CN108363049A - Coherent MIMO radar angle estimating method under nonstationary noise - Google Patents
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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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/414—Discriminating targets with respect to background clutter
Abstract
The invention discloses coherent MIMO radar angle estimating method under nonstationary noise, coherent MIMO radar angle estimating method under the nonstationary noise, specific steps include：1, system initialization；2, the signal data for obtaining MIMO radar matched filtering processing, calculates signal covariance matrix；3, the angle estimation of incoherent class information source is realized using conventional Subspace algorithm；4, new Toeplitz matrixes are configured to；5, incoherent information source is rejected, the covariance matrix of coherent is obtained；6, the direction of arrival of target is estimated to coherent angle estimation using m Capon algorithms；7, the wave of target is estimated from direction.The present invention realizes the angle estimation to coherent.
Description
Technical field
The present invention relates to Radar Technology fields, more specifically, are related to coherent MIMO radar angle under nonstationary noise
Spend method of estimation.
Background technology
With the development of EW Equipment, Battle Field Electromagnetic becomes to become increasingly complex, and utilizes multiple-input and multiple-output
(Multiple input multiple output, MIMO) radar necessarily faces following two problems as reconnaissance sensor：
First, due to multipath effect or electronic interferences, it is to be concerned with to mix with incoherent to receive signal；Second, cause when encountering wave
Spike or big reflector caused by flicker when, receive noise will be it is non-smoothly.The above problem constrains to a certain extent
MIMO radar in the extensive use of military field, seek effective technological means and be resolved by urgent need.
Document Lay Teen Ong.Experimental study on spatial smoothing direction of
Arrival estimation for coherent signals [C] .2016 IEEE Region 10Conference,
Singapore, 2016：1411-1414. and document Yuta Kamiya, Nobuyoshi Kikuma, Kunio
Sakakibara.DOA estimation of desired signals using in-phase combining of
multiple cyclic correlations and spatial smoothing processing[C].2016
International Symposium on Antennas and Propagation, Okinawa, Japan, 2016：1028-
1029. smoothing algorithms proposed can efficiently solve multipath-source, but array aperture loss is serious；Document Frank Meinl,
Martin Kunert, Holger Blume.Hardware acceleration of Maximum-Likelihood angle
estimation for automotive MIMO radars[C].2016 Conference on Design and
Architectures for Signal and Image Processing, Rennes, France, 2016：168-175. is situated between
Maximum likelihood class (Maximum likelihood, the ML) algorithm to continue can direct estimation coherent, but need higher-dimension spectral peak
Search, it is computationally intensive；Document Chen Hui, Huang Benxiong, Deng Bin.A modified Toeplitz
algorithm for DOA estimation of coherent signals[C].Proceedings of 2007
International Symposium on Intelligent Signal Processing and Communication
Systems.Nov.28-Dec.1,2007：80-83 separately differentiates incoherent information source and coherent, is increased with this distinguishable
Information source number, but the unstable mismatch of noise can not be solved.
Invention content
The present invention is directed to solve at least some of the technical problems in related technologies.For this purpose, the present invention
One purpose is to propose to be based on dependent vector Teoplitz matrix reconstructions and oblique projection operator (Correlation vector
Teoplitz reconstruction and oblique projection, CVTR-OP) algorithm, first with Toeplitz weight
Nonstationary noise is converted into white Gaussian noise by structure method, then excludes incoherent information source with oblique projection operator, is realized to relevant
The angle estimation of information source.
