CN104698431B - Based on the multichannel SAR orientation ambiguity solution method that obscuring component DOA estimates - Google Patents

Abstract

Estimation and multichannel SAR orientation ambiguity solution method the invention discloses a kind of obscuring component Space Angle, solve the problems, such as during conventional method solution azimuth ambiguity ADBF spatial domains covariance matrix signal cancellation and target guiding vector mismatch under systematic error, multichannel SAR echo signal model is built first, echo-signal after dimension of adjusting the distance again pulse compression carries out Fast Fourier Transform (FFT) (FFT) by range cell, secondly the Space Angle of each doppler ambiguity component is accurately estimated in real time using NSIT, and then the spatial information (si) Computer Aided Design spatial filter based on each obscuring component, and each doppler ambiguity component is extracted successively, finally it is spliced into complete without blurred signal, reach solution azimuth ambiguity purpose.While there is the signal cancellation that each obscuring component brings in the sample that this method efficiently solves the problems, such as because of ADBF covariance matrix；And the suppression of obscuring component is greatly improved.

Description

Based on the multichannel SAR orientation ambiguity solution method that obscuring component DOA estimates

Technical field

The invention belongs to airborne multichannel SAR wide-scene survey fields, and in particular to a kind of obscuring component Space Angle is estimated Meter method and multichannel SAR orientation ambiguity solution method.

Background technology

It is domestic to solve the contradiction between wide swath and orientation high-resolution in airborne synthetic aperture radar imaging Outer scholar has mainly done many research work in terms of two, is on the one hand SAR ambiguity solution treatment technologies, is on the other hand research and development More flexible new SAR system；Generally with relatively low pulse recurrence frequency (PRF) with guarantee scope wider in usual SAR system Interior coverage rate, but bearing signal is fuzzy, therefore ambiguity solution is that SAR imagings are necessary.In addition, the principal character of new SAR system It is the combination of multiple transmission/receiving channels and appropriate Digital Signal Processing.

By signal Analysis Doppler frequency and the corresponding relation of locus, propose to use space domain self-adapted Wave beam forming (ADBF) technology suppresses doppler ambiguity, and it can adaptively to doppler ambiguity component zero setting.

But there is each obscuring component in tradition ADBF technologies, can produce signal simultaneously in the sample of covariance matrix Cancellation problem, so as to the secondary lobe for causing sef-adapting filter is raised.Particularly when carrier aircraft speed has error, each time fuzzy point There is deviation between amount real space angle and theoretical value, cause follow-up target guiding vector severe mismatch.This all causes follow-up SAR Azimuth focus hydraulic performance decline.

The content of the invention

The technical problems to be solved by the invention are：Estimation and the multichannel SAR side of a kind of obscuring component Space Angle are provided Position ambiguity solution method, covariance matrix signal phase in ADBF spatial domains under systematic error when solving conventional method solution azimuth ambiguity The problem disappeared with target guiding vector mismatch.

The present invention is in order to solve the above technical problems, adopt the following technical scheme that：

The method of estimation of obscuring component Space Angle,

First, row distance dimension pulse compression is entered to the signal that radar is received and direction dimension Fourier transformation acquisition radar is each logical Road signal distance Dopplergram；Then K+1 array elements are chosen and constitutes M-K submatrix, wherein, K is doppler ambiguity number of components, and M is Spatial domain array number, first submatrix is that { 1 ..., K+1 }, second submatrix are { 2 ... K+2 }, and the method comprises the following steps：

Step 1, the average value that the covariance matrix that each submatrix is estimated is calculated according to equation below

Wherein,P=1 ..., M_sa

Wherein, L is the sample number for receiving signal, and l is the natural number less than or equal to 2L+1, and i is the distance in p-th submatrix The sequence number of unit, p is natural number, and H is conjugate transposition, M_sa=M-K, X_p(i)=[S_p(i,r),...,S_p+K(i,r)]^TIt is each son I-th range cell, r-th vector form of doppler cells signal that battle array is received；

Step 2, the initial value sequence θ of Space Angle for presetting K obscuring component_q, according to ε_q2 π of=- (/ λ) dsin (θ_q) Obtain vector sequence ε_q, wherein q=1 ..., K makes vector ε=[ε₁,...,ε_K], preset the signal of obscuring component composition Subspace W₁=1, convergence threshold value χ=0.5, λ is the wavelength of radar emission signal, and d is array element spacing；

