CN106443594A - Radar antenna array steady beam forming method based on sparse constraint - Google Patents

Radar antenna array steady beam forming method based on sparse constraint Download PDF

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Publication number
CN106443594A
CN106443594A CN201610782011.9A CN201610782011A CN106443594A CN 106443594 A CN106443594 A CN 106443594A CN 201610782011 A CN201610782011 A CN 201610782011A CN 106443594 A CN106443594 A CN 106443594A
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radar antenna
antenna array
signal
vector
covariance matrix
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冯大政
杨凡
崔思玉
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Xidian University
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Xidian University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/285—Receivers
    • G01S7/34—Gain of receiver varied automatically during pulse-recurrence period, e.g. anti-clutter gain control
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/2813—Means providing a modification of the radiation pattern for cancelling noise, clutter or interfering signals, e.g. side lobe suppression, side lobe blanking, null-steering arrays
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/35—Details of non-pulse systems
    • G01S7/352—Receivers

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

The invention belongs to the field of radar array signal processing and discloses a radar antenna array steady beam forming method based on sparse constraint. The method includes the steps that L receiving signals of a radar antenna array are acquired, and a covariance matrix estimated value (please see the formula in the specification) of the receiving signals is obtained through calculation according to the L receiving signals; an assumed target signal guide vector is s, and a target signal guide vector estimated value (please see the formula in the specification) is obtained according to the covariance matrix estimated value (please see the formula in the specification) of the receiving signals and the assumed target signal guide vector s; a complete interference and signal subspace is determined according to the covariance matrix estimated value (please see the formula in the specification) of the receiving signals and the target signal guide vector estimated value (please see the formula in the specification); an optimal adaptive beam forming weight vector of a radar antenna array output end is established according to the complete interference and signal subspace.

Description

A kind of radar antenna array robust ada- ptive beamformer method based on sparse constraint
Technical field
The invention belongs to array radar signal process field, more particularly, to a kind of radar antenna array based on sparse constraint Robust ada- ptive beamformer method.
Background technology
In array radar signal is processed, beam-forming technology is mainly used in radar, voice array signal, radio communication In field.Wave beam forming to the effect that keep desired signal directive gain constant while can Adaptive Suppression other The strong jamming in direction.Traditional Beamforming Method needs to set up in desired signal steering vector it is known that and receipt signal association On the basis of variance matrix is estimated accurately, but in practice it is desirable to signal guide vector mismatches, comprise in receipt signal to expect Signal is inaccurate compared with strong and receipt signal covariance matrix etc., all can lead to Wave beam forming hydraulic performance decline.Therefore, for Robust ada- ptive beamformer method under desired signal steering vector mismatch case becomes study hotspot.
At present more effective robust ada- ptive beamformer method is mainly diagonal loading technique, and it is to expectation steering vector not Join, sample size is respectively provided with preferable effect situations such as few, but when comprising desired signal in receipt signal, can lead under performance Fall.
Content of the invention
For the shortcoming of above-mentioned prior art, it is an object of the invention to provide a kind of radar antenna based on sparse constraint Array robust ada- ptive beamformer method is it is not necessary to known disturbances number, and computation complexity is low.
For reaching above-mentioned purpose, embodiments of the invention adopt the following technical scheme that and are achieved.
A kind of radar antenna array robust ada- ptive beamformer method based on sparse constraint, methods described comprises the steps：
Step 1, obtains L receipt signal of radar antenna array, is calculated reception letter according to described L receipt signal Number covariance matrix value
Step 2 it is assumed that echo signal steering vector be s, according to the covariance matrix value of described receipt signal And the echo signal steering vector s of described hypothesis, obtain echo signal steering vector estimated value
Step 3, according to the covariance matrix value of described receipt signalAnd described echo signal steering vector estimates EvaluationDetermine complete interference plus signal subspace；
Step 4, adaptive according to the optimum that described complete interference plus signal subspace constructs radar antenna array outfan Answer Wave beam forming weight vector.
The feature of technical solution of the present invention and being further improved to：
(1) step 1 is specially：Obtain receipt signal x (k) in radar antenna array kth moment, k=1,2 ... L, thus obtaining To L receipt signal of radar antenna array, and then obtain the covariance matrix value of receipt signal
Wherein, X=[x1..., xi... xL] it is radar antenna array receipt signal matrix, xiFor radar antenna array i-th Receipt signal x (i) in moment, 1≤i≤L, L represent that radar antenna array receives the number of sample, and symbol H represents conjugate transpose.
