CN108415014A - A kind of hologram radar imaging method and system based on compressed sensing - Google Patents
A kind of hologram radar imaging method and system based on compressed sensing Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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Abstract
The present invention provides a kind of hologram radar imaging method and system based on compressed sensing, including：To the echo-signal quadrature squeezing sampling that each antenna of aerial array receives, quadrature squeezing sample sequence is obtained, and to aerial array LS-SVM sparseness；By the quadrature squeezing sample sequence of the antenna of each rarefaction of aerial array, establishes quadrature squeezing sensor model and solved using synchronous orthogonal matching pursuit algorithm, recover I, Q orthogonal signalling；On the basis of I, Q orthogonal signalling recovered, establishes the echo compressed sensing model of sparse antenna and solve, recover the echo-signal of each antenna；Inverting is carried out to target image by the echo-signal recovered, establishes target imaging figure.The present invention has carried out rarefaction to echo data and array antenna, hence it is evident that reduces the data volume of acquisition and storage；The phase term information for remaining signal, is applicable not only to stepped frequency radar system, is equally applicable to multi-band signal system；Fast convergence rate, operational efficiency are high.
Description
Technical field
The present invention relates to electronics industry Radar Technology fields, and in particular, to a kind of hologram radar based on compressed sensing
Imaging method and system.
Background technology
Hologram radar obtains the electromagnetic information of target with the technical principle of " focusing photograph ", can penetrate cloud layer, ice and snow,
The media on target such as vegetation or even brick wall, sandy soil, concrete walls, various foams are imaged.Suitable for being hidden in shallow-layer
The high resolution 2 d planar imaging of target detects.Hologram radar is a kind of novel and advanced radar, is tracking and monitoring energy
There is revolutionary advantage in power.But the high-resolution memory space aggravation required so that radar return data occupy, and
Modulus (A/D) converter must have high sampling rate in digital sample.
Compressed sensing (CS) theory proposed in recent years brings new concept in low speed data acquisition.CS theories utilize
The sparsity of signal by recovery algorithms can restore signal completely with signal is acquired far below Nyquist sampling rates,
Ensure that signal is not suffered a loss simultaneously.Sampling rate depends no longer on the bandwidth of signal, the spatial structural form of direct sampled signal,
To realize the compression sampling of low rate.The echo-signal of radar can be expressed as：
Radar return to be spatially sparse condition be：The size of target is much smaller than radar coverage and number of targets
Amount is limited.At this point, compressed sensing imaging algorithm directly can build sparse basis using the transmitting signal of radar.To radar
Echo-signal analysis it is found that the echo Range Profile signal obtained only include the scattering amplitude information of target, and not comprising thunder
Up to signal in communication process obtained phase information.Hologram radar imaging can not thus be directly applied to.
In the imaging of array hologram radar, due to using array antenna so that array hologram radar imaging system has very
Big scale and huge echo data amount.It, can be to antenna array in order to reduce the scale of system and the complexity of signal processing
Row carry out LS-SVM sparseness.Recovery to the array hologram radar echo signal data of rarefaction is the key problem of CS theories.
Signal reconstruction essence is to solve for the optimization problem of sparse constraint.The sparse constraint of signal can pass through minimum l0Norm is realized.
For direct solution l0The optimization problem of norm is a np problem, it is difficult to solve the combination of its all signal, or even can not test
Demonstrate,prove the reliability of solution.
Invention content
For the defects in the prior art, the hologram radar imaging based on compressed sensing that the object of the present invention is to provide a kind of
Method and system.
According to a kind of hologram radar imaging method based on compressed sensing provided by the invention, including：
Step 1：To the echo-signal quadrature squeezing sampling that each antenna of aerial array receives, obtains quadrature squeezing and sample sequence
Row, and to aerial array LS-SVM sparseness；
Step 2：By the quadrature squeezing sample sequence of the antenna of each rarefaction of aerial array, quadrature squeezing perception mould is established
Type is simultaneously solved using synchronous orthogonal matching pursuit algorithm, and I, Q orthogonal signalling are recovered；
Step 3：On the basis of I, Q orthogonal signalling recovered, the echo compressed sensing model of sparse antenna is established simultaneously
It solves, recovers the echo-signal of each antenna；
Step 4：Inverting is carried out to target image by the echo-signal recovered, establishes target imaging figure.
