically.2005, the counterfeit hot light that history inkstone China group uses laser incident frosted glass to produce was finished the relevance imaging experiment of first thermal light source.2006, history inkstone China group realized lensless relevance imaging first.2011 history inkstones China group has realized utilizing the relevance imaging test in solar radiation source.Compare with the source relevance imaging of tangling, thermal light source relevance imaging emissive source produces simple, and signal stabilization degree height is used in actual engineering easilier.
Be the brand-new information theory of the different and classical Shannon information theory that grew up in nearly 30 years based on the data acquisition of sparse constraint and redundant presentation and signal reconstruction theory, demonstrate huge application potential in fields such as compressed sensing CS.D.Donoho, the famous scholars' of multidigit such as E.Candes and Terence Tao extensive work be strict the proof under the situation far below the nyquist sampling limit from the mathematics, uses the compressed sensing sampling can high probability reconstruct target information.Compressed sensing sampling request target has sparse characteristic or target has sparse characteristic under some presentation, and its detection matrix need satisfy limited equidistant characteristics RIP.In true imaging, sparse characteristic satisfies than being easier to, and gaussian random matrix, Bernoulli Jacob's stochastic matrix and Teoplitz stochastic matrix etc. all have been proved to be and satisfy limited equidistant characteristics RIP condition.At present, the compressed sensing theory is to comprising the development of fields such as medical imaging, chnnel coding, recognition of face, communication, Hyper spectral Imaging, radar and life science and having obtained many achievements in research.
As mentioned above, the quantum relevance imaging is realized with counterfeit thermal light source, day light source afterwards from initial use entangled light source, illustrates that the classical signals source realization relevance imaging that does not possess Quantum Properties is feasible.But owing to a little less than the light signal penetration power, be subjected to natural environment influences such as atmosphere easily, be difficult to realize the round-the-clock imaging of round-the-clock, and in radar system, use microwave signal as transmitting, can realize the round-the-clock imaging of round-the-clock; Aspect collection and processing, microwave signal has ripe collection and process chip, than the easier structure of entangled light source and counterfeit thermal light source system; Adopt microwave signal to realize that the key of relevance imaging is the microwave field of random fluctuation when realizing simulating light field empty, existing method is on the basis that makes up large-scale traditional surface antenna, the microwave radiation field of random fluctuation when radiation gaussian random signal is realized sky, system complexity is very high.
Compressed sensing is theoretical as the brand-new information theory that proposed in recent years, all demonstrate huge application potential in a lot of fields, but its applied research in microwave relevance imaging field is also fewer.
When prior art did not have non-radially relative motion in radar antenna and target, imaging effect was poor, and resolution is low.
Summary of the invention
The objective of the invention is to the deficiency at above-mentioned prior art, a kind of microwave relevance imaging system and formation method based on thinned array proposed, the relevance imaging theory is extended to microwave regime and utilizes theoretical corresponding problem, raising imaging effect and the resolution of solving of compressed sensing from optics.
For achieving the above object, the present invention is based on the microwave relevance imaging system of thinned array, comprise: emitting antenna 1, target 2, receiver 3 and signal processor 5, the microwave radiation field that utilizes emitting antenna 1 to produce shines the scatter echo that produces target to target 2, the corresponding microwave radiation field 4 in storage target 2 surfaces, the scatter echo of receiver 3 receiving targets, the target scattering echo that receiver 3 receives and the microwave radiation field that prestores 4 are handled by signal processor 5, obtain the imaging of target, it is characterized in that:
Described emitting antenna 1, employing is by the sparse thinned array antenna of arranging and constituting of a plurality of array elements, the different microwave coded signal of each array element emission forms microwave radiation field in the space non-coherent addition, random fluctuation characteristic when this microwave radiation field has counterfeit hot optical radiation field empty;
Described receiver 3 adopts single antenna, single.
As preferably, the present invention is based on the microwave relevance imaging system of thinned array, it is characterized in that emitting antenna 1 adjacent two array element distance d satisfy
Wherein λ is the wavelength of signal;
As preferably, the present invention is based on the microwave relevance imaging system of thinned array, it is characterized in that, the microwave radiation field that emitting antenna 1 produces is to the irradiation number of times M of the target 2 resolution element sum N much smaller than target 2, N=P * Q wherein, P is the horizontal resolution element number of target 2, and Q is the longitudinal resolution unit number of target 2.
