CN110361760A - GNSS receiver multi-beam based on subspace tracking is directed toward anti-interference method - Google Patents
GNSS receiver multi-beam based on subspace tracking is directed toward anti-interference method 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
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/13—Receivers
- G01S19/21—Interference related issues ; Issues related to cross-correlation, spoofing or other methods of denial of service
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Abstract
The invention discloses a kind of, and the GNSS receiver multi-beam based on subspace tracking is directed toward anti-interference method, high reject signal is eliminated using noise subspace tracer technique, then the correlation between the signal and satellite navigation signals after multichannel cycle delay is utilized, using the DOA estimation method based on Clean thought, estimate the steering vector of each satellite navigation signals, be respectively finally each satellite construction Wave beam forming weight vector matrix using steering vector, realize to satellite-signal come to enhancing.The present invention requires no knowledge about the pilot symbol and satellite position of transmission, it is a kind of blind adaptive MUD, while inhibiting complex jamming signal, the Signal to Interference plus Noise Ratio of navigation signal is effectively improved, system can be improved under complex environment to a certain extent to the reception ability of satellite navigation signals.
Description
Technical field
The invention belongs to the anti-interference fields of satellite navigation signals, are related to satellite navigation receiver adaptive blind Wave beam forming
A kind of Anti-Jamming Technique content, and in particular to GNSS receiver multi-beam direction anti-interference method based on subspace tracking.
Background technique
For navigation satellite generally in tens of thousands of kilometers from the ground of the aerial work of height, the signal that ground receiver receives is quite micro-
It is weak, it is usually to be submerged in receiver thermal noise.Therefore, when receiver is not intended to be influenced with intentional radio frequency interference by various
When, satellite-signal cannot be extracted from noise, eventually lead to positioning accuracy decline or track loop losing lock, sometimes even
Cisco unity malfunction.Satellite navigation signals power is very weak, is easily disturbed, so that it is outstanding to carry out satellite navigation Research on anti-interference technique
It is urgent.In order to ensure satellite navigation system is in the actual effect of increasingly complicated electromagnetic interference environment, carry out antijam receiver
Technical research has great national defense safety and national economy meaning.
Foreign countries have been carried out years of researches work at the anti-interference aspect of satellite navigation.In time-frequency domain Anti-Jamming Technique product
Change aspect, U.S.'s May Flower communication common carrier (Mayflower Communication Company) was applied in 1993,1997
Time-domain adaptive Anti-interference algorithm is applied to GPS receiver, have passed through the test of actual interference environment, achieve by patent
Good anti-jamming effectiveness.1998, the field in the sky of satellite navigation receiver Anti-Jamming Technique American scholar R.L.Fante
Deep theoretical research is compared, and has carried out more experiment on this basis and the particular problem in its theory is carried out
Verifying.Particular problem therein selection of anti-interference criterion and the influence of multi-path jamming etc. when including sky.After 1 year, beauty
State scholar W.L.Myrik also starts the field in the sky of satellite navigation receiver Anti-Jamming Technique and studies.Its main achievement
It is to be successfully introduced into multi-Stage Wiener Filter technology in anti-interference in sky, obtains the calculation amount to be carried out in space time processing
It significantly reduces, therefore the practical performance of Anti-Jamming Technique greatly increases when sky.
In addition, M.G.Amin is also to the extensive research of the anti-interference problem of satellite navigation receiver expansion, and achieve compared with
Good research achievement, including when time domain is anti-interference, solution in frequency domain, array are anti-interference and empty, are anti-interference.2000,
R.L.Fante is for the first time to based on the anti-of space-time adaptive processing (Space Time Adaptive Processing, STAP)
Interference navigation neceiver gives more complete discussion, this technology represents the new development of navigation neceiver Anti-Jamming Technique
Direction.Hereafter, scholars are to push STAP technology in the functionization in the anti-interference field of satellite navigation, with regard to reduced rank processing, non-
The problems such as STAP under uniform environment, is studied for a long period of time.Currently, to have become satellite navigation anti-interference for space-time adaptive filtering
The research emphasis in field, obtains extensive concern.