Preferably, the echo compressed sensing mould of sparse antenna is solved using orthogonal matching pursuit algorithm in the step 3
Type.
Preferably, the step 2 specifically includes：
Step 201：To echo-signal carry out quadrature squeezing sampling, intermediate-freuqncy signal r (t) first with mixed modulated sequence pi
(t) it is mixed, then by carrying out low speed sampling after bandpass filter, finally obtains quadrature squeezing by orthogonal bandpass sampling
I, Q component；
Step 202：IMV model conversations are MMV models by the joint supported collection for solving the intermediate-freuqncy signal r (t) of reconstruct, first
First construction measures vector Q, is then decomposed, acquires new matrix V, then solve equation V=CU again, passes through the iteration to V
Solve supported collection S；
Step 203：After reconstructing supported collection S in matrix V, using synchronous orthogonal matching pursuit algorithm, I, Q are being recovered just
Hand over signal.
Preferably, the step 3 specifically includes：
Step 301：For step frequency signal system, structure sparse basis space；
Step 302：Build echometric measurement matrix；
Step 303：It is carried out through orthogonal matching pursuit algorithm recovering echo-signal by observation.
According to a kind of hologram radar imaging system based on compressed sensing provided by the invention, including：
Rarefaction module：To the echo-signal quadrature squeezing sampling that each antenna of aerial array receives, quadrature squeezing is obtained
Sample sequence, and to aerial array LS-SVM sparseness；
Quadrature squeezing sensor model processing module：Sequence is sampled by the quadrature squeezing of the antenna of each rarefaction of aerial array
Row are established quadrature squeezing sensor model and are solved using synchronous orthogonal matching pursuit algorithm, recover I, Q orthogonal signalling；
Echo compressed sensing model processing modules：On the basis of I, Q orthogonal signalling recovered, sparse antenna is established
Echo compressed sensing model simultaneously solves, and recovers the echo-signal of each antenna；
Inversion imaging module：Inverting is carried out to target image by the echo-signal recovered, establishes target imaging figure.
Preferably, solving sparse day using orthogonal matching pursuit algorithm in the echo compressed sensing model processing modules
The echo compressed sensing model of line.
Preferably, the quadrature squeezing sensor model processing module specifically includes：
To echo-signal carry out quadrature squeezing sampling, intermediate-freuqncy signal r (t) first with mixed modulated sequence pi(t) it is mixed
Frequently, then by carrying out low speed sampling after bandpass filter, quadrature squeezing I, Q component finally are obtained by orthogonal bandpass sampling；
IMV model conversations are MMV models by the joint supported collection for solving the intermediate-freuqncy signal r (t) of reconstruct, and construction first is surveyed
Vector Q is measured, is then decomposed, acquires new matrix V, then solve equation V=CU again, the iterative solution support to V is passed through
Collect S；
After reconstructing supported collection S in matrix V, using synchronous orthogonal matching pursuit algorithm, I, Q orthogonal signalling are recovered.
Preferably, the echo compressed sensing model processing modules specifically include：
For step frequency signal system, structure sparse basis space；
Build echometric measurement matrix；
It is carried out through orthogonal matching pursuit algorithm recovering echo-signal by observation.
Compared with prior art, the present invention has following advantageous effect：
The present invention has carried out rarefaction to echo data and array antenna, hence it is evident that reduces the data of acquisition and storage
Amount；Quadrature squeezing cognitive method is proposed in the Thinning Process of echo-signal, remains the phase term information of signal, and is not only fitted
For stepped frequency radar system, it is equally applicable to multi-band signal system；Orthogonal matching is used in the recovery of array antenna
Tracing algorithm (OMP) algorithm carries out signal reconstruction, fast convergence rate, operational efficiency height.