Step 3, secondary cost function is calculated according to equation below：

W in formula_K+1It is signal subspace that K obscuring component is constituted, and W_K+1WithMeet following relation：

Wherein In P zero row vector for 1 × (K+1), U_K×(K+1)It is K row K+1 column matrix, order U_K×(K+1)Ranks identical element is 1 in matrix, and remaining element is 0；

Step 4, step 3 is performed according to the initial value in step 2, calculate the initial function value C of secondary cost function₀；

Step 5, k-th Space Angle of obscuring component of calculating, detailed process are as follows：

Step 5.1, the element in vector sequence ε is resequenced, obtained ε=[ε₁,...,ε_k-1,ε_k+1,...,ε_K, ε_k], according to ε and W after adjustment₁Using formulaCalculateAgain by formula EstimatedWillValue replaces ε in ε_kValue；

Step 5.2, repeat step 5.1 estimates all ε values, obtains the ε vector sequences after whole elements update；

ε vector sequences after the renewal that step 6, applying step 5 are obtained repeat the cost letter after step 3 is updated Numerical value C₁；

Step 7, judge threshold valueWhether initial threshold χ is more than, ifMake C₀=C₁, then Step 5 and step 6 are performed, step 8 is otherwise performed；

Step 8, according to equation below calculate k-th Space Angle of obscuring component：

ε_k2 π of=- (/ λ) dsin (θ_k)；

Step 9：Repeat step 8, obtains the Space Angle of all obscuring components.

Acquisition each channel signal range Doppler figure of radar is adopted with the following method：

Step A, radar m channel receiving signals are entered according to equation below row distance dimension pulse compression：

Wherein, t be the orientation time, τ be distance to the time, Nr be distance dimension sampling number, Na be orientation synthetic aperture Umber of pulse, FFT_τWithRepresent respectively on distance to the Fourier transformation of τ and on the Fourier's inversion apart from frequency domain Change,

K_rTo launch the chirp rate of pulse signal；

Step B, the signal after distance dimension pulse compression is tieed up by quick Fu by range cell travel direction according to equation below In leaf transformation, obtain range Doppler figure：

S_m(τ, f)=FFT_t[S_m(τ,t)]

Wherein FFT_tRepresent the Fourier transformation on orientation time t.

A kind of multichannel SAR orientation ambiguity solution method, comprises the following steps：

The Space Angle θ of step a, K doppler ambiguity component of each doppler cells of acquisition₁、θ₂、……θ_K；

Step b, according to equation below calculate k-th normalization spatial domain steering vector of obscuring component：

Wherein, k=1 ..., K；

Build k-th covariance matrix of doppler ambiguity componentAnd calculate corresponding ADBF weights；The ADBF weights Meet equation below：

Covariance matrixMeet：

Wherein, σ₀It is the noise power of loading, I is the unit matrix of M × M；

Step c, according to equation below calculate k-th ADBF weights of doppler ambiguity component：

Step d, write i-th range cell, r-th doppler cells signal that M array element is received as vector form and be：

Y=[S₁(i,r),...,S_M(i,r)]^T

Step e, according to equation below obtain k-th doppler ambiguity component signal P_r；k：

Step f, to extracting k-th doppler ambiguity component signal respectively simultaneously by doppler cells in i-th range cell It is designated as P (k), P (k)=[P_1；k..., P_Na；k], then arranged successively according to the corresponding obscuring component signal of different Doppler frequencies Row, obtain i-th range cell full bandwidth doppler frequency data S (i, f after ambiguity solution_a), i.e.,：

S(i,f_aP)=[(1) ..., P (K)]

Step g, data S (τ, f after Doppler ambiguity-resolution are obtained by range cell repeat step b~step f_a), and it is right It carries out orientation synthetic aperture processing, obtains SAR image.

The method of the step a application claims 1 obtains the K space of doppler ambiguity component of each doppler cells Angle θ₁、θ₂、……θ_K。

In the step b, σ₀=10^-4。

Compared with prior art, the present invention has the advantages that：

1st, when carrier aircraft speed does not have error, compared to traditional ADBF methods, the suppression of context of methods obscuring component is improved 7dB, efficiently solves in sample because of ADBF covariance matrix while there is the signal phase that each obscuring component brings Disappear problem；

2nd, when carrier aircraft speed has error, due to the Space Angle of real-time estimation obscuring component, steering vector is made not have mismatch And covariance matrix signal cancellation problem is overcome, compared to traditional ADBF methods, the suppression of context of methods obscuring component improves About 10dB or so.