For achieving the above object, the present invention is based on the microwave relevance imaging method of thinned array, comprise the steps:
1) obtains the radiation field matrix Φ of target and scatter echo vector y;
2) according to target at spatial distributions feature selecting sparse basis array Ψ;
3) radiation field matrix Φ and selected sparse basis array Ψ are multiplied each other, obtain measuring matrix Θ=Φ Ψ;
4) by scatter echo vector form y=Θ α+ε, wherein ε is the white Gaussian noise vector, finds the solution following formula and obtains sparse coefficient vector α:
‖ ‖ wherein
ω, 1Be weighting L1 norm, be expressed as:
|| the mould value of plural number, sparse coefficient vector α=[ζ are got in expression
1, ζ
2..., ζ
n..., ζ
N]
H∈ C
N * 1, H represents the conjugate transpose of vector, C represents complex number space; [ω
1, ω
2..., ω
n..., ω
N]
T∈ R
N * 1Be given non-negative weight vector, T represents the transposition of vector, and R represents real number space; ‖ ‖
2Be the L2 norm, γ is the constant relevant with noise level;
5) the sparse coefficient vector α substitution formula x=Ψ α that step 4 is tried to achieve solves the backscattering coefficient vector x of target;
6) the backscattering coefficient vector x of target being reset is the matrix corresponding with target sizes P * Q, utilizes the matrix imaging that obtains after resetting, and namely obtains the imaging of target.
The present invention compared with prior art has following advantage:
A) imaging system of the present invention does not need radar antenna and target to have the high-resolution imaging that non-radially relative motion just can obtain target, has non-radially relative motion with existing synthetic-aperture radar SAR Technology Need radar antenna and target, compare through the high-resolution imaging that the synthetic bigger aperture of long accumulation obtains target, the equipment use amount is few, and system complexity is low;
B) imaging system joint objective scatter echo of the present invention and radiation field data are carried out imaging to target, only utilize the target scattering echo data that target is carried out imaging to compare with the existing radar imagery technology of staring, the target imaging effect that obtains is better, resolution is higher;
C) imaging system of the present invention use penetration power strong, be not easy to be subjected to the microwave signal of natural environment influences such as atmosphere as transmitting, use light signal to compare as transmitting with existing hot light relevance imaging technology, can realize the round-the-clock imaging of round-the-clock.
Description of drawings
Fig. 1 is the microwave relevance imaging system schematic that the present invention is based on thinned array;
Fig. 2 is three peacekeeping two-dimensional representation of counterfeit hot optical radiation field;
Fig. 3 is that the present invention is in adjacent two array element distance of emitting antenna
Under the situation, three peacekeeping two-dimensional representation of microwave radiation field;
Fig. 4 be the present invention under the adjacent two array element distance d=40 λ situations of emitting antenna, three peacekeeping two-dimensional representation of microwave radiation field;
Fig. 5 is the microwave relevance imaging method flow diagram that the present invention is based on thinned array;
Fig. 6 is the validity score Butut of target;
Fig. 7 is with the simulation result of formation method of the present invention to Fig. 6.
Embodiment
The invention will be further described below in conjunction with each accompanying drawing, is exemplary below by the embodiment that is described with reference to the drawings, and only is used for explaining the present invention, and can not be interpreted as limitation of the present invention.
With reference to figure 1, microwave relevance imaging system based on thinned array of the present invention, comprise emitting antenna 1, target 2, receiver 3 and signal processor 5, wherein, emitting antenna 1 is made up of thinned array antenna, the different microwave coded signal of each array element emission forms microwave radiation field in the space non-coherent addition, this microwave radiation field shines target 2 and produces the target scattering echo, the corresponding microwave radiation field 4 in storage target 2 surfaces, receiver 3 receiving target scatter echos, the target scattering echo that receiver 3 receives and the microwave radiation field that prestores 4 are handled by signal processor 5, obtain the imaging of target.
