CN104931918B - Ship DOA direction estimation methods based on plural blind source separating - Google Patents
Ship DOA direction estimation methods based on plural blind source separating 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
- G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
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Abstract
The invention discloses a kind of ship DOA direction estimation methods based on plural blind source separating, comprise the following steps：(1) the detectable region ships quantity estimation based on cross validation；(2) the array response pseudo inverse matrix estimation based on plural blind source separating；(3) target ship DOA orientation is estimated.Target ship DOA orientation can be just detected because the inventive method only receives signal without launching any signal, and traditional DOA estimation method belongs to active probe object technology；Again because the inventive method can estimate the ships quantity in aerial array detectable region, and traditional DOA estimation method is needed known to number of targets；Again because the estimated accuracy of the inventive method is not limited by fast umber of beats, and the estimation quality of traditional DOA estimation method is seriously restricted by fast umber of beats so that the present invention calculates the advantage of simpler optimization.
Description
Technical field
The present invention relates to a kind of traffic and transport field, more particularly to a kind of ship DOA side based on plural blind source separating
Position method of estimation.
Background technology
The problem of ship DOA estimates in orientation is described.As shown in figure 1, in uniform line-array, m and d represent respectively array number and
Array element spacing, receiving array is located at the far-field region of n vessel position, and m >=n.Assuming that the source signal s that n target ship is sent
(t)=[s1(t),s2(t),…,sn(t)]TFor independence each other and the narrow band signal of zero-mean, and remember that they reach the 1st
Angle between array element direct rays and array normal direction is θi(i=1,2 ..., n), this angle be called ripple to orientation (angle),
That is the DOA orientation of ship.If the 1st array element is considered as into referential array, target source, which reaches non-reference array element, can all have delay,
There is a phase difference in the signal that i.e. non-reference array element is received, i-th of target source of note reaches the 2nd array element with target source signal
Caused phase difference is ωi, ωiWith θiBetween relation be：
In formula (1), λsFor signal wavelength,Ensure ωi≤ π, array element spacing must is fulfilled for 2d≤λs。
The vector that so i-th target source reaches phase difference composition caused by m array element is designated as：
In formula,For imaginary number.Other target source signals can similarly be obtained and reach the vector that m array element causes phase difference,
By institute's one matrix of dephased vector composition, A is designated as, it is with institute directed quantity aiRelation be：
Array response matrix A in formula (3) is the Vandermonde matrixes of m × n dimension, Rank (A)=n.If by m
The signal that individual array element is received is designated as x (t)=[x1(t),x2(t),…,xm(t)]T, then the relation between x (t) and s (t)
For：
X (t)=As (t) (4)
Ship DOA orientation estimate problem to be solved be exactly source signal s (t) and receiving array aliasing parameter A not
In the case of knowing, the independent statistics characteristic only according to source signal estimates each target from the aliasing signal x (t) observed
The residing DOA orientation relative to referential array of ship, i.e. θi(i=1,2 ..., n).
Existing DOA estimation method can be divided mainly into three classes：Multiple signal classification (multiple signal
Classification, MUSIC) method, ESPRIT (estimating signal parameter via
Rotational invariance techniques, ESPRIT) and maximum likelihood estimate.MUSIC methods have to noise
Good robustness, but it needs the fast umber of beats for receiving signal enough, and its estimated accuracy and target source to be positioned it
Between gun parallax condition each other；ESPRIT technologies can be suitably used for gun parallax it is larger in the case of, but it is not only to noise suppressed energy
Power difference is outer, and requires that the fast umber of beats of signal is enough as MUSIC methods of estimation.The likelihood function of maximal possibility estimation is
One nonlinear multimodal function, will optimize the problem of this object function is one highly difficult and complicated.
The content of the invention
It is an object of the invention to provide a kind of ship DOA based on plural blind source separating for calculating simpler optimization
Direction estimation method, this method is only by receiving signal without launching any signal passively for aerial array detectable region
Interior ships quantity and the DOA orientation of ship are estimated.