Description of the drawings
Upon reading the detailed description of non-limiting embodiments with reference to the following drawings, other feature of the invention,
Objects and advantages will become more apparent upon：
Fig. 1 is the flow chart of the present invention；
Fig. 2 is inventive antenna array rarefaction schematic diagram；
Fig. 3 is that the sampling of echo-signal quadrature squeezing restores block diagram；
Fig. 4 is that echo-signal quadrature squeezing samples recovery process figure；
Fig. 5 is CTF module frame charts；
Fig. 6 is that sparse antenna array handles block diagram.
Specific implementation mode
With reference to specific embodiment, the present invention is described in detail.Following embodiment will be helpful to the technology of this field
Personnel further understand the present invention, but the invention is not limited in any way.It should be pointed out that the ordinary skill of this field
For personnel, without departing from the inventive concept of the premise, several changes and improvements can also be made.These belong to the present invention
Protection domain.
A kind of hologram radar imaging method based on compressed sensing provided by the invention, including：
Step 1：To the echo-signal quadrature squeezing sampling that each antenna of aerial array receives, obtains quadrature squeezing and sample sequence
Row, and to aerial array LS-SVM sparseness；
Step 2：By the quadrature squeezing sample sequence of the antenna of each rarefaction of aerial array, quadrature squeezing perception mould is established
Type is simultaneously solved using synchronous orthogonal matching pursuit algorithm, and I, Q orthogonal signalling are recovered；
Step 3：On the basis of I, Q orthogonal signalling recovered, the echo compressed sensing model of sparse antenna is established simultaneously
It is solved using orthogonal matching pursuit algorithm, recovers the echo-signal of each antenna；
Step 4：Inverting is carried out to target image by the echo-signal recovered, establishes target imaging figure.
Step 2 specifically includes：
Step 201：To echo-signal carry out quadrature squeezing sampling, intermediate-freuqncy signal r (t) first with mixed modulated sequence pi
(t) it is mixed, then by carrying out low speed sampling after bandpass filter, finally obtains quadrature squeezing by orthogonal bandpass sampling
I, Q component；
Step 202：IMV model conversations are MMV models by the joint supported collection for solving the intermediate-freuqncy signal r (t) of reconstruct, first
First construction measures vector Q, is then decomposed, acquires new matrix V, then solve equation V=CU again, passes through the iteration to V
Solve supported collection S；
Step 203：After reconstructing supported collection S in matrix V, using synchronous orthogonal matching pursuit algorithm, I, Q are being recovered just
Hand over signal.
Step 3 specifically includes：
Step 301：For step frequency signal system, structure sparse basis space；
Step 302：Build echometric measurement matrix；
Step 303：It is carried out through orthogonal matching pursuit algorithm recovering echo-signal by observation.
On the basis of above-mentioned hologram radar imaging method based on compressed sensing, the present invention also provides one kind based on compression
The hologram radar imaging system of perception, including：
Rarefaction module：To the echo-signal quadrature squeezing sampling that each antenna of aerial array receives, quadrature squeezing is obtained
Sample sequence, and to aerial array LS-SVM sparseness；
Quadrature squeezing sensor model processing module：Sequence is sampled by the quadrature squeezing of the antenna of each rarefaction of aerial array
Row are established quadrature squeezing sensor model and are solved using synchronous orthogonal matching pursuit algorithm, recover I, Q orthogonal signalling；
Echo compressed sensing model processing modules：On the basis of I, Q orthogonal signalling recovered, sparse antenna is established
Echo compressed sensing model is simultaneously solved using orthogonal matching pursuit algorithm, and the echo-signal of each antenna is recovered；
Inversion imaging module：Inverting is carried out to target image by the echo-signal recovered, establishes target imaging figure.
Quadrature squeezing sensor model processing module specifically includes：
To echo-signal carry out quadrature squeezing sampling, intermediate-freuqncy signal r (t) first with mixed modulated sequence pi(t) it is mixed
Frequently, then by carrying out low speed sampling after bandpass filter, quadrature squeezing I, Q component finally are obtained by orthogonal bandpass sampling；
IMV model conversations are MMV models by the joint supported collection for solving the intermediate-freuqncy signal r (t) of reconstruct, and construction first is surveyed
Vector Q is measured, is then decomposed, acquires new matrix V, then solve equation V=CU again, the iterative solution support to V is passed through
Collect S；
After reconstructing supported collection S in matrix V, using synchronous orthogonal matching pursuit algorithm, I, Q orthogonal signalling are recovered.