The country starts late in satellite navigation Anti-Jamming Technique field, and there is presently no the mature productions that a large amount of equipments use
Product.Recently as the fast development of China's satellite navigation industry, domestic many R&D institutions and university all begin one's study satellite
Navigation Anti-Jamming Technique.Xian Electronics Science and Technology University, Civil Aviation University of China, the National University of Defense technology, air force engineering university, Harbin
The colleges and universities such as polytechnical university and Zhong electricity group, 504 institute of space flight, 704 Suo Deng scientific research institutions of space flight are in satellite navigation Anti-interference algorithm
And its realize that aspect is all done a lot of work, it is main that including having, model carries out anti-interference improvement and number antijam receiver is ground
System.Wherein, in terms of the existing anti-interference improvement of model, the domestic anti-interference improved technology used mainly utilizes antenna array at present
Column receive signal, realize that airspace is anti-interference in anti-interference process device, can adaptively resist each of the waveforms such as continuous waves, pulsed
Kind noise blanket jamming, interference free performance is able to satisfy model index request, but anti-interference number is by bay number
Limitation；In terms of digital antijam receiver development, the country has the research and development program element of multiple digital antijam receivers, each to develop
Unit proposes various circuit optimizations and anti-interference process scheme, and anti-interference ability increases relative to basic model scheme, but
The application demand not being able to satisfy still under complex electromagnetic environment.
From the point of view of domestic and international present Research, for satellite navigation resistance to compression standard interference problem expansion research can be summarized as with
Lower three aspects:
(1) time domain/frequency domain adaptive filtering technology
Time-domain filtering method is to inhibit interference signal by design adaptive temporal filter device.Frequency domain filter method is
Signal intensity is handled to frequency domain, by the way that thresholding is arranged, and the spectrum value that will be greater than the thresholding carries out zero-setting operation to press down
Interference signal processed.It is compared with time domain filtering algorithm, frequency domain processing is easier to Project Realization, is earlier satellite navigation anti-interference reception
The technological means that machine generallys use.Badke B, Ouyang X M, Zhao L et al. successively has studied to be become based on Fourier in short-term
It changes, the time-frequency domain satellite navigation Anti-Jamming Technique of sub-space technique etc., achieves certain achievement.
(2) airspace filter technology
Airspace filter method is theoretical using array signal processing and Wave beam forming, makees in airspace to spacing wave discrete
Parallel sampling, from coming to achieving the purpose that AF panel, it is anti-that this method has become satellite navigation for space region sub-signal and interference
The effective means of co-channel interference.More typical algorithm includes the minimum power algorithm that Gecan A et al. is proposed, the U.S.
What Moeness professor of Villanova university et al. proposed periodically restores Anti-interference algorithm from relevant using C/A code,
What Rong Z et al. was proposed re-expands multiple target array algorithm etc. using the least square despreading of known spreading codes information.
(3) Space-time domain Federated filter technology
It is 1973 by Brenna etc. that space-time adaptive, which handles (Space Time Adaptive Processing, STAP),
What scholar proposed, for solving the problems, such as in airborne radar in the ground bounce removal of space-time two-dimensional coupling distribution.Its essence is by one
Airspace filter Technique Popularizing is tieed up into time and space two-dimensional domain, forms Clutter suppression structure.In view of in airborne/missile-borne
In receiver application, array antenna aperture is often limited, and when interfering more than number and when type complexity, pure spatial processing is due to cannot
Enough freedom degree youngsters AF panel performance that cannot have reached is provided.Therefore, Fante et al. arrives STAP technical application
During GPS is anti-interference, the freedom degree of Adaptable System is substantially increased.
