CN106872949A - A kind of clutter spectrum registration compensation method based on adaptive equalization loading - Google Patents
A kind of clutter spectrum registration compensation method based on adaptive equalization loading Download PDFInfo
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Abstract
The invention discloses a kind of clutter spectrum registration compensation method based on adaptive equalization loading, including step：Airborne radar range cell echo data is rearranged into matrix；Space-time sub-aperture is carried out to gained matrix to smooth, smooth sample matrix is obtained, and obtains the covariance matrix of the training range cell under sub-aperture；Adaptive equalization loading is carried out, each training range cell clutter covariance matrix is obtained；The clutter scattering coefficient at discrete point is tried to achieve in calculating, the clutter scattering coefficient reconstruct data for calculating, clutter data and clutter covariance matrix after being reconstructed；Solve and obtain transformation matrix；Line translation is entered to each training range cell and obtains sample data, and estimate the clutter covariance matrix of range cell to be detected；Adaptive equalization loading is carried out again, obtains unit clutter covariance matrix estimate to be detected.The present invention improves the degree of accuracy of reference distance Cell Reconstruction data, can effectively improve detectability of the airborne radar to target at a slow speed.
Description
Technical field
The present invention relates to a kind of clutter spectrum registration compensation method based on adaptive equalization loading, belong to airborne radar clutter
The technical field of compensation.
Background technology
Airborne radar is faced with than more serious non-homogeneous clutter environment lower in the course of work, usually, is on the one hand
Caused due to the height fluctuations of landform；On the other hand it is because different array modes of emplacement or different arrays are several
What what configuration was caused.Typical non-working side array airborne radar, just occurs serious distance dependencies, shows as short range miscellaneous
The change violent with the change of range cell of the power spectrum of ripple.Now, the method for maximal possibility estimation is in environment heterogeneous
The clutter covariance matrix of range cell to be detected cannot exactly be estimated again down, so as to cause at traditional space-time adaptive
Manage the clutter recognition effect severe exacerbation of (Space-time Adaptive Processing, abbreviation STAP) algorithm.Therefore, exist
Under non-working side array environment, the clutter covariance matrix that unit to be detected how is estimated exactly is that STAP technologies need research
With the key problem for solving.
At present, the main thought for solving the problems, such as short range clutter distance dependencies is to carry out registration and compensation, such as Doppler frequently
Move penalty method (DW), angle Doppler effect correction method (ADC), the clutter spectrum compensation method (RBC) based on registration etc..DW algorithms belong to
The one-dimensional translation of Doppler, the parameter provided using radar platform inertial navigation system, calculates the clutter Doppler of each range cell frequently
Rate, then along Doppler frequency axle, by space-time clutter spectrum from the space-time clutter spectrum of range cell to be compensated to reference distance unit
Direction translates so that the Doppler frequency after translation in both directions is identical, so that reduce clutter spectrum widening degree, to reduce
Clutter heterogeneity；ADC algorithms belong to two-dimension translational, are that on the basis of the clutter spectrum center of reference distance unit, will respectively treat
Moved along wave beam and Doppler direction respectively at the clutter spectrum center of compensating unit so that after translation the clutter spectrum center of each unit with
The clutter spectrum center superposition of reference unit, improves the heterogeneity of clutter distance dimension distribution.But, these compensation methodes are all profits
With the thought of spectrum translation, the single-point compensation to main clutter point can only be realized, make clutter spectrum locate to overlap on one point, this is in actual measurement environment
It is relatively difficult to achieve in complex practical application and very sensitive to error.
