CN109001687A - Airborne radar space-time self-adaptive filtering method based on generalized sidelobe cancellation structure - Google Patents
Airborne radar space-time self-adaptive filtering method based on generalized sidelobe cancellation structure 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
- 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
- G01S7/28—Details of pulse systems
- G01S7/2813—Means providing a modification of the radiation pattern for cancelling noise, clutter or interfering signals, e.g. side lobe suppression, side lobe blanking, null-steering arrays
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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
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
- G01S7/292—Extracting wanted echo-signals
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Abstract
A kind of airborne radar space-time self-adaptive filtering method based on generalized sidelobe cancellation structure, implementation step is: building radar return signal matrix;Obtain distance unit to be detected and its training sample;Estimate the clutter covariance matrix of distance unit to be detected;Adaptive-filtering weight based on generalized sidelobe cancellation Structure Calculation radar;Data in testing distance unit are filtered.The data of testing distance unit are added when selecting training sample by the present invention, estimate testing distance unit clutter covariance matrix, utilize generalized sidelobe cancellation structure, target component in testing distance unit clutter covariance matrix is eliminated, retain interference information, and filter weights are calculated by the clutter covariance matrix after elimination target signal elements, it restrained effectively the interference in testing distance unit, the gain of interference signal is reduced, while improving the gain of the output echo signal when number of training is less.
Description
Technical field
The invention belongs to fields of communication technology, are related to a kind of airborne radar space-time self-adaptive filtering method, and in particular to one
Airborne radar space-time self-adaptive filtering method of the kind based on generalized sidelobe cancellation structure, the output that can be used for reducing airborne radar are dry
Signal gain is disturbed, and improves output targeted signal gain of the airborne radar when number of training is seldom.
Background technique
In recent years, increasingly mature with Radar Technology, radar has been widely used for military forecasting, missile guidance, civil aviaton
The various fields such as control, topographic survey, navigation.The main task of radar is inhibited to clutter, for airborne radar,
Clutter environment locating for it is extremely complex, and traditional filtering method can not effectively press down the received clutter of airborne radar
System, space-time self-adaptive filtering method are come into being.
At present the core procedure of traditional space-time self-adaptive filtering method be select it is adjacent with testing distance unit several
A distance unit estimates testing distance unit clutter covariance matrix as training sample, by these training samples, and utilizes
The clutter covariance matrix of estimation calculates adaptive-filtering weight, filters finally by adaptive-filtering weight to to-be-measured cell
Wave is to obtain output signal.The shortcomings that this method is the training sample for being difficult to obtain quantity abundance in non-homogeneous environment, is made
The estimation inaccuracy to to-be-measured cell clutter covariance matrix is obtained, and then is filtered by the calculated adaptive-filtering weight of the matrix
Performance decline leads to the targeted signal gain decline of output.
Paper " the Improving EFA-STAP performance using that Wang Tong et al. is delivered at it
persymmetric covariance matrix estimation”(IEEE Transactions On Aerosapce And
Electronic Systems, vol.51, No.2, pp.924-936,2015) in propose it is a kind of based on clutter architectural characteristic
Space-time self-adaptive filtering method.This method thes improvement is that compared to traditional space-time self-adaptive filtering method, this method
The architectural characteristic of clutter is utilized when estimating the clutter covariance matrix of to-be-measured cell, when number of training deficiency
To-be-measured cell clutter covariance matrix can accurately be estimated, be improved in number of training deficiency at through this method
Output targeted signal gain after reason.But its existing shortcoming is, does not account for list to be measured when selecting training sample
There is the case where interference in member, due to being free of the interference information of to-be-measured cell in training sample, causes through these training samples
The adaptive-filtering weight of calculating can not effectively inhibit interference present in testing distance unit, lead to the dry of output
It is higher to disturb signal gain.
