CN104076324A - Method for estimating high-accuracy arrival direction without knowing information source number - Google Patents
Method for estimating high-accuracy arrival direction without knowing information source number Download PDFInfo
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- CN104076324A CN104076324A CN201410325063.4A CN201410325063A CN104076324A CN 104076324 A CN104076324 A CN 104076324A CN 201410325063 A CN201410325063 A CN 201410325063A CN 104076324 A CN104076324 A CN 104076324A
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- information source
- source number
- arrival direction
- autocorrelation matrix
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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
- G01S3/02—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 using radio waves
- G01S3/74—Multi-channel systems specially adapted for direction-finding, i.e. having a single antenna system capable of giving simultaneous indications of the directions of different signals
Abstract
The invention discloses a method for estimating a high-accuracy arrival direction without knowing an information source number. Time smoothing processing is carried out on data received by an antenna array by setting K different time smoothing intervals to built K space-time autocorrelation matrixes; a final combined space-time autocorrelation matrix and a spatial spectrum function of arrival direction estimation are calculated; spectrum peak searching is carried out on the spatial spectrum function by gradually changing the searching direction, and then the information source number and the arrival direction are estimated. By means of the method for estimating the high-accuracy arrival direction without knowing the information source number, the arrival direction of signals is estimated without estimating the information source number in advance or carrying out characteristic decomposition on the autocorrelation matrixes of the received signals. Thus, the method is high in reliability, small in workload and easy to achieve through hardware, and makes application of arrival direction estimation to an actual system possible.
Description
Technical field
The invention belongs to array signal process technique field, be specifically related to a kind of unknown information source number high precision Wave arrival direction estimating method.
Background technology
The direction of arrival of signal estimate be Array Signal Processing field major issue, through the development of decades, the method for estimation of a lot of direction of arrival has been proposed, such as the most classical MUSIC, the algorithm for estimating such as ESPRIT.But these algorithms rarely have and can be applied in actual scene, mainly contain the reason of two aspects, first, most of Wave arrival direction estimating method is all that hypothesis information source number is known, yet in actual conditions, information source number is unknown, this just need to pre-estimate information source number, and Estimation Methods for Source Number is also very immature; The second, these high-resolution Wave arrival direction estimating methods, need to carry out feature decomposition to receiving autocorrelation matrix, and this real-time processing to hardware brings very large challenge.
At present, known being applicable to unknown information source number Wave arrival direction estimating method, is mainly Capon method.Although the method not characteristics of needs is decomposed, spatial spectrum is proportional to the signal power of correspondence direction, implement also fairly simple, but be subject to the restriction of array aperture, angular resolution is lower, especially, the in the situation that of low signal-to-noise ratio and low fast umber of beats, compares with classical super-resolution MUSIC algorithm, performance gap is very large, is difficult to reach the requirement of real system.
Summary of the invention
To be solved by this invention is the problem that existing unknown information source number Wave arrival direction estimating method will be subject to the restriction of array aperture, a kind of unknown information source number high precision Wave arrival direction estimating method is proposed, the in the situation that of information source number the unknown, need not estimate that information source number just can estimate with higher precision the direction of arrival of signal, and need not carry out feature decomposition, calculated amount is reduced greatly, be convenient to hardware and realize.
For addressing the above problem, the present invention is achieved by the following technical solutions:
A unknown information source number high precision Wave arrival direction estimating method, comprises the steps:
Step 1: set K different time smoothing interval τ
k, and use respectively this K level and smooth interval τ
kremove aerial array received data to carry out time smoothing processing autocorrelation matrix R while building thus K sky
x(τ
k); K=1 wherein, 2 ... K, K;
Step 2: autocorrelation matrix F while 1. calculating final combination sky according to formula;
In formula, R
x(τ
k) for step 1 is constructed, go out empty time autocorrelation matrix,
for R
x(τ
k) conjugate transpose;
Step 3: 2. calculate the spatial spectrum function that direction of arrival is estimated according to formula
②
In formula, F is step 2 combination of calculating autocorrelation matrix when empty,
for the direction vector of aerial array a direction, φ and
be respectively position angle and the angle of pitch,
for
conjugate transpose;
Step 4: progressively change the direction of search and progressively change angle
spatial spectrum function to step 3 gained
carry out spectrum peak search; The number of the maximum point that this spectrum peak search searches out and the corresponding direction of these maximum points, be estimated information source number and direction of arrival.
