CN107219511A - The STAP method and devices of wave beam Doppler's directional diagram sparse constraint - Google Patents
The STAP method and devices of wave beam Doppler's directional diagram sparse constraint Download PDFInfo
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- CN107219511A CN107219511A CN201710418125.XA CN201710418125A CN107219511A CN 107219511 A CN107219511 A CN 107219511A CN 201710418125 A CN201710418125 A CN 201710418125A CN 107219511 A CN107219511 A CN 107219511A
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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
- G01S7/41—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
- G01S7/414—Discriminating targets with respect to background clutter
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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
- G01S7/41—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
- G01S7/418—Theoretical aspects
Abstract
The present invention handles STAP method and devices suitable for radar signal processing field there is provided a kind of space-time adaptive of wave beam Doppler directional diagram sparse constraint, and methods described includes：According to the openness of wave beam Doppler's directional diagram, the l of joint space-time wave filter output2The l of norm and wave beam Doppler's directional diagram1The minimum of norm, sets up the mixing of L1 norm L2 norms and minimizes object function；Mixed according to the L1 norms L2 norms and minimize the weight vector w that object function solves space-time filterp；Wherein, subscript p represents independent same distribution number of training, and p is positive integer；The method parameter that the present invention is provided easily sets and calculates simple, can improve radar system clutter recognition level and target detection capabilities under conditions of independent same distribution number of training is limited.
Description
Technical field
The invention belongs to radar signal processing field, more particularly to a kind of wave beam-Doppler's directional diagram sparse constraint
STAP method and devices.
Background technology
In Phased Array Airborne Radar, STAP (Space-Time Adaptive Processing, space-time adaptive processing)
Technology is to improve one of technology for very advantageous of target detection performance.Due under non-homogeneous environment, it is difficult to obtain compared with
Many independent same distribution number of training, then how under conditions of independent same distribution number of training is limited, improve tradition
The problem of clutter recognition level and target detection capabilities of space-time adaptive filter, as asking that STAP researchs are primarily upon
Topic.
For the problem, scholars propose some correlation techniques, such as dimensionality reduction (Reduced Dimension) STAP methods
(such as local combination treatment method (Joint Domain Localized, JDL)), contraction (Reduced Rank) STAP methods
(such as method of principal component (Principle Components, PC)), the STAP methods based on model parameterization, Knowledge based engineering
(Knowledge-Aided, KA) STAP methods, based on the openness sparse space-time Beamforming Method of weight vector, min-max
STAP methods etc..Dimensionality reduction STAP methods are using the method for reducing degree of freedom in system, and improving independent same distribution training sample has
Clutter suppression capability and target detection performance under limit, but the algorithm reduces degree of freedom in system, compared to full space-time most major clique
For clutter recognition performance under system, performance decreases.Contraction (Reduced Rank) STAP methods are although can root in real time
According to environmental change and sample data design wave filter weight vector, the performance more superior than dimensionality reduction STAP methods can be also obtained, still
The performance of contraction STAP methods often relies on the accuracy of clutter rand estination in actual clutter environment, and in actual clutter environment
The estimation accuracy of clutter order still needs to more researchs.STAP methods based on model parameterization are solved solely using model parameter method
The problem of same distribution training sample is limited is found, but such method computation complexity is higher, and the performance of algorithm depends on model
The reasonability of parameter selection.Knowledge based engineering STAP methods, are solving to gather around the problem of independent same distribution number of training is limited
There is a huge advantage, but the performance of such method depends on the accuracy of knowledge.Based on the openness sparse space-time wave beam of weight vector
Forming method make use of the openness priori of weight vector, limited with potential advantages in independent same distribution training book number, but
When there is model mismatch, its clutter performance decreases.Min-max STAP methods utilize iteration min-max method choice
Antenna impulse is to reducing the demand to space-time snap, therefore, it is possible to soon take the preferable clutter suppression capability of acquisition limited,
But the iteration min-max process computation complexity being related in algorithm is higher, and when antenna impulse is to selecting not at that time, to calculate
Method performance severe exacerbation.
In the above-mentioned correlation technique that i.e. scholars propose, under conditions of independent same distribution number of training is limited, some
Algorithm due to there are some problems in the process of implementation causes that the clutter of traditional space-time adaptive filter can not be improved well
The problem of suppression level and target detection capabilities；There is the problem of computation complexity is high in other algorithms, or parameter setting is stranded
Difficult the problem of；Accordingly, it would be desirable to which a kind of parameter easily sets and calculates simple algorithm, can have in independent same distribution number of training
Under conditions of limit, the clutter recognition level and target detection capabilities of traditional space-time adaptive filter are improved.
