CN109444807A - A kind of single snap method for estimating signal wave direction out of place suitable for any linear array - Google Patents
A kind of single snap method for estimating signal wave direction out of place suitable for any linear array Download PDFInfo
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Abstract
The invention discloses a kind of single snap method for estimating signal wave direction out of place suitable for any linear array, belong to array signal processing technology.The present invention obtains the signal direction of arrival initial estimate being located on candidate lattices for single signal Mutual coupling out of place according to single snap array element data first, and obtains corresponding array steering vector accordingly；The orthogonal subspaces of the subspace of computing array steering vector；Feature decomposition is done to orthogonal subspaces, obtains the feature vector corresponding to nonzero eigenvalue；The angle value that will deviate from grid is corrected signal direction of arrival initial estimate as estimation parameter, obtains final direction of arrival.Using single method for estimating signal wave direction out of place, the Mutual coupling value and estimation amplitude of k-th signal in signal how out of place are obtained.The present invention can use any linear array, can obtain the accurate estimation of single signal out of place and signal direction of arrival how out of place.
Description
Technical field
The invention belongs to array signal processing technologies, and in particular to a kind of single snap suitable for any linear array is out of place
Method for estimating signal wave direction.
Background technique
Mutual coupling is always the Hot Contents of array signal processing, is had in fields such as communication, radar and sonars
It is widely applied.The invariable rotary sub-space technique of traditional multiple signal classification method and Signal parameter estimation has had higher
Estimation performance, but these algorithms are all based on and carry out on the basis of Eigenvalues Decomposition operation, and often in order to obtain
Good estimation performance needs a large amount of number of snapshots, can not be effectively applied to single snap situation, this is in actual engineer application
In it is not-so-practical.
In actual signal environment, high-speed moving object is high to the requirement of real-time of system, and the valid data received are only
There is snapshot data several times, the DOA estimation algorithm based on a large amount of snapshot datas is unable to satisfy under existing hardware system situation
Actual needs, carrying out Mutual coupling using single snapshot data thus becomes a solution.Have in array received data
Under the premise of limit, targeted cache movement, the real-time processing to target, and Mutual coupling with higher essence may be implemented
Degree, can provide technical support for the positioning and tracking of high-speed moving object.
With the rise of compressed sensing technology, sparse representation theory is gradually applied in Mutual coupling.It is dilute in application
Before dredging representation theory progress Mutual coupling, need to be divided at equal intervals in angle domain to construct fine excessively complete word
Allusion quotation, therefore, these DOA estimation algorithms based on rarefaction representation can only be estimated to be located on complete dictionary atom grid
Signal.(signal out of place is defined as) when the direction of arrival of signal is not located on grid, and the estimated accuracy of this kind of algorithm will sharply
Decline.Therefore the sparse reconstruction of signal out of place receives significant attention.
Linear array has extensive purposes in array treating process.Even linear array structure is simple, convenient for analysis and research.In battle array
In the case that first number is equal, compare even linear array, Nonuniform Linear Array can array extending as far as possible aperture, obtain it is higher from
By spending.Therefore, in practical applications, this just needs to find the Wave arrival direction estimating method for adapting to any linear array as far as possible.
Summary of the invention
In view of the actual demand of the limitation of single snapshot data and signal Mutual coupling out of place in practice, the present invention is used
Any linear array proposes a kind of single snap method for estimating signal wave direction out of place suitable for any linear array, for practical limited item
Signal Mutual coupling under part provides key technology.Any linear array includes even linear array and Nonuniform Linear Array.
A kind of single snap method for estimating signal wave direction out of place suitable for any linear array provided by the invention, including it is right
In single signal Mutual coupling out of place and for signal Mutual coupling how out of place.For the single signal out of place
Mutual coupling includes the following steps:
Step 1: receiving single snap array element data, is located at according to single snap array element data using Beamforming Method
Signal direction of arrival initial estimate on candidate lattices；
Step 2: according to signal direction of arrival initial estimate, corresponding array steering vector is obtained；
Step 3: the orthogonal subspaces of the subspace of the array steering vector is calculated；
Step 4: doing feature decomposition to orthogonal subspaces, obtains the feature vector corresponding to nonzero eigenvalue；
Step 5: array steering vector corresponding with signal direction of arrival initial estimate and feature vector are bonded
New matrix Fa, utilize matrix FaThe orthogonality of middle array steering vector and feature vector, the angle value that will deviate from grid, which is used as, to be estimated
Meter parameter is corrected signal direction of arrival initial estimate, obtains final direction of arrival.