The technical solution that the present invention solves above-mentioned technical problem is as follows：
1) system initialization；
MIMO radar has M transmitting array element, N number of reception array element, and array pitch is λ/2, and λ is operation wavelength, P, far field mesh
Mark corresponding wave is from direction (Direction of departure, DOD)Direction of arrival (Direction of
Arrival, DOA) it is θp；
2) the signal data y (t of MIMO radar matched filtering processing are obtainedl), wherein y (tl)=A α (tl)+n(tl), formula
In,ξpIndicate the reflectance factor of target p, fdpIndicate the Doppler frequency shift of target p, WithIt indicates
Emission array, receiving array are to the direction vector of target p, n (tl) indicate to receive noise, l=1,2, L, L indicate the pulse of accumulation
Number,Indicate Kronecker products, calculating signal covariance matrix R wherein R is
Wherein, A=[AC, ANC], Noise for noise covariance matrix, i-th, j pulse period is mutual
Correlation matrixMeet：
3) angle estimation of incoherent class information source is realized using conventional Subspace algorithm；
Compound information covariance matrix Q can be rewritten as following expression-form：
α in above formula0(tl) be coherent generation information source, βi=2 π d sin θsi/λ；ρlFor the phase of first of coherent
The dry factor.Above formula is substituted into formulaData covariance square can be obtained
Battle array R the first row element be：
Wherein, R1, iI-th of element in the 1st row of (i=1, L, NM) expression R,
4) by the 1st row vector V of covariance matrix R according to formula
It is configured to new Toeplitz matrixes RT；
Toeplitz reconstruct is carried out to matrix with T () expressions, then matrix RTIt can be expressed as：
Wherein, Q '=diag (S), diag () expression form diagonal matrix by vector, and I is that NM × NM ties up unit matrix,Q′NC=diag [| αG+1(tl)|2, L, | αP(tl)|2]T,
5) incoherent information source is rejected, the covariance matrix of coherent is obtained
Subspace<ANC>The subspace and<AC>Oblique projection operatorFor
It can obtain：Wherein,New matrix RCFor：Then RCOnly coherent information, to R after CVTRCEigenvalues Decomposition has G nonzero eigenvalue and NM-G
Zero eigenvalue；
6) direction of arrival of target can be solved using m-Capon algorithms and method of Lagrange multipliersTo coherent angle
Degree estimation, estimates the direction of arrival of target
7) wave of target is estimated from direction
P=1,2, L, G wherein,e1
It is 1 for the 1st element, remaining is 0 dimensional vectors of M × 1,It indicatesM-th of element, Γ () expression ask phase angle to transport
It calculates.
On the beneficial effects of the invention are as follows：The present invention proposes a kind of CVTR-OP algorithms, and solution phase is reconstructed with Toeplitz
It is dry, it is lost without array aperture, information source is detached using OP operators, is suitable for various array structures；It is reused when step-by-step processing
Data are received, it is strong that information source overload capacity and array element save ability；Meanwhile emulation also show the algorithm ratio MSWF algorithms more suitable for
The case where low signal-to-noise ratio.
Description of the drawings
Fig. 1 is the system construction drawing of the present invention；
Fig. 2 is the flow graph construction schematic diagram of the present invention；
Fig. 3 is the planisphere that information source of the present invention receives and dispatches that result is matched at angle；
Fig. 4 is the probability of success of the inventive algorithm statistic property with SNR；
Fig. 5 is root-mean-square error of the inventive algorithm statistic property with SNR；
Fig. 6 emulates for CVTR-OP algorithms information source overload capacity of the present invention；
Fig. 7 emulates for ESPRIT algorithms information source overload capacity of the present invention；
The Virtual array number of Fig. 8 each algorithms when being information source number difference of the present invention.
Specific implementation mode
The embodiment of the present invention is described below in detail, examples of the embodiments are shown in the accompanying drawings, wherein from beginning to end
Same or similar label indicates same or similar element or element with the same or similar functions.Below with reference to attached
The embodiment of figure description is exemplary, it is intended to for explaining the present invention, and is not considered as limiting the invention.
In the description of the present invention, it is to be understood that, term "center", " longitudinal direction ", " transverse direction ", " length ", " width ",
" thickness ", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outside", " up time
The orientation or positional relationship of the instructions such as needle ", " counterclockwise ", " axial direction ", " radial direction ", " circumferential direction " be orientation based on ... shown in the drawings or
Position relationship is merely for convenience of description of the present invention and simplification of the description, and does not indicate or imply the indicated device or element must
There must be specific orientation, with specific azimuth configuration and operation, therefore be not considered as limiting the invention.
In addition, term " first ", " second " are used for description purposes only, it is not understood to indicate or imply relative importance
Or implicitly indicate the quantity of indicated technical characteristic.Define " first " as a result, the feature of " second " can be expressed or
Implicitly include at least one this feature.In the description of the present invention, the meaning of " plurality " is at least two, such as two, three
It is a etc., unless otherwise specifically defined.
In the present invention unless specifically defined or limited otherwise, term " installation ", " connected ", " connection ", " fixation " etc.
Term shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or integral；Can be that machinery connects
It connects, can also be electrical connection；It can be directly connected, can also can be indirectly connected through an intermediary in two elements
The interaction relationship of the connection in portion or two elements, unless otherwise restricted clearly.For those of ordinary skill in the art
For, the specific meanings of the above terms in the present invention can be understood according to specific conditions.