The content of the invention
The present invention provides a kind of STAP method and devices of wave beam-Doppler's directional diagram sparse constraint, it is intended to independent same
Easily set there is provided a kind of parameter under conditions of distribution number of training is limited and calculate simple algorithm to improve traditional space-time certainly
The clutter recognition level and target detection capabilities of adaptive filter.
STAP methods, institute are handled the invention provides a kind of space-time adaptive of wave beam-Doppler's directional diagram sparse constraint
The method of stating includes：
According to the openness of wave beam-Doppler's directional diagram, the l of joint space-time wave filter output2Norm and wave beam-Doppler
The l of directional diagram1The minimum of norm, sets up the mixing of L1 norm-L2 norms and minimizes object function；
Mixed according to the L1 norms-L2 norms and minimize the weight vector w that object function solves space-time filterp；
Wherein, subscript p represents independent same distribution number of training, and p is positive integer.
Further, the L1 norms-L2 norms mixing minimum object function is：
s.t.(wp)HS=1.
Wherein, wpRepresent to be calculated by p space-time snap and obtain the weight vector that space-time filter is tieed up in NM × 1, J1(wp) represent with
wpFor the function of variable, (wp)HRpwpRepresent to calculate the l that obtained space-time filter is exported by p space-time snap2Norm, RpTable
Show and obtained array covariance matrix, κ calculated by p space-time snap | | zp||1Represent to calculate obtained ripple by p space-time snap
Beam-Doppler's directional diagram zpL1Sparse constraint, | | | |1Expression takes l1Norm,
Wave beam-Doppler's directional diagram of wave beam-Doppler space is represented, subscript T, H represent transposition, conjugate transposition respectively,Expression Doppler frequency is fd；i, spatial frequency be fs；jWave beam-Doppler's directional diagram,For NM × NdNsTie up matrix, NdRepresent whole Doppler domain Doppler frequency sampled point
Number, NsWhole Beam Domain spatial frequency sampling number is represented, κ is openness defeated with wave filter for balance wave beam-Doppler's directional diagram
Go out l2The regularization parameter of norm；Expression takes the corresponding parameter w of minimum valuep, s.t. represents constraints；
Tie up space-time snap and be expressed as in NM × 1：
X=αts+xu,
Wherein, M represents the element number of array of aerial array, and N represents coherent pulse number, αtFor target complex gain；It is for Doppler frequencySpatial frequency isTarget corresponding to space-time lead
To vector；xuIncluding clutter xc, interference xjWith noise xnVector.
Further, described mixed according to the L1 norms-L2 norms minimizes object function solution space-time filter
Weight vector wp, including：
L1 norms-L2 the norms are mixed into minimum object function and are converted into below equation：
Wherein, λ is Lagrange multiplier,Expression takes real part to the number in braces；
Using above-mentioned formula to (wp)*Derivation, and make result be 0, result is then substituted into (wp)HS=1, you can weighed
Vector wpExpression formula, according to weight vector wpExpression formula solve weight vector wp, wherein, wpExpression formula be：
Wherein,
Wherein, ()*Expression takes conjugation, diag { } represent using in braces element as diagonal element constituted to angular moment
Battle array, ε represents a normal number of very little.
Further, parameter RpSolution formula be：
Wherein, β is forgetting factor, xiRepresent i-th of space-time snap, xpP-th of space-time snap is represented, subscript H is represented respectively
Conjugate transposition, Rp-1P-1 space-time snap calculates obtained covariance matrix before representing.
Further, regularization parameter κ solution formula is：
Wherein,
Wherein, κp(zp) represent to calculate obtained regularization parameter κ by p space-time snap,For constant, and
STAP devices are handled present invention also offers a kind of space-time adaptive of wave beam-Doppler's directional diagram sparse constraint,
Described device includes：
Minimize object function and set up module, for according to the openness of wave beam-Doppler's directional diagram, joint space-time filtering
The l of device output2The l of norm and wave beam-Doppler's directional diagram1The minimum of norm, sets up L1 norm-L2 norms mixing minimum
Object function；
Weight vector wpModule is solved, space-time is solved for minimizing object function according to L1 norms-L2 norms mixing
The weight vector w of wave filterp；
Wherein, subscript p represents independent same distribution number of training, and p is positive integer.
Further, the L1 norms-L2 norms mixing minimum object function is：
s.t.(wp)HS=1.