From the prior art, time domain/frequency domain filtering technology has the advantages that at low cost, simple and easy, but more when existing
When a narrowband interference or single broadband interference (time domain broadband signal), they cannot all generate effective interference suppressioning effect.It is empty
Domain filtering technique is a kind of antijamming measure more commonly used at present, and it is dry that narrowband is effectively inhibited by adaptive antenna array
Disturb with broadband interference (array broadband signal), however, pure airspace filter technology inhibit the interference of narrowband need to sacrifice one from
By spending, if you need to inhibit broadband interference then to increase bay number, this will increase the cost of satellite navigation receiver and in antenna
The limited occasion in aperture is difficult to realize (such as airborne and missile-borne).The space-time adaptive inhibited originating from airborne early warning Radar Ground Clutter
Processing can be used for solving the above problems, which can be increased under the premise of not increasing array number by increasing time tap
The freedom degree of Avaptive filtering system.However, existing space-time adaptive anti-interference method focuses mostly on how in interference radiating way
Upper design generates deeper null, has only focused on the rejection ability of interference signal, and has ignored anti-interference process process to satellite
The influence of signal.
Summary of the invention
Goal of the invention: in order to overcome the deficiencies in the prior art, provide it is a kind of based on noise subspace tracking
GNSS receiver multi-beam is directed toward anti-interference method, and this method can overcome complex jamming environment to believe GNSS to a certain extent
Number received influence, and according to interference source characteristic self-adaptive construction Wave beam forming weight vector matrix in signal processing, from
And system is effectively improved under complex environment to the reception ability of satellite navigation signals.
Technical solution: to achieve the above object, present invention offer, a kind of more waves of GNSS receiver based on subspace tracking
Shu Zhixiang anti-interference method, includes the following steps:
S1: the base band letter that the satellite navigation receiver antenna array of M (M > 1, M ∈ N) a array element is received in moment n is set
Number be X (n), calculate its corresponding covariance matrix Rxx；
S2: it is iterated using orthonormal basis of the rapid data sciagraphy to the noise subspace projection of covariance matrix
It solves, obtains the corresponding characteristic vector estimation w of noise subspacesub；
S3: the noise subspace characteristic vector w obtained using step S2subExist to the aerial array of satellite navigation receiver
After the calibration that moment n is received baseband signal X (n) carry out projection process, obtain baseband signal X (n) noise subspace most
Excellent projection Ysub；
S4: respectively to data Y after projectionsubOne C/A code period of delay of each channel data, using based on Clean thought
The direction of arrival parameter of each satellite navigation signals is estimated one by oneL is the number of satellite signals that receiver receives；
S5: according to the direction of arrival parameter of each satellite antennaCorresponding wave is constructed up to vector
It can be obtained according to minimum mean square error criterion and be to the optimal array weight vector of each satelliteWherein
For the corresponding optimal array weight vector of the l satellite；
S6: the L optimal array weight vectors obtained using step S5 are respectively to optimal projection YsubBe weighted it is cumulative,
Obtain the observation output signal Y (n) of each satellite.
Further, the expression formula of baseband signal X (n) is as follows in the step S1:
Wherein, TsFor the sampling interval；L is satellite signal source quantity；To first of satellite, sl(n), clAnd τl(n) it is respectively
Its corresponding satellite useful signal, C/A code and signal delay；a(θl) be first of satellite steering vector, θlFor its direction of arrival
Angle parameter；K is interference source quantity；JkIt (n) is interference signal, dkFor its steering vector；V (n) is additive white Gaussian noise.