Summary of the invention
It is a kind of based on generalized sidelobe cancellation structure it is an object of the invention in view of the above shortcomings of the prior art, propose
The data of testing distance unit are added when selecting training sample for airborne radar space-time self-adaptive filtering method, estimate measured
From unit clutter covariance matrix, using generalized sidelobe cancellation structure, by the mesh in testing distance unit clutter covariance matrix
It marks ingredient to eliminate, retains interference information, and filter weights are calculated by the clutter covariance matrix after elimination target signal elements,
It restrained effectively the interference in testing distance unit, reduce the gain of interference signal, implement step are as follows:
(1) radar return signal matrix is constructed:
To the linear antenna arrays of airborne radar symmetry arrangement the received array emitter pulse at equal intervals echo
Data carry out K snap sampling, and construct JN × K by all reception signal phasors that sampling obtains and tie up radar return signal square
Battle array, wherein J indicates that the array number of radar antenna array, N indicate transmitting umber of pulse, J >=2, N >=2, K >=2JN+2;
(2) distance unit X and its training sample X to be detected is obtainedk:
(2a) optional column from radar return signal matrix receive signal phasor as distance unit X to be detected;
(2b) removes reception signal phasor adjacent with X in radar return signal matrix, obtains new radar return signal
Matrix, and by the L continuously chosen from new radar return signal matrix the reception signal phasors adjacent with X, as to be checked
Survey the training sample X of distance unit Xk, wherein k indicates training sample XkThe middle serial number for receiving signal phasor, k=1,2 ..., L,
L≥JN/2;
(3) the clutter covariance matrix R of distance unit X to be detected is estimated;
(4) based on the adaptive-filtering weight W of generalized sidelobe cancellation Structure Calculation radar:
(4a) calculates the steering vector S of area to be tested, and constructs blocking matrix B, it is made to meet BHS=0, H are indicated altogether
Yoke transposition;
(4b) eliminates the target signal elements in clutter covariance matrix R, obtains new clutter covariance matrix Rb, Rb=
BHRB;
(4c) is to new clutter covariance matrix RbFeature decomposition is carried out, and according to descending sequence to decomposition gained
Characteristic value be ranked up, pass through the corresponding feature vector of preceding r characteristic value and construct dimensionality reduction matrix U, r >=J+N-1;
(4d) is using U to RbCarry out dimension-reduction treatment, the clutter covariance matrix R after obtaining dimensionality reductionz, Rz=UHRbU;
The adaptive-filtering weight W of (4e) calculating radar:
Wherein, -1 inversion operation is indicated;
(5) data in testing distance unit X are filtered:
The data in testing distance unit X are filtered using adaptive-filtering weight W obtained in step (4e), are obtained
To output signal Y, Y=WHX。
Compared with prior art, the present invention having the advantage that
First, it joined the data in testing distance unit when selecting training sample due to the present invention, by these training
Sample estimates clutter covariance matrix, and is carried out by generalized sidelobe cancellation structure to the signal component in clutter covariance matrix
It eliminates, remains interference information, restrained effectively the interference in testing distance unit, compared with prior art, effectively drop
The low gain of interference signal.
Second, it is that difference is defenced jointly by the clutter after dimensionality reduction since the present invention is when calculating the adaptive-filtering weight of radar
What matrix was realized, it avoids the prior art and is lacked using original clutter covariance matrix bring training sample demand is high
It falls into, improves the precision to the estimation of testing distance unit clutter covariance matrix, and then improve when number of training is less
Output echo signal gain.
Detailed description of the invention
Fig. 1 is implementation flow chart of the invention;
Fig. 2 is the output signal power figure of prior art different distance unit after filtering when to-be-measured cell exists and interferes;
Fig. 3 is the output signal power figure of present invention different distance unit after filtering when to-be-measured cell exists and interferes;
Fig. 4 is the output signal power figure of different distance unit after the prior art is filtered when training sample is 50;
Fig. 5 is the output signal power figure of different distance unit after the present invention is filtered when training sample is 50.
Specific embodiment
In the following with reference to the drawings and specific embodiments, the present invention is described in further detail.
Referring to Fig.1, the present invention includes the following steps.
