CN104320205B - Sparse DOA algorithm for estimating in Spatial Doppler domain - Google Patents
Sparse DOA algorithm for estimating in Spatial Doppler domain Download PDFInfo
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- CN104320205B CN104320205B CN201410564367.6A CN201410564367A CN104320205B CN 104320205 B CN104320205 B CN 104320205B CN 201410564367 A CN201410564367 A CN 201410564367A CN 104320205 B CN104320205 B CN 104320205B
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Abstract
The present invention relates to the sparse DOA algorithm for estimating in a kind of Spatial Doppler domain, comprise the following steps：(1) the sparse DOA algorithm for estimating under CS frameworks；(2) signal intensity ymExtend to sparse angular domain and sparse Doppler domain；(3) in the sparse DOA algorithm for estimating of Doppler domain.On the basis of compressive sensing theory, the present invention has carried out detailed analysis and emulation to the DOA estimations under space angular domain and Doppler domain, has inquired into the correlated performance of multi-path antenna frequency spectrum perception.Sparse DOA is estimated in the range of Doppler frequency domain, resolution ratio is greatly improved compared to the estimated result in the past in time-domain, and the signal element needed has also been reduced.
Description
Technical field
The present invention relates in sparse angular domain and sparse Doppler domain, the compression frequency spectrum perception in the case of multi-antenna array
Algorithm.
Background technology
Method of estimation to ripple up to signal DOA (Direction Of Arrival) in the past several years is extensive
Applied to every field, such as radar, marine site traffic, underwater sound tracking and wireless communication field etc..Therefore on DOA estimations
Some algorithms also arise at the historic moment therewith, it is relatively common mainly to there are multiple signals to classify (Multiple Signal
Classification, MUSIC), minimum variance distortionless response (Minimum Variance Distortionless
Response, MVDR), the signal parameter changing method of maximum likelihood method (Maximum Likelihood) and invariable rotary
(Estimation of Signal Parameters via Rotational invariance techniques,ESPRIT)
Deng.But these methods generally require to know the prior information of signal number, but in the environment of the communication of current non-cooperating, nothing
Volatile growth is all presented in line equipment and the number of server, so the practicality of the above algorithm could be improved.
Compressed sensing (Compressed-Sensing, CS) can make to pass through as new a research method and means in recent years
Analyze the inherent sparse characteristic that signal is obtained at receiver, so that it may preferably improve the frequency spectrum perception performance of signal.If by CS
Technology is applied in DOA estimations, spacing wave hypotelorism can be equally solved well, the problem of fast umber of beats is less, and
The limitation caused by some method for parameter estimation can also be alleviated, such as common coherent signal and larger specimen support base etc.
Problem.
Estimation to DOA under CS theory supports would generally be related to two problems, i.e. spacing wave Power estimation and battle array
The selection of row flow pattern vector.
The content of the invention
For above mentioned problem of the prior art, the present invention is proposed in sparse angular domain and sparse Doppler domain, many days
Compression frequency spectrum perception in the case of linear array, joint sparse estimation is carried out using the angle sparse characteristic for receiving signal to DOA.
Sampling element considers the openness of frequency, so as to effectively mitigate the burden of whole communication system.In combination with Doppler frequency shift,
DOA under multi-path antenna battle array is estimated.
