CN110531311A - A kind of LTE external illuminators-based radar DOA estimation method based on matrix recombination - Google Patents
A kind of LTE external illuminators-based radar DOA estimation method based on matrix recombination 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
- 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
- G01S3/14—Systems for determining direction or deviation from predetermined direction
Abstract
The invention discloses a kind of LTE external illuminators-based radar DOA estimation methods based on matrix recombination, it is contemplated that coherent signal source problem is simultaneously handled using matrix recombination method, thus the coherence between removing signal source.The technical scheme adopted by the invention is that: the Toeplitz property by restoring signal covariance matrix realizes the decoherence to signal, and then the azimuth information of coherent signal in airspace is accurately estimated, it makes use of the Toeplitz properties of cross-correlated signal covariance matrix.Compared with the conventional method, the present invention has the advantages that arithmetic speed is fast, real-time is good, and estimated accuracy is high, can promote radar system detection performance, very significant for LTE external illuminators-based radar practical application.
Description
Technical field
The invention belongs to external illuminators-based radar technical fields, more particularly, to a kind of LTE external radiation based on matrix recombination
Source radar DOA estimation method.
Background technique
So-called external illuminators-based radar is also referred to as passive radar, chance radar etc., compared to the Active Radar system of traditional system
System, the reception system of external illuminators-based radar is completely passive, any electromagnetic wave of non-radiating, but passes through reception and processing target
The radio wave propagated in space of non-cooperation irradiation source of reflection extracts Delay, Doppler frequency and the incoming wave of target
The parameters such as direction, to realize the detection, positioning and tracking to target.Third party used in it irradiates source signal and belongs to non-conjunction
Make signal, it is many kinds of using radiation source, such as mobile communication signal, broadcast singal, digital audio and video signals, GPS signal.
Therefore, external radiation source radar system possesses good concealment, cheap cost, less frequency spectrum resource waste, wide letter
The covering of number airspace.Based on this, external illuminators-based radar application value with higher and meaning are studied.
In recent years, the extensive use of 4G signal of communication, that is, LTE signal causes the strong interest of radar detection circle scholar.It
Belong to one kind of wireless communication signals.It supports the big bandwidth of 1.4~20MHz；Compared with GSM and other signals, it has more
High distance resolution；Two kinds of dual-modes (FDD and TDD) of big band limits and support of 800-3500MHz, are able to achieve state
Interior and international scope LTE signal practical growth covers, and external illuminators-based radar is made to be configured as possibility.In addition, LTE is using orthogonal
Frequency division multiple access (OFDMA) guarantees the low sidelobe of ambiguity function, and just because of its unique advantage, more and more radars both at home and abroad are ground
The person of studying carefully begins to focus on the external radiation source radar system based on LTE signal.
It is carried out in target acquisition in external illuminators-based radar, target angle estimation is very important a function, DOA, that is, wave
Direction up to direction, when referring to electromagnetic wave incident to array antenna.DOA estimation is estimated that the incoming wave side of target and clutter
To, for monitoring channel in Adaptive beamformer and null filtering azimuth information is provided, be conducive at subsequent array signal
Reason.
Multiple signal classification (MUSIC) algorithm is classical DOA algorithm for estimating, and principle is to go to handle using feature decomposition
The covariance matrix of output data is computed the signal subspace and noise subspace that can must have orthogonality relation, according to them
Between this relationship establish space spectral function, find the peak value of spectrum, the DOA of signal can be estimated.
But MUSIC algorithm is primarily directed to incoherent signal.However, external illuminators-based radar of the work in complex environment,
Multipath effect in environment may generate multipath clutter and be monitored aerial array capture, such clutter with different direction of arrival
Between certain in time delay, cause it relevant.Furthermore it can also be made when some same frequency noise signals are deliberately arranged in enemy
It is concerned between signal.Relevant signal can be merged into a signal, the independent signal number meeting for causing monitoring aerial to receive
It tails off, the covariance matrix R of input signal is no longer invertible matrix, and signal subspace energy leakage is made into noise subspace
It fails at traditional MUSIC algorithm, just can not obtain accurate azimuth information.