Step 1, radar return signal matrix is constructed:
To the linear antenna arrays of airborne radar symmetry arrangement the received array emitter pulse at equal intervals echo
Data carry out K snap sampling, and construct JN × K by all reception signal phasors that sampling obtains and tie up radar return signal square
Battle array, wherein J indicates that the array number of radar antenna array, N indicate transmitting umber of pulse, J=14, N=16, K=630;
Step 2, distance unit X and its training sample X to be detected are obtainedk:
(2a) optional column from radar return signal matrix receive signal phasor as distance unit X to be detected;
(2b) removes reception signal phasor adjacent with X in radar return signal matrix, obtains new radar return signal
Matrix, and the reception signal by the L continuously chosen from new radar return signal matrix including testing distance unit
Vector, the training sample X as distance unit X to be detectedk, so that training is also added in the interference information in testing distance unit
In sample, wherein k indicates training sample XkThe middle serial number for receiving signal phasor, k=1,2 ..., L, L=112;
Step 3, the clutter covariance matrix R of distance unit X to be detected is estimated:
(3a) constructs airspace transition matrix Ts:
Wherein, ΙsIndicate one N × N-dimensional unit matrix, JsIndicate that a counter-diagonal element is 1, the J that remaining element is zero
× J ties up matrix,Indicate Kronecker product;
(3b) is to training sample XkIn all reception signal phasors carry out airspace conversion, obtain new training sample
(3c) constructs time domain transition matrix Tt:
Wherein, ΙtIndicate one J × J dimension unit matrix, JtIndicate that a counter-diagonal element is 1, the N that remaining element is zero
× N-dimensional matrix;
(3d) is to training sample XkIn all reception signal phasors carry out time domain conversion, obtain new training sample * it indicates to take conjugation;
(3e) constructs Space-time domain transition matrix Tst,
(3f) is to training sample XkIn all reception signal phasors carry out Space-time domain conversion, obtain new training sample
(3g) uses Xk、WithEstimate that clutter assists square matrix R:
Wherein, L indicates training sample XkThe middle number for receiving signal phasor, k indicate training sample XkMiddle reception signal phasor
Serial number, L >=JN/2;
Step 4, based on the adaptive-filtering weight W of generalized sidelobe cancellation Structure Calculation radar:
(4a) calculates the steering vector S of area to be tested, and constructs blocking matrix B, it is made to meet BHS=0 is indicated to be measured
The orthogonal intersection space of the steering vector S of distance unit X, H indicate conjugate transposition, calculate the reality of the steering vector S of testing distance unit X
Existing step are as follows:
(4a1) constructs the airspace steering vector S in region to be measureds:
Wherein, T indicates transposition,D indicates the array element spacing of radar antenna array, and λ indicates thunder
Up to operation wavelength, θ is azimuth of the region to be measured relative to radar,Pitch angle for region to be measured relative to radar;
(4a2) constructs the time domain steering vector S in region to be measuredt:
Wherein,V indicates airplane motion speed, frIndicate the pulse recurrence frequency of radar;
(4a3) calculates the steering vector S in region to be measured,
(4b) is since the echo signal in actual environment has directionality, and noise signal does not have directionality and interference letter
It is number different from the directionality of echo signal, all data in clutter covariance matrix are mapped to the sky orthogonal with echo signal
Between in, interference in testing distance unit and clutter information, root can be retained under the premise of eliminating as much as target component
According to this principle, the target signal elements in clutter covariance matrix R are eliminated by blocking matrix, obtain new clutter covariance
Matrix Rb, Rb=BHRB;
(4c) is to new clutter covariance matrix RbFeature decomposition is carried out, and according to descending sequence to decomposition gained
Characteristic value be ranked up, pass through the corresponding feature vector of preceding r characteristic value and construct dimensionality reduction matrix U, r=56, which indicates
By the subspace of clutter;
(4d) is using U to RbDimension-reduction treatment is carried out, by RbIn data be mapped to clutter subspace, it is miscellaneous after obtaining dimensionality reduction
Wave covariance matrix Rz, Rz=UHRbU is reduced after dimension-reduction treatment for estimating testing distance unit clutter covariance square
The training sample demand of battle array;
The adaptive-filtering weight W of (4e) calculating radar:
Wherein, -1 inversion operation is indicated;
Step 5, the data in testing distance unit X are filtered:
The data in testing distance unit X are filtered using adaptive-filtering weight W obtained in step (4e), are obtained
To output signal Y, Y=WHX。
Verifying explanation is carried out to above-mentioned beneficial effect of the invention below by way of emulation experiment.