Wherein, wpRepresent to be calculated by p space-time snap and obtain the weight vector that space-time filter is tieed up in NM × 1, J1(wp) represent with
wpFor the function of variable, (wp)HRpwpRepresent to calculate the l that obtained space-time filter is exported by p space-time snap2Norm, RpTable
Show and obtained array covariance matrix, κ calculated by p space-time snap | | zp||1Represent to calculate obtained ripple by p space-time snap
Beam-Doppler's directional diagram zpL1Sparse constraint, | | | |1Expression takes l1Norm,
Wave beam-Doppler's directional diagram of wave beam-Doppler space is represented, subscript T, H represent transposition, conjugate transposition respectively,Expression Doppler frequency is fd；i, spatial frequency be fs；jWave beam-Doppler's directional diagram,For NM × NdNsTie up matrix, NdRepresent whole Doppler domain Doppler frequency sampled point
Number, NsWhole Beam Domain spatial frequency sampling number is represented, κ is openness defeated with wave filter for balance wave beam-Doppler's directional diagram
Go out l2The regularization parameter of norm；Expression takes the corresponding parameter w of minimum valuep, s.t. represents constraints；
Tie up space-time snap and be expressed as in NM × 1：
X=αts+xu,
Wherein, M represents the element number of array of aerial array, and N represents coherent pulse number, αtFor target complex gain；It is for Doppler frequencySpatial frequency isTarget corresponding to space-time lead
To vector；xuIncluding clutter xc, interference xjWith noise xnVector.
Further, the weight vector wpModule is solved, mesh is minimized specifically for the L1 norms-L2 norms are mixed
Scalar functions are converted into below equation：
Wherein, λ is Lagrange multiplier,Expression takes real part to the number in braces；
And using above-mentioned formula to (wp)*Derivation, and make result be 0, result is then substituted into (wp)HS=1, you can obtain
Weight vector wpExpression formula, according to weight vector wpExpression formula solve weight vector wp, wherein, wpExpression formula be：
Wherein,
Wherein, ()*Expression takes conjugation, diag { } represent using in braces element as diagonal element constituted to angular moment
Battle array, ε represents a normal number of very little.
Further, parameter RpSolution formula be：
Wherein, β is forgetting factor, xiRepresent i-th of space-time snap, xpP-th of space-time snap is represented, subscript H is represented respectively
Conjugate transposition, Rp-1P-1 space-time snap calculates obtained covariance matrix before representing.
Further, regularization parameter κ solution formula is：
Wherein,
Wherein, κp(zp) represent to calculate obtained regularization parameter κ by p space-time snap,For constant, and
Compared with prior art, beneficial effect is the present invention：A kind of wave beam-Doppler's directional diagram that the present invention is provided is dilute
The STAP method and devices of constraint are dredged, in the case where independent same distribution number of training is p, by traditional STAP wave filters
The openness of wave beam-Duo Putu directional diagrams is introduced on the basis of design, STAP filter design problems are described as L1 norms-L2
Norm mixing minimizes optimization problem, the l of joint space-time wave filter output2The l of norm and wave beam-Doppler's directional diagram1Norm
Minimize, set up the mixing of L1 norm-L2 norms and minimize object function, and minimum is mixed according to the L1 norms-L2 norms
Object function solves the weight vector w of space-time filterp, so as to solve above-mentioned minimum optimization problem；The side that the present invention is provided
Method parameter easily sets and calculates simple, can improve radar system miscellaneous under conditions of independent same distribution number of training is limited
Ripple suppression level and target detection capabilities.
Brief description of the drawings
Fig. 1 is a kind of space-time adaptive processing of wave beam provided in an embodiment of the present invention-Doppler's directional diagram sparse constraint
The schematic flow sheet of STAP methods；
Fig. 2 is the schematic diagram of SINR loss and number of training relations provided in an embodiment of the present invention；
Fig. 3 is SINR losses provided in an embodiment of the present invention and the schematic diagram of target Doppler frequency relation；
Fig. 4 is the schematic diagram of detection probability provided in an embodiment of the present invention and the relation of target input signal-to-noise ratio (SNR)；
Fig. 5 is a kind of space-time adaptive processing of wave beam provided in an embodiment of the present invention-Doppler's directional diagram sparse constraint
The module diagram of STAP devices.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
The main of the present invention realizes that thought is：In the case where independent same distribution number of training is p, by tradition
The openness of wave beam-Duo Putu directional diagrams is introduced on the basis of the design of STAP wave filters, STAP filter design problems are described
Optimization problem, the l of joint space-time wave filter output are minimized for the mixing of L1 norm-L2 norms2Norm and wave beam-Doppler direction
The l of figure1The minimum of norm, sets up the mixing of L1 norm-L2 norms and minimizes object function, and according to the L1 norms-L2 models
Number mixing minimizes the weight vector w that object function solves space-time filterp, so as to solve above-mentioned minimum optimization problem.