For the DOA estimation in coherent signal source, front-rear space smooth algorithm is mostly used at present, is substantially reduction input
The order of signal covariance matrix is until equal with information source number N.It is by even linear array to divide in a manner of slip backward forward
At multiple overlapped subarrays, the covariance matrix of each subarray is first found out respectively, then it is averaged, is finally used
This mean value removes the covariance matrix in replacement MUSIC algorithm, obtains space smoothing covariance matrix after forward direction finally.Although should
Algorithm has good decorrelation energy, but sacrifices effective aperture, and distinguishable information source sum is caused to tail off.
In order to solve above-mentioned defect problem, the present invention studies a kind of Toeplitz (Conjugate reset based on conjugation
Rearrangement-Toeplitz, CR-Toeplitz) matrix reassembly algorithm, by restoring reference signal and monitoring signals
The Toeplitz property of covariance matrix realizes the decoherence to signal, and then accurately estimates signal source orientation in airspace and believe
Breath.
Summary of the invention
MUSIC angle-of- arrival estimation algorithm is caused due to complicated multipath bring coherent signal source for external illuminators-based radar
Problem of Failure, the invention proposes the decoherence methods in external illuminators-based radar coherent signal source.
The technical scheme adopted by the invention is that: a kind of estimation side LTE external illuminators-based radar DOA based on matrix recombination
Method, for the coherence problems of monitoring channel receiving signal, by the Toeplitz property realization pair for restoring signal covariance matrix
The decoherence of signal obtains pure reference signal using external illuminators-based radar reference channel, is carried out using matrix recombination method
Processing, and then the azimuth information of coherent signal in airspace accurately is estimated, so that the coherence between signal source is removed, to guarantee
The validity of DOA estimation method.Its overall procedure as shown in Figure 1, specifically includes the following steps:
Step 1, signal is received to LTE external illuminators-based radar to model, obtain monitoring array signal expression formula and reference
Channel signal expression formula, and reference channel signal is reconstructed to obtain pure reference signal；
Step 2, cross-correlation is carried out by clean reference signal obtained in step 1 and per monitoring array channel signal all the way,
Obtain cross-correlation matrix function；
Step 3, matrix recombinates, and reconfigures to the cross-correlation function in step 2, and construct the Toeplitz square of full rank
Battle array；
Step 4, matrix obtained in step 3 is reset using switching matrix J, obtains revised covariance matrix；
Step 5, matrix merges, and matrix acquired in step 3 is taken conjugation, then and after amendment obtained in step 4
Covariance matrix together, the average value both taken the covariance matrix final as signal, the matrix also has Toeplitz
Matrix properties；
Step 6, Eigenvalues Decomposition is carried out to covariance matrix final obtained by step 5 and obtains matrix USEstimated valueAnd square
Battle array UNEstimated valueWherein USRefer to the unit matrix of signal, UNRefer to the unit matrix of noise；
Step 7, to step 6 gained Eigenvalues Decomposition matrixEstimate signal source number；
Step 8, spectrum peak search is carried out according to step 6 and step 7 result, obtains signal source orientation.
Further, the specific implementation that monitoring each channel signal expression formula of array is obtained in step 1 is as follows, monitoring letter
Number be received as M member even linear array, between array element between be divided into λ/2 d=, for even linear array, leftmost array element is the 1st battle array
Member, as reference point, when signal is using θ as incident angles, delay of the m-th array element relative to Far Left array element are as follows:
The steering vector expression formula that even linear array can be obtained is
A (θ)=[1, e-jφ(θ),...,e-jφ(θ)(M-1)]T
Define A=[a (θ1),a(θ2),...,a(θP)] be array antenna flow pattern vector, be containing signal arrival bearing
Vandermonde matrix, wherein P indicates antenna array receiver to P incoming signal；
For monitoring receiving array, reception system involves multipath clutter to being scattered back from target and carries out continuous sampling,
The each data sampled are known as snap, then monitor k-th of channel reception of channel aerial array to signal are as follows:
Wherein,To monitor receiving array kth channel receiving signal, k=1~M, c0、Δτ0For direct-wave jamming
Complex envelope amplitude and delay relative to reference signal；cl、Δτl(l=1,2 ..., Nc) be i-th of multipath clutter multiple packet
Network amplitude and delay relative to reference signal；NcFor multipath sum；M (n) is target echo signal；It is received for monitoring
Array kth channel noise, be average value be 0, variance σ2White Gaussian noise.