The expression formula of the baseband signal X (n) is written over using data vector form:
X (n)=s (n)+u (n)+V (n)
The covariance matrix for calculating the signal x (n) that satellite navigation receiver antenna array is arrived in n reception, then have
Rxx=E { X (n) XH(n) }=Rs+Ru+Rv
Wherein, E { } is statistical expection, ()HIt is handled for the conjugate transposition of matrix, Rs, RuAnd RVRespectively GNSS letter
Number, the covariance matrix of interference signal and noise, be respectively defined as
Further, it is projected in the step S2 using noise subspace of the rapid data sciagraphy to covariance matrix
Orthonormal basis is iterated solution, and specific step is as follows:
S2-1: initialization iteration count n=0 is arranged pre-determined threshold δ=0.001, using random orthogonal initial method
Noise subspace projection matrix is initialized, orthogonal matrix U is obtained0；
S2-2: to nth iteration, current subspace signal projection is calculated
S2-3: calculating Householder reflection matrix has
Wherein, e1=[1,0 ..., 0]T,For vector rnThe corresponding argument value of first element；
S2-4: orthonormal matrix is calculated
Whereinβ >=0 is Learning Step；
S2-5: to znRegularization is carried out, U is assigned ton+1, i.e.,
Un+1=znD
Wherein,
S2-6: incremental, n=n+1 is carried out to iteration count；
If | | Un+1-Un||2>=δ, then repeatedly step S2-1~S2-5, otherwise exports optimal projection matrix Uopt。
Further, optimal projection in the step S3
Further, respectively to data Y after projection in the step S4subOne C/A code week of delay of each channel data
Phase then has the signal to i-th of channel, after delay to be expressed as
Wherein, ai(θl) it is a (θl) i-th of element, vi(n) be projection after i-th of channel noise signal；In view of C/
A code is periodic signal, to there is cl(nTs-τl(n)-T)=cl(nTs-τl(n)), above formula is expressed as
Signal since the C/A code of each satellite is independent of one another, then after projectingWith the signal u after delayi(n) mutual
Dependent vector is expressed as
Wherein,For complex constant,For the power of the l satellite-signal；Construct new vectorThen above formula is represented by
Wherein,For Kronecker product, enableAbove formula is expressed as
It enablesThen above formula is represented by matrix form
Wherein,Utilize sample cross-correlation vectorInstead ofAnd by minimizing mesh as follows
Scalar functions are estimatedAnd θ.
Estimated using objective function is minimizedWith the detailed process of θ are as follows:
S4-1: setting L=1, enablesEstimated using following formula
S4-2: to L=2, residual error is calculatedEstimated using following formula
S4-3: to L=k, residual error is calculatedEstimated using following formula
S4-4: repeating the above steps, and presets satellite number until L is equal to, thus obtains the DOA parameter of whole satellite-signals
The method of the present invention eliminates high reject signal first with noise subspace tracer technique, then utilizes the multichannel period
The correlation between signal and satellite navigation signals after delay, using the DOA estimation method based on Clean thought, estimation is each
The steering vector of a satellite navigation signals is respectively finally each satellite construction Wave beam forming weight vector square using steering vector
Battle array, realize to satellite-signal come to enhancing.
The utility model has the advantages that compared with prior art, the present invention the reception for satellite navigation signals under complex electromagnetic environment is asked
Topic, using the noise subspace tracing algorithm of low computation complexity, effectively inhibits pressing type high reject signal, passes through simultaneously
Satellite-signal Mutual coupling (DOA) based on spreading code period auto-correlation and Clean thought passes through least mean-square error standard
The weight matrix of array beams formation is then constructed, to effectively enhance satellite navigation communication signal.The present invention does not need to know
The pilot symbol and satellite position of road transmission, are a kind of blind adaptive MUDs, while inhibiting complex jamming signal, effectively
The Signal to Interference plus Noise Ratio for improving navigation signal, improve capture and tracking ability of the satellite navigation receiver in interference environment,
System under complex environment can be improved to a certain extent, and satellite navigation reception is improved to the reception ability of satellite navigation signals
Machine received signal quality.
Detailed description of the invention
Fig. 1 is that the GNSS receiver multi-beam based on subspace tracking is directed toward anti-interference functional block diagram；
Fig. 2 is the strong interference suppression method process flow diagram tracked based on subspace；
Fig. 3 is the satellite-signal source direction parameter Estimation process flow diagram based on Clean thought；
Fig. 4 is even linear array array element distribution map.
Specific embodiment
In the following with reference to the drawings and specific embodiments, the present invention is furture elucidated.