Lower mask body introduces the space-time adaptive processing STAP methods of this wave beam-Doppler's directional diagram sparse constraint, such as
Shown in Fig. 1, methods described includes：
Step S1, according to the openness of wave beam-Doppler's directional diagram, the l of joint space-time wave filter output2Norm and ripple
The l of beam-Doppler's directional diagram1The minimum of norm, sets up the mixing of L1 norm-L2 norms and minimizes object function；
Specifically, the openness of wave beam-Doppler direction refers to that wave beam-Doppler's directional diagram forms high increasing in target direction
Benefit, and very small gain is formed in other directions in addition to target direction, i.e., in one vector the value of most of components compared with
Small, the value of only several components is larger, that is, says that signal has openness.The embodiment of the present invention is the output designed in traditional STAP
In minimum power problem, it is assumed that space-time snap number is p (p is positive integer), the ripple of space-time filter weight vector formation is utilized
Beam-Doppler's directional diagram it is openness, (mathematical meaning of space-time filter power output is joint space-time filter output power
l2Norm) and wave beam-Doppler's directional diagram l1Norm minimum, obtains objective optimisation problems.
Specifically, the method for expressing on space-time snap is explained as follows：
Assuming that a pulse Doppler radar, its aerial array is even linear array, comprising M array element, during a Coherent processing
In with isopulse repetition rate (PRF) frSend N number of coherent pulse, range cell only one of which target interested, then NM
× 1 dimension space-time snap x is expressed as：
X=αts+xu (1)
Wherein, αtFor target complex gain；It is for Doppler frequencySpace frequency
Rate isTarget corresponding to space-time steering vector；xuIncluding clutter xc, interference xjWith noise xnVector.
Specifically, the L1 norms-L2 norms mixing minimum object function is：
Wherein, wpRepresent to be calculated by p space-time snap and obtain the weight vector that space-time filter is tieed up in NM × 1, J1(wp) represent with
wpFor the function of variable, (wp)HRpwpRepresent to calculate the l that obtained space-time filter is exported by p space-time snap2Norm, RpTable
Show and obtained array covariance matrix, κ calculated by p space-time snap | | zp||1Represent to calculate obtained ripple by p space-time snap
Beam-Doppler's directional diagram zpL1Sparse constraint, | | | |1Expression takes l1Norm,
Wave beam-Doppler's directional diagram of wave beam-Doppler space is represented, wherein, subscript T, H represent transposition, conjugate transposition respectively,Expression Doppler frequency is fd；i, spatial frequency be fs；jWave beam-Doppler's directional diagram, v
() represents space-time steering vector, fd；iSpan be -0.5 to 0.5, fs；jSpan be -0.5 to 0.5,For NM × NdNsTie up matrix, NdRepresent whole Doppler domain Doppler frequency sampled point
Number, NsWhole Beam Domain spatial frequency sampling number is represented, κ is openness defeated with wave filter for balance wave beam-Doppler's directional diagram
Go out l2The regularization parameter of norm；Expression takes the corresponding parameter w of minimum valuep, s.t. represents constraints.
Step S2, mixes according to the L1 norms-L2 norms and minimizes the weight vector that object function solves space-time filter
wp。
Specifically, the L1 norms-L2 norms are first mixed into minimum object function and is converted into below equation：
Wherein, λ is Lagrange multiplier,Expression takes real part to the number in braces；
Then, it is the weight vector w in solution formula (3)p, using above-mentioned formula (3) to (wp)*Derivation, and make result be 0, so
Result is substituted into (w afterwardsp)HS=1, you can obtain weight vector wpExpression formula, according to weight vector wpExpression formula can solve power
Vector w, wherein, wpExpression formula be：
Wherein, formula (4) is space-time filter weight vector expression formula；
Wherein,
Wherein, ()*Expression takes conjugation, diag { } represent using in braces element as diagonal element constituted to angular moment
Battle array, ε represents a normal number of very little.
Specifically, for the R in formula (4)p, solved by following alternative manner：
Wherein, β is forgetting factor, and p space-time snap is expressed as X=[x1,x2,…,xp], xiRepresent that i-th of space-time is fast
Clap, i=1,2 ..., p, xpP-th of space-time snap is represented, subscript H represents conjugate transposition, R respectivelyp-1P-1 space-time is fast before representing
Clap the covariance matrix for calculating and obtaining.
Specifically, it is w in further solution formula (4)p, parameter κ is used into following iteration form
Wherein, formula (7) is the adaptive alternative and iterative algorithm of regularization parameter, κp(zp) represent to be calculated by p space-time snap
Obtained regularization parameter κ, to ensure that algorithm can converge to global optimum, makes
Wherein,For constant, and
Formula (6) and formula (7) are combined, and weight vector w can be tried to achieve using formula (4)p。
The STAP methods for a kind of wave beam-Doppler's directional diagram sparse constraint that the embodiment of the present invention is proposed, at independent same point
In the case that cloth number of training is p, first by introducing wave beam-Doppler side on the basis of the design of traditional STAP wave filters
To the openness of figure, and L1 norm-L2 norms mixing minimum object function is set up, then utilize adaptive alternative and iterative algorithm
Optimal weight vector and regularization parameter are updated, the weight vector w for obtaining space-time filter is solvedp.Institute's extracting method of the present invention can have
Limit independent same distribution number of training and under conditions of there is array error, improves radar system clutter recognition level and is examined with target
Survey ability.