Echo compressed sensing model processing modules specifically include：
For step frequency signal system, structure sparse basis space；
Build echometric measurement matrix；
It is carried out through orthogonal matching pursuit algorithm recovering echo-signal by observation.
The thought of compressive sensing theory is, can be with being far below for can be with the original signal of rarefaction representation in a certain domain
The sampling rate of Nyquist sample frequencys samples signal, after data are restored, undistorted can reconstruct original
Beginning signal.Compressive sensing theory breaches the limit of Shannon's theorems, is overturned to traditional theory, including three main aspects：
Rarefaction representation, the irrelevant measurement of signal and the restructing algorithm of signal of signal.Wherein, the restructing algorithm of signal is compression sense
The core known.
If vector x=[x1,x2,…,xN]T, matrix A=[a1,a2,…,aN] it is a transformation base, signal x is on transformation base A
Be expressed as：
Wherein s=[s1,s2,…,sN]TFor the weight coefficient vector of N × 1.If the nonzero element number in s is to have
Limit, for example be K, or only K element is larger (K ＜ ＜ N), then vector x is referred to as sparse.
The irrelevant measurement of signal
The linear measurement of sparse signal x can be expressed as：
Y=Φ x (2)
WhereinFor calculation matrix.
Formula (1) is substituted into formula (2) to obtain
Y=Φ x=Φ As (3)
Formula (3) can be abbreviated as
Y=Ψ s (4)
Wherein Ψ=Φ A are known as perceiving matrix or restore matrix.
In above-mentioned conversion process, only meet limited isometry criterion (RIP), is possible to through restructing algorithm from sight
It surveys in signal y and recovers original signal x.RIP criterion are：
If there are constant δK∈ [0,1), to arbitrary s, formula (5) is set up,
Perception matrix or recovery matrix Ψ is claimed to meet RIP criterion, δKFor the RIP constants of Ψ.
Signal reconstruction algorithm
Signal reconstruction refers to the process of recovering original signal by the observation signal of compression sampling.Signal reconstruction algorithm is compression
Most important content in three cores of perception theory, directly affects the signal quality of reconstruct and the complexity of reconstruct.Signal
The premise of reconstruct is the sparse attribute of signal or compressible property, and essence is to solve for the optimization problem of sparse constraint.Letter
Number sparse constraint can pass through minimum l0Norm is realized.For direct solution l0The optimization problem of norm is a np problem, difficult
To solve the combination of its all signal, or even the reliability of solution can not be verified.Therefore l is used1Norm come replace solve l0Norm.
The algorithm of generally use has：Base track algorithm (BP), matching pursuit algorithm (MP), smooth l0Norm Method (Smoothed l0,
SL0) etc., matching pursuit algorithm is mainly introduced below.
Matching pursuit algorithm is a kind of greedy algorithm, and by constantly improving, improved matching pursuit algorithm mainly has OMP
Algorithm, Stagewise OMP (St OMP) algorithm, Regularized OMP (ROMP) algorithms and Compressive
Sampling Matching Pursuit (Co Sa MP) algorithm etc..By taking OMP algorithms as an example, the thought of matching pursuit algorithm is,
By constantly looking for the component of the correlation maximum between residual vector and calculation matrix, when meeting the condition of convergence, so that it may with
Obtain the sparse decomposition result of signal.It is sparse that orthogonal matching pursuit thought is substantially also to solve for K.It is simple in order to solve, it is first false
If K=1, unique nonzero element y is solvedqCorresponding position q and the row at place in y.Then pass through iteration, find out other K
Value.Match tracing is to find out these column vectors by the thought of " greediness ".Residual error is being selected in each step iterative process always just
It hands over, this row is then subtracted from residual error, into iterative process next time, until meeting iteration exit criteria.