Brief description of the drawings

Fig. 1 is positive side-looking stripmap SAR geometrical relationship schematic diagram.

Fig. 2 (a) is ground echo Doppler frequency and azimuth graph of a relation without doppler ambiguity.

Fig. 2 (b) is the ground echo Doppler frequency and azimuth graph of a relation for having doppler ambiguity.

Fig. 3 is the Doppler ambiguity-resolution wave filter design flow diagram based on NISE.

Fig. 4 (a) be carrier aircraft speed it is error free without be compressed under hazy condition as figure.

Fig. 4 (b) is the error free orientation profile without point target under hazy condition of carrier aircraft speed.

Fig. 5 (a) has image under hazy condition for carrier aircraft speed is error free.

Fig. 5 (b) has the orientation profile of point target under hazy condition for carrier aircraft speed is error free.

Fig. 6 (a) is the error free actual two-dimentional genealogical relationship without ambiguity ground echo of carrier aircraft speed.

Fig. 6 (b) is the error free ideal two dimension genealogical relationship without ambiguity ground echo of carrier aircraft speed.

Fig. 6 (c) has the actual two-dimentional genealogical relationship of ambiguity ground echo for carrier aircraft speed is error free.

Fig. 6 (d) has the ideal two dimension genealogical relationship of ambiguity ground echo for carrier aircraft speed is error free.

Fig. 7 (a) is the inventive method in the filtered each obscuring component and spliced of extracting of the error free situation of carrier aircraft speed As a result.

Fig. 7 (b) is the error free traditional ADBF processing method results of carrier aircraft speed.

Fig. 8 (a) has error without ambiguity point target orientation profile for carrier aircraft speed.

Fig. 8 (b) has ambiguity point target orientation profile for carrier aircraft speed has error.

Fig. 9 (a) has actual two-dimentional genealogical relationship of the error without ambiguity ground echo for carrier aircraft speed.

Fig. 9 (b) is the ideal two dimension genealogical relationship that carrier aircraft speed has error without ambiguity ground echo.

Fig. 9 (c) has the actual two-dimentional genealogical relationship of ambiguity ground echo for carrier aircraft speed has error.

Fig. 9 (d) has the ideal two dimension genealogical relationship of ambiguity ground echo for carrier aircraft speed has error.

Figure 10 (a) is the inventive method has the filtered each obscuring component and spliced of extracting of error condition in carrier aircraft speed As a result.

Figure 10 (b) has the traditional ADBF processing method results of error for carrier aircraft speed.

Specific embodiment

Technical scheme is described in detail below in conjunction with the accompanying drawings：

Airborne radar geometric configuration is as shown in figure 1, carrier aircraft is flown with speed V along X-axis, and carrier aircraft flying height H, M are uniform Linear array is along course lineal layout, it is stipulated that along navigation direction high order end array element to receive and dispatch array element (being array element 1 in Fig. 1), remaining is Receive array element.Assuming that aircraft is in origin of coordinates overhead in t=0, certain one when t, the position x=V*t of aircraft, then target is to the The oblique distance of m array element is：

WhereinH represents aircraft altitude, and d represents array element spacing.

Obtained through abbreviation, the echo model of each passage is：

K in formula_rRefer to the frequency modulation rate of transmitting pulse signal, τ represents distance to the time, and λ is wavelength.

The ground echo Doppler frequency f of carried SAR_dShown in relation such as Fig. 2 (a) between azimuth angle theta, i.e.,：

When echo-signal doppler bandwidth is higher than radar pulse repetition frequency (PRF), now azimuth spectrum produces fuzzy. Fig. 2 (b) give azimuth spectrum 3 times it is fuzzy when space-time-frequency relation.In conventional methods where self adaptation is used by range cell Wave beam forming (ADBF) technology extracts each doppler ambiguity component signal successively, and then realizes that azimuth spectrum is rebuild.But due to There is each obscuring component simultaneously in the sample of ADBF covariance matrix, ADBF signal cancellations can be caused to lose；In addition carrier aircraft When speed has error, there is deviation between each obscuring component real space angle and calculated value, cause follow-up ADBF targets to be led Draw vector mismatch.Above-mentioned factor will all cause ADBF to decline obscuring component rejection, cause to synthesize frequency spectrum azimuth focus pair Valve level lifting.In consideration of it, this patent proposes the multichannel SAR orientation ambiguity solution method estimated based on obscuring component DOA.Bag Include：The pulse compression of echo-signal distance dimension, obscuring component DOA are estimated, the design of Doppler ambiguity-resolution wave filter.Fig. 3 gives this The part signal handling process of algorithm.