(2) step 2 is specially：
(2a) the echo signal steering vector assumed is s, according to the covariance matrix value of described receipt signalReally Fixed following cost function：
s.t.sHE=0, (s+e)HRI(s+e)≤sHRIs
Wherein, RIFor interference covariance matrix, e represents error vector, and symbol H represents conjugate transpose, above-mentioned cost function Solve in meet the constraint condition sHE=0, (s+e)HRI(s+e)≤sHRIS, and the output of echo signal Minimum error vector e when maximummin；
(2b) thus echo signal steering vector estimated value
(3) complete in step 3 interference plus signal subspace is empty according to interference plus signal being decomposed based on EVD Between, then step 3 specifically includes following sub-step：
(3a1) the covariance matrix value to described receipt signalCarry out Eigenvalues Decomposition, obtain Wherein Λ=diag (σ1, σ2..., σN) it is diagonal matrix, σ1, σ2..., σNFor corresponding eigenvalue；U is unit unitary matrice, and Its column vector is the covariance matrix value of receipt signalCharacteristic vector, relative with the eigenvalue in diagonal matrix Λ Should, symbol H represents conjugate transpose, and N is the array number of radar antenna array；
(3b1) according to unit unitary matrice U, construction interference plus signal subspace E: E=U (：, 1: K)
Wherein, K is interference number estimated value, and K >=P, the number that P disturbs for far field arrowband, P ＜ N, U (：, 1: K) represent All row of the 1st to K row in unit unitary matrice；
(3c1) and then determine complete interference plus signal subspace
Wherein, s is the echo signal steering vector assumed,For echo signal steering vector estimated value.
(4) complete in step 3 interference plus signal subspace is empty according to interference plus signal estimated based on DOA Between, then step 3 specifically includes following sub-step：
(3a2) determine the estimated value of receipt signal source azimuth angleWherein, P disturbs for far field arrowband Number,Represent the azimuth estimated value of j-th far field arrowband interference, j=1 ..., p；
(3b2) estimated values theta according to described receipt signal source azimuth angle, obtains disturbing array manifold matrix RepresentThe array steering vector of angle；
(3c2) and then determine complete interference plus signal subspace
Wherein, s is the echo signal steering vector assumed.
(5) complete in step 3 interference plus signal subspace is according to interference plus signal based on Krylov space Space, then step 3 specifically include following sub-step：
(3a3) the covariance matrix value being s and receipt signal according to the echo signal steering vector assumedDetermine Krylov space
(3b3) due to Krylov spaceIn each column vector be linear independence, therefore Krylov spaceMeet：
(3c3) and then determine complete interference plus signal subspace
Wherein, D represents the exponent number in Krylov space, and D≤P+1, the number that P disturbs for far field arrowband, and P ＜ N, N are thunder Reach the array number of aerial array.
(6) step 4 specifically includes following sub-step：
(4a) because the Adaptive beamformer weight vector of radar antenna array outfan is located at complete interference plus signal Subspace, using described complete interference plus signal subspaceThe Adaptive beamformer of construction radar antenna array outfan Weight vectorWherein, β is combined vectors；
(4b) according to the undistorted preparation of minimum variance, according to the covariance matrix value of described receipt signalAnd institute State echo signal steering vector estimated valueObtain following optimizing expression：
(4c) sparse constraint is carried out to described combined vectors β, obtain improved optimizing expression：
Wherein,Represent the l of combined vectors β1Norm, regularization parameter λ isWeights, λ is bigger, sparse to β Property require stronger, symbol H represents conjugate transpose；
(4d) solve above-mentioned improved optimizing expression, obtain the optimum adaptive beam shape of radar antenna array outfan Become weight vector.
(7) described combined vectorsWherein, UIIt is by interference covariance matrix RINon-zero special The matrix of N × P dimension of value indicative corresponding characteristic vector composition, ΛIFor the diagonal matrix of P × P dimension, s is the hypothesis of N × 1 dimension Echo signal steering vector, I is unit matrix, and symbol H represents transposition, and subscript -1 represents inversion operation.