In the present invention unless specifically defined or limited otherwise, fisrt feature can be with "above" or "below" second feature
It is that the first and second features are in direct contact or the first and second features pass through intermediary mediate contact.Moreover, fisrt feature exists
Second feature " on ", " top " and " above " but fisrt feature be directly above or diagonally above the second feature, or be merely representative of
Fisrt feature level height is higher than second feature.Fisrt feature second feature " under ", " lower section " and " below " can be
One feature is directly under or diagonally below the second feature, or is merely representative of fisrt feature level height and is less than second feature.
The present embodiment is as follows：
Step 1: system initialization
Consider that MIMO radar has M transmitting array element, N number of reception array element, array pitch is λ/2, and λ is operation wavelength, far field P
The corresponding wave of a target is from direction (Direction of departure, DOD)Direction of arrival (Direction of
Arrival, DOA) it is θp, then it is represented by after the matched filtering of echo-signal received：
y(tl)=A α (tl)+n(tl) (1)
In formula,ξpIndicate the reflectance factor of target p, fdpIndicate the Doppler frequency shift of target p, WithTable
Show emission array, receiving array to the direction vector of target p, n (tl) indicate to receive noise, l=1,2, L, L indicate the arteries and veins of accumulation
Number is rushed,Indicate Kronecker products.
Step 2: obtaining the signal data y (t of MIMO radar matched filtering processingl), calculate signal covariance matrix
When existing incoherent information source also has coherent in P information source, if preceding G is coherent, then incoherent letter
Source number U=P-G, covariance matrix R can be analyzed to：
Wherein, A=[AC, ANC], For noise covariance matrix.
The noise cross-correlation matrix of i-th, j pulse periodsMeet：
If reception noise is space non-stationary white noise, noise power is not equal and orthogonal between array element, i.e., Indicate the noise power of array element i.In this case, based on the normal of Gaussian noise model
It is larger to advise Power estimation algorithm evaluated error, the performance loss of angle estimation algorithm can be caused.
Step 3: realizing the angle estimation of incoherent class information source using conventional Subspace algorithm：
Based on the angle estimation algorithm of CVTR-OP processing, CVTR method information source decorrelation LMSs, compound information covariance matrix Q
It can be rewritten as following expression-form：
α in above formula0(tl) be coherent generation information source, βi=2 π d sin θsi/λ；ρlFor the phase of first of coherent
The dry factor.Above formula is substituted into formula (2) the first row element of data covariance matrix R can be obtained and is：
Wherein, R1, iI-th of element in the 1st row of (i=1, L, NM) expression R,η
=(ρ1+L+ρG)|α0(t)|2,
Step 4: by covariance matrixThe 1st row vector V new Toeplitz matrixes are configured to according to formula (6)
Toeplitz reconstruct is carried out to matrix with T () expressions, then is had：
Then matrix RTIt can be expressed as：
Wherein, Q '=diag (S), diag () expression form diagonal matrix by vector, and I is that NM × NM ties up unit matrix,Q′NC=diag [| αG+1(tl)|2, L, | αP(tl)|2]T}。
As it can be seen that the order of covariance matrix Q ' is P after operation, and realize the whitening processing of noise.
OP methods reject incoherent source
Subspace<ANC>The subspace and<AC>Oblique projection operatorFor
According to formula (8), can obtain：
Wherein, It is predictable.
The case where formula (9) is the only relevant source information that we want, but due to ACIt is unknown,Non-availability, therefore formula (9)
Directly it cannot get.
But if meeting U+1 ＜ NM, have
SoIt can also be acquired by following formula：
Wherein, ()#Inverse, the R for matrix Moore-Penrose1 #=(A#)H(P′)-1A#, A#=(AHA)-1AH。
Step 5: rejecting incoherent information source according to formula (9), the covariance matrix R of coherent is obtainedC；Definition can be asked
The new matrix R of solutionCFor：
Then RCOnly coherent information, to R after CVTRCEigenvalues Decomposition has G nonzero eigenvalue and NM-G zero special
Value indicative.
Step 6: the direction of arrival of target can be solved according to m-Capon algorithms [11] and method of Lagrange multipliersAnd wave
From directionRespectively：
Step 7: estimating the wave of target from direction according to formula (14)
Wherein,e1It is 1 for the 1st element, remaining is 0 dimensional vectors of M × 1,It indicatesM-th of element, Γ () expression ask phase angle operation.
So far the biradical MIMO radar angle estimation based on cross-correlation matrix is completed.