After M target reflects or scatters, the echo signal of intermediate frequency received can be expressed as radar transmitting wave
Wherein, a (t) and φ (t) is the envelope and phase for emitting signal, and baseband signal can be expressed as
s0(t)=a (t) ejφ(t) (7)
The complex envelope for receiving signal can be expressed as
Therefore, receiving I, the Q component of signal r (t) can be expressed as
I, Q component can completely express complex envelope s (t).Therefore, quadrature squeezing sensory perceptual system is the intermediate frequency from reception
Echo-signal r (t) obtains I, Q component.Hologram radar Irnaging procedures based on compressed sensing are as shown in Figure 1, Fig. 2 is holographic thunder
Reach image antenna thinned array schematic diagram.Echo-signal quadrature squeezing samples recovery process as shown in figure 3, being as follows：
Step 1：
Low rate samples.Low rate sampling is similar to modulation wide-band transducer, as shown in Figure 4.Receiving intermediate frequency signal r (t)
First with mixed modulated sequence pi(t) it is mixed, pi(t) it can be expressed as
Wherein, pi(t) it is periodic signal, for example p can be expressed asi(t+nTp)=pi(t),n∈Z。
Mixing frequencies are fp=1/Tp, Fp=[- fp/2,+fp/ 2] and sample frequency is fs=1/Ts, Fs=[- fs/2,+fs/
2].Mixer output signal is expressed asFourier transformation isMixer output signalIn frequency domain
On be with fpFor the linear combination of multiple band signals of frequency displacement unit.Assuming that the frequency response of filter h (t) is ideal square
Shape window, the output sequence y that then uniform sampling obtainsi[n] contains only the frequency spectrum in frequency domain.
Ith sample sequences yiThe discrete time Fourier transform of [n] can be expressed as
The form for being write as matrix is
Y (f)=Cz (f) (13)
Wherein, y (f) is the matrix of m × 1, and i-th of representation in components isThe element of the Matrix C of M × L
It is coefficient cil.Z (f) is the matrix of L × 1, is expressed as z (f)=[z1(f),…,zL(f)]T.And zi(f)=X (f+ (i-L0-1)
fp), 1≤i≤L, wherein L=2L0+1。
After simulation low-pass filter H (f), output signal can be expressed as
Compress complex envelope scs(t) it can be expressed as
And I, Q component can be expressed as
Ics(t)=Re { scs(t)} (16)
Qcs(t)=Im { scs(t)} (17)
After being sampled by ADC, sample frequency is set as
Wherein, l be l >=| fL/2Bcs| positive integer.After intermediate frequency over-sampling, the output of signal can be expressed as
Then, the frequency spectrum of signal is moved to base band, is with fpFor the linear combination of multiple band signals of frequency displacement unit.
Assuming that Y (f)=[Y1(f),Y2(f),…,Ym(f)], wherein Yi(f) be i-th of channel sample sequence frequency spectrum.Z
(f)=[Z1(f),Z2(f),…,ZL(f)], wherein Zi(f)=X (f+ (i-L0-1)fp)
It is hereby achieved that quadrature squeezing sensor model is
Y (f)=AZ (f) (20)
Then it can show that the compressed sensing model in time domain is
y[n]m×d=Cm×LZ[n]L×d (21)
Matrix form is
Y [n]=AZ [n] (22)
Step 2
Solve the joint supported collection of reconstruction signal r (t).As shown in figure 5, being MMV models, first structure by IMV model conversations
It makes and measures vector Q, then decomposed, acquire new matrix V, then solve equation V=CU again, you can by changing to V
In generation, solves supported collection S.
Step 3
After reconstructing supported collection S in finite dimensioned V, you can quadrature signal is restored.
Synchronous orthogonal matching pursuit algorithm：
1. initializing：Surplus r=V, iterations t=1；
2. the inner product for calculating surplus r and observing matrix finds the maximum row of inner product：
3. updating supported collection Λt=Λt-1∪{λt, observing matrix
4. updating surplusT=t+1, whereinFor AtPseudo inverse matrix
5. calculating
6. if t ＞ N, iteration terminate；Otherwise enter 1..