For the signal Mutual coupling how out of place, include the following steps:
Step 1: assuming there be K signal, K is greater than 2.Position is obtained using Beamforming Method according to single snap array element data
In each signal direction of arrival initial estimate on candidate lattices；
Step 2: according to each signal direction of arrival initial estimate and single snap array element data, using Wave beam forming side
Method estimates signal amplitude, obtains each signal estimation amplitude；
Step 3: by the corresponding array steering vector of the direction of arrival initial estimate of preceding K-1 signal and each signal
Estimation amplitude is multiplied the array element data of K-1 signal before obtaining；
Step 4: cutting the array element data of preceding K-1 signal from received single snap array element data, k-th letter is obtained
Number array element data obtain the Mutual coupling value of k-th signal using single method for estimating signal wave direction out of place.
Step 5: according to the array element data of the Mutual coupling value of k-th signal and k-th signal, using wave beam shape
At the amplitude of method estimation k-th signal, the estimation amplitude of k-th signal is obtained；
And so on, the Mutual coupling value and estimation amplitude of K signal are obtained, then follow back and forth three times in " z " font
Ring corrects the angle and amplitude of all signals.
The present invention has the advantages that
1, the present invention is suitable for single snap method for estimating signal wave direction out of place of any linear array, can use any line
Battle array, under conditions of single snapshot data, accurately estimates signal out of place, is the signal direction of arrival under practical limited conditions
Estimation provides key technology.
2, the present invention is suitable for single snap method for estimating signal wave direction out of place of any linear array, can not only obtain list
The accurate estimation of one signal direction of arrival out of place can also accurately estimate signal direction of arrival how out of place.
Detailed description of the invention
Figure 1A is the single method for estimating signal wave direction flow chart out of place of single snap that the present invention is suitable for any linear array.
Figure 1B is single snap method for estimating signal wave direction flow chart how out of place that the present invention is suitable for any linear array.
Fig. 2 is 8 antenna even linear array schematic diagrames.
Fig. 3 is single signal mean square error out of place under 8 antenna even linear arrays with signal-to-noise ratio change curve.
Fig. 4 is 32 antenna even linear array schematic diagrames.
Fig. 5 is lower three signal mean square errors out of place of 32 antenna even linear arrays with signal-to-noise ratio change curve.
Fig. 6 is 8 antenna Nonuniform Linear Array schematic diagrames.
Fig. 7 is single signal mean square error out of place under 8 antenna Nonuniform Linear Arrays with signal-to-noise ratio change curve.
Fig. 8 is 32 antenna Nonuniform Linear Array schematic diagrames.
Fig. 9 is lower three signal mean square errors out of place of 32 antenna Nonuniform Linear Arrays with signal-to-noise ratio change curve.
Specific embodiment
The present invention is described in further detail below in conjunction with the accompanying drawings.
A kind of single snap method for estimating signal wave direction out of place suitable for any linear array provided by the invention, such as Figure 1A
It is shown, for single signal Mutual coupling out of place, the specific steps are as follows:
Step 1: receiving single snap array element data, is located at according to single snap array element data using Beamforming Method
Signal direction of arrival initial estimate on candidate lattices.
If single snap array element data are y=a (θ) s1+ n, θ are signal incident angle, and array steering vector a (θ) isWherein, c1,c2,...,cNRepresent N root bay position, s1It is determined for real value
Property signal, n is white Gaussian noise.X=Fy is obtained using Beamforming Method to single snap array element data, F is M × N-dimensional matrix,
Array element (p, q) is in matrix FP=1 ..., M, q=1 ..., N.Single snap array element data are used
P-th of array element data of Beamforming Method are as follows:
The position for occurring peak value in x is denoted as pini, signal direction of arrival initial estimate is obtained according to peak position:
Step 2: according to signal direction of arrival initial estimate, corresponding array steering vector is obtained:
Step 3: the orthogonal subspaces of the subspace of this array steering vector is calculated:
I is N × N-dimensional unit matrix.
Step 4: doing feature decomposition to orthogonal subspaces, obtains the feature vector corresponding to N-1 nonzero eigenvalue
a2,…,aN。
Step 5: array steering vector corresponding with signal direction of arrival initial estimate and feature vector are bonded
New matrix Fa=[a1,a2,…aN], utilize matrix FaThe orthogonality of middle array steering vector and feature vector, will deviate from grid
Angle value η as estimation parameter signal direction of arrival initial estimate is corrected.
Definition vector z=[1,0 ..., 0]T.Correction course are as follows:
Φ (η) y=Faz (4)
Wherein, correction matrix isAssuming that the amplitude of real value deterministic signal is
1, i.e. s1=1.
In muting situation, formula (4) is write as matrix form:
The angle value η that will deviate from grid is used as estimation parameter to signal direction of arrival initial estimate θiniIt is corrected, obtains
To signal Mutual coupling value:
For signal Mutual coupling how out of place, the specific steps are as follows:
Step 1: assuming there be K signal, is obtained according to single snap array element data using Beamforming Method and be located at candidate net
Each signal direction of arrival initial estimate on lattice.