Described receiver 3 adopts single antenna, single channel receiving mode, is used for receiving the target scattering echo that microwave radiation field produces target irradiation back.
Described signal processor 5 adopts at a high speed, the computing machine of big internal memory, for the treatment of target scattering echo and radiation field data, realizes the imaging of target.
Described emitting antenna 1 adopts the bidimensional thinned array antenna, and this bidimensional thinned array antenna adopts the rectangular array pattern, but is not limited to this structure, and it is provided with 25 array elements, is evenly distributed in the rectangular surfaces; The adjacent two array element distance d of thinned array antenna satisfy
This example is got but is not limited to d=40 λ, and wherein λ is signal wavelength.Each array element emission but be not limited to the stack of the microwave coded signal that frequency accidental changes
I=1,2 ..., the different array element of 25 expressions, wherein L is given constant, f
IlBe the frequency of microwave coded signal, this frequency is along with variation random variation in the 0-1GHz scope of l.
The microwave coded signal of each array element emission
The microwave radiation field that produces in the space non-coherent addition is expressed as:
Random fluctuation characteristic when this microwave radiation field S (t) has counterfeit hot optical radiation field empty.
The feature that the microwave radiation field S (t) that this example produces has is explained by the following drawings:
Fig. 2 (a) and Fig. 2 (b) are three peacekeeping two-dimensional representation of counterfeit hot optical radiation field, and as can be seen from Figure 2, this radiation field has good random fluctuation characteristic when empty;
Fig. 3 (a) and Fig. 3 (b) are in adjacent two array element distance of emitting antenna with the present invention
Under the situation, the three peacekeeping two-dimensional representation of microwave radiation field S (t) can be seen with Fig. 2 contrast, and the random fluctuation characteristic is relatively poor during microwave radiation field shown in Figure 3 empty;
Fig. 4 (a) and Fig. 4 (b) use the present invention under the adjacent two array element distance d=40 λ situations of emitting antenna, and the three peacekeeping two-dimensional representation of microwave radiation field S (t) can be seen with Fig. 3 contrast, arrange because transmitting antenna array is sparse, i.e. adjacent two array element distance
Make that when forming transmitting antenna array with identical array number random character strengthens during the microwave radiation field of generation empty; Can see that with Fig. 2 contrast microwave radiation field shown in Figure 4 has similar to counterfeit hot optical radiation field random fluctuation characteristic when empty.
With reference to Fig. 5, the present invention is based on the microwave relevance imaging method of thinned array, comprise the steps:
1.1) with the microwave radiation field S (t) that produces target P * Q is shone, wherein P and Q represent the transverse and longitudinal resolution element number of target respectively, in each irradiation, microwave radiation field S (t) are done statistical study, and it is arranged the vector φ into delegation again
mAnd storage, φ
m∈ C
1 * N, wherein N=P * Q is the resolution element sum of target, C represents complex number space; Receiver receiving target scatter echo signal, the target scattering echoed signal summation back storage with receiving is designated as r
m, r
m∈ C
1 * 1It is a scalar;
1.2) microwave radiation field S (t) to imageable target irradiation M time after, by vectorial φ
mWith scalar r
mConstitute the radiation field matrix respectively
With scatter echo vector y=[r
1, r
2..., r
m..., r
M]
H, wherein H represents conjugate transpose, m=1, and 2 ..., M, M is much smaller than N.
When target was sparse distribution in the space, then selection unit's matrix was as sparse basis array Ψ;
When target is non-sparse distribution in the space, then select discrete cosine transform DCT or wavelet transform DWT matrix as sparse basis array Ψ.