The present invention is analyzed by constituting to optimum Adaptive beamformer weight vector, finds optimum adaptive beam Form weight vector to be only located in interference plus signal subspace (interference plus signal subspace, IPSS).By In general radar system degree of freedom in system will much larger than need suppression interference source number, therefore only require echo signal is led Disturb plus signal subspace to vector, then solve combined vectors and can be obtained by radar antenna array outfan Excellent self adaptation weight vector, and have relatively low computation complexity.With respect to traditional reduced-rank STAP, the present invention does not need known dry The number disturbed, and the present invention is sane under multiple common goal orientation vector mismatch cases.
Brief description
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing Have technology description in required use accompanying drawing be briefly described it should be apparent that, drawings in the following description be only this Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, acceptable Other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 is a kind of radar antenna array robust ada- ptive beamformer method based on sparse constraint provided in an embodiment of the present invention Schematic flow sheet；
Fig. 2 is SINR provided in an embodiment of the present invention with regularization parameter change curve schematic diagram；
Fig. 3 is SINR provided in an embodiment of the present invention with complete space dimension variation curve synoptic diagram；
Fig. 4 is output SINR provided in an embodiment of the present invention with input SNR change curve schematic diagram (ideal situation)；
Fig. 5 is SINR provided in an embodiment of the present invention with sample changed curve synoptic diagram (ideal situation)；
Fig. 6 is output SINR provided in an embodiment of the present invention with input SNR change curve schematic diagram (deviation of directivity)；
Fig. 7 is output SINR provided in an embodiment of the present invention with sample changed curve synoptic diagram (deviation of directivity).
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete Site preparation description is it is clear that described embodiment is only a part of embodiment of the present invention, rather than whole embodiments.It is based on Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of not making creative work Embodiment, broadly falls into the scope of protection of the invention.
Before carrying out the detailed description of technical solution of the present invention, first supplement following theory analysis：
Assume a N unit even linear array, there is the interference of P far field arrowband, the receipt signal that can obtain the k moment is x (k), According to the undistorted criterion of minimum variance, and pass through matrix inversion operation, the optimum of radar antenna array outfan can be obtained certainly Adaptation power is fully located in interference plus signal subspace.
Specifically：
A () assumes a N unit even linear array, there is the interference of P far field arrowband, then receipt signal can be expressed as：
Wherein x (k) is the receipt signal in k moment；asK () represents the multiple amplitude in the k moment for the echo signal, aiK () represents the The i complex magnitude disturbing in the k moment, i=1,2 ... P, as(k) and aiK () is orthogonal；S (θ) is the array guiding arrow of θ angle Amount；θsFor the azimuth of target, θiFor disturber's parallactic angle；N (k) represents the reception noise in k moment, and L represents reception number of samples；A =[s (θs), s (θ1) ... s (θP)] add interference array manifold matrix for signal；Y (k)=[as(k), a1(k) ..., aP(k)]TFor Amplitude response vector.
B () assumes that echo signal steering vector is s, according to the undistorted criterion of minimum variance, the then optimum of array output end Adaptive beamformer weight vector can be expressed as：
Wherein,
RI+NInterference plus noise covariance matrix for N × N.
(c) general interference plus noise covariance matrix RI+NIt is made up of two parts, that is,
RI+N=RI+RN(4)
Wherein RIFor interference covariance matrix, RNFor noise covariance matrix.Without loss of generality, RN=σnI, I are unit square Battle array, and assume σn=1.Under normal circumstances, interference number is less than element number of array, i.e. rank (RI)=P ＜ N, wherein, rank (RI) For RIOrder.
D () is to interference covariance matrix RICarry out Eigenvalues Decomposition, obtain
Wherein ΛIDiagonal matrix for P × P, its diagonal element is interference covariance matrix RIEigenvalue, UIIt is by doing Disturb covariance matrix RIThe N × P of nonzero eigenvalue corresponding characteristic vector composition matrix, symbol H represents transposition.
E () utilizes matrix inversion lemma, the optimum Adaptive beamformer weight vector that can obtain array output end is permissible It is expressed as：
C is combined vectors：
Wherein RIFor interference covariance matrix, RNFor noise covariance matrix, UIIt is by interference covariance matrix RINon-zero The matrix of the N × P of eigenvalue corresponding characteristic vector composition, ΛIDiagonal matrix for P × P, s is that the echo signal of N × 1 is led To vector, symbol H represents transposition.Above formula shows that the optimum Adaptive beamformer weight vector of array output end is fully located at interference In plus signal subspace.