Clutter spectrum compensation method based on registration can carry out registration in full spectral domain to clutter spectrum, be a kind of effective compensation
Method, but still come with some shortcomings.RBC methods are, by the reconstruct and conversion to each training unit data, to make each training unit
Noise performance with reference distance unit reaches unanimity, and then realizes the compensation of full spectral domain.However, RBC backoff algorithms are in reconstruct
Larger error can be produced during each range cell data, especially in short range clutter range cell, error becomes apparent, and with reference to away from
The registration accuracy reduction of each training unit, RBC compensation method hydraulic performance declines are will result directly in from the evaluated error of unit.RBC is mended
Algorithm is repaid for prior art, additionally, such as document (the airborne non-sidelooking arrays thunder under Liu Jinhui, Liao Guisheng, Li Ming range ambiguities
New method [J] electronic letters, vols, 2011,39 (9) are compensated up to clutter:2060-2066.) described, airborne non-sidelooking arrays radar is miscellaneous
Wave spectrum compensation new method is a kind of innovatory algorithm based on the compensation of RBC clutters, this method increase the pact to long-range clutter data
Beam is protected, while short range clutter distance dependencies are compensated, it is ensured that the space-time distribution of long-range clutter does not change.But should
Method is still present the larger problem of clutter covariance matrix estimate error in data reconstruction process, in registering compensation process
In cannot effectively improve the registration accuracy of RBC backoff algorithms.
Therefore, how to reduce clutter covariance matrix evaluated error present in data reconstruction process, improve to each distance
Unit is with particular reference to the weight that the degree of accuracy that the clutter covariance matrix of range cell is estimated is that the algorithm needs to study and solve
Want problem.
The content of the invention
The technical problems to be solved by the invention are to overcome the deficiencies in the prior art, there is provided one kind is based on adaptive equalization
The clutter spectrum registration compensation method of loading, solves how existing method reduces clutter covariance present in data reconstruction process
Matrix Estimation error, improves to each range cell with particular reference to the degree of accuracy of the clutter covariance matrix estimation of range cell
Problem, is balanced by efficient adaptive and loaded, and smooth sample data and training sample data are carried out into adaptive equalization respectively
Loading, improves the accuracy to covariance matrix.
It is of the invention specific using following technical scheme solution above-mentioned technical problem：
A kind of clutter spectrum registration compensation method based on adaptive equalization loading, comprises the following steps：
Step 1, the echo data X for tieing up NK × 1 of l-th range cell of airborne radarlIt is rearranged into N × K dimensions
Matrix
Step 2, spatial domain sub-aperture is taken for G, Time domain sub-aperture is J, to step 1 gained matrixSpace-time sub-aperture is carried out to put down
It is sliding, obtain (N-G+1) (K-J+1) individual smooth sample matrix Qs,t；
Step 3, using step 2 gained (N-G+1) (K-J+1) individual smooth sample matrix Qs,tObtain the training range cell
Covariance matrix under sub-aperture
Step 4, the covariance matrix to each training range cell of step 3 gainedAdaptive equalization is carried out to add
Carry, each training range cell clutter covariance matrix after being loaded
There is P clutter discrete point to be evenly distributed in its angle Doppler in step 5, l-th training range cell of setting
On distribution curve, using step 4 gained clutter covariance matrixCalculate amplitude of the Capon spectrums at discrete point as the point
Value, the clutter scattering coefficient at the point is tried to achieve with calculating；
Step 6, the clutter scattering coefficient calculated using step 5 reconstruct data, clutter data after being reconstructed and miscellaneous
Ripple covariance matrix；
Step 7, the clutter covariance matrix solution acquisition transformation matrix T with step 6 gained reconstructl；
Step 8, using the transformation matrix T obtained in step 7l, line translation is entered to each training range cell, obtain sample
Data, and estimate to obtain the clutter covariance matrix of range cell to be detected
Step 9, to step 8 gained clutter covariance matrixAdaptive equalization loading is carried out again, after being loaded
Unit clutter covariance matrix estimate R to be detected0。
Further, as a preferred technical solution of the present invention, the step 4 pair gained each training range cell
Covariance matrixAdaptive equalization is loaded, and is specifically included：
Step 41, take statistics consistent sex factors of the weight coefficient α as the smooth sample clutter vector of measurement sub-aperture；
Step 42, the covariance matrix to each training range cell of step 3 gainedCarry out adaptive equalization loading；
Step 43, loaded after each training range cell clutter covariance matrix
Further, as a preferred technical solution of the present invention, in the step 41, weight coefficient α uses formula
Calculate：
Wherein, n is the number of samples for participating in estimating, i.e. n=(N-G+1) (K-J+1)；It is covariance matrix；
M(s,t)=V (Qs,t)V(Qs,t)H；Wherein, M(s,t)For each sub-aperture of the training range cell smooths the clutter covariance of sample
Matrix；Wherein ()HConjugate transposition is represented, V () is represented to be placed on the latter row of matrix below previous column and is transformed into one
Column vector.