‖ ‖ wherein
ω, 1Be weighting L1 norm, be expressed as:
|| the mould value of plural number, sparse coefficient vector α=[ζ are got in expression
1, ζ
2..., ζ
n..., ζ
N]
H∈ C
N * 1, H represents the conjugate transpose of vector, C represents complex number space; [ω
1, ω
2..., ω
n..., ω
N]
T∈ R
N * 1Be given non-negative weight vector, get here but be not limited to vector of unit length, namely get each element and be 1:[ω
1, ω
2..., ω
n..., ω
N]
T=[1,1 ..., 1 ..., 1]
T, T represents the transposition of vector, R represents real number space;
‖ ‖ wherein
2Be the L2 norm, γ is the constant relevant with noise level, gets γ=var (ε), the variance of var () for getting noise vector;
Here define signal to noise ratio snr=10log (e
y/ e
ε), e wherein
yBe the average energy value of scatter echo vector y, e
εThe average energy value for the white Gaussian noise vector is respectively:
Y=[r wherein
1, r
2..., r
m..., r
M]
H, ε=[σ
1, σ
2..., σ
m..., σ
M]
H
Step 5 with the sparse coefficient vector α substitution formula x=Ψ α that step 4 is tried to achieve, solves the backscattering coefficient vector x of target.
The microwave relevance imaging method that the present invention is based on thinned array can realize that the theoretical analysis of target imaging is as follows:
The described radiation field matrix of step 1 Φ is obtained by microwave radiation field S (t), random fluctuation characteristic when this microwave radiation field S (t) has counterfeit hot optical radiation field empty, the random character that makes the radiation field matrix Φ of acquisition have Gaussian distribution;
With reference to the compressed sensing theory as can be known, because the sparse basis array Ψ that step 2 is selected is the distribution character of influence matrix Φ not, when radiation field matrix Φ has the random character of Gaussian distribution, the measurement matrix Θ=Φ Ψ that is obtained by step 3, satisfy the limited equidistant characteristics RIP in the compressed sensing theory, namely for a positive integer S, there is a constant δ
S, make that measuring matrix Θ can guarantee to set up as lower inequality:
δ wherein
S Satisfy 0＜δ
S＜1, β is any vector that degree of rarefication is no more than S, namely contains S nonzero value, ‖ ‖ among the vectorial β at most
2The L2 norm of expression vector;
Measurement matrix Θ satisfies the limited equidistant characteristics RIP in the compressed sensing theory, can guarantee that the formation method of this example is realized correct, reliable target imaging.
The imaging effect of this example formation method can further specify by following simulation result:
1. simulated conditions
The even rectangular array emitting antenna that consideration is made up of 25 array elements, the above-mentioned microwave coded signal of each array element emission
I=1,2 ..., 25, other parameters are: carrier frequency f
c=3GHz, carrier wavelength lambda=c/f
c, wherein c is the light velocity, adjacent two array element distance d=40 λ, signal bandwidth B=1GHz, the distance R between emitting antenna and target
c=1000m, receiver adopt single antenna, single, and selection unit's matrix is as sparse basis array Ψ, signal to noise ratio snr=10dB, the Rayleigh diffraction limit under this configuration
2. emulation content
Under described simulated conditions, carry out following experiment:
Fig. 6 is the validity score Butut of target 20m * 20m, and the interval of 4 bar targets is respectively 1m among the figure, and 2m and 4m are approximately 4 times above the Rayleigh diffraction limit, 2 times and 1 times.
To Fig. 6 target irradiation 200 times, with the formation method of this example Fig. 6 is carried out simulation imaging with the microwave radiation field of this example, simulation result as shown in Figure 7.
From the simulation result of Fig. 7 as can be seen, utilize the microwave radiation field of this example and the corresponding imaging algorithm can be than the super-resolution imaging of realizing surpassing the Rayleigh diffraction limit under the low signal-to-noise ratio, though have some assorted noises in the imaging results, the global feature of target and detailed information are all high-visible.
To sum up, this simulating, verifying correctness of the present invention, realizability and reliability.
Claims (6)
1. microwave relevance imaging system based on thinned array, comprise: emitting antenna (1), target (2), receiver (3) and signal processor (5), the microwave radiation field that utilizes emitting antenna (1) to produce shines target (2) and produces the target scattering echo, the microwave radiation field (4) on storage target (2) surface, receiver (3) receiving target scatter echo, the target scattering echo that receiver (3) receives and the microwave radiation field (4) that prestores are handled by signal processor (5), obtain the imaging of target, it is characterized in that:
Described emitting antenna (1), employing is by the sparse thinned array antenna of arranging and constituting of a plurality of array elements, the different microwave coded signal of each array element emission forms microwave radiation field in the space non-coherent addition, random fluctuation characteristic when this microwave radiation field has counterfeit hot optical radiation field empty;
Described receiver (3) adopts single antenna, single.