Step 4
The echo-signal and local oscillation signal received carries out down coversion, does not consider that envelope is delayed, zero intermediate frequency signals are
The K of exponential part is converted, is obtained
Into two-dimensional fourier transform is crossed, ignore constant term,
E (X, Y)=IFT2{FT2[A(x,y)exp(-jRKz)]} (25)
Fourier inverse transformations are made to formula (25), can be obtained：
A (x, y)=IFT2{FT2[E(X,Y)]exp(jRKz)} (26)
As array hologram radar imaging formula.
For step frequency, sparse basis space can be expressed as
Wherein, fmIndicate the frequency of signal, tnIndicate the orientation sampling time.Echo-signal is dilute at evacuated space Ψ
It dredges and is expressed as
S=Ψα (28)
Wherein, α indicates sparse sparse vectors of the array echo signal s at the Ψ of sparse basis space, in α, only K (K≤
N) a nonzero value.Therefore when N-dimensional echo-signal s by calculation matrix carry out dimensionality reduction observation after, can obtain M tie up observation signal,
Wherein M<N can be expressed as
yM×1=ΦM×NsN×1=ΦM×NΨN×NαN×1 (29)
It is as shown in Figure 6 that thinned array handles block diagram.
Recovery original echoed signals data are carried out through OMP algorithms by observation y, the specific steps are：
1. initializing：Surplus r=V, iterations t=1；
2. the inner product for calculating surplus r and observing matrix finds the maximum row of inner product：
λt=max | ＜ AH t,yt＞ |
3. updating surplusT=t+1, whereinFor AtPseudo inverse matrix
4. calculating
5. if t ＞ N, iteration terminate；Otherwise enter 1..；
Following optimization problem is solved, the transform domain of original signal x is obtained
Wherein, s is the measured value of original signal x, and Φ, Ψ indicate calculation matrix and transformation matrix respectively.Acquire transform domain
Later, by inverse transformation, you can reconstruct original signal x.
After compressed sensing recovery thinned array, you can three-dimensional to be carried out to target according to traditional Wavenumber Domain Algorithms
Imaging.
One skilled in the art will appreciate that in addition to realizing system provided by the invention in a manner of pure computer readable program code
It, completely can be by the way that method and step be carried out programming in logic come so that the present invention provides and its other than each device, module, unit
System and its each device, module, unit with logic gate, switch, application-specific integrated circuit, programmable logic controller (PLC) and embedding
Enter the form of the controller that declines etc. to realize identical function.So system provided by the invention and its every device, module, list
Member is considered a kind of hardware component, and also may be used for realizing the device of various functions, module, unit to include in it
To be considered as the structure in hardware component；It can also will be considered as realizing the device of various functions, module, unit either real
The software module of existing method can be the structure in hardware component again.
In the description of the present application, it is to be understood that term "upper", "front", "rear", "left", "right", " is erected at "lower"
Directly ", the orientation or positional relationship of the instructions such as "horizontal", "top", "bottom", "inner", "outside" is orientation based on ... shown in the drawings or position
Relationship is set, description the application is merely for convenience of and simplifies to describe, do not indicate or imply the indicated device or element is necessary
With specific orientation, with specific azimuth configuration and operation, therefore should not be understood as the limitation to the application.
Specific embodiments of the present invention are described above.It is to be appreciated that the invention is not limited in above-mentioned
Particular implementation, those skilled in the art can make a variety of changes or change within the scope of the claims, this not shadow
Ring the substantive content of the present invention.In the absence of conflict, the feature in embodiments herein and embodiment can arbitrary phase
Mutually combination.
Claims (8)
1. a kind of hologram radar imaging method based on compressed sensing, which is characterized in that including：
Step 1：To the echo-signal quadrature squeezing sampling that each antenna of aerial array receives, quadrature squeezing sample sequence is obtained,
And to aerial array LS-SVM sparseness；
Step 2：By the quadrature squeezing sample sequence of the antenna of each rarefaction of aerial array, quadrature squeezing sensor model is established simultaneously
It is solved using synchronous orthogonal matching pursuit algorithm, recovers I, Q orthogonal signalling；
Step 3：On the basis of I, Q orthogonal signalling recovered, establishes the echo compressed sensing model of sparse antenna and solves,
Recover the echo-signal of each antenna；
Step 4：Inverting is carried out to target image by the echo-signal recovered, establishes target imaging figure.