A specific embodiment is named, the space-time for wave beam-Doppler's directional diagram sparse constraint that the present invention is provided is adaptive
STAP methods should be handled to swear with JDL, STMB (Space-Time Multiple-Beam, space-time multi-beam), PC and based on power
The openness sparse space-time Beamforming Method (Sparsity-Aware Beamformer) of amount is contrasted, to illustrate this hair
The beneficial effect that the technical scheme of bright offer is obtained in terms of clutter recognition performance and target detection performance.
Consider the equal linear array airborne radar platform of positive side view, array number is M=12, and arteries and veins is sent in a Coherent processing time
Number N=12 is rushed, carrier frequency is 1.2GHz, pulse recurrence frequency fr=2kHz, platform speed is 125 metre per second (m/s)s, podium level
For 8 kms, miscellaneous noise ratio (CNR) is 45dB, and two interference radiating way are -45 degree and 60 degree, and dry make an uproar than (JNR) is 30dB, it is considered to deposited
In array amplitude phase error：Array amplitude and phase error meet the variance of zero-mean gaussian distribution, range error and phase error
Respectively 0.05,0.05* pi/2s.Each algorithm parameter sets as follows：In JDL algorithms, 3 Doppler's passages of selection and 3 wave beams lead to
Road；In STMB algorithms, 8 Doppler frequency passages of selection and 3 wave beam passages；In PC algorithms, big characteristic value number is set to
50；The technology of the present invention proposed in algorithm, w0=s, β=0.9998, ε=10-6,
On clutter recognition performance：
To investigate the clutter recognition performance for carrying algorithm, relatively institute's extracting method of the present invention and existing JDL, STMB, PC and power
Output Signal to Interference plus Noise Ratio (SINR) loss of the openness sparse space-time Beamforming Method of vector, is normally defined as
It should be noted that being that the w in formula (9) is taken into w for institute's extracting method of the present inventionp, i.e. wHTake (wp)H, utilize
The technical scheme that the present invention is provided calculates the weight vector w of space-time filterp, and bring above-mentioned formula (9) into, dried obtaining property
Than (SINR).
In fig. 2, if the normalization Doppler frequency of interesting target is 0.25.As seen from Figure 2, it is several compared to other
Algorithm is planted, the present invention shows faster convergence rate and Geng Gao stable state output SINR.
In figure 3, if the number of training of each algorithm is space-time, snap number is 50.As seen from Figure 3, normalizing is worked as
When changing Doppler frequency less than or equal to 0.1, the output SINR for carrying algorithm is slightly less than JDL algorithms, but in other Doppler frequency
In rate value, carry algorithm output SINR and be all substantially better than other algorithms.
On detection performance：
It is empty during the detection performance of institute's extracting method and other method of the present invention, i.e. detection probability curve are as shown in figure 4, emulate
Alert rate PfaIt is set to 10-3, the Monte Carlo number of times that detection threshold and detection probability are obtained is set to 10/Pfa, interesting target normalizing
It is 0.25 to change Doppler frequency.It can be obtained by Fig. 4：The present invention has highest detection probability, i.e. target to examine compared to other traditional algorithms
Survey performance and be better than other algorithms.
It can be obtained by above example, method provided by the present invention is in limited independent same distribution number of training and there is battle array
Under conditions of row error, it can obtain better than JDL, STMB, PC and the openness sparse space-time Beamforming Method of weight vector
Clutter recognition performance.
STAP devices are handled present invention also offers a kind of space-time adaptive of wave beam-Doppler's directional diagram sparse constraint,
As shown in figure 5, described device includes：
Minimize object function and set up module 1, for according to the openness of wave beam-Doppler's directional diagram, joint space-time filter
The l of ripple device output2The l of norm and wave beam-Doppler's directional diagram1The minimum of norm, sets up the mixing of L1 norm-L2 norms minimum
Change object function；
Weight vector wpModule 2 is solved, space-time is solved for minimizing object function according to L1 norms-L2 norms mixing
The weight vector w of wave filterp。
The embodiment of the present invention on the basis of the design of traditional STAP wave filters by introducing the dilute of wave beam-Duo Putu directional diagrams
Dredge property, by STAP filter design problems be described as L1 norm-L2 norms mix minimize optimization problem, that is, set up L1 norms-
The mixing of L2 norms minimizes object function, and then minimizing object function according to L1 norms-L2 norms mixing solves space-time
The weight vector w of wave filterp.The embodiment of the present invention can apply to motion platform radar clutter and suppress field, same in limited independence
Distribution number of training and under conditions of there is array error, improves radar system clutter recognition level and target detection capabilities.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
Any modifications, equivalent substitutions and improvements made within refreshing and principle etc., should be included in the scope of the protection.