The embodiment of the present invention provides a kind of radar antenna array robust ada- ptive beamformer method based on sparse constraint, reference picture 1, methods described comprises the steps：
Step 1, obtains L receipt signal of radar antenna array, is calculated reception letter according to described L receipt signal Number covariance matrix value
Step 1 is specially：
Obtain receipt signal x (k) in radar antenna array kth moment, k=1,2 ... L, thus obtain radar antenna array L receipt signal, and then be calculated the covariance matrix value of receipt signal
Wherein, X=[x1..., xi... xL] it is radar antenna array receipt signal matrix, xiFor radar antenna array i-th Receipt signal x (i) in moment, 1≤i≤L, L represent that radar antenna array receives the number of sample, and symbol H represents conjugate transpose.
Step 2 it is assumed that echo signal steering vector be s, according to the covariance matrix value of described receipt signal And the echo signal steering vector s of described hypothesis, obtain echo signal steering vector estimated value
Step 2 is specially：
(2a) the echo signal steering vector assumed is s, according to the covariance matrix value of described receipt signalReally Fixed following cost function：
s.t.sHE=0, (s+e)HRI(s+e)≤sHRIs
Wherein, RIFor interference covariance matrix, e represents error vector, and symbol H represents conjugate transpose, above-mentioned cost function Solve in meet the constraint condition sHE=0, (s+e)HRI(s+e)≤sHRIS, and the output of echo signalMinimum error vector e when maximummin；
Further, the target of cost function is to make signal power export maximum, and equality constraint is in order to ensure error Vector e is orthogonal to the echo signal steering vector s of hypothesis, and inequality constraints condition restrains in order to avoid correct goal orientation vector To on its interference radiating way.
(2b) due to the covariance matrix value of receipt signalFor positive semi-definite, above formula optimization problem existence anduniquess is Excellent solution, thus echo signal steering vector estimated value
Step 3, according to the covariance matrix value of described receipt signalAnd described echo signal steering vector estimates EvaluationDetermine complete interference plus signal subspace.
Specifically, complete in step 3 interference plus signal subspace is according to interference plus signal being decomposed based on EVD Space, then step 3 specifically include following sub-step：
(3a1) the covariance matrix value to described receipt signalCarry out Eigenvalues Decomposition, obtain Wherein Λ=diag (σ1, σ2..., σN) it is diagonal matrix, σ1, σ2..., σNFor corresponding eigenvalue；U is unit unitary matrice, and Its column vector is the covariance matrix value of receipt signalCharacteristic vector, relative with the eigenvalue in diagonal matrix Λ Should, symbol H represents conjugate transpose, and N is the array number of radar antenna array；
(3b1) according to unit unitary matrice U, construction interference plus signal subspace E：
E=U (：, 1：K)
Wherein, K is interference number estimated value, and K >=P, the number that P disturbs for far field arrowband, P ＜ N, U (：, 1：K) represent All row of the 1st to K row in unit unitary matrice；
(3c1) consider to contain target signal elements in interference plus signal subspace E, but echo signal component be weaker, And inaccurate, in order to ensure to disturb the completeness of plus signal subspace E, construct complete interference plus signal subspaceAnd then Determine complete interference plus signal subspace
Wherein, s is the echo signal steering vector assumed,For echo signal steering vector estimated value.
Again specific, interference plus signal subspace complete in step 3 is according to the interference plus signal estimated based on DOA Subspace, then step 3 specifically include following sub-step：
(3a2) estimate to determine estimating of receipt signal source azimuth angle first with ROOT-MUSIC based on the IPSS that DOA estimates EvaluationWherein, the number that P disturbs for far field arrowband,Represent the azimuth of j-th far field arrowband interference Estimated value, j=1 ..., p；
(3b2) estimated values theta according to described receipt signal source azimuth angle, obtains disturbing array manifold matrix RepresentThe array steering vector of angle；
(3c2) and then determine complete interference plus signal subspace
Wherein, s is the echo signal steering vector assumed.