Single snap array element data are y=As+n, array manifold matrix A are as follows: A=[a (θ1),...a(θK)], wherein θ=
[θ1,...,θK] be K signal incident angle, the array steering vector a (θ of k-th of signalk) bec1,c2,...,cNN root bay position is represented, K × 1 ties up real value and determines
Property signal s=[s1,s2,...sK], n is white Gaussian noise.X=is obtained using Beamforming Method to single snap array element data
Fy, F are M × N-dimensional matrix, and array element (p, q) is in matrix FP=1 ..., M, q=1 ..., N.To list
Snap array element data use the data of p-th of array element of Beamforming Method are as follows:
Wherein, skFor the amplitude of k-th of signal.
The position for occurring K peak value in x is denoted asK signal direction of arrival is obtained according to peak position initially to estimate
Evaluation:
Step 2: estimating signal using Beamforming Method according to signal direction of arrival initial estimate and array element data
Amplitude obtains estimation amplitude:
Step 3: by the corresponding array steering vector of preceding K-1 signal direction of arrival initial estimate and estimation amplitude phase
The multiplied array element data to preceding K-1 signal:
Step 4: cutting the array element data of preceding K-1 signal from received original array element data, k-th signal is obtained
Array element data yK=y-y(K-1), using single method for estimating signal wave direction out of place, obtain the direction of arrival of k-th signal
Estimated value:
According to k-th signal direction of arrival initial estimate, corresponding array steering vector is obtained:
Calculate the orthogonal subspaces of the subspace of this array steering vector:I is N × N-dimensional
Unit matrix.
Feature decomposition is done to orthogonal subspaces, obtains the feature vector corresponding to N-1 nonzero eigenvalue
Array steering vector corresponding with k-th signal direction of arrival initial estimate and feature vector are bonded newly
MatrixUtilize matrixThe orthogonality of middle array steering vector and feature vector, will be inclined
The angle value η of off-network lattice is corrected signal direction of arrival initial estimate as estimation parameter:
Wherein, [1,0 ..., 0] vector z=Τ.Correction matrix isyKFor K
The array element data of a signal,New matrix is bonded for the array steering vector and feature vector of k-th signal.
In muting situation, formula (11) is write as matrix form:
The angle value η that will deviate from grid is used as estimation parameter to signal direction of arrival initial estimateIt is corrected, obtains
To k-th signal Mutual coupling value
Step 5: according to the array element data of the Mutual coupling value of k-th signal and k-th signal, using wave beam shape
The estimation amplitude of k-th signal is obtained at method:
Thus the Mutual coupling value and estimation amplitude of K signal are obtained, then cyclic corrects three times in " z " font
The direction of arrival and amplitude of all signals.
Embodiment:
To verify correctness of the invention, related emulation experiment has been carried out.Single signal Mutual coupling out of place is imitated
The even linear array of 8 antennas is used in true experiment as shown in Fig. 2, element position is with the half of information source wavelengthFor unit.Signal
Incident angle is 30.5 °, signal amplitude 1.Number of snapshots are 1.Using mean square error as measurement standard:
The curve that mean square error changes with signal-to-noise ratio is as shown in figure 3, the statistics that simulation result is 200 Monte Carlo experiments
As a result.As the result is shown when signal-to-noise ratio is greater than 5dB, mean square error approaches carat Mei Lao circle, there is higher estimated accuracy.It is more
The even linear array of 32 antennas is used in the emulation experiment of signal Mutual coupling out of place as shown in figure 4, element position is to believe
The half of source wavelengthFor unit.3 incoherent signal incident angles are 30.5 °, and 60.5 °, 80.5 °, signal amplitude is 1.
Number of snapshots are 1.Mean square error is as shown in Figure 5 with the curve that signal-to-noise ratio changes.Simulation result is the system of 200 Monte Carlo experiments
Count result.As the result is shown in the case that signal-to-noise ratio be greater than 0dB, the mean square error of three signals approaches carat Mei Lao circle, have compared with
High estimated accuracy.
In the emulation experiment of single signal Mutual coupling out of place using 8 antennas Nonuniform Linear Array as shown in fig. 6,
Element position is with the half of information source wavelengthFor unit.Signal incident angle is 30.5 °, signal amplitude 1.Number of snapshots are 1.?
The curve that square error changes with signal-to-noise ratio is as shown in fig. 7, the statistical result that simulation result is 200 Monte Carlo experiments.As a result
Signal-to-noise ratio is shown in greater than in the case of 5dB, mean square error approaches carat Mei Lao circle, there is higher estimated accuracy.Signal mostly out of place
The Nonuniform Linear Array of 32 antennas is used in the emulation experiment of Mutual coupling as shown in figure 8, element position is with information source wavelength
HalfFor unit.3 incoherent signal incident angles are 30.5 °, and 60.5 °, 80.5 °, signal amplitude is 1.Number of snapshots
It is 1.Mean square error is as shown in Figure 9 with the curve that signal-to-noise ratio changes.Simulation result is the statistics knot of 200 Monte Carlo experiments
Fruit.As the result is shown when signal-to-noise ratio is greater than 0dB, the mean square error of three signals approaches carat Mei Lao circle, has higher
Estimated accuracy.