Claims (10)
1. a kind of space-time adaptive processing STAP methods of wave beam-Doppler's directional diagram sparse constraint, it is characterised in that the side
Method includes：
According to the openness of wave beam-Doppler's directional diagram, the l of joint space-time wave filter output2Norm and wave beam-Doppler direction
The l of figure1The minimum of norm, sets up the mixing of L1 norm-L2 norms and minimizes object function；
Mixed according to the L1 norms-L2 norms and minimize the weight vector w that object function solves space-time filterp；
Wherein, subscript p represents independent same distribution number of training, and p is positive integer.
2. STAP methods as claimed in claim 1, it is characterised in that the L1 norms-L2 norms mixing minimizes target letter
Number is：
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s.t.(wp)HS=1.
Wherein, wpRepresent to be calculated by p space-time snap and obtain the weight vector that space-time filter is tieed up in NM × 1, J1(wp) represent with wpFor
The function of variable, (wp)HRpwpRepresent to calculate the l that obtained space-time filter is exported by p space-time snap2Norm, RpRepresent by p
Individual space-time snap calculates obtained array covariance matrix, κ | | zp||1The wave beam that expression is obtained by p space-time snap calculating-many
General Le directional diagram zpL1Sparse constraint, | | | |1Expression takes l1Norm,Represent
The wave beam of wave beam-Doppler space-Doppler's directional diagram, subscript T, H represent transposition, conjugate transposition respectively,Expression Doppler frequency is fd；i, spatial frequency be fs；jWave beam-Doppler's directional diagram,For NM × NdNsTie up matrix, NdRepresent whole Doppler domain Doppler frequency sampled point
Number, NsWhole Beam Domain spatial frequency sampling number is represented, κ is openness defeated with wave filter for balance wave beam-Doppler's directional diagram
Go out l2The regularization parameter of norm；Expression takes the corresponding parameter w of minimum valuep, s.t. represents constraints；
Tie up space-time snap and be expressed as in NM × 1：
X=αts+xu,
Wherein, M represents the element number of array of aerial array, and N represents coherent pulse number, αtFor target complex gain；It is for Doppler frequencySpatial frequency isTarget corresponding to space-time lead
To vector；xuIncluding clutter xc, interference xjWith noise xnVector.
3. STAP methods as claimed in claim 2, it is characterised in that described to mix minimum according to the L1 norms-L2 norms
Change the weight vector w that object function solves space-time filterp, including：
L1 norms-L2 the norms are mixed into minimum object function and are converted into below equation：
Wherein, λ is Lagrange multiplier,Expression takes real part to the number in braces；
Using above-mentioned formula to (wp)*Derivation, and make result be 0, result is then substituted into (wp)HS=1, you can obtain weight vector
wpExpression formula, according to weight vector wpExpression formula solve weight vector wp, wherein, wpExpression formula be：
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1
Wherein,
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<mrow>
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<mn>1</mn>
<mo>/</mo>
<mo>(</mo>
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<msubsup>
<mi>z</mi>
<mrow>
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<mi>N</mi>
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<mi>p</mi>
</msubsup>
<mo>+</mo>
<mi>&epsiv;</mi>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>,</mo>
</mrow>
Wherein, ()*Expression takes conjugation, and diag { } represents the diagonal matrix that element is constituted as diagonal element using in braces, ε
Represent a normal number of very little.
4. STAP methods as claimed in claim 3, it is characterised in that parameter RpSolution formula be：
<mrow>
<msup>
<mi>R</mi>
<mi>p</mi>
</msup>
<mo>=</mo>
<msubsup>
<mi>&Sigma;</mi>
<mrow>
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<msup>
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<mrow>
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<mi>x</mi>
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<mi>H</mi>
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Wherein, β is forgetting factor, xiRepresent i-th of space-time snap, xpP-th of space-time snap is represented, subscript H represents conjugation respectively
Transposition, Rp-1P-1 space-time snap calculates obtained covariance matrix before representing.
5. STAP methods as claimed in claim 4, it is characterised in that regularization parameter κ solution formula is：
<mrow>
<msup>
<mi>&kappa;</mi>
<mi>p</mi>
</msup>
<mrow>
<mo>(</mo>
<msup>
<mi>z</mi>
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</msup>
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<mi>p</mi>
</msup>
</mrow>
<mrow>
<mi>&rho;</mi>
<mo>-</mo>
<mo>|</mo>
<mo>|</mo>
<msup>
<mi>z</mi>
<mi>p</mi>
</msup>
<mo>|</mo>
<msub>
<mo>|</mo>
<mn>1</mn>
</msub>
</mrow>
</mfrac>
<mo>,</mo>
</mrow>
Wherein,
Wherein, κp(zp) represent to calculate obtained regularization parameter κ by p space-time snap,For constant, and
6. a kind of space-time adaptive processing STAP devices of wave beam-Doppler's directional diagram sparse constraint, it is characterised in that the dress
Put including：
Minimize object function and set up module, for according to the openness of wave beam-Doppler's directional diagram, joint space-time wave filter to be defeated
The l gone out2The l of norm and wave beam-Doppler's directional diagram1The minimum of norm, sets up the mixing of L1 norm-L2 norms and minimizes target
Function；
Weight vector wpModule is solved, space-time filter is solved for minimizing object function according to L1 norms-L2 norms mixing
Weight vector wp；
Wherein, subscript p represents independent same distribution number of training, and p is positive integer.