The present invention takes following technical scheme：Sparse DOA algorithm for estimating in Spatial Doppler domain, it is characterised in that bag
Include following steps：
Step 1: the sparse DOA algorithm for estimating under CS frameworks,
(1) there is L electromagnetic plane wave,Wherein, l=1 ... L,
Represent unknown signaling direction θlNumber,Represent projecting direction；
(2) for the narrow band signal of identical frequency, its incoming wave signal reaches the signal intensity after aerial arrayM is bay number, xmBe bay in the position of x-axis, f is antenna array
The effective length of member, nmIt is the additive Gaussian noise sample that average is zero on m-th of antenna；Above formula can be changed into y=A (θ) s+n,
Wherein y=[y1,y2,...,yM]T∈CM×1, θ=[θ1,θ2,...,θL], A (θ)=[a (θ1),a(θ2),...,a(θL)] be M ×
The array manifold vector of L dimensions, s=[W1,W2,...,WL]T∈CL×1, n=[n1,n2,...,nM]T∈CM×1, expansion is represented by
Step 2: by the signal intensity y described in step onemSparse angular domain and sparse Doppler domain are extended to,
(1) y=A (θ) s+n is subjected to Fourier transformation, obtains yf=Asf+nf, now sfAnd yfIt is sparse；
(2) for K non-zero signal, signal s is represented with ζfIn certainty performance number corresponding to per a line unknown parameter
Or energy value, the estimation process for obtaining DOA is as follows：A) L=k=1 is made；B) ζ is worked asn≠ 0, and θL=θkWhen, L=L+1；If c) k
＜ K, then k=k+1, while being back to step b)；Otherwise DOA calculating process is exited；
(3) number of winning the confidence yfBlock row signal, the sparse signal of needs, wherein non-zero signal are recovered from each row block
I.e. required DOA estimates；
Step 3: sparse DOA algorithm for estimating,
(1) for the K narrow band signal from far field, the signal s=[W at receiver1,W2,...,WL]TFor sparse square
Battle array, n=[n1,n2,...,nM]TFor noise matrix, due to only having K row elements to be not zero in signal s, y=As+n=[y
(t1),...,y(tM)] signal s MMV problems are represented by searching y joint sparse.
(2) object function of MMV problems isWhereinWork as p=2, during q=0, can be written as
(3) define It can obtain：Making an uproar
Under environment,During noiseless,It can obtainWherein combining row sparse matrix isThereforeFurther turn
Turn to
It is preferred that, λ values are 0.5 in step 3 (3).
Compared with prior art, the present invention has advantages below and beneficial effect：On the basis of compressive sensing theory, this hair
The bright DOA estimations under space angular domain and Doppler domain have carried out detailed analysis and emulation, have inquired into multi-path antenna frequency spectrum sense
The correlated performance known.Sparse DOA is estimated in the range of Doppler frequency domain, compared to estimation knot in the past in time-domain
Fruit greatly improves resolution ratio, and the signal element needed has also been reduced.Analysis result understands the L2 in use, during 0 algorithm,
Good DOA estimation performances can be also obtained when signal number increased in actual environment emulation, compared to classics
MUSIC algorithms, L2, MSE result of the 0-DOA algorithm for estimating under different noises reaches unanimity substantially, illustrates L2,0 algorithm for estimating
Have to the noise jamming in test environment insensitive, there is higher robustness.
Brief description of the drawings
Fig. 1 is line style adaptive antenna array；
Fig. 2 is the sparse DOA power spectrum charts that information source number is 6；
Fig. 3 is the Broadband DOA Estimation energy spectrogram under horizontal view angle；
Fig. 4 is the Broadband DOA Estimation energy spectrogram under any observation angle in space；
DOA evaluated error analysis results when Fig. 5 is SNR=-10dB；
DOA evaluated error analysis results when Fig. 6 is SNR=-4dB.
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 present invention is analyzed for the linear antenna array shown in Fig. 1, specifically includes following operating procedure：
Step one：Spacing wave s is sent, spacing wave has sparse characteristic, is not required to carry out rarefaction to it again in itself.
Step 2：For the spacing wave s of transmission, obtain receiving signal y=As+n, array manifold accordingly in receiving terminal
The calculation matrix Φ (being also regarded as perceiving matrix Θ) that matrix A is equivalent under compressed sensing, array similar with calculation matrix Φ
Flow pattern matrix A is also required to meet some requirements, and n is to meet zero-mean, and variance is σ2Additive white Gaussian noise, channel meet
Gaussian Profile fσ(h)=exp (- h2/2σ2)。
Step 3：Y=As+n is subjected to Fourier transformation, its frequency domain representation mode is obtained, in frequency domain, to signal
Detected, extracted and recovered, wherein recover the process of signal mainly by L2,0 algorithm is realized.
Step 4：Bandpass filter group is setHwIt it is one using analog frequency w as digital center frequency
Narrow band filter, generally take b=0.99, reduce filter bandwidht while, additionally it is possible to ensure the stability of system.Then
Analyze the DOA estimations under broadband.
Step 5：Signal to noise ratio snr threshold value is set, the DOA estimated power spectrum density in the case of different SNR is analyzed.
