CN108490417A - A kind of accurate SAR moving target parameter estimation methods - Google Patents
A kind of accurate SAR moving target parameter estimation methods Download PDFInfo
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- CN108490417A CN108490417A CN201810492900.0A CN201810492900A CN108490417A CN 108490417 A CN108490417 A CN 108490417A CN 201810492900 A CN201810492900 A CN 201810492900A CN 108490417 A CN108490417 A CN 108490417A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
Abstract
The present invention discloses a kind of accurate SAR moving target parameter estimation methods, it can only estimating part parameter and the defects of operand is big, accuracy is inadequate for existing algorithm, the present invention carries out moving-target parameter Estimation using Radon transformation and LVD, it is influenced by interference such as clutters smaller, the parameters information of moving-target can be estimated；And accurate estimates of parameters is obtained come thinning parameter using the iterative shrinkage thresholding algorithm based on study.
Description
Technical field
The invention belongs to Radar Technology field, more particularly to a kind of synthetic aperture radar (SAR) moving-target estimation technique.
Background technology
SAR (synthetic aperture radar) is a kind of round-the-clock, round-the-clock radar system, has that image scene is big, resolution ratio
High advantage is applied widely in military, civil field.Compared to single-channel synthetic aperture radar system, multichannel closes
More data are obtained because increasing receiving channel at aperture radar system, can obtain more target informations.SARGMTI
(ground moving target estimation) is always the important topic of SAR, there are many methods of estimation, but the time complexity of these methods with
Mostly there is conflict between moving-target estimated accuracy, it is therefore desirable to be able to minimize algorithm under the premise of obtaining high-precision
Complexity.And existing SAR GMTI methods are usually mainly for the moving-target at a slow speed for not generating doppler ambiguity, the present invention
It is equally applicable to High-speed target.
In the correlative theses for the SAR moving-targets estimation published at present, general algorithm mainly has CSI
(Clutter Suppression Interferometry) is (see document 1：Deming,Ross W.,Scott MacIntosh,
and Matthew Best."Three-channel processing for improved geo-location
performance in SAR-based GMTI interferometry."Algorithms for Synthetic
Aperture Radar Imagery XIX.Vol.8394.International Society for Optics and
Photonics, 2012.), this is a kind of moving-target algorithm for estimating based on phase method, but this method can only estimate dynamic mesh
Target distance is to speed, and there are phase windings in calculating process.Xuepan Zhang utilize RT (Radon
Transform) and FrFT (Fractional Fourier Transform), pass through the transient echo after calculating Range compress
Signal, it is proposed that it is a kind of based on the moving-target algorithm for estimating of amplitude method (see document 2：Zhang,Xuepan,et al."
Geometry-information-aided efficient radial velocity estimation for moving
target imaging and location based on Radon transform."IEEE Transactions on
Geoscience and Remote Sensing 53.2(2015):1105-1117.) Lei Yang in 2015 using CSI and
LVD (Lv ' s Distribution) proposes a kind of moving-target algorithm for estimating (see document 3：Yang,Lei,et al."
Airborne SAR moving target signatures and imagery based on LVD."IEEE
Transactions on Geoscience and Remote Sensing 53.11(2015):5958-5971.), it can estimate
The orientation of moving-target, distance are counted to position and orientation, distance to speed.But this algorithm is there are some defects, than
If there are phase windings to speed for CSI estimated distances, range migration correction effect is or not PFA (Polar Format Algorithm)
It reaches, complexity height etc..Qisong Wu are based on STAP (Space-time adaptive processing) and SBL (Sparse
Bayesian Learning) propose a kind of moving-target algorithm for estimating (see document 4：Wu,Qisong,et al."Space–time
adaptive processing and motion parameter estimation in multistatic passive
radar using sparse Bayesian learning."IEEE Transactions on Geoscience and
Remote Sensing 54.2(2016):944-957.), but STAP computation complexities are high, and the SBL methods are easily fallen into
Enter local optimum.
Invention content
In order to solve existing algorithm can only estimating part parameter, operand is big, accuracy is inadequate the defects of, the present invention propose
A kind of accurate SAR moving target parameter estimation methods carry out moving-target parameter Estimation, by clutter etc. using Radon transformation and LVD
The influence of interference is smaller, can estimate the parameters information of moving-target.And it is calculated using the iterative shrinkage threshold value based on study
Method carrys out thinning parameter, obtains accurate estimates of parameters.
The technical solution adopted by the present invention is：A kind of accurate SAR moving target parameter estimation methods, including：
S1, Range compress is carried out to echo-signal；
S2, clutter recognition processing is carried out to the echo-signal after Range compress；
S3, the echo-signal that obtains after step S2 processing is converted using Radon, obtains the distance of moving-target to speed
Degree；
S4, migration correction is carried out to the echo-signal that obtains after step S2 processing, obtains the distance of moving-target to position；
Echo-signal after S5, migration of being adjusted the distance according to LVD correction carries out parameter Estimation, obtains the orientation position of moving-target
It sets and orientation speed；
S6, using LISTA to the distance of moving-target to speed, distance to position, orientation position and orientation speed
It is refined.
Further, the step S3 include it is following step by step：
S31, the Radon transform methods according to standard, using pre-set first search range and the first step-size estimation
Go out the coarse value at the signal amplitude inclination angle after Range compress；
S32, the second search range is determined according to the coarse value of step S31 estimation, then the second step-length is set, described second
Step-length is less than the first step-length；
S33, the Radon transform methods according to standard estimate Range compress using the second search range and the second step-length
The exact value at signal amplitude inclination angle afterwards；
S34, the exact value obtained according to step S33 calculate the distance of moving-target to speed.