To achieve the above object, technical solution of the invention is：
1st, a kind of ship DOA direction estimation methods based on plural blind source separating, it is characterised in that：Comprise the following steps：
Step 1：Detectable region ships quantity estimation based on cross validation
Array received data are divided into two parts, a portion is used for the feature for extracting data, and other parts are used to test
These features are demonstrate,proved, the criterion of formula (5) and formula (6) for estimation detectable region ships quantity is proposed,
In formula, i=1,2 ..., m, trace () is Matrix Calculating mark computing, and C is array received data x covariance matrix
C=xxT,ΛiFor the diagonal matrix that diagonal element is i characteristic value before C, UiColumn vector be its corresponding spy
Levy vector；And calculate'sDiagonal matrixDiagonal and ΛmBe intersect and two matrixes diagonal
Element sequence on line is opposite；
Step 2：Array response pseudo inverse matrix estimation based on plural blind source separating
Do not knowing source signal and the parameter to unknown aliasing system (array received system) does not do any prior information
Assuming that in the case of, find an optimal array response pseudo inverse matrix W so that W meets WA=I, I with array response matrix A
For dimension of m m unit matrix, subscript " H " symbol is Hermitian transposition computings；Remember wi (i=1,2 ..., n) for one of W arrange to
Amount, thenBy for the complex vector located of m dimension,WithIt is real number；
By solving n wiFinal also to obtain W, W is calculated and obtained by formula (7a)-(7d), (8)；
yi(t)=wix(t) (7b)
In formula, E [] is average computing, [αi,1,αi,2,…,αi,2m-1]∈[02π](2m-1)；In addition, in order to avoid production
Raw two identical wi, using formula (8) come decorrelative transformation；
Step 3：Estimate in target ship DOA orientation
A phase is all differed between two adjacent row vectors of array response matrix, if L1=[I(m-1)×(m-1)0(m-1)×1]
And L2=[0(m-1)×1I(m-1)×(m-1)], it can obtain
Thus
ωi=jln [(L1ai)#L2ai] (10)
I=1,2 in formula ..., n.
2nd, the ship DOA direction estimation methods according to claim 1 based on plural blind source separating, its feature exists
In：Array response pseudo inverse matrix estimation of the step 2 based on plural blind source separating comprises the following steps：
Step 2.1 sets convergence error value Δ；F is randomly generated between 0~2 πSThe data set of individual n × 2m-1 dimensions, respectively
It is designated as θ (l, d), l=1,2 ..., FS, d=1,2 ..., n × 2m-1；
Step 2.2
For l=1to Fs
The value of l-th of data set θ (l, d) is assigned to n [αi,1,αi,2,…,αi,2m-1]；
For i=1to n
ByConstruct wi；
ByDecorrelative transformation；
Calculate yi(t)=wix(t)；
Calculate
end
Calculate
end
T=1；
Step 2.3 iteration evolutionary operation
Step 2.3.1
For l=1to Fs
For d=1to n × 2m-1
By θnew(l, d)=θ (l, d)+rand [θ (l, d)-θ (r, d)] is calculated, and rand is the random number between [01], r
For in [1FS] between produce not be l random integers；
end
By l-th of data set θnewThe value of (l, d) is assigned to n [αi,1,αi,2,…,αi,2m-1]；
For i=1to n
ByConstruct wi；
ByDecorrelative transformation；
Calculate yi(t)=wix(t)；
Calculate
end
Calculate
if Jnew(l)>J(l)
J (l)=Jnew(l)；
By θnewThe value of (l, d) is assigned to θ (l, d)；
end
end
Step 2.3.2
Jglobal(t)=J (1)；
1st data set θ value is assigned to θglobal；
For l=2to Fs
if Jglobal(t)<J(l)
Jglobal(t)=J (l)；
L-th of data set θ value is assigned to θglobal；
end
end
Step 2.3.3
If t=1
T=t+1；
Return to step 2.3.1；
else
Calculate ε=Jglobal(t)-Jglobal(t-1)；
ifε<Δ
Skip to step 2.4；
else
T=t+1；
Return to step 2.3.1；
end
end
Step 2.4
Step 2.4.1 is by θglobalValue be assigned to n [αi,1,αi,2,…,αi,2m-1]；
Step 2.4.2
For i=1to n
ByConstruct wi；
ByDecorrelative transformation；
end
Step 2.4.3 is by n wiConstruct W=[w1,w2,…,wn], array response is obtained by the generalized inverse matrix for calculating W
Matrix.