7. STAP devices as claimed in claim 6, it is characterised in that the L1 norms-L2 norms mixing minimizes target letter
Number is：
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<munder>
<mrow>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
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<mi>w</mi>
<mi>p</mi>
</msup>
</munder>
<msub>
<mi>J</mi>
<mn>1</mn>
</msub>
<mrow>
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</mrow>
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</munder>
<mrow>
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</mrow>
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<mi>p</mi>
</msup>
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<mi>w</mi>
<mi>p</mi>
</msup>
<mo>+</mo>
<mi>&kappa;</mi>
<mo>|</mo>
<mo>|</mo>
<msup>
<mi>z</mi>
<mi>p</mi>
</msup>
<mo>|</mo>
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<mo>|</mo>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
<mo>,</mo>
</mrow>
s.t.(wp)HS=1.
Wherein, wpRepresent to be calculated by p space-time snap and obtain the weight vector that space-time filter is tieed up in NM × 1, J1(wp) represent with wpFor
The function of variable, (wp)HRpwpRepresent to calculate the l that obtained space-time filter is exported by p space-time snap2Norm, RpRepresent by p
Individual space-time snap calculates obtained array covariance matrix, κ | | zp||1The wave beam that expression is obtained by p space-time snap calculating-many
General Le directional diagram zpL1Sparse constraint, | | | |1Expression takes l1Norm,Represent
The wave beam of wave beam-Doppler space-Doppler's directional diagram, subscript T, H represent transposition, conjugate transposition respectively,Expression Doppler frequency is fd；i, spatial frequency be fs；jWave beam-Doppler's directional diagram,For NM × NdNsTie up matrix, NdRepresent whole Doppler domain Doppler frequency sampled point
Number, NsWhole Beam Domain spatial frequency sampling number is represented, κ is openness defeated with wave filter for balance wave beam-Doppler's directional diagram
Go out l2The regularization parameter of norm；Expression takes the corresponding parameter w of minimum valuep, s.t. represents constraints；
Tie up space-time snap and be expressed as in NM × 1：
X=αts+xu,
Wherein, M represents the element number of array of aerial array, and N represents coherent pulse number, αtFor target complex gain；It is for Doppler frequencySpatial frequency isTarget corresponding to space-time lead
To vector；xuIncluding clutter xc, interference xjWith noise xnVector.
8. STAP devices as claimed in claim 7, it is characterised in that the weight vector wpModule is solved, specifically for by described in
The mixing of L1 norm-L2 norms minimizes object function and is converted into below equation：
Wherein, λ is Lagrange multiplier,Expression takes real part to the number in braces；
And using above-mentioned formula to (wp)*Derivation, and make result be 0, result is then substituted into (wp)HS=1, you can obtain power arrow
Measure wpExpression formula, according to weight vector wpExpression formula solve weight vector wp, wherein, wpExpression formula be：
<mrow>
<msup>
<mi>w</mi>
<mi>p</mi>
</msup>
<mo>=</mo>
<mfrac>
<mrow>
<msup>
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<mi>p</mi>
</msup>
<mo>+</mo>
<mi>&kappa;</mi>
<mi>&Phi;</mi>
<mi>&Gamma;</mi>
<mo>(</mo>
<msup>
<mi>z</mi>
<mi>p</mi>
</msup>
<mo>)</mo>
<msup>
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<mi>H</mi>
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<mo>(</mo>
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<mi>z</mi>
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</mrow>
</msup>
<msup>
<mi>s</mi>
<mi>H</mi>
</msup>
</mrow>
</mfrac>
</mrow>
Wherein,
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<mi>p</mi>
</msup>
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</mrow>
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<mo>,</mo>
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<mo>,</mo>
<mn>1</mn>
<mo>/</mo>
<mo>(</mo>
<mrow>
<msubsup>
<mi>z</mi>
<mrow>
<msub>
<mi>N</mi>
<mi>d</mi>
</msub>
<mo>,</mo>
<msub>
<mi>N</mi>
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</msub>
</mrow>
<mi>p</mi>
</msubsup>
<mo>+</mo>
<mi>&epsiv;</mi>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>,</mo>
</mrow>
Wherein, ()*Expression takes conjugation, and diag { } represents the diagonal matrix that element is constituted as diagonal element using in braces, ε
Represent a normal number of very little.