Further, the specific implementation that clean reference channel signal expression formula is obtained in step 1 is as follows,
For original reference signals expression formula received by reference channel are as follows:
Wherein, Δ ni(i=1,2 ..., Nb) it is delay of each multipath clutter relative to direct wave in reference channel, a0, be
The complex envelope amplitude of direct wave；aiFor the complex envelope amplitude of i-th multipath clutter；D (n) is direct-path signal；NbFor reference channel
Received multipath sum；vrefIt (n) is reference channel noise；
Original reference signals obtain pure reference signal after reconstruct are as follows:
x0(n)=d (n).
Further, the specific implementation of step 2 is as follows,
Firstly, by the reference signal x after reconstruct0(n) and per monitoring array channel signal x all the wayk(n) correlation is carried out, is obtained
Cross-correlation function r (0, k) expression formula are as follows:
Wherein, k=1,2 ..., M；A (k) is the row k element of A, RsFor x0(n) with the cross-correlation letter of each incoming signal
Number, σVFor Gaussian noise variance, I is unit matrix, and E is the symbol for seeking mathematic expectaion, and H is to ask matrix transposition and complex conjugate symbol
Number；
Monitoring aerial array includes mutiple antennas, and each antenna is an array element, by reference signal and whole array element difference
Correlation function operation is carried out, M correlation function vector can be obtained:
From the above equation, we can see that the information of all incoming signals is all in this correlation function vector.
Further, the expression formula that the Toeplitz matrix of full rank is constructed in step 3 is as follows,
RTIt is the Toeplitz matrix of M × M rank.
Further, the specific implementation of step 4 is as follows,
If being reset using switching matrix J arrayed data vector x (n), form are as follows:
Y (n)=Jx*(n)
Wherein, x*(n) be x (n) conjugation, and J is defined as:
Then obtain revised covariance matrix:
Similarly, in actual treatment, obtaining revised covariance matrix isWherein,For RTConjugation.
Further, the specific implementation of step 6 is as follows,
If final covariance matrix in step 5Obviously,It is Toeplitz matrix, passes through feature point
Solution can be calculated:
Wherein, S and N respectively refers to signal and noise, USThen refer to the unit matrix of signal, USTransposition and complex-conjugate matrix beUNRefer to the unit matrix of noise, UNTransposition and complex-conjugate matrix be
It is prepared by the followingEstimated value
Enabling L is the number of snap, wherein must then assist using the clean reference channel signal after reconstruct as the data in channel 0
Variance matrix
It willThe first row element be assigned to corresponding correlation function, i.e., willIt is assigned to r (0, k-1), wherein k=
1 ... ..., M, to construct R by r (0, k-1)TMatrix, and then obtained by the method in step 5Estimated valueIt is rightEstimated valueSingular value decomposition is carried out, obtaining characteristic value is λ1,λ2,...,λPMatrix As USEstimated value, with
And characteristic value isMatrix As UNEstimated value.
Further, the specific implementation of step 7 is as follows,
It is rightEstimated valueSingular value decomposition is carried out, according to matrixIt is λ that characteristic value, which can obtain signal subspace,1,λ2,...,
λP, equal with signal sum P, the matrix that corresponding feature vector obtains is US=[u1,u2,...,up]；Noise subspace is
λP+1,λP+2,...,λM, sum is M-P, and is metThe matrix that its corresponding feature vector obtains
For UN=[uP+1,uP+2,...,uM]。
Further, the specific implementation of step 8 is as follows,
Since noise will cause array steering vector a (θ) and UNCannot be all orthogonal, therefore use minimum optimization searching method structure
It makes such as minor function:
Enable MUSIC algorithm spatial spectrum are as follows:
The azimuth estimation value of signal is obtained according to above formula peak position.