After such scheme, the present invention has advantages below：
(1) the inventive method only receives signal can just detect target ship DOA orientation without launching any signal, and pass
The DOA estimation method of system belongs to active probe object technology；
(2) the inventive method can estimate the ships quantity in aerial array detectable region, and traditional DOA estimation method
Need known to number of targets；
(3) estimated accuracy of the inventive method is not limited by fast umber of beats, and the estimation quality of traditional DOA estimation method is tight
Restricted again by fast umber of beats.
The present invention is further illustrated with specific embodiment below in conjunction with the accompanying drawings.
Brief description of the drawings
Fig. 1 is that uniform line-array of the present invention reaches orientation diagram with ripple；
Fig. 2 is that the ship DOA direction estimation methods of the invention based on plural blind source separating realize flow chart；
Fig. 3 is that the detectable region ships quantity method of estimation of the invention based on cross validation realizes flow chart；
Fig. 4 is that flow chart is realized in target ship DOA orientation estimation of the present invention.
Embodiment
As shown in Fig. 2 the present invention is a kind of ship DOA direction estimation methods based on plural blind source separating, including it is following
Step：
Step 1：Detectable region ships quantity estimation based on cross validation
The thought of cross validation is that data are divided into two parts, and a portion is used for the feature for extracting data, other portions
Dividing is used to verify these features.Using this thought, the standard of formula (5) and formula (6) for estimation detectable region ships quantity is proposed
Then, this method realizes that flow is as shown in Figure 3.
In formula, i=1,2 ..., m, trace () is Matrix Calculating mark computing, and C is x covariance matrix C=xxT,ΛiFor the diagonal matrix that diagonal element is i characteristic value before C, UiColumn vector be its corresponding characteristic vector；
And calculate'sDiagonal matrixDiagonal and ΛmIt is to intersect, and two matrixes are on the diagonal
Element sequence is opposite.
As shown in figure 3, step 2：Array response pseudo inverse matrix estimation based on plural blind source separating
The purpose of plural blind source separating seeks to do not knowing source signal and not to unknown aliasing system (reception system)
Parameter do in the case that any prior information assumes, find an optimal W so that WH=A, i.e. WA=I, I are dimension of m m
Unit matrix, subscript " H " symbol is Hermitian transposition computings.Remember wi(i=1,2 ..., a n) column vector for being W, thenBy for the complex vector located of m dimension,WithIt is real number.Pass through
Solve n wiFinal also to obtain W, W is calculated and obtained by formula (7a)-(7d), (8).
yi(t)=wix(t) (7b)
In formula, E [] is average computing, [αi,1,αi,2,…,αi,2m-1]∈[02π](2m-1).In addition, in order to avoid production
Raw two identical wi, using formula (8) come decorrelative transformation.