Again specific, interference plus signal subspace complete in step 3 is added according to based on the interference in Krylov space Signal subspace, then step 3 specifically include following sub-step：
(3a3) the covariance matrix value being s and receipt signal according to the echo signal steering vector assumedDetermine Krylov space
(3b3) due to Krylov spaceIn each column vector be linear independence, therefore Krylov spaceMeet：
(3c3) and then determine complete interference plus signal subspace
Wherein, D represents the exponent number in Krylov space, and D≤P+1, the number that P disturbs for far field arrowband, and P ＜ N, N are thunder Reach the array number of aerial array.
Step 4, adaptive according to the optimum that described complete interference plus signal subspace constructs radar antenna array outfan Answer Wave beam forming weight vector.
Step 4 specifically includes following sub-step：
(4a) because the Adaptive beamformer weight vector of radar antenna array outfan is located at complete interference plus signal Subspace, using described complete interference plus signal subspaceThe Adaptive beamformer of construction radar antenna array outfan Weight vectorWherein, β is combined vectors；
(4b) according to the undistorted preparation of minimum variance, according to the covariance matrix value of described receipt signalAnd institute State echo signal steering vector estimated valueObtain following optimizing expression：
(4c) due to complete interference plus signal subspaceIn except interference plus signal space in addition to, also comprise a part and make an uproar Sound, this can lead to solution combined vectors β to be easily affected by noise.Need combined vectors β are entered to solve this problem Described combined vectors β are carried out sparse constraint by row sparse constraint, obtain improved optimizing expression：
Wherein,Represent the l of combined vectors β1Norm, regularization parameter λ isWeights, λ is bigger, sparse to β Property require stronger, symbol H represents conjugate transpose；
(4d) solve above-mentioned improved optimizing expression, obtain the optimum adaptive beam shape of radar antenna array outfan Become weight vector.
Due to l1Norm is convex, therefore the optimal solution of above formula existence anduniquess, can be solved using containing method, obtain The optimum Adaptive beamformer weight vector w of the radar antenna array outfan of combined vectors β and array output endopt.
Described combined vectors
Wherein, UIIt is by interference covariance matrix RINonzero eigenvalue corresponding characteristic vector composition N × P dimension square Battle array, ΛIFor the diagonal matrix of P × P dimension, s is the echo signal steering vector of the hypothesis of N × 1 dimension, and I is unit matrix, symbol H Represent transposition, subscript -1 represents inversion operation.
With reference to emulation experiment, the effect of the present invention is done and verifies further.
Assume an even linear array, element number of array is N=16, array element distance is the half of radar operation wavelength.Real mesh The arrival bearing of mark signal and four interference is respectively 5 ° and -35 °, 20 °, 12 °, 30 °, and the echo signal arrival bearing assuming For 0 °, and the dry ratio of making an uproar of four interference is for 30dB.In order to verify the effectiveness of the inventive method, the inventive method is added with diagonal Load sampling covariance inversion technique (LSMI), eigenspace projection method (Eigenspace based BF), Worst-case are sane Beamforming Method (RBF) is compared.The wherein covariance matrix minimal eigenvalue of the loading capacity number of winning the confidence of LSMI method 10 times, the interference number required for characteristic space method is accurately known, the error bounds required for Worst-case Wave beam forming For 4 (steering vector sHS=N).Output signal-to-noise ratio is defined as：
Wherein, σsFor the power of echo signal,For real echo signal steering vector, w is the battle array of a certain special algorithm The self adaptation power of row outfan.Columns for constructing IPSS is always 10, is decomposed based on EVD, DOA estimates and Krylov space The corresponding regularization parameter of IPSS spatial configuration method be 10,10,1.
Emulation experiment one：The impact of regularization parameter change
This emulation experiment mainly verifies that balance factor (regularization parameter) the λ and interference number K of hypothesis calculates to the present invention The impact of method effect.
Output SINR shown in Fig. 2 is with the change curve of regularization parameter λ, wherein signal to noise ratio snr=0dB, sample number used Mesh is L=50.As seen from the figure, the inventive method parameter lambda is had sane well, λ in a wide range, the present invention The performance of method is all close to optimal solution.Fig. 3 show the change curve with selected interference space dimension K for the inventive method, Wherein SNR=0dB, sample number L=50.When K ＜ 5 algorithm performance degradation, when K >=5, algorithm performance close to optimal value, It can be seen that selected interference space dimension have to be larger than equal to interference number, otherwise algorithm inefficacy, also from the other hand Demonstrate the requirement for IPSS space completeness for the inventive method.