Further, as a preferred technical solution of the present invention, in the step 4, each after being loaded
Train the clutter covariance matrix of range cellFor：
Wherein, α is weight coefficient；I is unit matrix；It is covariance matrix.
Further, as a preferred technical solution of the present invention, in the step 8, estimate to obtain distance to be detected
The clutter covariance matrix of unitFor：
Wherein, YlIt is the sample data after registration compensation, and Yl=TlXl, l ∈ [- L, L], l ≠ 0；TlIt is transformation matrix；2L
It is the total number of training unit, L then respectively takes the number of training unit for the right and left；XlIt is l-th original time of range cell
Wave number evidence.
Further, as a preferred technical solution of the present invention, the step 9 is to step 8 gained clutter covariance
MatrixAdaptive equalization loading is carried out again, is specifically included：
Step 91, the statistics for taking the training range cell sample clutter vector after weight coefficient α ' is compensated as measurement registration
Consistent sex factor；
Step 92, to step 8 gained clutter covariance matrixCarry out adaptive equalization loading；
Step 93, loaded after unit clutter covariance matrix estimate R to be detected0。
Further, as a preferred technical solution of the present invention, in the step 91, weight coefficient α ' uses formula
Calculate：
Wherein, Ml' it is l-th clutter covariance matrix of training range cell, its size isYlIt is each instruction
Practice the sample data after range cell registration compensation；And n=2L, wherein n are the total number of training unit, L is then the right and left
Respectively take the number of training unit；It is the clutter covariance matrix of range cell to be detected.
The present invention uses above-mentioned technical proposal, can produce following technique effect：
The present invention provide based on adaptive equalization loading clutter spectrum registration compensation method, first, reconstruct training away from
During from unit and reference distance cell data, the clutter covariance matrix that the smooth sample data of sub-aperture is estimated is carried out adaptive
Loading should be balanced, is improved to each training range cell with particular reference to the accurate of the clutter covariance matrix estimation of range cell
Degree, improves registration accuracy.
Secondly, in the covariance matrix of the training sample data estimation unit to be detected after using reconstruct compensation, again
Loaded using adaptive equalization, further improve the degree of accuracy that the clutter covariance matrix of range cell to be detected is estimated, effectively
Improve the performance of RBC backoff algorithms.
Also, the present invention is when adaptive equalization loading is carried out, weight coefficient α is for measuring the smooth sample of sub-aperture
Or the consistent sex factor of statistics of training sample clutter vector, it reflects the stability of each sample, can measure out each sample
Notebook data deviates the degree of estimated mean value.If deviateing, average is less, its statistics uniformity is preferable, between different training samples
Relevance it is stronger, the statistical property for estimating is more accurate；Conversely, if deviateing, average is larger, it counts uniformity
Poor, the relevance between different training samples is weaker, and the clutter covariance matrix distortion for estimating is also larger.Therefore, exist
In the more serious short range clutter of clutter distance dependencies, statistics uniformity factor-alpha can be with the change of the stability of training sample
Change and adaptively change, can more accurately estimate the clutter covariance matrix of each range cell so that follow-up
Data reconstruction and registration effect are more accurate.
Therefore, by carrying out adaptive equalization loading, the estimated accuracy of single rang ring clutter covariance matrix is improved, is obtained
More accurate each range cell reconstruct data are obtained, the degree of accuracy of reference distance Cell Reconstruction data is especially improve.This side
Performance of the method in main lobe area and secondary lobe area has clear improvement, and can effectively improve detectability of the airborne radar to target at a slow speed,
Detectability of the airborne radar to target at a slow speed can be effectively improved, with certain theory significance and practical value.
Brief description of the drawings
Fig. 1 is the flow chart of the clutter spectrum registration compensation method based on adaptive equalization loading of the invention.