The present embodiment applies the method for the present invention in GNSS system, as shown in Figure 1, itself specific steps are as follows:
S1: the antenna array elements number for enabling satellite navigation receiver is M, and M is the natural number greater than 1, and satellite navigation receives
Machine aerial array is denoted as x (n) in the baseband signal that moment n is received, then has
Wherein, TsFor the sampling interval；L is satellite signal source quantity；To first of satellite, sl(n), clAnd τl(n) it is respectively
Its corresponding satellite useful signal, C/A code and signal delay；a(θl) be first of satellite steering vector, θlFor its direction of arrival
Angle parameter；K is interference source quantity；JkIt (n) is interference signal, dkFor its steering vector；V (n) is additive white Gaussian noise.Benefit
It can be rewritten as with data vector form above formula
X (n)=s (n)+u (n)+V (n)
Calculate the covariance matrix R for the signal X (n) that satellite navigation receiver antenna array is arrived in n receptionxx, then have
Rxx=E { X (n) XH(n) }=Rs+Ru+Rv
Wherein, E { } is statistical expection, ()HIt is handled for the conjugate transposition of matrix, Rs, RuAnd RVRespectively GNSS letter
Number, the covariance matrix of interference signal and noise, be respectively defined as
S2: using rapid data sciagraphy (FDPM) to covariance matrix RxxNoise subspace projection orthonormal basis
It is iterated solution, obtains the corresponding characteristic vector estimation w of noise subspacesub, below to the step for make and illustrating:
Under strong interference environment, it is further assumed that uncorrelated each other between the signal in disturbance source, interference, noise and lead
Navigate satellite-signal between it is irrelevant each other, then the signal covariance matrix that satellite navigation system receives can approximate description be
Rxx=Ru+R′s
Wherein, R 's=Rs+RVFor the component collectively constituted by signal and noise component(s), since high reject signal power is general
Much stronger than receiver noise level, and it is usually 20- lower than noise level without the GNSS signal power of auto-correlation processing
Therefore 30dB receives in signal entirely, interfering signal power is occupied an leading position, and GNSS signal and receiver thermal noise can quilts
It is considered noise signal.At this point, if to RxxCarry out Eigenvalues Decomposition, then can by receive signal decomposition be two sub-spaces and
Collection, i.e.,
Wherein, ∑I=diag { λ1..., λKIt is the K × K dimension diagonal matrix being made of K maximum eigenvalue, it is corresponding
K feature vector constitutes M × K dimension matrix UI, open into interference signals subspace；And ∑V=diag { λK+1..., λM-KInclude
Remaining M-K characteristic value, corresponding M-K feature vector constitute M × (M-K) dimension matrix UV, at including
The noise signal subspace of GNSS signal and receiver thermal noise.
Conventional method generally by carrying out Eigenvalues Decomposition to the covariance matrix for receiving signal, will receive signal and project to
To inhibit strongly disturbing influence in noise signal subspace.But these methods are more for bay and receiving platform movement
Time-varying scene is not applicable, needs to obtain by the data of multiple snaps preferable as a result, computational complexity is high.
This method step introduces data projection model in strong jamming inhibition processing, by the anti-of orthogonal intersection cast shadow matrix
Multiple iteration, can be completed the estimation to subspace projection matrix using the sampled data of single snap, avoids to multiple snaps
The calculating and matrix inversion of data autocorrelation matrix, reduce computation complexity.
As shown in Fig. 2, steps are as follows for its concrete implementation:
S2-1: initialization iteration count n=0 is arranged pre-determined threshold δ=0.001, using random orthogonal initial method
Noise subspace projection matrix is initialized, orthogonal matrix U is obtained0；
S2-2: to nth iteration, current subspace signal projection is calculated
S2-3: calculating Householder reflection matrix has
Wherein, e1=[1,0 ..., 0]T,For vector rnThe corresponding argument value of first element；
S2-4: orthonormal matrix is calculated
Whereinβ >=0 is Learning Step；
S2-5: to znRegularization is carried out, U is assigned ton+1, i.e.,
Un+1=znD
Wherein,
S2-6: incremental, n=n+1 is carried out to iteration count；
If | | Un+1-Un||2>=δ, then repeatedly step S2-1~S2-5, otherwise exports optimal projection matrix Uopt。
S3: the noise subspace characteristic vector w obtained using step S2subExist to the aerial array of satellite navigation receiver
After the calibration that moment n is received baseband signal X (n) carry out projection process, obtain baseband signal X (n) noise subspace most
Excellent projectionIt realizes to strongly disturbing inhibition.