The effect of the present invention is further illustrated by following l-G simulation test：
Algorithm angle estimation performance evaluation
1. information source overload capacity
For M transmitting array element, N number of MIMO radar for receiving array element, Virtual array number NM.It is flat according to forward direction space
Sliding (Forward space smoothing, FSS) algorithm, can at most estimate NM/2 coherent source, using front-rear space smooth
Algorithm (Forward and backward spatiai smoothing, FBSS), can at most estimate 2NM/3 coherent source.Institute
Two step angle estimations of algorithm are carried, the first step is estimated the angle of incoherent information source using conventional Subspace algorithm, can at most estimated
NM-2, second step can at most estimate NM-1, therefore can estimate 2NM- in total using CVTR processing estimation coherent angles
3 information sources.Illustrate that carried algorithm is not had to be larger than information source number by Virtual array number and limited to, the overload capacity of information source is stronger.
2. array element saves ability
Assuming that incoherent information source number is U in P information source, coherent number is G.Estimate all information source angles with FSS algorithms,
The Virtual array number needed is 2G+U；It is 3/2G+U with the Virtual array number needed if FBSS algorithms.Carried algorithm
One step estimates incoherent class information source, and U+2 Virtual array, second step is needed to estimate coherent, need G+1 Virtual array, total battle array
First number is max [U+2, G+1].
It is illustrated in figure 8 virtual using MIMO radar used in FSS, FBSS and carried algorithm estimation angle when information source number difference
The comparison of array number.
3. computer artificial result
Assuming that MIMO radar emits array element M=3, array element N=2, nonstationary noise are received
Signal-to-noise ratioWhereinIndicate signal power,Indicate noise power.
4. algorithm angle estimation result
Assuming that 3 constant power coherent angles are (- 15 °, 20 °), (0 °, -15 °), (10 °, 10 °), nonstationary noiseSignal to Noise Ratio (SNR)=10dB, it is 200 to receive number of snapshots, is illustrated in figure 3 CVTR-OP algorithms 100 times
The angle estimation situation of Monte-Carlo emulation.
5. algorithm statistic property compares
Assuming that the coherent angle of 2 constant powers is (- 15 °, 20 °), (- 10 °, 10 °), nonstationary noiseFixed reception number of snapshots are 200, carry out 100 Monte-Carlo experiment simulation CVTR-OP algorithms
With the statistic property of multistage wiener filter algorithm (Multistage Wiener filter algorithm, MSWF) [12],
It obtains if Fig. 4, such as Fig. 5 estimations probability of success, root-mean-square error are with SNR situations of change.
By emulation as it can be seen that this paper algorithms have better statistical estimate performance relative to MSWF algorithms, that is, have lower
SNR resolution threshold and estimation mean square error, illustrate that this paper algorithms have the ability for better adapting to nonstationary noise.
6. algorithm information source overload capacity
Assuming that 7 constant power incidence information source angles are (- 15 °, 20 °), (0 °, -15 °), (10 °, 10 °), (15 °, -10 °),
(- 25 °, 15 °), (- 10 °, 0 °), (- 20 °, 20 °) receive zero-mean, variance isWhite Gaussian noise, number of snapshots 200,
Signal to Noise Ratio (SNR)=20dB receives and dispatches angular estimation knot as Fig. 6, such as Fig. 7 are set forth using CVTR-OP algorithms and ESPRIT algorithms
The planisphere of fruit.
By Fig. 6 and Fig. 7 as it can be seen that CVTR-OP algorithms still there is preferable target angle to estimate when array number is less than information source number
Performance is counted, the overload capacity of information source is stronger, and at this time according to conventional signal subspace angle estimation algorithm ESPRIT algorithms
It will cannot tell the angle of information source.
The problems such as being interfered for nonstationary noise, multipath effect and coherent electron, this paper presents a kind of CVTR-OP calculations
Method, reconstructs decorrelation LMS with Toeplitz, is lost without array aperture, detaches information source using OP operators, is suitable for various array junctions
Structure；Recycling receives data when step-by-step processing, and it is strong that information source overload capacity and array element save ability；Meanwhile emulation also shows this
The case where algorithm ratio MSWF algorithms are more suitable for low signal-to-noise ratio.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or spy described in conjunction with this embodiment or example
Point is included at least one embodiment or example of the invention.In the present specification, schematic expression of the above terms are not
It must be directed to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described can be in office
It can be combined in any suitable manner in one or more embodiments or example.In addition, without conflicting with each other, the skill of this field
Art personnel can tie the feature of different embodiments or examples described in this specification and different embodiments or examples
It closes and combines.
Although the embodiments of the present invention has been shown and described above, it is to be understood that above-described embodiment is example
Property, it is not considered as limiting the invention, those skilled in the art within the scope of the invention can be to above-mentioned
Embodiment is changed, changes, replacing and modification should all be included in the protection scope of the present invention.