1. distance dimension pulse compression

It is assumed that radar m channel receiving signals are S_m(τ, t), and S_m(τ, t) size is Nr × Na, when wherein t is orientation Between, t=0 is remembered with impact point to flight track (orientation) vertical line and flight path point of intersection；τ represents distance to the time, is in hair The uniform sampling point penetrated in the pulse width of signal；Nr is distance dimension sampling number, and Na is orientation synthetic aperture umber of pulse, now right S_m(τ t) enters row distance dimension pulse compression, i.e.,：

FFT in formula_τWithRepresent respectively on distance to the Fourier transformation of τ and on the Fourier apart from frequency domain Inverse transformation,It is matched filter function of the distance to pulse pressure, K_rFor the frequency modulation for launching pulse signal is oblique Rate；

2. obscuring component DOA estimates

Under the conditions of being surveyed and drawn in wide-scene, the orientation doppler bandwidth of echo-signal is much larger than radar pulse repetition frequency (PRF), therefore in each doppler cells there are multiple obscuring components, we use noise subspace iterative estimation technique (NSIT) The space angle of different obscuring components in each doppler cells is estimated one by one；It is assumed that doppler ambiguity number of components is K, M is spatial domain Array number, meets M ＞ K；Each channel signal after first by Range compress becomes by range cell travel direction dimension fast Fourier (FFT) is changed, range Doppler figure is obtained, i.e.,：

S_m(τ, f)=FFT_t[S_m(τ,t)] (2)

Wherein FFT_tRepresent the Fourier transformation on orientation time t；

By taking the Space Angle of obscuring component in estimating i-th range cell, r-th doppler cells as an example, NSIT algorithm picks Wherein K+1 array elements constitute M-K sub-aperture come estimate K difference obscuring components Space Angle；Due to the array number of sub-aperture It is K+1, { 1 ..., K+1 } array element is constituted into the 1st submatrix, { 2 ... K+2 } array element constitutes the 2nd submatrix, by that analogy, this The common M of submatrix of sample composition_sa=M-K；I-th range cell, r-th doppler cells signal that each submatrix is received is write as vector Form is：

X_p(i)=[S_p(i,r),...,S_p+K(i,r)]^T, p=1 ..., M_sa (3)

S in formula_p(i, r) is i-th of pth passage, r-th of range cell doppler cells information, subscript^TIt is transposition computing Symbol；

NSIT estimates the specific steps of each obscuring component DOA：

Step 1：The average value of the covariance matrix for each detecing estimation is calculated according to below equation Wherein,

Subscript in formula^HRepresent conjugate transposition operator；

Step 2：Initialization of variable：The K DOA initial values θ of obscuring component of setting_q, according to ε_q2 π of=- (/ λ) dsin (θ_q) Obtain vector sequence ε_p, wherein q=1,2 ..., K, λ be wavelength, d is array element spacing, makes vector ε=[ε₁,...,ε_K], ε (q) It is q-th value of element, i.e. ε (q)=ε in vector ε_q；；The signal subspace W that setting obscuring component is constituted₁=1；Convergence threshold Value χ=0.5；

Step 3：Calculate secondary cost function：Defining secondary cost function first is：

W in formula_K+1It is signal subspace that K obscuring component is constituted, and W_K+1WithMeet following relation：

Wherein Zero row vector is 1 × (K+1) in P；U_K×(K+1)It is K row K+1 column matrix, order U_K×(K+1)Ranks identical element is 1 in matrix, and remaining element is 0；Step 4：According to initial value ε and W in step 2₁, Can recurrence calculation W one by one according to formula (6)_K+1, secondary cost function C is calculated further according to formula (5), and perform C₀=C；