1, simulation parameter is arranged:
Using the file rl050575 in multichannel airborne radar measured data MCARM, the 1 to 14th battle array therein is taken
Clutter data in member, the 1 to 16th pulse and whole 630 distance unit carries out emulation experiment.
2. emulation content:
Emulation experiment 1:
Use document [Yalong Tong, Tong Wang, and Jianxin Wu " Improving EFA-STAP
performance using persymmetric covariance matrix estimation,"IEEE
Transactions On Aerosapce And Electronic Systems,vol.51,No.2,pp.924-936,
2015.] space-time self-adaptive filtering method based on clutter architectural characteristic proposed in is compared with the present invention, by to-be-measured cell
It is set as the 3rd doppler cells in the 290th distance unit, the 65th angle-unit, the phase in identical distance unit
With the interference signal that a signal to noise ratio is -30dB is added in the 4th doppler cells of angle-unit, 112 training samples are utilized
The clutter covariance matrix of to-be-measured cell is estimated, and calculates adaptive-filtering weight, it is single to the 270 to 340th distance
Member is filtered, and draws the filtered signal power figure of different distance unit.
The result of emulation experiment 1 is as shown in Fig. 2 and Fig. 3, and wherein abscissa is distance unit, and ordinate is output signal
Power, the output signal power in different distance unit obtained after being filtered in Fig. 2 by existing method pass through in Fig. 3
The output signal power in different distance unit obtained after the method for the present invention filtering.
Emulation experiment 2:
To-be-measured cell is added in the echo signal that one signal to noise ratio is -30dB, using 50 training samples to to-be-measured cell
Clutter covariance matrix is estimated, and calculates adaptive-filtering weight, is filtered, draws to the 270 to 340th distance unit
The filtered output signal power figure of different distance unit processed.
The result of emulation experiment 2 is as shown in Fig. 4 and Fig. 5, and wherein abscissa is distance unit, and ordinate is output signal
Power, the output signal power in different distance unit obtained after being filtered in Fig. 4 by existing method pass through in Fig. 5
The output signal power in different distance unit obtained after the method for the present invention filtering.
3. analysis of simulation result:
Comparison diagram 2 and Fig. 3 can be seen that can be in detecting the 290th distance unit after the method for the present invention is handled
Echo signal, and existing method can not detect the echo signal of the 290th distance unit.
Comparison diagram 4 and Fig. 5 can be seen that in the case where number of training is 50, after the method for the present invention is handled
The output gain signal of 290th distance unit existing for target is higher than through existing method treated output gain signal.