The present invention has the advantage that compared with the conventional method
First, since the present invention is when carrying out correlation matrix calculating, using the reference after reconstructed from reference channel
Signal, arithmetic speed is fast, good in convergence effect, overcomes existing method from sampling and calculates the more problem of elapsed time.
Second, since the present invention is when carrying out conjugate matrices calculating, using the clean reference signal after reconstruct, letter
It makes an uproar than substantially increasing the signal-to-noise ratio of operation matrix much higher than the higher monitoring channel signal of existing method noise, so that this
Not only real-time is good for multipath and DOA estimation when serious interference under complex environment for invention, but also estimated accuracy is high, improves thunder
It is very significant for LTE external illuminators-based radar practical application up to system detection performance.
Detailed description of the invention
Fig. 1: being the method flow diagram of the embodiment of the present invention；
Fig. 2: being DOA estimating system structural block diagram；
Fig. 3: being independent signal DOA estimation；
Fig. 4: being the DOA estimation containing coherent signal；
Fig. 5: being that matrix is reset and two kinds of algorithm decorrelations of space smoothing can compare；
Fig. 6: being that matrix is reset and two kinds of algorithm DOA Estimation in Coherent Signal of space smoothing compare；
Fig. 7: being that estimate variance compares under different signal-to-noise ratio；
Fig. 8: being that estimate variance compares under different number of snapshots；
Fig. 9: being that two methods runing time compares.
Specific embodiment
Understand for the ease of those of ordinary skill in the art and implement the present invention, with reference to the accompanying drawings and embodiments to this hair
It is bright to be described in further detail, it should be understood that implementation example described herein is merely to illustrate and explain the present invention, not
For limiting the present invention.
Implementation method flow figure of the present invention is referring to Fig.1, signal is the LTE signal under fdd mode, band in the embodiment of the present invention
Width is 15MHz, and receiving end sample rate is 23.04MHz.The present invention provides a kind of LTE external illuminators-based radar based on matrix recombination
DOA estimation method, specific implementation the following steps are included:
Step 1: signal being received to LTE external illuminators-based radar and is modeled, each channel of monitoring array and reference channel are obtained
Signal expression, and pure reference signal is obtained by reconstruct.
The reference signal receiving channel of LTE external illuminators-based radar is single channel (channel 0), and monitoring signals are received as M member
Even linear array, between array element between be divided into λ/2 d=, as shown in Figure 2.DOA, that is, direction of arrival refers to electromagnetic wave incident to array day
Direction when line.DOA estimation method is estimated that the arrival bearing of wave, can be the Adaptive beamformer in monitoring channel
It is filtered with null and azimuth information is provided, be conducive to subsequent array signal processing.From Figure 2 it can be seen that entire DOA estimating system is by three
Part forms: object space is made of various incoming signals and spatial parameter；Observation space is believed by antenna array receiver incidence
Number；Estimation space carries out orientation estimation to incoming signal using space spectral technology.
For even linear array, leftmost array element is the 1st array element, as reference point, when signal is using θ as incident angles
When, delay of the m-th array element relative to Far Left array element are as follows:
The steering vector expression formula that even linear array can be obtained is
A (θ)=[1, e-jφ(θ),...,e-jφ(θ)(M-1)]T
Define A=[a (θ1),a(θ2),...,a(θP)] be array antenna flow pattern vector, be containing signal arrival bearing
Vandermonde matrix, wherein P indicates antenna array receiver to P incoming signal.
For monitoring receiving array, reception system involves multipath clutter to being scattered back from target and carries out continuous sampling,
The each data sampled are known as snap, then monitor k-th of channel reception of channel aerial array to signal are as follows:
Wherein,To monitor receiving array kth channel receiving signal (k=1~M), c0、Δτ0For direct-wave jamming
Complex envelope amplitude and delay relative to reference signal；cl、Δτl(l=1,2 ..., Nc) be i-th of multipath clutter multiple packet
Network amplitude and delay relative to reference signal；NcFor multipath sum；M (n) is target echo signal；It is received for monitoring
Array kth channel noise (k=1~M), be average value be 0, variance σ2White Gaussian noise.