According to analogous diagram, it can be seen that, the present invention is suitable for any linear array.Even if in the case where bay number is less,
The present invention proposes that the mean square error of method remains to approach carat Mei Lao circle, algorithm estimated accuracy still with higher.Meanwhile this
The method that invention proposes whether can accurately be estimated have and compare reason to single signal out of place or to signal how out of place
The estimation performance thought.
Claims (2)
1. a kind of single snap method for estimating signal wave direction out of place suitable for any linear array, it is characterised in that: including for
Single signal Mutual coupling out of place and for signal Mutual coupling how out of place；For the single signal wave out of place
Up to direction estimation, include the following steps:
Step 1: single snap array element data are received, is obtained according to single snap array element data using Beamforming Method and is located at candidate
Signal direction of arrival initial estimate on grid；
Step 2: according to signal direction of arrival initial estimate, corresponding array steering vector is obtained；
Step 3: the orthogonal subspaces of the subspace of the array steering vector is calculated；
Step 4: doing feature decomposition to orthogonal subspaces, obtains the feature vector corresponding to nonzero eigenvalue；
Step 5: array steering vector corresponding with signal direction of arrival initial estimate and feature vector are bonded new
Matrix Fa, utilize matrix FaThe orthogonality of middle array steering vector and feature vector will deviate from the angle value of grid as estimation ginseng
Several pairs of signal direction of arrival initial estimates are corrected, and obtain final direction of arrival；
For the signal Mutual coupling how out of place, include the following steps:
Step 1: assuming there be K signal, K is greater than 2；It obtains to be located at using Beamforming Method according to single snap array element data and wait
Each signal direction of arrival initial estimate on network selection lattice；
Step 2: being estimated according to each signal direction of arrival initial estimate and single snap array element data using Beamforming Method
Signal amplitude is counted, each signal estimation amplitude is obtained；
Step 3: the corresponding array steering vector of the direction of arrival initial estimate of preceding K-1 signal and each signal are estimated
Amplitude is multiplied the array element data of K-1 signal before obtaining；
Step 4: cutting the array element data of preceding K-1 signal from received single snap array element data, k-th signal is obtained
Array element data obtain the Mutual coupling value of k-th signal using single method for estimating signal wave direction out of place；
Step 5: according to the array element data of the Mutual coupling value of k-th signal and k-th signal, using Wave beam forming side
Method estimates the amplitude of k-th signal, obtains the estimation amplitude of k-th signal；
The Mutual coupling value and estimation amplitude of K signal are obtained as a result, then cyclic corrects institute three times in " z " font
There are the angle and amplitude of signal.
2. a kind of single snap method for estimating signal wave direction out of place suitable for any linear array according to claim 1,
It is characterized by: correction described in step 5, specific correction course are,
Definition vector z=[1,0 ..., 0]T:
Φ (η) y=Faz (4)
Wherein, correction matrix isAssuming that the amplitude of real value deterministic signal is 1, i.e. s1
=1；
In muting situation, formula (4) is write as matrix form:
The angle value η that will deviate from grid is used as estimation parameter to signal direction of arrival initial estimate θiniIt is corrected, obtains letter
Number Mutual coupling value:
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| WO2018076072A1 (en) * | 2016-10-28 | 2018-05-03 | Macquarie University | Direction of arrival estimation |
| CN108445462A (en) * | 2018-02-05 | 2018-08-24 | 江苏大学 | A kind of DOD and DOA estimation method of the bistatic MIMO radar based on management loading |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018076072A1 (en) * | 2016-10-28 | 2018-05-03 | Macquarie University | Direction of arrival estimation |
| CN108445462A (en) * | 2018-02-05 | 2018-08-24 | 江苏大学 | A kind of DOD and DOA estimation method of the bistatic MIMO radar based on management loading |
Non-Patent Citations (3)
| Title |
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| BO LIN 等: "SUPER-RESOLUTION DOA ESTIMATION USING SINGLE SNAPSHOT VIA COMPRESSED SENSING OFF THE GRID", 《IEEE》 * |
| ZAI YANG 等: "Off-Grid Direction of Arrival Estimation Using Sparse Bayesian Inference", 《IEEE TRANSACTIONS ON SIGNAL PROCESSING》 * |
| 李根 等: "Khatri-Rao积变换下的离格信号DOA估计", 《电讯技术》 * |
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