In step 1, establishing aerial array received data is X (t), is smoothly spaced apart τ; Autocorrelation matrix R during gained empty after smoothing processing
x(τ) be:
R
x(τ)＝E[X(t)X
H(t-τ))] ③
In formula, X
h(t-τ) is the conjugate transpose of X (t-τ).
Described level and smooth interval τ
knumber K between 3～5.
Described level and smooth interval τ
knumber K be 3.
Compared with prior art, the present invention has following features:
1, the in the situation that of information source number the unknown, information source number need not be pre-estimated and just the direction of arrival of signal can be estimated reliably, and do not need autocorrelation matrix to received signal to carry out feature decomposition, therefore the method reliability is strong, calculated amount is little, be easy to hardware and realize, make direction of arrival estimate to be applied in real system to become possibility, the direction of arrival that can be applicable to any array is estimated;
2, utilize and receive the correlativity of useful signal self and the non-correlation of useful signal and noise in signal, adopt the method for time smoothing, while making the signal sky after processing, autocorrelation matrix is not affected by noise, therefore avoided solving of noise subspace or signal subspace, and when low signal-to-noise ratio, still there is reasonable performance;
3, need not carry out feature decomposition to autocorrelation matrix, calculated amount reduces greatly than other method, and what make hardware system is treated as possibility in real time, and in the situation that signal to noise ratio (S/N ratio) is lower, the method still can guarantee higher estimated accuracy;
4, the present invention is not subject to the restriction of receiving antenna formation, makes its application more extensive.
Accompanying drawing explanation
Fig. 1 is a kind of process flow diagram of unknown information source number high precision Wave arrival direction estimating method;
Fig. 2 is the sphere conformal array array antenna model that emulation is used;
Fig. 3 is the inventive method and MUSIC, Capon algorithm, 2-d direction finding is estimated relatively schematic diagram of root-mean-square error under the same conditions, incoming signal is [40 ° of two independent sources, 30 °] and [100 °, 10 °], fast umber of beats is 200, carries out 200 Monte Carlo experiments, Fig. 3 is information source [40 °, 30 °] evaluated error comparison under different signal to noise ratio (S/N ratio)s;
Fig. 4 is the inventive method and MUSIC, Capon algorithm, 2-d direction finding is estimated relatively schematic diagram of root-mean-square error under the same conditions, incoming signal is [40 ° of two independent sources, 30 °] and [100 °, 10 °], fast umber of beats is 200, carries out 200 Monte Carlo experiments, Fig. 4 is information source [100 °, 10 °] evaluated error comparison under different signal to noise ratio (S/N ratio)s;
Fig. 5 is the inventive method and MUSIC, Capon algorithm, 2-d direction finding is estimated relatively schematic diagram of root-mean-square error under the same conditions, incoming signal is [40 ° of two independent sources, 30 °] and [100 °, 10 °], signal to noise ratio (S/N ratio) is 25dB, carries out 200 Monte Carlo experiments, Fig. 5 is information source [40 °, 30 °] evaluated error comparison under the fast umber of beats of difference;
Fig. 6 is the inventive method and MUSIC, Capon algorithm, 2-d direction finding is estimated relatively schematic diagram of root-mean-square error under the same conditions, incoming signal is [40 ° of two independent sources, 30 °] and [100 °, 10 °], signal to noise ratio (S/N ratio) is 25dB, carries out 200 Monte Carlo experiments, Fig. 6 is information source [100 °, 10 °] evaluated error comparison under the fast umber of beats of difference.
Embodiment
The sphere conformal array array antenna model of Fig. 2 of take describes as example, and unknown information source number high precision Wave arrival direction estimating method of the present invention, as shown in Figure 1, comprises that step is as follows:
1, utilize M aerial receiver that is placed on sphere, form the conformal spherical array antenna of M unit.