For original reference signals expression formula received by reference channel are as follows:
Wherein, τi(i=1,2 ..., Nb) it is delay of each multipath clutter relative to direct wave in reference channel, a0, be straight
Up to the complex envelope amplitude of wave；aiFor the complex envelope amplitude of i-th multipath clutter；D (n) is direct-path signal；NbFor reference channel institute
The multipath sum received；vrefIt (n) is reference channel noise.It can be seen that by above formula, reference channel is not only received from radiation source
Direct wave, multipath echo can be also received, so that original reference signals signal-to-noise ratio is relatively low.
Original reference signals obtain pure reference signal after reconstruct are as follows:
x0(n)=d (n)
Step 2: carrying out cross-correlation by reference signal obtained in step 1 and per monitoring array channel signal all the way, obtain
Cross-correlation matrix；
Firstly, by the reference signal x after reconstruct0(n) and per monitoring array channel signal x all the wayk(n) correlation is carried out, is obtained
Cross-correlation function r (0, k) expression formula are as follows:
Wherein, k=1,2 ..., M；A (k) is the row k element of A, RsFor x0(n) mutually with the cross-correlation letter of each incoming signal
Number, σVFor Gaussian noise variance, I is unit matrix, and E is the symbol for seeking mathematic expectaion, and H is to ask matrix transposition and complex conjugate symbol
Number.
Monitoring aerial array includes mutiple antennas, and each antenna is an array element, carries out related letter respectively to whole array element
Number operation, can obtain M correlation function vector:
From the above equation, we can see that the information of all incoming signals is all in this correlation function vector.
Step 3: matrix recombination: in order to effective decoherence, the correlation function in step 2 being reconfigured, and is constructed
The Toeplitz matrix of full rank, expression formula is as follows,
RTIt is the Toeplitz matrix of M × M rank.Whether as it can be seen that be concerned with regardless of signal, the order of the covariance square of signal is all etc.
In signal number.
Step 4: covariance matrix amendment: matrix obtained in step 3 being reset using switching matrix J, must be corrected
Covariance matrix afterwards；
If being reset using switching matrix J arrayed data vector x (n), form are as follows:
Y (n)=Jx*(n)
Wherein, x*(n) be x (n) conjugation, and J is defined as:
Revised covariance matrix can then be obtained:
Similarly, in actual treatment of the present invention, obtaining revised covariance matrix isWherein,For RT's
Conjugation.
Step 5: matrix fusion: matrix acquired in step 3 being taken into conjugation, then and after amendment obtained in step 4
Covariance matrix together, take R'TAnd RTThe average value of the two covariance matrix final as signal:
Obviously,Also there are Toeplitz matrix properties.
Step 6: to step 5 gained matrixIt carries out Eigenvalues Decomposition and obtains matrix USAnd UNEstimated value；
It is Toeplitz matrix, can be calculated by feature decomposition:
Wherein, S and N respectively refers to signal and noise, USThen refer to the unit matrix of signal, USTransposition and complex-conjugate matrix beUNWithIt is similar.But it generally can not directly obtain in practiceIts estimated value can pass through the snap to sampling
Data carry out limited times sampling and obtain.
Enabling L is the number of snap, wherein can then obtain using the clean reference channel signal after reconstruct as the data in channel 0
Covariance matrix
It willThe first row element be assigned to corresponding correlation function, i.e., willIt is assigned to r (0, k-1) (wherein k=
1 ... ..., M), so as to construct R by r (0, k-1)TMatrix, and then obtained according to the method in step 5Estimated value
It is rightEstimated valueSingular value decomposition is carried out, obtaining characteristic value is λ1,λ2,...,λPMatrix As USEstimated value,
And characteristic value isMatrix As UNEstimated value.
Step 7: according to step 6 gained Eigenvalues Decomposition matrixTo estimate independent signal source number；
According to matrixIt is λ that characteristic value, which can obtain signal subspace,1,λ2,...,λP, it is equal with signal sum P, it is corresponding
The matrix that feature vector obtains is US=[u1,u2,...,uP]；Noise subspace is λP+1,λP+2,...,λM, sum is M-N,
And meetThe matrix that its corresponding feature vector obtains is UN=[uP+1,uP+2,...,uM]。
Step 8: spectrum peak search being carried out according to step 6 and step 7 result, obtains signal source orientation.