Emulation experiment two：Ideal situation
Fig. 4 show when echo signal steering vector is accurately known, and output Signal to Interference plus Noise Ratio (SINR) is changed with input SNR Curve, wherein number of samples L=50.Even if echo signal steering vector is accurately known as seen from the figure, due to training sample In contain echo signal, traditional LSMI and Worst-case BF leads to hydraulic performance decline due to signal cancellation performance.And this No matter bright method is better than traditional algorithm in high s/n ratio or low signal-to-noise ratio, algorithm performance.Fig. 5 depicts several algorithm performances With sample data change curve, input SNR=0dB, other parameters are consistent with Fig. 4.The inventive method as seen from the figure Suitable with other convergence of algorithm speed.
Emulation experiment three：Direction mismatches
Fig. 6 show when echo signal steering vector has error in pointing, exports SINR with input SNR change curve, It is assumed that target bearing be 5 °, real target bearing be 6 °.In low signal-to-noise ratio, characteristic space method poor-performing, and diagonal Load, Worst-case BF and the inventive method in low signal-to-noise ratio, performance quite, and the inventive method be slightly better than other two Plant algorithm.In high s/n ratio, diagonally load and Worst-case BF method hydraulic performance decline, the inventive method is slightly better than feature Space law.Fig. 7 depicts the normalized output signal-to-noise performance of each algorithm with sample changed curve.
The above, the only specific embodiment of the present invention, but protection scope of the present invention is not limited thereto, and any Those familiar with the art the invention discloses technical scope in, change or replacement can be readily occurred in, all should contain Cover within protection scope of the present invention.Therefore, protection scope of the present invention should be defined by described scope of the claims.

Claims (8)

1. a kind of radar antenna array robust ada- ptive beamformer method based on sparse constraint is it is characterised in that methods described includes Following steps：
Step 1, obtains L receipt signal of radar antenna array, is calculated receipt signal according to described L receipt signal Covariance matrix value
Step 2 it is assumed that echo signal steering vector be s, according to the covariance matrix value of described receipt signalAnd institute State the echo signal steering vector s of hypothesis, obtain echo signal steering vector estimated value
Step 3, according to the covariance matrix value of described receipt signalAnd described echo signal steering vector estimated value Determine complete interference plus signal subspace；
Step 4, constructs the optimum self adaptation ripple of radar antenna array outfan according to described complete interference plus signal subspace Bundle forms weight vector.
2. a kind of radar antenna array robust ada- ptive beamformer method based on sparse constraint according to claim 1, it is special Levy and be, step 1 is specially：
Obtain receipt signal x (k) in radar antenna array kth moment, k=1,2 ... L, thus obtaining L of radar antenna array Receipt signal, and then it is calculated the covariance matrix value of receipt signal
R ^ = 1 L Σ i = 1 L x i x i H = 1 L XX H
Wherein, X=[x1,…,xi,…xL] it is radar antenna array receipt signal matrix, xiFor radar antenna array i-th moment Receipt signal x (i), 1≤i≤L, L represent that radar antenna array receives the number of sample, and symbol H represents conjugate transpose.
3. a kind of radar antenna array robust ada- ptive beamformer method based on sparse constraint according to claim 1, it is special Levy and be, step 2 is specially：
(2a) the echo signal steering vector assumed is s, according to the covariance matrix value of described receipt signalDetermine such as Lower cost function：
m i n e ( s + e ) H R ^ - 1 ( s + e )
s.t.sHE=0, (s+e)HRI(s+e)≤sHRIs
Wherein, RIFor interference covariance matrix, e represents error vector, and symbol H represents conjugate transpose, and subscript -1 represents the behaviour that inverts Make, above-mentioned cost function solves in meet the constraint condition sHE=0, (s+e)HRI(s+e)≤sHRIS, and the output of echo signal PowerMinimum error vector e when maximummin；
(2b) thus echo signal steering vector estimated value
4. a kind of radar antenna array robust ada- ptive beamformer method based on sparse constraint according to claim 1, it is special Levy and be, complete interference plus signal subspace is according to the interference plus signal subspace decomposed based on EVD in step 3, then Step 3 specifically includes following sub-step：
(3a1) the covariance matrix value to described receipt signalCarry out Eigenvalues Decomposition, obtainWherein Λ=diag (σ1,σ2,…,σN) it is diagonal matrix, σ1,σ2,…,σNFor corresponding eigenvalue；U is unit unitary matrice, and its row Vector is the covariance matrix value of receipt signalCharacteristic vector, corresponding with the eigenvalue in diagonal matrix Λ, symbol Number H represents conjugate transpose, and N is the array number of radar antenna array；
(3b1) according to unit unitary matrice U, construction interference plus signal subspace E：
E=U (:,1:K)
Wherein, K is interference number estimated value, and K >=P, the number that P disturbs for far field arrowband, P<N, U (:,1:K) represent unit All row of the 1st to K row in unitary matrice；
(3c1) and then determine complete interference plus signal subspace
E &OverBar; = &lsqb; E , s ^ , s &rsqb;
Wherein, s is the echo signal steering vector assumed,For echo signal steering vector estimated value.