Step 5, k-th Space Angle of obscuring component of calculating, detailed process are as follows：Step 5.1, by vector sequence ε Element is resequenced, and obtains ε=[ε₁,...,ε_k-1,ε_k+1,...,ε_K,ε_k], according to ε and W after adjustment₁Using formulaCalculateAgain by formulaEstimatedWillValue replaces ε in ε_k Value；

Step 5.2, repeat step 5.1, estimate all ε values, obtain the ε vector sequences after whole elements update；

Step 6：ε vector sequences after the renewal that applying step 5 is obtained repeat the cost letter after step 3 is updated Numerical value C₁；

Step 7, judge threshold valueWhether initial threshold χ is more than, ifMake C₀=C₁, so Step 5 and step 6 are performed afterwards, otherwise perform step 8；Step 8, according to equation below calculate k-th Space Angle of obscuring component： Vector ε=[ε according to final updating₁,...,ε_K], to each ε (k), k=1 ..., K, by formulaThe K DOA value of obscuring component can be respectively obtained；

Here is NSIT algorithm flow charts：

Initialization：

ε_q2 π of=- (/ λ) dsin (θ_q), q=1,2 ..., K；

ε=[ε₁,...,ε_K]；W₁=1, χ=0.5；

By ε and W₁, according to formula (6) recurrence calculation W_K+1, according to

Formula (5) calculation cost function C, and perform C₀=C；

The DoA Estimation：

Do{

For i=1 ..., K do

End for

ε values and w after by updating₁, according to formula (6) recurrence calculation W_K+1, then calculation cost function C,

And perform C₁=C；

}while(((C₀-C₁)/C₀) ＞ χ)

The DOA Calculation：

By the vector ε of final updating, computing formula

ε (k), k=1 ... K, can respectively obtain the K DOA value of obscuring component；

3. Doppler ambiguity-resolution wave filter design

The DOA values of K obscuring component of each doppler cells are obtained using NSIT alternative manners；Now with the i-th distance above As a example by r-th doppler cells of unit, it is assumed that the space angle respectively θ of the K obscuring component estimated₁、θ₂、……θ_K, then respectively The normalization spatial domain steering vector of obscuring component is：

Because each range cell has each obscuring component simultaneously, directly utilize and receive data estimation covariance matrix, and Calculating ADBF weights will cause signal cancellation；Therefore the doppler ambiguity component that we are based on extracting builds corresponding association side respectively Difference matrixAnd calculate corresponding ADBF weights；It is assumed that extracting k-th doppler ambiguity component, its spatial domain steering vector is A_k, Its ADBF weights meets：

Covariance matrixMeet：

σ in formula₀It is the noise power of loading, σ can be set₀=10^-4, I is the unit matrix of M × M；Then extract more than k-th It is general strangle obscuring component ADBF weights be：

Being write i-th range cell, r-th doppler cells signal of full array received as vector form is：

Y=[S₁(i,r),...,S_M(i,r)]^T (10)

Now utilize W_kK-th doppler ambiguity component signal is extracted in i-th range cell, r-th doppler cells, Use P_r；kRepresent, i.e.,：

To extracting k-th doppler ambiguity component signal in i-th range cell respectively by doppler cells and being designated as P (k), P (k)=[P_1；k,...,P_Na；k], then it is arranged in order according to the corresponding obscuring component signal of different Doppler frequencies, i.e., Obtain i-th range cell full bandwidth doppler frequency data S (i, f after ambiguity solution_a), i.e.,：

S(i,f_aP)=[(1) ..., P (K)] (12)

It is that can obtain data S (τ, f after Doppler ambiguity-resolution to repeat said process by range cell_a), to its side of carrying out Position synthetic aperture processing can obtain High Resolution SAR Images.

This patent correctness is verified below by Computer Simulation.Airborne positive side-looking array synthetic-aperture radar imagery emulation ginseng Number is as shown in table 1, array number M=4, obscuring component number K=3, and scattering points P takes 51, and point target is distributed in and is longitudinally formed one Row, each point is at intervals of 3m.It is reference unit with the 512nd range cell in following emulation experiment.