Since noise will cause array steering vector a (θ) and UNCannot be all orthogonal, therefore use minimum optimization searching method structure
It makes such as minor function:
Enable MUSIC algorithm spatial spectrum are as follows:
The azimuth estimation value of signal can be obtained according to above formula peak position.
Below with reference to emulation experiment, the present invention will be further described.
1. simulated conditions:
Emulation uses 16 unit even linear arrays, and array element spacing is 0.0803m, and snap number is 1024, signal-to-noise ratio 10dB.
Assuming that existing 4 information sources are incident in aerial array with -50 °, -15 °, 30 °, 60 ° of angle respectively.
2. emulation content and interpretation of result:
Emulation experiment of the invention has 4.
Emulation experiment 1:MUSIC algorithm estimates incoherent and coherent signal DOA respectively.
If this 4 signals are all mutually indepedent, simulation result is as shown in Figure 3；If the 2nd and the 4th signal coherence,
Remaining is mutually indepedent, then simulation result is as shown in Figure 4.
Simulation result illustrates that MUSIC algorithm can be very good independent signal to estimate arrival bearing, but in LTE external radiation
In the radar system of source, since the DOA estimation of the coherent clutter of multipath generation cannot use MUSIC algorithm, the spectrum of coherent clutter
Peak is submerged, and be will lead to the signal number estimated and is tailed off.
Emulation experiment two: the verifying to CR-Toepltiz matrix reassembly algorithm decorrelation energy.
2nd and the 4th signal coherence, remaining is mutually indepedent.Respectively with CR-Toepltiz matrix reassembly algorithm and
MUSIC algorithm carries out DOA estimation, verifies the decorrelation LMS performance of modified hydrothermal process, as shown in Figure 5.
Simulation result illustrates that CR-Toepltiz matrix reassembly algorithm can accurately tell coherent signal and independent letter
Number, and resolving accuracy can be used for the DOA estimation of monitoring signals in LTE external radiation source radar system compared with MUSIC high.
Emulation experiment three: there are when coherent, compare front-rear space smooth algorithm and the recombination of CR-Toepltiz matrix
The DOA estimation effect of algorithm.
As can be seen from Figure 6, all there is spectral peak in preset azimuth position in two kinds of algorithms, illustrate both algorithms to relevant letter
Number DOA can accurately estimate.But comparatively more another algorithm of CR-Toepltiz algorithm spectral peak is sharp
Sharper, resolving accuracy is more preferable.
Emulation experiment four: comparison front-rear space smooth algorithm and CR-Toepltiz matrix reassembly algorithm DOA estimation property
Energy.
In order to verify the validity of new algorithm, 100 Monte Carlo experiments are carried out in experiment, different noises is set
Than with snap number, the estimate variance of comparison algorithm, as shown in Figure 7,8.Different coherent signal quantity is set again, observes two kinds
The runing time of algorithm, as a result as shown in Figure 9.
Simulation result Fig. 7 can be seen that CR-Toepltiz matrix reassembly algorithm in the case where signal-to-noise ratio is equal, relative to
Another algorithm estimate variance is smaller, and algorithm performance is more stable.As it can be observed in the picture that estimation side of the size of number of snapshots to algorithm
Difference is influential, and the estimate variance of CR-Toepltiz matrix reassembly algorithm is bigger when number is less, but
After number is gradually increased to 200 times, the estimate variance of two kinds of algorithms all becomes relatively stable.As can be seen from Figure 9 when aerial array connects
When the coherent signal number increase received, the CR-Toepltiz matrix reassembly algorithm time is relatively stable and the time is short, not by shadow
It rings.And another algorithm, when coherent signal number is p, at least needs 2p/3 array element due to needing to submatrix smoothing processing.
CR-Toepltiz matrix reassembly algorithm does not need smooth submatrix, does not have to sacrifice array aperture, it is only necessary to takeFirst trip element just
Next step operation can be carried out, calculation amount is lower, and runing time is short.