Shown in Fig. 2, be M element array antenna, the radius of sphere carrier is r, and in figure, " * " represents array element, and θ is the angle that array element loca becomes with z axle positive dirction,
for the angle that array element loca becomes with x axle positive dirction, the position of m array element is
2, N incoherent same narrow band signal frequently incides array antenna.
Centre frequency is ω
0n uncorrelated with narrow band signal frequently respectively from
(i=1,2 ..., N) direction incides bay, wherein φ
iwith
the position angle and the angle of pitch that represent respectively i incoming signal, the popular matrix of array can be expressed as A so,
wherein
i=1,2 ..., N, γ
mibe that i signal arrives the time delay of reference point with respect to this signal to m array element,
c is the light velocity.
3, select K different time smoothing interval τ
kpair array antenna reception data are carried out time smoothing processing, autocorrelation matrix R while building thus K sky
x(τ
k).
Due to, the output data matrix X (t) of pair array: X (t)=AS (t)+W (t), carries out after smoothing processing, autocorrelation matrix R while obtaining not being subject to noise empty
x(τ): R
x(τ)=E[X (t) X
h(t-τ))]=AR
s(τ) A
h;
Wherein, A represents this array manifold matrix, and S (t) represents the signal phasor that N incoherent signal source forms, S (t)=[S
1(t) ..., S
n(t)]
h, W (t) represents the noise vector that M array element receives, W (t)=[W
1(t) ..., W
m(t)]
h, R
s(τ) autocorrelation matrix while representing empty after level and smooth of useful signal, R
s(τ)=E[S (t) S
h(t-τ)]=diag[r
1(τ) ..., r
n(τ)], wherein
Therefore,
1<k<K。In the present invention, the level and smooth interval τ setting
knumber K>=3, general K gets 3～5.In the preferred embodiment of the present invention, level and smooth interval τ
knumber K get 3.
Autocorrelation matrix F while 4, calculating final combination sky.
5, calculate the spatial spectrum function that direction of arrival is estimated.
the direction vector that represents corresponding this array a direction,
wherein
6, progressively change angle
to spatial spectrum function
carry out spectrum peak search, the direction that the resulting N of a spectrum peak search maximum point is corresponding can be used as direction of arrival estimated result; And the number N of maximal point is identical with information source number N.
Application conditions of the present invention is:
A. each information source average is zero, uncorrelated each other, has separately regular hour correlativity;
B. each reception array element additive noise is the white noise of zero-mean, uncorrelated each other;
C. any array, array number is M, information source number is N, and M>N.
Validity of the present invention can describe by following emulation:
1, simulated conditions and method:
Adopt the conformal spherical array antenna shown in Fig. 2, array number is that 5, two narrow band signals incide this array, and position angle and the angle of pitch of two signals is respectively [40 °, 30 °] and [100 °, 10 °], spectrum peak search angle intervals 0.1 degree.Carry out 200 Monte Carlo experiments, result is averaged, by the root-mean-square error of two dimension angular as evaluation index:
Wherein, J is experiment number.
2, emulation content and result:
Emulation 1, the inventive method and high-resolution MUSIC, unknown information source number Capon algorithm, under the same conditions, fast umber of beats is 200, variation along with signal to noise ratio (S/N ratio), 2-d direction finding is estimated root-mean-square error comparison, Fig. 3 and Fig. 4 represent respectively [40 ° of information sources, 30 °] and [100 ° of information sources, 10 °] evaluated error, from simulation result, can find out: the inventive method is under the condition of unknown information source number, and estimated accuracy and high-resolution MUSIC algorithm are very approaching, and performance is far longer than unknown information source number Capon algorithm.
Emulation 2, the inventive method and high-resolution MUSIC, unknown information source number Capon algorithm, under the same conditions, signal to noise ratio (S/N ratio) is 25dB, variation along with fast umber of beats, 2-d direction finding is estimated root-mean-square error comparison, Fig. 5 and Fig. 6 represent respectively [40 ° of information sources, 30 °] and the evaluated error of information source [100 °, 10 °], from simulation result, can find out: when low fast umber of beats, the estimated accuracy of algorithm of the present invention still can approach high-resolution MUSIC algorithm, and along with the increase of fast umber of beats, estimated accuracy is more and more higher, performance is obviously better than unknown information source number Capon method.