The simulation of Radar System parameter of table 1

(1) the error free situation processing procedure of carrier aircraft speed is as follows

First, the docking collection of letters number is done apart from the dimension two dimensional compaction treatment of peacekeeping direction.As Fig. 4 (a), Fig. 4 (b) are indicated without orientation Result figure when fuzzy, Fig. 4 (a) is the impact point after peacekeeping azimuth dimension pulse pressure, and Fig. 4 (b) is cutd open for the orientation of point target Face figure.Result figure when Fig. 5 (a), Fig. 5 (b) indicate azimuth ambiguity, Fig. 5 (a) show distance to orientation pulse pressure after mesh Punctuate, Fig. 5 (b) is the orientation figure of point target.

Secondly, be estimated with azimuth ambiguity using NSIT and during without azimuth ambiguity obscuring component DOA, while draw passing through The theoretical value that formula is calculated.The actual value of Doppler frequency correspondence space angular dependence when result such as Fig. 6 (a) is without azimuth ambiguity, Doppler frequency correspondence space angular dependence ideal value when Fig. 6 (b) is without azimuth ambiguity, Fig. 6 (c) expressions exist many during azimuth ambiguity The general actual value for strangling frequency correspondence space angular dependence, Fig. 6 (d) represents that Doppler frequency correspondence Space Angle is closed when there is azimuth ambiguity The ideal value of system, from Fig. 6 (a), Fig. 6 (b) it can be seen that actual value and ideal value are about the same during without azimuth ambiguity, error compared with It is small.Actual space corresponding with preferable Doppler frequency angular dependence when Fig. 6 (c), Fig. 6 (d) indicate azimuth ambiguity, it is known that in nothing Actual value and theoretical value are close in the case of velocity error, but actual curve has certain roughness, and ideal value is one strict Linear line in meaning, therefore there is certain error.It should be noted that producing frequency spectrum to jump three sections of junctions of obscuring component Become phenomenon, be caused by the finite-length effect of signal.

Finally, using the Space Angle actual value Computer Aided Design adaptive spatial filter estimated, each obscuring component is extracted And complete Doppler signal is spliced into, shown in such as Fig. 7 (a), Fig. 7 (b).Fig. 7 (a) is context of methods result, Fig. 7 (b) It is that neighbor distance cell signal estimates each spatial domain covariance matrix of blurred signal, further according to theoretical spatial domain steering vector difference Suppress each blurred signal, and then carry out frequency spectrum splicing.By contrast, context of methods filtered blurry component suppresses to improve 7dB, So as to overcome ADBF covariance matrix signal cancellation and target guiding vector mismatch problems under systematic error.

(2) carrier aircraft speed has error condition processing procedure as follows

There is certain deviation according to actual conditions carrier aircraft speed, carrier aircraft speed V presence ± 5m/s errors are set, during emulation It is (V+5) m/s with velocity deviation, other simulated conditions are constant.

First, the orientation profile of point target when drawing without azimuth ambiguity and having an azimuth ambiguity, as a result as Fig. 8 (a), Shown in Fig. 8 (b).

Secondly azimuth ambiguity is estimated with according to NSIT and real space angle during without azimuth ambiguity, while providing in the presence of speed Their theoretical space angle during degree deviation, the reality of Doppler frequency correspondence space angular dependence when such as Fig. 9 (a) is without azimuth ambiguity Value, Doppler frequency correspondence space angular dependence ideal value when Fig. 9 (b) is without azimuth ambiguity, when Fig. 9 (c) indicates azimuth ambiguity The actual value of Doppler frequency correspondence space angular dependence, Fig. 9 (d) represents Doppler frequency correspondence Space Angle when there is azimuth ambiguity The ideal value of relation, from Fig. 9 (a), Fig. 9 (b) it can be seen that velocity deviation reason is preferably empty when fuzzy without orientation Between angle have certain deviation compared with actual value, it is larger compared with without velocity error.Fig. 9 (c), Fig. 9 (d) represent that carrier aircraft speed is deposited In error, the DOA actual values of obscuring component are contrasted with ideal value, understand that actual value fluctuates in the presence of some from figure, not a line Property straight line, and ideal value is the linear line of stricti jurise.Therefore because carrier aircraft speed has deviating cause, if recycling preferable Value processing data will cause target guiding vector severe mismatch, it is impossible to effectively filter obscuring component.