2. the hologram radar imaging method according to claim 1 based on compressed sensing, which is characterized in that in the step
The echo compressed sensing model of sparse antenna is solved in 3 using orthogonal matching pursuit algorithm.
3. the hologram radar imaging method according to claim 1 based on compressed sensing, which is characterized in that the step 2
It specifically includes：
Step 201：To echo-signal carry out quadrature squeezing sampling, intermediate-freuqncy signal r (t) first with mixed modulated sequence pi(t) it carries out
Mixing finally obtains I, Q points of quadrature squeezing then by carrying out low speed sampling after bandpass filter by orthogonal bandpass sampling
Amount；
Step 202：IMV model conversations are MMV models, first structure by the joint supported collection for solving the intermediate-freuqncy signal r (t) of reconstruct
It makes and measures vector Q, then decomposed, acquire new matrix V, then solve equation V=CU again, pass through the iterative solution to V
Supported collection S；
Step 203：After reconstructing supported collection S in matrix V, using synchronous orthogonal matching pursuit algorithm, the orthogonal letter of I, Q is recovered
Number.
4. the hologram radar imaging method according to claim 1 based on compressed sensing, which is characterized in that the step 3
It specifically includes：
Step 301：For step frequency signal system, structure sparse basis space；
Step 302：Build echometric measurement matrix；
Step 303：It is carried out through orthogonal matching pursuit algorithm recovering echo-signal by observation.
5. a kind of hologram radar imaging system based on compressed sensing, which is characterized in that including：
Rarefaction module：To the echo-signal quadrature squeezing sampling that each antenna of aerial array receives, quadrature squeezing sampling is obtained
Sequence, and to aerial array LS-SVM sparseness；
Quadrature squeezing sensor model processing module：By the quadrature squeezing sample sequence of the antenna of each rarefaction of aerial array, build
It attentions and hands over compressed sensing model and solved using synchronous orthogonal matching pursuit algorithm, recover I, Q orthogonal signalling；
Echo compressed sensing model processing modules：On the basis of I, Q orthogonal signalling recovered, the echo of sparse antenna is established
Compressed sensing model simultaneously solves, and recovers the echo-signal of each antenna；
Inversion imaging module：Inverting is carried out to target image by the echo-signal recovered, establishes target imaging figure.
6. the hologram radar imaging system according to claim 5 based on compressed sensing, which is characterized in that in the echo
The echo compressed sensing model of sparse antenna is solved in compressed sensing model processing modules using orthogonal matching pursuit algorithm.
7. the hologram radar imaging system according to claim 5 based on compressed sensing, which is characterized in that the orthogonal pressure
Contracting sensor model processing module specifically includes：
To echo-signal carry out quadrature squeezing sampling, intermediate-freuqncy signal r (t) first with mixed modulated sequence pi(t) it is mixed, so
Afterwards by carrying out low speed sampling after bandpass filter, finally quadrature squeezing I, Q component are obtained by orthogonal bandpass sampling；
Solve reconstruct intermediate-freuqncy signal r (t) joint supported collection, by IMV model conversations be MMV models, first construction measure to
Q is measured, is then decomposed, acquires new matrix V, then solve equation V=CU again, pass through the iterative solution supported collection S to V；
After reconstructing supported collection S in matrix V, using synchronous orthogonal matching pursuit algorithm, I, Q orthogonal signalling are recovered.
8. the hologram radar imaging system according to claim 5 based on compressed sensing, which is characterized in that the echo pressure
Contracting sensor model processing module specifically includes：
For step frequency signal system, structure sparse basis space；
Build echometric measurement matrix；
It is carried out through orthogonal matching pursuit algorithm recovering echo-signal by observation.
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