Claims (3)
1. a kind of airborne radar space-time self-adaptive filtering method based on generalized sidelobe cancellation structure, which is characterized in that including such as
Lower step:
(1) radar return signal matrix is constructed:
To the linear antenna arrays of airborne radar symmetry arrangement the received array emitter pulse at equal intervals echo data
K snap sampling is carried out, and constructs JN × K by all reception signal phasors that sampling obtains and ties up radar return signal matrix,
Wherein, J indicates that the array number of radar antenna array, N indicate transmitting umber of pulse, J >=2, N >=2, K >=2JN+2;
(2) distance unit X and its training sample X to be detected is obtainedk:
(2a) optional column from radar return signal matrix receive signal phasor as distance unit X to be detected;
(2b) removes reception signal phasor adjacent with X in radar return signal matrix, obtains new radar return signal matrix,
And by the reception signal phasor from the L continuously chosen in new radar return signal matrix including testing distance unit X,
Training sample X as distance unit X to be detectedk, wherein k indicates training sample XkThe middle serial number for receiving signal phasor, k=1,
2 ..., L, L >=JN/2;
(3) the clutter covariance matrix R of distance unit X to be detected is estimated;
(4) based on the adaptive-filtering weight W of generalized sidelobe cancellation Structure Calculation radar:
(4a) calculates the steering vector S of area to be tested, and constructs blocking matrix B, it is made to meet BHS=0, H indicate that conjugation turns
It sets;
(4b) eliminates the target signal elements in clutter covariance matrix R, obtains new clutter covariance matrix Rb, Rb=BHRB;
(4c) is to new clutter covariance matrix RbFeature decomposition is carried out, and to the resulting characteristic value of decomposition according to descending
Sequence is ranked up, and constructs dimensionality reduction matrix U, r >=J+N-1 by the corresponding feature vector of preceding r characteristic value;
(4d) is using U to RbCarry out dimension-reduction treatment, the clutter covariance matrix R after obtaining dimensionality reductionz, Rz=UHRbU;
The adaptive-filtering weight W of (4e) calculating radar:
Wherein, -1 inversion operation is indicated;
(5) data in testing distance unit X are filtered:
The data in testing distance unit X are filtered using adaptive-filtering weight W obtained in step (4e), are obtained defeated
Signal Y out, Y=WHX。
2. the airborne radar space-time self-adaptive filtering method according to claim 1 based on generalized sidelobe cancellation structure,
It is characterized in that, the clutter covariance matrix R of estimation distance unit X to be detected described in step (3) realizes step are as follows:
(3a) constructs airspace transition matrix Ts:
Wherein, ΙsIndicate one N × N-dimensional unit matrix, JsIndicate that a counter-diagonal element is 1, J × J dimension that remaining element is zero
Matrix,Indicate Kronecker product;
(3b) is to training sample XkIn all reception signal phasors carry out airspace conversion, obtain new training sample
(3c) constructs time domain transition matrix Tt:
Wherein, ΙtIndicate one J × J dimension unit matrix, JtIndicate that a counter-diagonal element is 1, N × N-dimensional that remaining element is zero
Matrix;
(3d) is to training sample XkIn all reception signal phasors carry out time domain conversion, obtain new training sample * it indicates to take conjugation;
(3e) constructs Space-time domain transition matrix Tst,
(3f) is to training sample XkIn all reception signal phasors carry out Space-time domain conversion, obtain new training sample
(3g) uses Xk、WithEstimate that clutter assists square matrix R:
Wherein, L indicates training sample XkThe middle number for receiving signal phasor, k indicate training sample XkThe middle sequence for receiving signal phasor
Number, L >=JN/2.
3. the airborne radar space-time self-adaptive filtering method according to claim 1 based on generalized sidelobe cancellation structure,
It is characterized in that, the steering vector S of calculating distance unit X to be detected described in step (4a) realizes step are as follows:
(4a1) constructs the airspace steering vector S in region to be measureds:
Wherein, T indicates transposition,D indicates the array element spacing of radar antenna array, and λ indicates radar work
Wavelength, θ are azimuth of the region to be measured relative to radar,Pitch angle for region to be measured relative to radar;
(4a2) constructs the time domain steering vector S in region to be measuredt:
Wherein,V indicates airplane motion speed, frIndicate the pulse recurrence frequency of radar;
(4a3) calculates the steering vector S in region to be measured,
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CN113406578A (en) * | 2021-05-25 | 2021-09-17 | 中山大学 | Target detection method and device for distributed unmanned airborne radar and storage medium |
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CN114859299A (en) * | 2022-07-06 | 2022-08-05 | 长沙莫之比智能科技有限公司 | Weighting constraint composite filtering method based on unmanned aerial vehicle obstacle avoidance millimeter wave radar |
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