Finally using real space angle Computer Aided Design adaptive spatial filter is obtained, extract each obscuring component and be spliced into Complete Doppler signal, the orientation profile of point target as shown in Figure 10 (a), Figure 10 (b).Figure 10 (a) is context of methods Result, Figure 10 (b) is estimated at each spatial domain covariance matrix method of blurred signal using neighbor distance cell signal Reason, suppresses each blurred signal, and then carry out frequency spectrum splicing respectively further according to preferable spatial domain steering vector.By contrast, herein Method filtered blurry component suppresses overall and improves 10dB or so, efficiently solves the problems, such as covariance matrix signal cancellation and target The problem of steering vector mismatch.

There is doppler ambiguity in the present invention, it is proposed that one kind is based on mould for the mapping of airborne multichannel SAR wide-scenes The multichannel SAR orientation ambiguity solution method that paste component DOA estimates.Proposed in text and accurately estimate each Doppler in real time using NSIT The DOA of obscuring component, and then the spatial information (si) Computer Aided Design spatial filter based on each obscuring component, and extract each how general successively Strangle obscuring component.Emulation experiment shows that context of methods efficiently solves the routine ADBF covariance matrixes under systematic error and estimates Meter signal cancellation and target guiding vector mismatch problems.When carrier aircraft speed does not have error, compared to traditional ADBF methods, this paper The suppression of method obscuring component improves 7dB；When carrier aircraft speed has error, due to the Space Angle of real-time estimation obscuring component, Steering vector is not had mismatch and overcome covariance matrix signal cancellation problem, compared to traditional ADBF methods, context of methods mould The suppression for pasting component improves about 10dB or so.If last orientation umber of pulse accumulation increases, the algorithm advantage is more prominent, And algorithm operation efficiency is high, it is easy to engineering construction.

Claims (5)

1. the method for estimation of obscuring component Space Angle, it is characterised in that：

First, row distance dimension pulse compression is entered to the signal that radar is received and direction dimension Fourier transformation obtains each passage letter of radar Number range Doppler figure；Then K+1 array elements are chosen and constitutes M-K submatrix, wherein, K is doppler ambiguity number of components, and M is spatial domain Array number, first submatrix is { 1 ..., K+1 }, second submatrix is { 2 ... K+2 }, and the method comprises the following steps：

Step 1, the average value that the covariance matrix that each submatrix is estimated is calculated according to equation below

Wherein, Wherein, L is the sample number for receiving signal, and l is the natural number less than or equal to 2L+1, and i is the sequence of the range cell in p-th submatrix Number, p is natural number, and H is conjugate transposition, M_sa=M-K, X_p(i)=[S_p(i,r),…,S_p+K(i,r)]^TFor each submatrix receive the R-th vector form of doppler cells signal of i range cell；

Step 2, the initial value sequence θ of Space Angle for presetting K obscuring component_q, according to ε_q2 π of=- (/ λ) dsin (θ_q) obtain Vector sequence ε_q, wherein q=1 ..., K make vector ε=[ε₁,…,ε_K], preset the signal subspace of obscuring component composition W₁=1, convergence threshold value χ=0.5, λ is the wavelength of radar emission signal, and d is array element spacing；

Step 3, secondary cost function is calculated according to equation below：

$C=W_{K+1}^H{\hat{R}}_{sa}{W}_{K+1}$

W in formula_K+1It is signal subspace that K obscuring component is constituted, and W_K+1WithMeet following relation：

$W_{K+1}={\stackrel{\‾}{W}}_K-e^{j\mathrm{\ϵ}\left(K\right)}P{\stackrel{\‾}{W}}_K$

WhereinIn P zero row vector for 1 × (K+1), U_K×(K+1)It is K row K+1 column matrix, order U_K×(K+1)Ranks identical element is 1 in matrix, and remaining element is 0；

Step 4, step 3 is performed according to the initial value in step 2, calculate the initial function value C of secondary cost function₀；

Step 5, k-th Space Angle of obscuring component of calculating, detailed process are as follows：

Step 5.1, the element in vector ε is resequenced, obtained ε=[ε₁,…,ε_k-1,ε_k+1,…,ε_K,ε_k], according to tune ε and W after whole₁Using formulaCalculateAgain by formulaEstimatedWillValue replaces ε in ε_kValue；

Step 5.2, repeat step 5.1 estimates all ε values, obtains the ε vectors after whole elements update；

ε vectors after the renewal that step 6, applying step 5 are obtained repeat the cost function value C after step 3 is updated₁；

Step 7, judge threshold valueWhether initial threshold χ is more than, ifMake C₀=C₁, then perform Step 5 and step 6, otherwise perform step 8；

Step 8, according to equation below calculate k-th Space Angle of obscuring component：

ε_kThe π λ of=- (2) dsin (θ_k)；

Step 9：Repeat step 8, obtains the Space Angle of all obscuring components.