Array response pseudo inverse matrix estimation of the step 2 based on plural blind source separating comprises the following steps：
Step 2.1 sets convergence error value Δ；F is randomly generated between 0~2 πSThe data set of individual n × 2m-1 dimensions, respectively
It is designated as θ (l, d), l=1,2 ..., FS, d=1,2 ..., n × 2m-1；
Step 2.2
For l=1to Fs
The value of l-th of data set θ (l, d) is assigned to n [αi,1,αi,2,…,αi,2m-1]；
For i=1to n
ByConstruct wi；
ByDecorrelative transformation；
Calculate yi(t)=wix(t)；
Calculate
end
Calculate
end
T=1；
Step 2.3 iteration evolutionary operation
Step 2.3.1
For l=1to Fs
For d=1to n × 2m-1
By θnew(l, d)=θ (l, d)+rand [θ (l, d)-θ (r, d)] is calculated, and rand is the random number between [01], r
For in [1FS] between produce not be l random integers；
end
By l-th of data set θnewThe value of (l, d) is assigned to n [αi,1,αi,2,…,αi,2m-1]；
For i=1to n
ByConstruct wi；
ByDecorrelative transformation；
Calculate yi(t)=wix(t)；
Calculate
end
Calculate
if Jnew(l)>J(l)
J (l)=Jnew(l)；
By θnewThe value of (l, d) is assigned to θ (l, d)；
end
end
Step 2.3.2
Jglobal(t)=J (1)；
1st data set θ value is assigned to θglobal；
For l=2to Fs
if Jglobal(t)<J(l)
Jglobal(t)=J (l)；
L-th of data set θ value is assigned to θglobal；
end
end
Step 2.3.3
If t=1
T=t+1；
Return to step 2.3.1；
else
Calculate ε=Jglobal(t)-Jglobal(t-1)；
ifε<Δ
Skip to step 2.4；
else
T=t+1；
Return to step 2.3.1；
end
end
Step 2.4
Step 2.4.1 is by θglobalValue be assigned to n [αi,1,αi,2,…,αi,2m-1]；
Step 2.4.2
For i=1to n
ByConstruct wi；
ByDecorrelative transformation；
end
Step 2.4.3 is by n wiConstruct W=[w1,w2,…,wn], array response is obtained by the generalized inverse matrix for calculating W
Matrix.
As shown in figure 4, step 3：Estimate in target ship DOA orientation
Compare the difference of two row vectors adjacent in background technology Chinese style (3), it is seen that all differing one between them
Individual phase, if L1=[I(m-1)×(m-1)0(m-1)×1] and L2=[0(m-1)×1I(m-1)×(m-1)], it can obtain
Thus it is easy to get
ωi=jln [(L1ai)#L2ai] (10)
I=1,2 in formula ..., n.
Example：If λ s=2d, such as step 2 estimation are obtained
aiFor the i-th column vector of matrix A.
ω1=jln [(L1a1)#L2a1]=0.0548, θ1=arcsin (0.0548 λ s/2 π d)=1 °；
ω2=jln [(L1a2)#L2a2]=0.8131, θ1=arcsin (0.8131 λ s/2 π d)=15 °.
The above, only present pre-ferred embodiments, therefore the scope that the present invention is implemented can not be limited with this, i.e., according to
Equivalence changes and modification that scope of the present invention patent and description are made, all should still belong to the model that patent of the present invention covers
In enclosing.
Claims (1)
1. a kind of ship DOA direction estimation methods based on plural blind source separating, it is characterised in that：Comprise the following steps：
Step 1：Detectable region ships quantity estimation based on cross validation
Array received data are divided into two parts, a portion is used for the feature for extracting data, and other parts are used to verify this
A little features, propose the criterion of formula (5) and formula (6) for estimation detectable region ships quantity,
In formula, i=1,2 ..., m, trace () is Matrix Calculating mark computing, and C is array received data x covariance matrix C=C
=XXT,ΛiFor the diagonal matrix that diagonal element is i characteristic value before C, Ui column vector is its corresponding spy
Levy vector；And calculate'sDiagonal matrixDiagonal and ΛmBe intersect and two matrixes in diagonal
On element sequence be opposite；
Step 2：Array response pseudo inverse matrix estimation based on plural blind source separating