2. the microwave relevance imaging system based on thinned array as claimed in claim 1 is characterized in that, the adjacent two array element distance d of emitting antenna (1) satisfy
Wherein λ is the wavelength of signal.
3. the microwave relevance imaging system based on thinned array as claimed in claim 1, it is characterized in that, the microwave radiation field that emitting antenna (1) produces is to the irradiation number of times M of target (2) the resolution element sum N much smaller than target (2), N=P * Q wherein, P is the horizontal resolution element number of target (2), and Q is the longitudinal resolution unit number of target (2).
4. the microwave relevance imaging method based on thinned array comprises the steps:
1) obtains the radiation field matrix Φ of target and scatter echo vector y;
2) according to target at spatial distributions feature selecting sparse basis array Ψ;
3) radiation field matrix Φ and selected sparse basis array Ψ are multiplied each other, obtain measuring matrix Θ=Φ Ψ;
4) by scatter echo vector form y=Θ α+ε, wherein ε is the white Gaussian noise vector, finds the solution following formula and obtains sparse coefficient vector α:
Wherein || ||
ω, 1Be weighting L1 norm, be expressed as:
|| the mould value of plural number, sparse coefficient vector α=[ζ are got in expression
1, ζ
2..., ζ
n..., ζ
N]
H∈ C
N * 1, H represents the conjugate transpose of vector, C represents complex number space; [ω
1, ω
2..., ω
n..., ω
N]
T∈ R
N * 1Be given non-negative weight vector, T represents the transposition of vector, and R represents real number space; || ||
2Be the L2 norm, γ is the constant relevant with noise level;
5) the sparse coefficient vector α substitution formula x=Ψ α that step 4 is tried to achieve solves the backscattering coefficient vector x of target;
6) the backscattering coefficient vector x of target being reset is the matrix corresponding with target sizes P * Q, utilizes the matrix imaging that obtains after resetting, and namely obtains the imaging of target.
5. the microwave relevance imaging method based on thinned array as claimed in claim 4 is characterized in that step 2) describedly select sparse basis array Ψ according to target in the spatial distributions characteristic, carry out as follows:
When target was sparse distribution in the space, then the selected cell matrix was as sparse basis array Ψ;
When target is non-sparse distribution in the space, then select discrete cosine transform DCT or wavelet transform DWT matrix as sparse basis array Ψ.
6. the microwave relevance imaging method based on thinned array as claimed in claim 4, it is characterized in that, described being multiplied each other by radiation field matrix Φ and selected sparse basis array Ψ of step 3) obtains measuring matrix Θ=Φ Ψ, this measurement matrix Θ satisfies the limited equidistant characteristics RIP in the compressed sensing theory, namely for a positive integer S, there is a constant δ
S, make that measuring matrix Θ can guarantee to set up as lower inequality:
δ wherein
SSatisfy 0＜δ
S＜1, β is any vector that degree of rarefication is no more than S, namely contains S nonzero value among the vectorial β at most, || ||
2The L2 norm of expression vector.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310167360.6A CN103235298B (en) | 2013-05-08 | 2013-05-08 | Based on microwave relevance imaging system and the formation method of thinned array |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310167360.6A CN103235298B (en) | 2013-05-08 | 2013-05-08 | Based on microwave relevance imaging system and the formation method of thinned array |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103235298A true CN103235298A (en) | 2013-08-07 |
| CN103235298B CN103235298B (en) | 2015-08-05 |
Family
ID=48883349