2. the method for estimation of obscuring component Space Angle according to claim 1, it is characterised in that：Acquisition each passage of radar Signal distance Dopplergram is adopted with the following method：

Step A, radar m channel receiving signals are entered according to equation below row distance dimension pulse compression：

$S_m(\mathrm{\τ},t)={\left\{{\mathrm{IFFT}}_{f_r}\right\{{\mathrm{FFT}}_{\mathrm{\τ}}\[S_m(\mathrm{\τ},t)\]\·{\mathrm{FFT}}_{\mathrm{\τ}}\[H_r\left(\mathrm{\τ}\right)\]\left\}\right\}}_{Nr\×Na}$

Wherein, t be the orientation time, τ be distance to the time, Nr be distance dimension sampling number, Na be orientation synthetic aperture pulse Number, FFT_τWithRepresent respectively on distance to the Fourier transformation of time τ and on the Fourier's inversion apart from frequency domain Change,

K_rTo launch the chirp rate of pulse signal；

Step B, according to equation below by distance dimension pulse compression after signal by range cell travel direction tie up fast Fourier Conversion, obtains range Doppler figure：

S_m(τ, f)=FFT_t[S_m(τ,t)]

Wherein FFT_tRepresent the Fourier transformation on orientation time t.

3. the multichannel SAR orientation ambiguity solution method of the method for estimation of obscuring component Space Angle described in claim 1 is based on, and it is special Levy and be：Comprise the following steps：

The Space Angle θ of step a, K doppler ambiguity component of each doppler cells of acquisition₁、θ₂、……θ_K；

Step b, according to equation below calculate k-th normalization spatial domain steering vector of obscuring component：

Wherein, k=1 ..., K；

Build k-th covariance matrix of doppler ambiguity componentAnd calculate corresponding ADBF weights；The ADBF weights meet Equation below：

$\left\{\begin{array}{cc}s.t.& W_{ADBF\_k}^H{A}_k=1\\ \underset{w_k}{\min }& W_{ADBF\_k}^H{\stackrel{\‾}{R}}_k{W}_{ADBF\_k}\end{array}\right.$

Covariance matrixMeet：

G=1 ..., K and g ≠ k,

Wherein, σ₀It is the noise power of loading, I is the unit matrix of M × M；

Step c, according to equation below calculate k-th ADBF weights of doppler ambiguity component：

$W_{ADBF\_k}=\frac{{{\stackrel{\‾}{R}}_k}^{-1}{A}_k}{{A_k}^H{{\stackrel{\‾}{R}}_k}^{-1}{A}_k}$

Step d, write i-th range cell, r-th doppler cells signal that M array element is received as vector form and be：

Y=[S₁(i,r),…,S_M(i,r)]^T

Step e, according to equation below obtain k-th doppler ambiguity component signal P_r；k：

$P_{r;k}=W_{ADBF\_k}^{H}Y$

Step f, to extracting k-th doppler ambiguity component signal in i-th range cell respectively by doppler cells and being designated as P (k), P (k)=[P_1；k,…,P_Na；k], then it is arranged in order according to the corresponding obscuring component signal of different Doppler frequencies, obtain I-th range cell full bandwidth doppler frequency data S (i, f after ambiguity solution_a), i.e.,：

S(i,f_aP)=[(1) ..., P (K)]

Step g, data S (τ, f after Doppler ambiguity-resolution are obtained by range cell repeat step b~step f_a), and to its carry out Orientation synthetic aperture processing, obtains SAR image.

4. multichannel SAR orientation ambiguity solution method according to claim 3, it is characterised in that：

The method of the step a application claims 1 obtains the Space Angle θ of K doppler ambiguity component of each doppler cells₁、 θ₂、……θ_K。

5. multichannel SAR orientation ambiguity solution method according to claim 3, it is characterised in that：In the step b, σ₀= 10^-4。