S4: as shown in figure 3, respectively to data after projectionOne C/A code of delay of each channel data
Cycle T then has the signal to i-th of channel, after delay to be represented by
Wherein, ai(θl) it is a (θl) i-th of element, viIt (n) is the noise signal in i-th of channel after projection, it is contemplated that
C/A code is periodic signal, to there is cl(nTs-τl(n)-T)=cl(nTs-τl(n)), then above formula is represented by
Signal since the C/A code of each satellite is independent of one another, then after projectingWith the signal u after delayi(n) mutual
Dependent vector is represented by
Wherein,For complex constant,For the power of the l satellite-signal, new vector is constructedThen above formula is represented by
Wherein,For Kronecker product.It enablesThen above formula is represented by
It enablesThen above formula is represented by matrix form
Wherein,Utilize sample cross-correlation vectorInstead ofAnd by minimizing mesh as follows
Scalar functions are estimatedAnd θ.
Referring to Fig. 3, estimationSteps are as follows with the specific method of θ:
S4-1: setting L=1, enablesEstimated using following formula
S4-2: to L=2, residual error is calculatedEstimated using following formula
S4-3: to L=k, residual error is calculatedEstimated using following formula
S4-4: repeating the above steps, and presets satellite number until L is equal to, thus obtains the DOA parameter of whole satellite-signals
S5: according to the direction of arrival parameter of each satellite antennaConstruct steering vector matrixWhereinFor the guiding arrow of the l satellite-signal determined by antenna array structure
Amount.
The present embodiment is by taking simple even linear array shown in Fig. 4 as an example, if each array element spacing is d, then it corresponds to steering vector
Matrix is
It enablesFor the steering vector of the l satellite-signal, then
Its corresponding array weight vector is had by minimum mean square error criterion
Then the output signal of first of wave beam is
S6: the L that is obtained using step S5 optimal array weight vector is respectively weighted input signal cumulative, obtains
The observation output signal Y (n) of each satellite=[z1(n), z2(n) ..., zL(n)]。
It is led by the way that the above-mentioned multi-beam based on subspace tracking is directed toward anti-interference method applied to satellite in the present embodiment
Boat reception system, this method can enhance satellite navigation signals, effectively raise while inhibiting to suppress standard interference
The anti-interference ability of GNSS system.
Claims (7)
1. a kind of GNSS receiver multi-beam based on subspace tracking is directed toward anti-interference method, it is characterised in that: including as follows
Step:
S1: setting the satellite navigation receiver antenna array of M (M > 1, M ∈ N) a array element in the baseband signal that moment n is received is X
(n), its corresponding covariance matrix R is calculatedxx；
S2: it is iterated and is asked using orthonormal basis of the rapid data sciagraphy to the noise subspace projection of covariance matrix
Solution obtains the corresponding characteristic vector estimation w of noise subspacesub；
S3: the noise subspace characteristic vector w obtained using step S2subTo the aerial array of satellite navigation receiver in moment n
Baseband signal X (n) carries out projection process after the calibration received, obtains baseband signal X (n) in the optimal projection of noise subspace
Ysub；
S4: respectively to data Y after projectionsubOne C/A code period of delay of each channel data, using based on Clean thought one by one
Estimate the direction of arrival parameter of each satellite navigation signalsL is the number of satellite signals that receiver receives；
S5: according to the direction of arrival parameter of each satellite antennaCorresponding wave is constructed up to vectorAccording to
Minimum mean square error criterion can obtainWhereinIt is
The corresponding optimal array weight vector of l satellite；
S6: the L optimal array weight vectors obtained using step S5 are respectively to optimal projection YsubIt is weighted cumulative, obtains
The observation output signal Y (n) of each satellite.