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310167360.6A Expired - Fee Related CN103235298B (en) | 2013-05-08 | 2013-05-08 | Based on microwave relevance imaging system and the formation method of thinned array |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103235298B (en) |
Cited By (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103558606A (en) * | 2013-10-29 | 2014-02-05 | 南京邮电大学 | Condition part measuring associated imaging method based on compressive sensing |
| CN103605121A (en) * | 2013-11-18 | 2014-02-26 | 南京理工大学 | Broadband radar data fusion method based on rapid sparse Bayesian learning algorithm |
| CN103744078A (en) * | 2013-12-30 | 2014-04-23 | 中国科学技术大学 | Microwave stare correlated imaging device capable of performing random frequency hopping based on different code speeds |
| CN103837873A (en) * | 2014-03-14 | 2014-06-04 | 中国科学技术大学 | Microwave and stare correlated imaging system and method based on floating platform and intensive array antennae |
| CN104159048A (en) * | 2014-07-24 | 2014-11-19 | 南京邮电大学 | Compressive sensing uniform weighting relevance imaging method for non-uniform light field |
| CN104199028A (en) * | 2014-09-03 | 2014-12-10 | 西安电子科技大学 | Microwave correlated imaging method based on radar rotating emission array |
| CN104306022A (en) * | 2014-10-24 | 2015-01-28 | 西安电子科技大学 | Compressive sense ultrasound imaging method through GPU (graphics processing unit) |
| CN104306023A (en) * | 2014-10-24 | 2015-01-28 | 西安电子科技大学 | Method for quickly implementing ultrasonic imaging on basis of compressive sensing |
| CN104360345A (en) * | 2014-09-29 | 2015-02-18 | 林子怀 | High-resolution through-wall imaging system and method based on random antenna arrays and microwave correlated imaging principles |
| CN104569974A (en) * | 2015-02-09 | 2015-04-29 | 中国科学技术大学 | Random radiation array element arrangement quantitative characterization method of microwave staring correlated imaging system |
| CN105223698A (en) * | 2015-09-21 | 2016-01-06 | 西安电子科技大学 | A kind of counterfeit thermal light source based on array beams |
| CN105866772A (en) * | 2016-04-18 | 2016-08-17 | 浙江大学 | Novel method for positioning metal object in human body based on microwave coherence imaging |
| CN106680778A (en) * | 2017-01-03 | 2017-05-17 | 中国科学技术大学 | Three dimensional stereo random antenna array construction method |
| CN107024693A (en) * | 2017-03-07 | 2017-08-08 | 西安交通大学 | A kind of radar relevance imaging method of single-shot beam |
| CN110187498A (en) * | 2019-05-27 | 2019-08-30 | 中国科学院国家空间科学中心 | A kind of very hot smooth relevance imaging system |
| CN110780296A (en) * | 2019-10-25 | 2020-02-11 | 西安电子科技大学 | Real aperture radar imaging method based on digital coding metamaterial and compressed sensing |
| CN111257871A (en) * | 2020-03-09 | 2020-06-09 | 中国科学技术大学 | Single-antenna radiation source design method for microwave staring correlated imaging |
| CN111896957A (en) * | 2020-08-11 | 2020-11-06 | 西安电子科技大学 | Ship target foresight three-dimensional imaging method based on wavelet transformation and compressed sensing |
| CN112882039A (en) * | 2021-01-11 | 2021-06-01 | 中国科学院声学研究所 | Array sparse method |
| CN113516826A (en) * | 2020-04-10 | 2021-10-19 | 郑州任道智能科技有限公司 | Multidirectional intelligent abandon-prevention alarm device |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101620273A (en) * | 2009-08-08 | 2010-01-06 | 桂林电子科技大学 | Method for detecting underwater object by relevance imaging |
| CN102141618A (en) * | 2011-01-04 | 2011-08-03 | 中国科学技术大学 | Microwave staring imaging method |
-
2013
- 2013-05-08 CN CN201310167360.6A patent/CN103235298B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101620273A (en) * | 2009-08-08 | 2010-01-06 | 桂林电子科技大学 | Method for detecting underwater object by relevance imaging |
| CN102141618A (en) * | 2011-01-04 | 2011-08-03 | 中国科学技术大学 | Microwave staring imaging method |
Non-Patent Citations (3)
| Title |
|---|
| LING CEN等: "Linear Sparse Array Synthesis via Convex Optimization", 《2010 IEEE》, 31 December 2010 (2010-12-31), pages 4233 - 4236 * |