It should be understood that the above-mentioned description for preferred embodiment is more detailed, can not therefore be considered to this
The limitation of invention patent protection range, those skilled in the art under the inspiration of the present invention, are not departing from power of the present invention
Benefit requires to make replacement or deformation under protected ambit, fall within the scope of protection of the present invention, this hair
It is bright range is claimed to be determined by the appended claims.
Claims (9)
1. a kind of LTE external illuminators-based radar DOA estimation method based on matrix recombination, it is characterised in that: utilize cross-correlated signal
The Toeplitz property of covariance matrix, is handled using matrix recombination method, by restoring signal covariance matrix
Toeplitz property realizes the decoherence to signal, and then accurately estimates the azimuth information of coherent signal in airspace, specific
The following steps are included:
Step 1, signal is received to LTE external illuminators-based radar to model, obtain monitoring array signal expression formula and reference channel
Signal expression, and reference channel signal is reconstructed to obtain pure reference signal；
Step 2, cross-correlation is carried out by clean reference signal obtained in step 1 and per monitoring array channel signal all the way, obtained
Cross-correlation matrix function；
Step 3, matrix recombinates, and reconfigures to the cross-correlation function in step 2, and construct the Toeplitz matrix of full rank；
Step 4, matrix obtained in step 3 is reset using switching matrix J, obtains revised covariance matrix；
Step 5, matrix merge, matrix acquired in step 3 is taken into conjugation, then with revised association obtained in step 4
Together, the covariance matrix for taking the average value of the two final as signal, the matrix also has Toeplitz matrix to variance matrix
Property；
Step 6, Eigenvalues Decomposition is carried out to covariance matrix final obtained by step 5 and obtains matrix USEstimated valueAnd matrix UN
Estimated valueWherein USRefer to the unit matrix of signal, UNRefer to the unit matrix of noise；
Step 7, to step 6 gained Eigenvalues Decomposition matrixEstimate signal source number；
Step 8, spectrum peak search is carried out according to step 6 and step 7 result, obtains signal source orientation.
2. a kind of LTE external illuminators-based radar DOA estimation method based on matrix recombination as described in claim 1, feature exist
In: the specific implementation that monitoring each channel signal expression formula of array is obtained in step 1 is as follows,
Monitoring signals are received as M member even linear array, between array element between be divided into λ/2 d=, for even linear array, leftmost array element
It is the 1st array element, as reference point, when signal is using θ as incident angles, m-th array element is prolonged relative to Far Left array element
Late are as follows:
The steering vector expression formula that even linear array can be obtained is
A (θ)=[1, e-jφ(θ),...,e-jφ(θ)(M-1)]T
Define A=[a (θ1),a(θ2),...,a(θP)] be array antenna flow pattern vector, be containing signal arrival bearing
Vandermonde matrix, wherein P indicates antenna array receiver to P incoming signal；
For monitoring receiving array, reception system involves multipath clutter to being scattered back from target and carries out continuous sampling, sampling
To each data be known as snap, then monitor k-th of channel reception of channel aerial array to signal are as follows:
Wherein,To monitor receiving array kth channel receiving signal, k=1~M, c0、Δτ0For the multiple packet of direct-wave jamming
Network amplitude and delay relative to reference signal；cl、Δτl(l=1,2 ..., Nc) be i-th of multipath clutter complex envelope amplitude
With the delay relative to reference signal；NcFor multipath sum；M (n) is target echo signal；For monitoring receiving array the
K channel noise, be average value be 0, variance σ2White Gaussian noise.
3. a kind of LTE external illuminators-based radar DOA estimation method based on matrix recombination as claimed in claim 2, feature exist
In: the specific implementation that clean reference channel signal expression formula is obtained in step 1 is as follows,
For original reference signals expression formula received by reference channel are as follows:
Wherein, Δ ni(i=1,2 ..., Nb) it is delay of each multipath clutter relative to direct wave in reference channel, a0, be through
The complex envelope amplitude of wave；aiFor the complex envelope amplitude of i-th multipath clutter；D (n) is direct-path signal；NbIt is connect by reference channel
The multipath sum received；vrefIt (n) is reference channel noise；
Original reference signals obtain pure reference signal after reconstruct are as follows:
x0(n)=d (n).