2. a kind of GNSS receiver multi-beam based on subspace tracking according to claim 1 is directed toward anti-interference method,
It is characterized by: the expression formula of baseband signal X (n) is as follows in the step S1:
Wherein, TsFor the sampling interval；L is satellite signal source quantity；To first of satellite, sl(n), clAnd τlIt (n) is respectively its correspondence
Satellite useful signal, C/A code and signal delay；a(θl) be first of satellite steering vector, θlFor its direction of arrival angle ginseng
Number；K is interference source quantity；JkIt (n) is interference signal, dkFor its steering vector；V (n) is additive white Gaussian noise.
3. a kind of GNSS receiver multi-beam based on subspace tracking according to claim 2 is directed toward anti-interference method,
It is characterized by: the expression formula of the baseband signal X (n) is written over using data vector form:
X (n)=s (n)+u (n)+V (n)
The covariance matrix for calculating the signal X (n) that satellite navigation receiver antenna array is arrived in n reception, then have
Rxx=E { X (n) XH(n) }=Rs+Ru+Rv
Wherein, E { } is statistical expection, ()HIt is handled for the conjugate transposition of matrix, Rs, RuAnd RVRespectively GNSS signal, interference
The covariance matrix of signal and noise, is respectively defined as
4. a kind of GNSS receiver multi-beam based on subspace tracking according to claim 1 is directed toward anti-interference method,
It is characterized by: utilizing the standard of noise subspace projection of the rapid data sciagraphy to covariance matrix in the step S2 just
Handing over base to be iterated solution, specific step is as follows:
S2-1: initialization iteration count n=0 is arranged pre-determined threshold δ=0.001, using random orthogonal initial method to making an uproar
Phonon space projection matrix is initialized, and orthogonal matrix U is obtained0；
S2-2: to nth iteration, current subspace signal projection is calculated
S2-3: calculating Householder reflection matrix has
Wherein, e1=[1,0 ..., 0]T,For vector rnThe corresponding argument value of first element；
S2-4: orthonormal matrix is calculated
Whereinβ >=0 is Learning Step；
S2-5: to znRegularization is carried out, U is assigned ton+1, i.e.,
Un+1=znD
Wherein,
S2-6: incremental, n=n+1 is carried out to iteration count；
If | | Un+1-Un||2>=δ, then repeatedly step S2-1~S2-5, otherwise exports optimal projection matrix Uopt。
5. a kind of GNSS receiver multi-beam based on subspace tracking according to claim 4 is directed toward anti-interference method,
It is characterized by: optimal projection in the step S3
6. a kind of GNSS receiver multi-beam based on subspace tracking according to claim 1 is directed toward anti-interference method,
It is characterized by: respectively to data Y after projection in the step S4subOne C/A code period of delay of each channel data, then have
To i-th of channel, the signal after delay is expressed as
Wherein, ai(θl) it is a (θl) i-th of element, viIt (n) is the noise signal in i-th of channel after projection；In view of C/A code
For periodic signal, to there is cl(nTs-τl(n)-T)=cl(nTs-τl(n)), above formula is expressed as
Signal since the C/A code of each satellite is independent of one another, then after projectingWith the signal u after delayi(n) cross-correlation
Vector representation is
Wherein,For complex constant,For the power of the l satellite-signal；Construct new vectorThen above formula is represented by
Wherein,For Kronecker product, enableAbove formula is expressed as
It enablesThen above formula is represented by matrix form
Wherein,Utilize sample cross-correlation vectorInstead ofAnd by minimizing target letter as follows
Number is to estimateAnd θ.
7. a kind of GNSS receiver multi-beam based on subspace tracking according to claim 6 is directed toward anti-interference method,
It is characterized by: being estimated in the step S4 using objective function is minimizedWith the detailed process of θ are as follows:
S4-1: setting L=1, enablesEstimated using following formula
S4-2: to L=2, residual error is calculatedEstimated using following formula
S4-3: to L=k, residual error is calculatedEstimated using following formula
S4-4: repeating the above steps, and presets satellite number until L is equal to, thus obtains the DOA parameter of whole satellite-signals
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