Claims (1)
1. coherent MIMO radar angle estimating method under nonstationary noise, which is characterized in that MIMO radar has M transmitting battle array
First, N number of reception array element, array pitch are λ/2, and λ is operation wavelength, and target corresponding wave in P, far field is from direction (Direction
Of departure, DOD) beDirection of arrival (Direction of arrival, DOA) is θp, under the nonstationary noise
Coherent MIMO radar angle estimating method includes the following steps：
(1) system initialization；
MIMO radar has M transmitting array element, N number of reception array element, and array pitch is λ/2, and λ is operation wavelength, P, far field target pair
The wave answered is from direction (Direction of departure, DOD)Direction of arrival (Direction of arrival,
DOA) it is θp；
(2) the signal data y (t of MIMO radar matched filtering processing are obtainedl), wherein y (tl)=A α (tl)+n(tl), in formula,ξpIndicate the reflectance factor of target p, fdpIndicate the Doppler frequency shift of target p,With
Indicate emission array, receiving array to the direction vector of target p, n (tl) indicate to receive noise, l=1,2, L, L indicate accumulation
Umber of pulse,Indicate Kronecker products, calculating signal covariance matrix R wherein R is
Wherein, A=[AC, ANC],Noise for noise covariance matrix, i-th, j pulse period is mutual
Close matrixMeet：
(3) angle estimation of incoherent class information source is realized using conventional Subspace algorithm；
Compound information covariance matrix Q can be rewritten as following expression-form：
α in above formula0(tl) be coherent generation information source, βi=2 π dsin θi/λ；ρlFor first coherent it is relevant because
Above formula is substituted into formula by sonData covariance matrix R can be obtained
The first row element be：
Wherein, R1, iI-th of element in the 1st row of (i=1, L, NM) expression R,
η=(ρ1+L+ρG)|α0(t)|2,,
By the 1st row vector V of covariance matrix R according to formula
It is configured to new Toeplitz matrixes RT；
Toeplitz reconstruct is carried out to matrix with T () expressions, then matrix RTIt can be expressed as：
Wherein, Q '=diag (S), diag () expression form diagonal matrix by vector, and I is that NM × NM ties up unit matrix,Q′NC=diag [| αG+1(tl)|2, L, | αP(tl)|2]T],
(4) incoherent information source is rejected, the covariance matrix of coherent is obtained
Subspace<ANC>The subspace and<AC>Oblique projection operatorForIt can obtain：Wherein,New matrix RCFor：Then RCOnly phase
Dry information source information, to R after CVTRCEigenvalues Decomposition has G nonzero eigenvalue and NM-G zero eigenvalue；
(5) direction of arrival of target can be solved using m-Capon algorithms and method of Lagrange multipliersCoherent angle is estimated
Meter, estimates the direction of arrival of target
(6) wave of target is estimated from direction
P=1,2, L, G wherein,e1For
1st element is 1, remaining is 0 dimensional vectors of M × 1,It indicatesM-th of element, Γ () expression ask phase angle to transport
It calculates.
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| CN109828252B (en) * | 2019-04-02 | 2023-02-28 | 河海大学 | MIMO radar parameter estimation method |
| CN110412559A (en) * | 2019-07-26 | 2019-11-05 | 西安电子科技大学 | The non-coherent of distributed unmanned plane MIMO radar merges object detection method |
| CN110412559B (en) * | 2019-07-26 | 2023-05-26 | 西安电子科技大学 | Non-coherent fusion target detection method for MIMO radar of distributed unmanned aerial vehicle |
| CN110736958A (en) * | 2019-09-18 | 2020-01-31 | 中国人民解放军国防科技大学 | self-adaptive source number estimation method based on multi-strategy matrix reconstruction |
| CN110736958B (en) * | 2019-09-18 | 2021-09-28 | 中国人民解放军国防科技大学 | Self-adaptive source number estimation method based on multi-strategy matrix reconstruction |
| CN110907930A (en) * | 2019-11-29 | 2020-03-24 | 成都纳雷科技有限公司 | Vehicle-mounted radar target detection and estimation method and device based on angle estimation |
| CN111521968A (en) * | 2020-05-22 | 2020-08-11 | 南京理工大学 | Underdetermined DOA estimation method based on target space diversity |
| CN115913423A (en) * | 2022-10-31 | 2023-04-04 | 华中科技大学 | Multi-step prediction model training method and prediction method for non-stationary large-scale MIMO channel |
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