4. a kind of LTE external illuminators-based radar DOA estimation method based on matrix recombination as claimed in claim 3, feature exist
In: the specific implementation of step 2 is as follows,
Firstly, by the reference signal x after reconstruct0(n) and per monitoring array channel signal x all the wayk(n) correlation is carried out, is obtained mutually
Close function r (0, k) expression formula are as follows:
Wherein, k=1,2 ..., M；A (k) is the row k element of A, RsFor x0(n) with the cross-correlation function of each incoming signal, σV
For Gaussian noise variance, I is unit matrix, and E is the symbol for seeking mathematic expectaion, and H is to ask matrix transposition and complex conjugate symbol；
Monitoring aerial array includes mutiple antennas, and each antenna is an array element, and reference signal and whole array elements are carried out respectively
Correlation function operation can obtain M correlation function vector:
From the above equation, we can see that the information of all incoming signals is all in this correlation function vector.
5. a kind of LTE external illuminators-based radar DOA estimation method based on matrix recombination as claimed in claim 4, feature exist
In: the expression formula that the Toeplitz matrix of full rank is constructed in step 3 is as follows,
RTIt is the Toeplitz matrix of M × M rank.
6. a kind of LTE external illuminators-based radar DOA estimation method based on matrix recombination as claimed in claim 5, feature exist
In: the specific implementation of step 4 is as follows,
If being reset using switching matrix J arrayed data vector x (n), form are as follows:
Y (n)=Jx*(n)
Wherein, x*(n) be x (n) conjugation, and J is defined as:
Then obtain revised covariance matrix:
Similarly, in actual treatment, obtaining revised covariance matrix isWherein,For RTConjugation.
7. a kind of LTE external illuminators-based radar DOA estimation method based on matrix recombination as claimed in claim 6, feature exist
In: the specific implementation of step 6 is as follows,
If final covariance matrix in step 5Obviously,It is Toeplitz matrix, passes through feature decomposition meter
Calculation can obtain:
Wherein, S and N respectively refers to signal and noise, USThen refer to the unit matrix of signal, USTransposition and complex-conjugate matrix be
UNRefer to the unit matrix of noise, UNTransposition and complex-conjugate matrix be
It is prepared by the followingEstimated value
Enabling L is the number of snap, wherein then obtaining covariance using the clean reference channel signal after reconstruct as the data in channel 0
Matrix
It willThe first row element be assigned to corresponding correlation function, i.e., willIt is assigned to r (0, k-1), wherein k=1 ... ...,
M, to construct R by r (0, k-1)TMatrix, and then obtained by the method in step 5Estimated valueIt is rightEstimation
ValueSingular value decomposition is carried out, obtaining characteristic value is λ1,λ2,...,λPMatrix As USEstimated value and characteristic value
ForMatrixAs UNEstimated value.
8. a kind of LTE external illuminators-based radar DOA estimation method based on matrix recombination as claimed in claim 7, feature exist
In: the specific implementation of step 7 is as follows,
It is rightEstimated valueSingular value decomposition is carried out, according to matrixIt is λ that characteristic value, which can obtain signal subspace,1,λ2,...,λP, with
Signal sum P is equal, and the matrix that corresponding feature vector obtains is US=[u1,u2,...,up]；Noise subspace is λP+1,
λP+2,...,λM, sum is M-P, and is metThe matrix that its corresponding feature vector obtains is UN
=[uP+1,uP+2,...,uM]。
9. a kind of LTE external illuminators-based radar DOA estimation method based on matrix recombination as claimed in claim 8, feature exist
In: the specific implementation of step 8 is as follows,
Since noise will cause array steering vector a (θ) and UNCannot be all orthogonal, therefore the minimum optimization searching method construction of use is such as
Minor function:
Enable MUSIC algorithm spatial spectrum are as follows:
The azimuth estimation value of signal is obtained according to above formula peak position.
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