Fig. 2 is the geometric configuration schematic diagram of non-working side array airborne radar.
Fig. 3 be as radar slant-range respectively 8km, 12km, 30km, 50km, 80km, during 150km, forward sight battle array clutter spectrum side
Position Dopplergram.
Fig. 4 is that, as radar slant-range respectively 8km, 12km, 30km, 50km, 80km, during 150km, the clutter spectrum of forward sight battle array is special
The situation of change of value indicative.
Fig. 5 is that the clutter power spectrum contrast that directly treatment, RBC compensation methodes and the inventive method are processed is respectively adopted
Figure.
Fig. 6 (a) be main lobe direction be 10 degree when, using OPT optimal processings algorithm, RBC compensation methodes and the inventive method
When improvement factor comparison diagram.Fig. 6 (b) be main lobe direction be 30 degree when, using OPT optimal processings algorithm, RBC compensation methodes and
Improvement factor comparison diagram during the inventive method.
Specific embodiment
Embodiments of the present invention are described with reference to Figure of description.
Assuming that radar antenna is the even linear array of N number of array element, array element spacing is d, and carrier aircraft is flown with speed V along X-direction,
Aerial array is θ with the angle of velocity attitudeP, its array geometry configuration is as shown in Figure 2.
If height of the carrier aircraft apart from ground is H, if oblique distance is RcRang ring top parallactic angle for θ clutter scattering point be P.
Clutter sample data corresponding to l-th rang ring can be regarded as by NaIndividual clutter scattering point superposition composition.For orientation
Angle is θiScattering point, the clutter data of its l-th range gate can be expressed as：
In formula (1)Kronecker products are represented, β (l, i) represents the complex magnitude of the scattering point, NnRepresent NK × 1 dimension
Zero-mean Gaussian noise vector, ss(l, i) and stWhen (l, i) represents the corresponding steric direction vector of the clutter scattering point respectively
Between steering vector, and meet respectively：
Wherein, () in formula (2), (3)TThe transposition of representing matrix, frIt is pulse recurrence frequency, fs(l, i) and fd(l,
I) spatial frequency and Doppler frequency are respectively, are met respectively：
Wherein, λ represents the operation wavelength of radar,It is l-th angle of site of range gate.
Ignore the influence of earth curvature, the relational expression between spatial domain cone angle and normalization Doppler frequency can be extrapolated
For
Wherein, fdmIt is the maximum doppler frequency of clutter, its size is
From relation above expression formula, work as θPWhen being spent for 0 to 90, presented between clutter spatial domain cone angle and Doppler frequency
Elliptic systems；Work as θPBe 90 degree, i.e., forward sight battle array when, circular distribution is presented between clutter spatial domain cone angle and Doppler frequency.Fig. 3 gives
Go out as radar slant-range respectively 8km, 12km, 30km, 50km, 80km, during 150km, the clutter spectrum orientation Doppler of forward sight battle array
Figure, from the figure 3, it may be seen that clutter spectrum changes with distance change, and it is more violent in the change of short range, and delay relatively in remote change
Slowly until convergence.Fig. 4 gives the situation of change of clutter spectroscopic eigenvalue under different oblique distances, from Fig. 4 it can also be seen that short range clutter
The characteristic value of spectrum is changed greatly, and the clutter spectroscopic eigenvalue in long-range range cell tends to similar, demonstrate short range clutter away from
From dependence.
The invention provides a kind of RBC clutters compensation method based on adaptive equalization loading solve above-mentioned short range clutter away from
From dependency problem, the general frame of the method is as shown in figure 1, specifically include following steps：
Step 1, respectively taken before and after range cell to be detected first L range cell as training range cell, take l-th
Training range cell is used as reference distance unit.The echo data X that NK × 1 of l-th range cell of airborne radar is tieed uplAgain
The matrix of N × K dimensions is arranged in, i.e.,
Step 2, spatial domain sub-aperture is taken for G, Time domain sub-aperture is J, rightCarry out space-time sub-aperture to smooth, then can obtain
(N-G+1) (K-J+1) individual smooth sample matrix Qs,t∈CG×J,
Step 3, the training distance can be obtained using smoothing (N-G+1) (K-J+1) individual sample data for obtaining in step 2
Covariance matrix of the unit under sub-aperture
Wherein, ()HConjugate transposition is represented, V () is represented to be placed on the latter row of matrix below previous column and is transformed into
One column vector.