With reference to the embodiment in above-mentioned steps, simulating, verifying is carried out to effectiveness of the invention as follows：
Receiving antenna array is even linear array, and array element number is 8, and array element spacing is half-wavelength, and fast umber of beats is 100, and noise is
Additive white Gaussian noise.Fig. 2 gives the sparse DOA estimations figure that information source number is 6, using L2, and 0-DOA algorithm for estimating can be accurate
The peak in actual channel is really measured, and does not produce other peak interferences, this is for obtaining concrete signal at receiver
And it is highly important it to be sampled, quantified, is encoded etc., the energy that whole system handles useful signal can be effectively increased
Power, has saved every cost.What Fig. 3 was represented is the horizontal view angle Broadband DOA Estimation after bandpass filter is set up.In receiver
Place can clearly detect the signal at -10 °, -30 ° and 30 ° very much, be not detect it in other angular positions
Its signal, that is, it is substantially not present other interference.Fig. 4 is shown in planar perspective space diagram, except can accurately obtain signal
Position outside, can also substantially find out it is determined that in angle signal substantially distribution situation, so as to preferably to ripple up to letter
Number analyzed and discussed, it is very important in real-time DOA tests.Fig. 5 is observed, when noise is -10dB, Ke Yifa
Existing, the angle detection and localization of signal is not highly desirable, there is more interference signal and error is larger, however when SNR for-
The signal that can be just positioned exactly during 4dB at 80 ° of azimuths is transmission signal, reduces the error of DOA estimations, such as schemes
Shown in 6.
Above is the better embodiment of the present invention, but protection scope of the present invention not limited to this.It is any to be familiar with this area
Technical staff disclosed herein technical scope in, the conversion or replacement expected without creative work should all be covered
Within protection scope of the present invention.Therefore the protection domain that protection scope of the present invention should be limited by claim is defined.
Claims (2)
1. the sparse DOA estimation method in Spatial Doppler domain, it is characterised in that comprise the following steps：
Step 1: the sparse DOA algorithm for estimating under CS frameworks,
(1) there is L electromagnetic plane wave,Wherein, l=1 ... L, represent not
Know sense θlNumber,Represent projecting direction；
(2) for the narrow band signal of identical frequency, its incoming wave signal reaches the signal intensity after aerial arrayM is bay number, xmBe bay in the position of x-axis, f is antenna array
The effective length of member, nmIt is the additive Gaussian noise sample that average is zero on m-th of antenna；Above formula can be changed into y=A (θ) s+n,
Wherein y=[y1,y2,...,yM]T∈CM×1, θ=[θ1,θ2,...,θL], A (θ)=[a (θ1),a(θ2),...,a(θL)] be M ×
The array manifold vector of L dimensions, s=[W1,W2,...,WL]T∈CL×1, n=[n1,n2,...,nM]T∈CM×1, expansion is represented by
Step 2: by the signal intensity y described in step onemSparse angular domain and sparse Doppler domain are extended to,
(1) y=A (θ) s+n is subjected to Fourier transformation, obtains yf=Asf+nf, now sfAnd yfIt is sparse；
(2) for K non-zero signal, signal s is represented with ζfIn certainty performance number corresponding to per a line unknown parameter or energy
Value, the estimation process for obtaining DOA is as follows：A) L=k=1 is made；B) ζ is worked asn≠ 0, and θL=θkWhen, L=L+1；If c) k ＜ K, together
When be back to step b)；Otherwise DOA calculating process is exited；
(3) number of winning the confidence yfBlock-shaped signal, the sparse signal of needs is recovered from each row block, needed for wherein non-zero signal is
The DOA estimates wanted；
Step 3: sparse DOA algorithm for estimating design,
(1) for the K narrow band signal from far field, the signal s=[W at receiver1,W2,...,WL]TFor sparse matrix, n=
[n1,n2,...,nM]TFor noise matrix, due to only having K row elements to be not zero in signal s, y=As+n=[y (t1),...,
y(tM)] signal s MMV problems are represented by searching y joint sparse；
(2) object function of MMV problems isWhereinWork as p=2, q=0, can be written as
(3) defineIt can obtain：In ring of making an uproar
Under border,During noiseless,It can obtainWherein combining row sparse matrix isThereforeFurther turn
Turn to
2. the sparse DOA estimation method in Spatial Doppler domain according to claim 1, it is characterised in that the step
λ values are 0.5 in three (3).
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