| 乞耀龙等: "基于压缩感知的稀疏阵列近景微波三维成像", 《电子测量技术》, vol. 35, no. 5, 31 May 2012 (2012-05-31), pages 66 - 71 * |
| 白旭等: "基于压缩感知的差分关联成像方案研究", 《物理学报》, vol. 62, no. 4, 30 April 2013 (2013-04-30) * |
Cited By (30)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103558606A (en) * | 2013-10-29 | 2014-02-05 | 南京邮电大学 | Condition part measuring associated imaging method based on compressive sensing |
| CN103605121A (en) * | 2013-11-18 | 2014-02-26 | 南京理工大学 | Broadband radar data fusion method based on rapid sparse Bayesian learning algorithm |
| CN103744078B (en) * | 2013-12-30 | 2016-04-13 | 中国科学技术大学 | A kind of microwave based on different code speed random frequency hopping stares relevance imaging device |
| CN103744078A (en) * | 2013-12-30 | 2014-04-23 | 中国科学技术大学 | Microwave stare correlated imaging device capable of performing random frequency hopping based on different code speeds |
| CN103837873A (en) * | 2014-03-14 | 2014-06-04 | 中国科学技术大学 | Microwave and stare correlated imaging system and method based on floating platform and intensive array antennae |
| CN103837873B (en) * | 2014-03-14 | 2016-08-17 | 中国科学技术大学 | A kind of microwave based on floating platform closely spaced array antenna stares relevance imaging system and formation method |
| CN104159048A (en) * | 2014-07-24 | 2014-11-19 | 南京邮电大学 | Compressive sensing uniform weighting relevance imaging method for non-uniform light field |
| CN104199028A (en) * | 2014-09-03 | 2014-12-10 | 西安电子科技大学 | Microwave correlated imaging method based on radar rotating emission array |
| CN104199028B (en) * | 2014-09-03 | 2016-08-24 | 西安电子科技大学 | The microwave relevance imaging method of emission array is rotated based on radar |
| CN104360345A (en) * | 2014-09-29 | 2015-02-18 | 林子怀 | High-resolution through-wall imaging system and method based on random antenna arrays and microwave correlated imaging principles |
| CN104306023A (en) * | 2014-10-24 | 2015-01-28 | 西安电子科技大学 | Method for quickly implementing ultrasonic imaging on basis of compressive sensing |
| CN104306023B (en) * | 2014-10-24 | 2016-05-25 | 西安电子科技大学 | Ultrasonic imaging Fast implementation based on compressed sensing |
| CN104306022B (en) * | 2014-10-24 | 2016-05-25 | 西安电子科技大学 | Realize the method for compressed sensing ultrasonic imaging with GPU |
| CN104306022A (en) * | 2014-10-24 | 2015-01-28 | 西安电子科技大学 | Compressive sense ultrasound imaging method through GPU (graphics processing unit) |
| CN104569974A (en) * | 2015-02-09 | 2015-04-29 | 中国科学技术大学 | Random radiation array element arrangement quantitative characterization method of microwave staring correlated imaging system |
| CN105223698A (en) * | 2015-09-21 | 2016-01-06 | 西安电子科技大学 | A kind of counterfeit thermal light source based on array beams |
| CN105866772A (en) * | 2016-04-18 | 2016-08-17 | 浙江大学 | Novel method for positioning metal object in human body based on microwave coherence imaging |
| CN106680778A (en) * | 2017-01-03 | 2017-05-17 | 中国科学技术大学 | Three dimensional stereo random antenna array construction method |
| CN107024693B (en) * | 2017-03-07 | 2019-12-24 | 西安交通大学 | Radar correlation imaging method of single-emission system |
| CN107024693A (en) * | 2017-03-07 | 2017-08-08 | 西安交通大学 | A kind of radar relevance imaging method of single-shot beam |
| CN110187498A (en) * | 2019-05-27 | 2019-08-30 | 中国科学院国家空间科学中心 | A kind of very hot smooth relevance imaging system |
| CN110187498B (en) * | 2019-05-27 | 2021-08-17 | 中国科学院国家空间科学中心 | True heat light correlation imaging system |
| CN110780296A (en) * | 2019-10-25 | 2020-02-11 | 西安电子科技大学 | Real aperture radar imaging method based on digital coding metamaterial and compressed sensing |
| CN111257871A (en) * | 2020-03-09 | 2020-06-09 | 中国科学技术大学 | Single-antenna radiation source design method for microwave staring correlated imaging |