Step 4, in the processing procedure of above-mentioned steps 3, the clutter covariance matrix of reconstructStill there is larger mistake
Difference, then becomes apparent in short range clutter range cell error.In order that the clutter covariance matrix that respectively training range cell is estimated
It is more accurate, it is of the invention to propose to being carried out certainly by the covariance matrix for smoothing sample to estimate and obtaining in each training range cell
Adapt to balance loading.The step of adaptive equalization is loaded includes：
Step 41, statistics consistent sex factors of the weight coefficient α as the smooth sample clutter vector of measurement sub-aperture is taken, i.e.,：
Wherein, M(s,t)=V (Qs,t)V(Qs,t)H, n is the number of samples for participating in estimating, here n=(N-G+1) (K-J+1).
M(s,t)For each sub-aperture of the training range cell smooths the clutter covariance matrix of sample；Wherein ()HRepresent that conjugation turns
Put, V () is represented to be placed on the latter row of matrix below previous column and is transformed into a column vector.
Step 42, the covariance matrix that obtains carries out adaptive equalization and adds to be estimated by smoothing sample to each range cell
Carry, i.e.
Step 43, each sample unit are balanced by efficient adaptive and loaded, you can obtain more accurate each distance single
First clutter covariance matrix
There is P clutter discrete point to be evenly distributed in its angle Doppler in step 5, l-th range cell of hypothesis to be distributed
On curve, the clutter covariance matrix estimated using step 4 calculates the Capon spectrums at these points, in this, as the width that these are put
Angle value, and then try to achieve the clutter scattering coefficient at the point, i.e.,：
Wherein,Represent i-th scattering point sub-aperture it is smooth after space-time steering vector,
Step 6, the clutter scattering coefficient calculated using step 5 can obtain more accurate reconstruct number according to formula (1)
According to i.e. clutter data and clutter covariance matrix is respectively：
Wherein, W (l, i, p) ∈ CNK×1The space-time steering vector at a certain discrete point in space-time plane is represented, and
Step 7, in order that l-th training range cell it is consistent with the clutter statistical characteristicses of reference distance unit, need profit
Transformation matrix T is solved with the range cell data of reconstructl, and using transformation matrix TlTo the reconstruct data of each training range cell
Compensate, realize training registration of the range cell to reference distance unit.
IfIt is the clutter covariance matrix that reference distance unit is reconstructed by step 6, solves transformation matrix Tl∈CNK×NK,
It is allowed to meet：
This majorized function can be further converted into,
Wherein, Vl∈CNK×NKAnd Λl∈CNK×NKIt is rightCarry out feature matrix and feature that Eigenvalues Decomposition is obtained
Value matrix；VL∈CNK×NKAnd ΛL∈CNK×NKIt is rightCarry out feature matrix and characteristic value square that Eigenvalues Decomposition is obtained
Battle array.
Step 8, using the transformation matrix T obtained in step 7l, line translation is entered to each training range cell, obtain sample
Data Yl=TlXl, l ∈ [- L, L], l ≠ 0, and estimate that the clutter covariance matrix of range cell to be detected is：
Step 9, the clutter covariance matrix for treating detecting distance unitCorresponding adaptive equalization loading is carried out again,
The distance dependencies of each training range cell clutter spectrum are reduced, more accurate unit clutter covariance matrix to be detected is obtained and is estimated
Evaluation R0.The step of adaptive equalization is loaded includes：
Step 91, take weight coefficient α ' as measurement registration compensation after training unit sample clutter vector statistics it is consistent
Sex factor, i.e.,
Wherein, Ml' it is l-th clutter covariance matrix of training range cell, its size isYlIt is each instruction
Practice the sample data after range cell registration compensation.And n=2L, wherein n are the total number of training unit, L is then the right and left
Respectively take the number of training unit.