Do not know source signal and the parameter of unknown aliasing system is not being done in the case that any prior information assumes, find one
Individual optimal array response pseudo inverse matrix W so that W meets WA=I with array response matrix A, I is dimension of m m unit matrix, on
It is Hermitian transposition computings to mark " H " symbol；Remember Wi(i=1,2 ..., a n) column vector for being W, thenBy for the complex vector located of m dimension,WithIt is real number；Pass through
Solve n wiFinal also to obtain W, W is calculated and obtained by formula (7a)-(7d), (8)；
yi(t)=wix(t) (7b)
In formula, E [] is average computing, [αi,1,αi,2,…,αi,2m-1]∈[02π](2m-1)；In addition, in order to avoid producing two
Individual identical wi, using formula (8) come decorrelative transformation；
Step 3：Estimate in target ship DOA orientation
A phase is all differed between two adjacent row vectors of array response matrix, ifWithIt can obtain
Thus
ω1=j ln [(L1ai)#L2ai] (10)
I=1 in formula, 2 ..., n,
Array response pseudo inverse matrix estimation of the step 2 based on plural blind source separating comprises the following steps：
Step 2.1 sets convergence error value Δ；The data set of FS n × 2m-1 dimension is randomly generated between 0~2 π, is designated as respectively
θ (l, d), l=1,2 ..., FS, d=1,2 ..., n × 2m-1；
Step 2.2
L is set to 1 by step 2.2.1；
If step 2.2.2 l≤Fs, skip to step 2.2.3, step 2.2.8 is otherwise skipped to；
The value of l-th of data set θ (l, d) is assigned to n by step 2.2.3
I is set to 1 by step 2.2.4；
If step 2.2.5 i≤n, step 2.2.6 calculating will be performed, otherwise skip to step 2.2.7；
Step 2.2.6
ByConstruct wi；
ByDecorrelative transformation；
Calculate yi(t)=wix(t)；
Calculate
I=i+1；
Skip to step 2.2.5；
Step 2.2.7 is calculated
L=l+1；
Skip to step 2.2.2；
Step 2.2.8 t=1；
Step 2.3 iteration evolutionary operation
L is set to 1 by step 2.3.1.1；
If step 2.3.1.2 l≤Fs, skip to step 2.3.1.3, step 2.3.2 is otherwise skipped to；
D is set to 1 by step 2.3.1.3；
If step 2.3.1.4 d≤n × 2m-1, skip to step 2.3.1.5, step 2.3.1.6 is otherwise skipped to；
Step 2.3.1.5
By θnew(l, d)=θ (l, d)+rand [θ (l, d)-θ (r, d)] is calculated, and rand is random number between [01], r be
[1 FS] between produce not be l random integers；
D=d+1；
Skip to step 2.3.1.4；
Step 2.3.1.6
By l-th of data set θnewThe value of (l, d) is assigned to n
I is set to 1 by step 2.3.1.7；
If step 2.3.1.8 i≤n, step 2.3.1.9 calculating will be performed, otherwise skip to step 2.3.1.10；
Step 2.3.1.9
ByConstruct wi；
ByDecorrelative transformation；
Calculate yi(t)=wix(t)；
Calculate
I=i+1；
Skip to step 2.3.1.8；
Step 2.3.1.10 is calculated
Step 2.3.1.11
If Jnew(l)>J (l) is so
J (l)=Jnew(l)；
By θnewThe value of (l, d) is assigned to θ (l, d)；
L=l+1；
Skip to step 2.3.1.2
Step 2.3.2
Step 2.3.2.1 Jglobal(t)=J (1)；
1st data set θ value is assigned to θ by step 2.3.2.2global；
L is set to 2 by step 2.3.2.3；
If step 2.3.2.4 l≤Fs, step 2.3.2.5 calculating will be performed, otherwise skip to step 2.3.3；
Step 2.3.2.5
If Jglobal(t)<J (l) is so
Jglobal(t)=J (l)；
L-th of data set θ value is assigned to θglobal；
L=l+1；
Skip to step 2.3.2.4
Step 2.3.3
If t=1, then
T=t+1；
Return to step 2.3；
If t ≠ 1, then
Calculate ε=Jglobal(t)-Jglobal(t-1)；
If ε<Δ, then
Skip to step 2.4；
If ε >=Δ, then
T=t+1；
Return to step 2.3；
Step 2.4
Step 2.4.1 is by θglobalValue be assigned to n
Step 2.4.2
I is set to 1 by step 2.4.2.1；
If step 2.4.2.2 i≤n, step 2.4.2.3 calculating will be performed, otherwise skip to step 2.4.3；
Step 2.4.2.3
ByConstruct wi；
ByDecorrelative transformation；
I=i+1；
Skip to step 2.4.2.2；
Step 2.4.3 is by n wiConstruct W=[w1,w2,…,wn], obtain array response matrix by calculating W generalized inverse matrix.
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