| CN111257871B (en) * | 2020-03-09 | 2023-06-16 | 中国科学技术大学 | Single-antenna radiation source design method for microwave staring correlated imaging |
| CN113516826A (en) * | 2020-04-10 | 2021-10-19 | 郑州任道智能科技有限公司 | Multidirectional intelligent abandon-prevention alarm device |
| CN111896957A (en) * | 2020-08-11 | 2020-11-06 | 西安电子科技大学 | Ship target foresight three-dimensional imaging method based on wavelet transformation and compressed sensing |
| CN111896957B (en) * | 2020-08-11 | 2023-03-14 | 西安电子科技大学 | Ship target foresight three-dimensional imaging method based on wavelet transformation and compressed sensing |
| CN112882039A (en) * | 2021-01-11 | 2021-06-01 | 中国科学院声学研究所 | Array sparse method |
| CN112882039B (en) * | 2021-01-11 | 2023-01-03 | 中国科学院声学研究所 | Array sparse method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103235298B (en) | 2015-08-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103235298B (en) | Based on microwave relevance imaging system and the formation method of thinned array | |
| CN103698763B (en) | Based on the linear array SAR sparse formation method of hard-threshold orthogonal matching pursuit | |
| Jin et al. | Polarimetric scattering and SAR information retrieval | |
| CN102879782B (en) | Compressed sensing synthetic aperture radar (SAR) imaging method based on fractional order fourier transformation | |
| CN103149561B (en) | Microwave imaging method based on scenario block sparsity | |
| CN104111458B (en) | Compressed sensing synthetic aperture radar image-forming method based on dual sparse constraint | |
| CN103353595B (en) | Meter wave radar height measurement method based on array interpolation compression perception | |
| CN104237883B (en) | Airborne radar space time self-adaptation processing method with sparse representation | |
| CN106405548A (en) | Inverse synthetic aperture radar imaging method based on multi-task Bayesian compression perception | |
| CN105849582B (en) | For reducing the method and apparatus of the noise in the radar of code aperture | |
| CN102313888A (en) | Linear array SAR (synthetic aperture radar) three-dimensional imaging method based on compressed sensing | |
| CN102854505B (en) | Weighting sparse-driven self-focusing SAR (Synthetic Aperture Radar) imaging method | |
| CN106950555A (en) | A kind of Area Objects imaging method based on Terahertz aperture coded imaging system | |
| CN107576961B (en) | A kind of relatively prime down-sampled sparse imaging method of interval synthetic aperture radar | |
| CN103837873A (en) | Microwave and stare correlated imaging system and method based on floating platform and intensive array antennae | |
| CN102854507B (en) | Imaging method of bistatic SAR (synthetic aperture radar) based on GPU (graphics processing unit) back projection | |
| Sun et al. | Recent advances in synthetic aperture radar remote sensing—systems, data processing, and applications | |
| US8401793B2 (en) | High resolution wind measurements for offshore wind energy development | |
| CN101464956A (en) | Method for classifying polarization synthetic aperture radar image based on sub-aperture analysis | |
| CN104199029A (en) | Measurement matrix design method for improving target imaging performance of compressed sensing radar | |
| CN104483671B (en) | Sparse representation theory-based synthetic aperture radar imaging method | |
| CN107656271A (en) | Terahertz radar imagery algorithm based on compressed sensing reconstruct | |
| Hu et al. | Joint sparsity‐driven three‐dimensional imaging method for multiple‐input multiple‐output radar with sparse antenna array | |
| CN104714229A (en) | Microwave gazing correlated imaging treatment method convenient in extracting of object contour | |
| Ding et al. | Discrimination and identification between mainlobe repeater jamming and target echo via sparse recovery |
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 | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20150805 Termination date: 20200508 |