5. a kind of radar antenna array robust ada- ptive beamformer method based on sparse constraint according to claim 1, it is special Levy and be, complete interference plus signal subspace is according to the interference plus signal subspace estimated based on DOA in step 3, then Step 3 specifically includes following sub-step：
(3a2) determine the estimated value of receipt signal source azimuth angleWherein, P for far field arrowband disturb Number,Represent the azimuth estimated value of j-th far field arrowband interference, j=1 ..., p；
(3b2) estimated values theta according to described receipt signal source azimuth angle, obtains disturbing array manifold matrix RepresentThe array steering vector of angle；
(3c2) and then determine complete interference plus signal subspace
E &OverBar; = &lsqb; s , B ^ &rsqb; = &lsqb; s , s ( &theta; ^ 1 ) , s ( &theta; ^ 2 ) , ... , s ( &theta; ^ P ) &rsqb;
Wherein, s is the echo signal steering vector assumed.
6. a kind of radar antenna array robust ada- ptive beamformer method based on sparse constraint according to claim 1, it is special Levy and be, complete interference plus signal subspace is according to the interference plus signal subspace based on Krylov space in step 3, Then step 3 specifically includes following sub-step：
(3a3) the covariance matrix value being s and receipt signal according to the echo signal steering vector assumedDetermine Krylov space
(3b3) due to Krylov spaceIn each column vector be linear independence, therefore Krylov space Meet：
(3c3) and then determine complete interference plus signal subspace
E &OverBar; = K D ( s , R ^ )
Wherein, D represents the exponent number in Krylov space, and D≤P+1, the number that P disturbs for far field arrowband, P<N, N are radar antenna The array number of array.
7. a kind of radar antenna array robust ada- ptive beamformer method based on sparse constraint according to claim 1, it is special Levy and be, step 4 specifically includes following sub-step：
(4a) because the Adaptive beamformer weight vector of radar antenna array outfan is located at complete interference plus signal sky Between, using described complete interference plus signal subspaceThe Adaptive beamformer power arrow of construction radar antenna array outfan AmountWherein, β is combined vectors；
(4b) according to the undistorted criterion of minimum variance, according to the covariance matrix value of described receipt signalAnd described mesh Mark signal guide vector estimated valueObtain following optimizing expression：
m i n &beta; w H R ^ w
s . t . w = E &OverBar; &beta; w H s ^ = 1
(4c) sparse constraint is carried out to described combined vectors β, obtain improved optimizing expression：
m i n &beta; ( E &OverBar; &beta; ) H R ^ ( E &OverBar; &beta; ) + &lambda; | | &beta; | | l 1
s . t . ( E &OverBar; &beta; ) H s ^ = 1
Wherein,Represent the l of combined vectors β1Norm, regularization parameter λ isWeights, λ is bigger, will to the openness of β Ask stronger, symbol H represents conjugate transpose；
(4d) solve above-mentioned improved optimizing expression, obtain the optimum Adaptive beamformer power of radar antenna array outfan Vector.
8. a kind of radar antenna array robust ada- ptive beamformer method based on sparse constraint according to claim 7, it is special Levy and be,
Described combined vectors
Wherein, UIIt is by interference covariance matrix RINonzero eigenvalue corresponding characteristic vector composition N × P dimension matrix, ΛIFor the diagonal matrix of P × P dimension, s is the echo signal steering vector of N × 1 dimension assumed, I is unit matrix, and symbol H represents Transposition, subscript -1 represents inversion operation.
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