Step 92, the covariance matrix that obtains carries out adaptive equalization to be estimated by smoothing sample to each training range cell
Loading, i.e.
Step 93, each training range cell carry out efficient adaptive balance loading, and sample data now is that registration is mended
The clutter data of each training unit after repaying.Suppress to train the heterogeneity of range cell by equilibrium, reduce each distance single
The distance dependencies of first clutter spectrum, obtain more accurate unit clutter covariance matrix estimate R to be detected0。
It is available more accurate unit clutter covariance matrix estimate R to be detected according to above step0, effectively
The distance dependencies of short range clutter are inhibited, with more preferable ground clutter suppression effect.
In sum, the RBC clutters compensation method based on adaptive equalization loading of the invention is compensated for existing RBC and calculated
Method is improved, and improves registration accuracy, treats detecting distance unit clutter covariance matrix and estimates more accurate, can be effective
Improve clutter distance dependencies problem in non-working side battle array, improve the performance of RBC backoff algorithms.
It is the performance of checking the inventive method, the airborne phased array radar when yaw angle using carrier aircraft is 90 degree is used as emulation
Platform is emulated.Design parameter is：Emission wavelength lambda=the 0.32m of radar, antenna spacing d=0.5 λ, flying speed is v=
130m/s, pulse recurrence frequency is fr=2v/d, the spacing between sampled distance ring is Δ R=10m, and the height of carrier aircraft flight is
H=6000m.Reception antenna is even linear array, and array number N=10 receives pulse number K=12.Under the conditions of above-mentioned parameter, figure
5 and Fig. 6 (a) and (b) respectively show the simulation result contrast of clutter power spectrum and improvement factor.
Fig. 5 is given using the clutter work(after directly treatment SMI methods, RBC compensation methodes and the inventive method treatment
Rate composes comparison diagram, it can be seen that the space-time two-dimensional distribution dopplerbroadening of SMI clutter power spectrums is more serious.RBC side
Method chooses the ultimate range unit for participating in training as reference distance unit, by unit to be detected and the clutter of other training units
Characteristic compensation weakens the influence that clutter distance is relied on to a certain extent to consistent with the distribution character of reference unit.And this hair
Bright method is all carried out the clutter covariance matrix of unit to be detected and the estimation unit for participating in training before and after compensating certainly
Adapt to balance loading method to be processed so that the statistical property of the final range cell to be detected for estimating is more accurate.
Fig. 6 (a) and (b) sets forth main lobe direction for 10 degree and 30 degree when, using OPT optimal processings algorithm, RBC benefits
Improvement factor comparison diagram when compensation method and the inventive method.Be can be seen that compared with RBC backoff algorithms from Fig. 6 (a) and (b),
Performance of the improvement factor of improved method of the present invention in main lobe area and secondary lobe area will be better than RBC backoff algorithms, averagely have
The improvement of the improvement of 3.88dB, up to 7.53dB, improvement is more obvious, effectively increases the property of RBC backoff algorithms
Can, the simulation experiment result effectively demonstrates the advantage that the present invention carries innovatory algorithm.
Embodiments of the present invention are explained in detail above in conjunction with accompanying drawing, but the present invention is not limited to above-mentioned implementation
Mode, in the ken that those of ordinary skill in the art possess, can also be on the premise of present inventive concept not be departed from
Make a variety of changes.