9. STAP devices as claimed in claim 8, it is characterised in that parameter RpSolution formula be：
<mrow>
<msup>
<mi>R</mi>
<mi>p</mi>
</msup>
<mo>=</mo>
<msubsup>
<mi>&Sigma;</mi>
<mrow>
<mi>i</mi>
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<mn>1</mn>
</mrow>
<mi>p</mi>
</msubsup>
<msup>
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<mrow>
<mi>p</mi>
<mo>-</mo>
<mi>i</mi>
</mrow>
</msup>
<msub>
<mi>x</mi>
<mi>i</mi>
</msub>
<msup>
<msub>
<mi>x</mi>
<mi>i</mi>
</msub>
<mi>H</mi>
</msup>
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<msup>
<mi>&beta;R</mi>
<mrow>
<mi>p</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<mo>+</mo>
<msub>
<mi>x</mi>
<mi>p</mi>
</msub>
<msup>
<msub>
<mi>x</mi>
<mi>p</mi>
</msub>
<mi>H</mi>
</msup>
<mo>,</mo>
</mrow>
Wherein, β is forgetting factor, xiRepresent i-th of space-time snap, xpP-th of space-time snap is represented, subscript H represents conjugation respectively
Transposition, Rp-1P-1 space-time snap calculates obtained covariance matrix before representing.
10. STAP devices as claimed in claim 9, it is characterised in that regularization parameter κ solution formula is：
<mrow>
<msup>
<mi>&kappa;</mi>
<mi>p</mi>
</msup>
<mrow>
<mo>(</mo>
<msup>
<mi>z</mi>
<mi>p</mi>
</msup>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mrow>
<msup>
<mrow>
<mo>(</mo>
<msup>
<mi>W</mi>
<mi>p</mi>
</msup>
<mo>)</mo>
</mrow>
<mi>H</mi>
</msup>
<msup>
<mi>R</mi>
<mi>p</mi>
</msup>
<msup>
<mi>w</mi>
<mi>p</mi>
</msup>
</mrow>
<mrow>
<mi>&rho;</mi>
<mo>-</mo>
<mo>|</mo>
<mo>|</mo>
<msup>
<mi>z</mi>
<mi>p</mi>
</msup>
<mo>|</mo>
<msub>
<mo>|</mo>
<mn>1</mn>
</msub>
</mrow>
</mfrac>
<mo>,</mo>
</mrow>
Wherein,
Wherein, κp(zp) represent to calculate obtained regularization parameter κ by p space-time snap,For constant, and
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| CN109031227A (en) * | 2018-06-25 | 2018-12-18 | 深圳大学 | A kind of conjugate gradient space-time adaptive processing method and system |
| WO2020000123A1 (en) * | 2018-06-25 | 2020-01-02 | 深圳大学 | Conjugate gradient space-time adaptive processing method and system |
| CN110658517A (en) * | 2019-10-11 | 2020-01-07 | 深圳大学 | Dimensionality reduction sparse STAP method and device based on uncertain priori knowledge |
| CN110677179A (en) * | 2019-10-09 | 2020-01-10 | 河北科技大学 | Receiving antenna selection method and device and terminal equipment |
| CN110764069A (en) * | 2019-11-14 | 2020-02-07 | 内蒙古工业大学 | Sparse recovery STAP color loading method based on knowledge assistance |
| CN111624556A (en) * | 2020-06-08 | 2020-09-04 | 河海大学 | Meteorological radar WTC (wind turbine controller) inhibition method based on morphological component analysis |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2018223285A1 (en) * | 2017-06-06 | 2018-12-13 | 深圳大学 | Stap method and device with beam-doppler pattern sparsity constraint |
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| CN110677179A (en) * | 2019-10-09 | 2020-01-10 | 河北科技大学 | Receiving antenna selection method and device and terminal equipment |
| CN110677179B (en) * | 2019-10-09 | 2020-11-10 | 河北科技大学 | Receiving antenna selection method and device and terminal equipment |
| CN110658517A (en) * | 2019-10-11 | 2020-01-07 | 深圳大学 | Dimensionality reduction sparse STAP method and device based on uncertain priori knowledge |
| CN110764069A (en) * | 2019-11-14 | 2020-02-07 | 内蒙古工业大学 | Sparse recovery STAP color loading method based on knowledge assistance |
| CN110764069B (en) * | 2019-11-14 | 2021-08-10 | 内蒙古工业大学 | Sparse recovery STAP color loading method based on knowledge assistance |
| CN111624556A (en) * | 2020-06-08 | 2020-09-04 | 河海大学 | Meteorological radar WTC (wind turbine controller) inhibition method based on morphological component analysis |
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