Claims (4)
1. a unknown information source number high precision Wave arrival direction estimating method, is characterized in that comprising the steps:
Step 1: set K different time smoothing interval τ
k, and use respectively this K level and smooth interval τ
kremove aerial array received data to carry out time smoothing processing autocorrelation matrix R while building thus K sky
x(τ
k); K=1 wherein, 2 ... K, K;
Step 2: autocorrelation matrix F while 1. calculating final combination sky according to formula;
In formula, R
x(τ
k) for step 1 is constructed, go out empty time autocorrelation matrix,
for R
x(τ
k) conjugate transpose;
Step 3: 2. calculate the spatial spectrum function that direction of arrival is estimated according to formula
②
In formula, F is step 2 combination of calculating autocorrelation matrix when empty,
for the direction vector of aerial array a direction, φ and
be respectively position angle and the angle of pitch,
for
conjugate transpose;
Step 4: progressively change the direction of search and progressively change angle
spatial spectrum function to step 3 gained
carry out spectrum peak search; The number of the maximum point that this spectrum peak search searches out and the corresponding direction of these maximum points, be estimated information source number and direction of arrival.
2. a kind of unknown information source number high precision Wave arrival direction estimating method according to claim 1, is characterized in that, in step 1, establishing aerial array received data is X (t), is smoothly spaced apart τ; Autocorrelation matrix R during gained empty after smoothing processing
x(τ) be:
R
x(τ)＝E[X(t)X
H(t-τ))] ③
In formula, X
h(t-τ) is the conjugate transpose of X (t-τ).
3. a kind of unknown information source number high precision Wave arrival direction estimating method according to claim 1 and 2, is characterized in that described level and smooth interval τ
knumber K between 3～5.
4. a kind of unknown information source number high precision Wave arrival direction estimating method according to claim 3, is characterized in that described level and smooth interval τ
knumber K be 3.
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Cited By (5)
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| CN107576947A (en) * | 2017-08-08 | 2018-01-12 | 西安电子科技大学 | L-type battle array based on time smoothing is to coherent estimating two-dimensional direction-of-arrival method |
| CN108414965A (en) * | 2018-06-05 | 2018-08-17 | 电子科技大学 | The signal source DOA estimation method of structure when based on the sky for going predelay module |
| CN113625220A (en) * | 2021-06-28 | 2021-11-09 | 台州学院 | New method for quickly estimating direction of arrival and diffusion angle of multipath signal |
| CN114007187A (en) * | 2021-10-29 | 2022-02-01 | 蓝色创源(北京)科技有限公司 | Information source direction judging method, device, system, equipment and readable storage medium |
| CN114186186A (en) * | 2020-09-15 | 2022-03-15 | 华为技术有限公司 | Matrix calculation method and related equipment |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107576947A (en) * | 2017-08-08 | 2018-01-12 | 西安电子科技大学 | L-type battle array based on time smoothing is to coherent estimating two-dimensional direction-of-arrival method |
| CN108414965A (en) * | 2018-06-05 | 2018-08-17 | 电子科技大学 | The signal source DOA estimation method of structure when based on the sky for going predelay module |
| CN114186186A (en) * | 2020-09-15 | 2022-03-15 | 华为技术有限公司 | Matrix calculation method and related equipment |
| CN114186186B (en) * | 2020-09-15 | 2023-08-04 | 华为技术有限公司 | Matrix calculation method and related equipment |
| CN113625220A (en) * | 2021-06-28 | 2021-11-09 | 台州学院 | New method for quickly estimating direction of arrival and diffusion angle of multipath signal |
| CN114007187A (en) * | 2021-10-29 | 2022-02-01 | 蓝色创源(北京)科技有限公司 | Information source direction judging method, device, system, equipment and readable storage medium |
| CN114007187B (en) * | 2021-10-29 | 2023-12-05 | 蓝色创源(北京)科技有限公司 | Information source direction judging method, device, system, equipment and readable storage medium |
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