Claims (7)
1. a kind of clutter spectrum registration compensation method based on adaptive equalization loading, it is characterised in that comprise the following steps：
Step 1, the echo data X for tieing up NK × 1 of l-th range cell of airborne radarlIt is rearranged into the matrix of N × K dimensions
Step 2, spatial domain sub-aperture is taken for G, Time domain sub-aperture is J, to step 1 gained matrixSpace-time sub-aperture is carried out to smooth,
Obtain (N-G+1) (K-J+1) individual smooth sample matrix Qs,t；
Step 3, using step 2 gained (N-G+1) (K-J+1) individual smooth sample matrix Qs,tThe training range cell is obtained in son
Covariance matrix under aperture
Step 4, the covariance matrix to each training range cell of step 3 gainedAdaptive equalization loading is carried out, is obtained
Each training range cell clutter covariance matrix after loading
There is P clutter discrete point to be evenly distributed in its angle Doppler in step 5, l-th training range cell of setting to be distributed
On curve, using step 4 gained clutter covariance matrixRange value of the Capon spectrums at discrete point as the point is calculated, with
The clutter scattering coefficient at the point is tried to achieve in calculating；
Step 6, the clutter scattering coefficient calculated using step 5 reconstruct data, clutter data and the clutter association after being reconstructed
Variance matrix；
Step 7, the clutter covariance matrix solution acquisition transformation matrix T with step 6 gained reconstructl；
Step 8, using the transformation matrix T obtained in step 7l, line translation is entered to each training range cell, sample data is obtained,
And estimate to obtain the clutter covariance matrix of range cell to be detected
Step 9, to step 8 gained clutter covariance matrixAdaptive equalization loading is carried out again, it is to be checked after being loaded
Survey unit clutter covariance matrix estimate R0。
2. the clutter spectrum registration compensation method based on adaptive equalization loading according to claim 1, it is characterised in that described
Step 4 pair gained each training range cell covariance matrixAdaptive equalization is loaded, and is specifically included：
Step 41, take statistics consistent sex factors of the weight coefficient α as the smooth sample clutter vector of measurement sub-aperture；
Step 42, the covariance matrix to each training range cell of step 3 gainedCarry out adaptive equalization loading；
Step 43, loaded after each training range cell clutter covariance matrix
3. the clutter spectrum registration compensation method based on adaptive equalization loading according to claim 2, it is characterised in that：It is described
In step 41, weight coefficient α is calculated using formula：
Wherein, n is the number of samples for participating in estimating, i.e. n=(N-G+1) (K-J+1)；It is covariance matrix；M(s,t)=V
(Qs,t)V(Qs,t)H；Wherein, M(s,t)For each sub-aperture of the training range cell smooths the clutter covariance matrix of sample；Its
In ()HConjugate transposition is represented, V () is represented to be placed on the latter row of matrix below previous column and is transformed into a column vector.
4. the clutter spectrum registration compensation method based on adaptive equalization loading according to claim 1, it is characterised in that：It is described
In step 4, the clutter covariance matrix of each training range cell after being loadedFor：
Wherein, α is weight coefficient；I is unit matrix；It is covariance matrix.
5. the clutter spectrum registration compensation method based on adaptive equalization loading according to claim 1, it is characterised in that：It is described
In step 8, estimate to obtain the clutter covariance matrix of range cell to be detectedFor：
Wherein, YlIt is the sample data after registration compensation, and Yl=TlXl, l ∈ [- L, L], l ≠ 0；TlIt is transformation matrix；2L is instruction
Practice the total number of unit, L then respectively takes the number of training unit for the right and left；XlIt is l-th original echo number of range cell
According to.
6. the clutter spectrum registration compensation method based on adaptive equalization loading according to claim 1, it is characterised in that：It is described
Step 9 is to step 8 gained clutter covariance matrixAdaptive equalization loading is carried out again, is specifically included：
Step 91, to take weight coefficient α ' consistent as the vectorial statistics of the training range cell sample clutter after measurement registration compensation
Sex factor；
Step 92, to step 8 gained clutter covariance matrixCarry out adaptive equalization loading；
Step 93, loaded after unit clutter covariance matrix estimate R to be detected0。
7. the clutter spectrum registration compensation method based on adaptive equalization loading according to claim 6, it is characterised in that：It is described
In step 91, weight coefficient α ' is calculated using formula：
Wherein, M 'lIt is l-th clutter covariance matrix of training range cell, its size is M 'l=YlYl H, YlFor it is each training away from
Sample data after unit registration compensation；And n=2L, wherein n are the total number of training unit, L is then for the right and left respectively takes
The number of training unit；It is the clutter covariance matrix of range cell to be detected.
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| CN114779198A (en) * | 2022-04-24 | 2022-07-22 | 中国人民解放军空军预警学院 | Conformal array airborne radar space-time clutter spectrum adaptive compensation and clutter suppression method |
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