Further, second search range value is specially：Less than the coarse value in the first search range
In all values, choose and lower limit of the value as the second search range of the difference absolute value minimum of the coarse value；In the first search
More than in all values of the coarse value in range, the value of the difference absolute value minimum of selection and the coarse value is as the second search model
The upper limit enclosed.
Further, the distance for moving-target being obtained described in step S4 is specially to position：Echo after being corrected according to migration
Range gate where signal obtains the distance of moving-target to position.
Further, step S6 specifically include it is following step by step：
The maximum N ' of echo signal amplitude of S61, interception after step S2 clutter recognitionsrThe data of a range gate merge
At a column vector conduct
The moving-target orientation speed that S62, the moving-target distance obtained according to step S3 are obtained to speed and step S5, structure
The first parameter set is made, to the first parameter matrix of construction；
S63, calculation matrix is constructed according to the parameter matrix of step S62 constructions；
S64, moving-target distance is obtained to velocity estimation value and orientation using standard LISTA methods according to calculation matrix
Velocity estimation value；
The moving-target orientation position that S65, the moving-target distance obtained according to step S4 are obtained to position and step S5, structure
The second parameter set is made, to the second parameter matrix of construction；
S66, the second calculation matrix is constructed according to the second parameter matrix of step S65 constructions；
S67, moving-target distance is obtained to position estimation value and side using standard LISTA methods according to the second calculation matrix
Position is to position estimation value.
Further, it if the moving-target orientation speed after step S6 refinements is more than the 1/15 of platform speed, also wraps
It includes：The orientation speed estimated according to step S5 carries out clutter recognition processing to the echo-signal after Range compress；So
Step S3 is executed afterwards.
Beneficial effects of the present invention：A kind of accurate SAR moving target parameter estimation methods of the present invention believe original echo
Number clutter recognition laggard row distance compression is carried out, converts to obtain the distance of moving-target using Radon to speed vr, then pass through FFST
Migration correction is carried out, the position after correction can calculate the distance of moving-target to position r；Then LVD is utilized to obtain moving-target
Linear FM signal relevant parameter, and acquire by these parameters the orientation position y and orientation speed v of moving-targeta；
The method of the present invention refines these parameters estimated by using LISTA, obtains more accurately being worth；And to prevent
There is estimated difference away from too big situation, keeps parameter more accurate using reRT.
Description of the drawings
Fig. 1 is the solution of the present invention flow chart.
Specific implementation mode
For ease of those skilled in the art understand that the present invention technology contents, below in conjunction with the accompanying drawings to the content of present invention into one
Step is illustrated.
In order to facilitate description present disclosure, make following term definition first：
Define 1, synthetic aperture radar (SAR)
Synthetic aperture radar be it is a kind of radar is fixed on motion platform, carry out synthesizing linear in conjunction with the movement of motion platform
Array, come realize distance to scene imaging, recycle distance to echo be delayed complete distance to scene imaging, to realize
A kind of the radar exploration technique of the two-dimensional imaging of scene or target." the Digital processing of that refer to document
synthetic aperture radar data."Cumming,Ian G.,and Frank H.Wong.Artech house
1.2(2005):3.
Define 2, SAR multi-channel model moving-target oblique distances
Oblique distance of i-th of channel at the orientation slow time η moment be
Wherein, VtIndicate platform speed, r0Indicate platform to the most short oblique distance of moving-target, vrIndicate moving-target distance to speed
Degree, vaIndicate that moving-target orientation speed, a are moving-target orientation positions, d indicates channel spacing.
Define 3, DPCA
DPCA (displaced phase center antenna, phase center biased antenna technology) is a kind of common
Moving target detection method, classical DPCA generally uses two antennas, full in pulse recurrence frequency, antenna spacing, platform speed
Clutter recognition and moving-target detection are carried out in the case of sufficient certain condition." the Three-channel processing that refer to document
for improved geo-location performance in SAR-based GMTI interferometry."
Deming,Ross W.,Scott MacIntosh,and Matthew Best.Algorithms for Synthetic
Aperture Radar Imagery XIX.Vol.8394.International Society for Optics and
Photonics,2012.
Define 4, Radon transformation
In rectangular coordinate system, f (x, y) is the point on straight line L, and P is distance of the origin to L, and θ indicates L normal directions
Angle, therefore straight line can be expressed as xcos θ+ysin θ=P, then the Radon on L lines is transformed to
Define 5, LVD methods
LVD methods can estimate that the parameter in LFM (linear frequency modulated, linear FM signal) is more
General Le frequency f and linear frequency modulation rate γ." the Lv's distribution that refer to document:principle,implementation,
properties,and performance."Lv,Xiaolei,et al.IEEE Transactions on Signal
Processing 59.8(2011):3576-3591.
Define 6, Taylor expansion
If function g (x) is in a point x0Neighborhood have n+1 order derivatives, then in the neighborhood g (x) n rank Taylor expansions
Formula is
Wherein,It is g (x) in x0The i order derivatives at place, i=1,2 ..., n, n are just whole
Number.Refer to Network Document：http://en.wikipedia.org/wiki/Taylor_series
Define 7, Range compress
Range compress is a kind of process of pulse-compression technology, it is therefore an objective to obtain focusing good image.Refer to document "
Digital processing of synthetic aperture radar data”[J].Cumming I G,Wong F
H.Artech house,2005,1(2):3.
Define 8, orientation, distance to
By radar platform move direction be called orientation, will be perpendicular to orientation direction be called distance to.
Define the correction of 9, FFST migrations
FFST range walks are a kind of methods for the range migration phenomenon inhibiting imaging results caused by being moved by platform.In detail
See document " SAR imaging of moving targets " [J] .Perry R P, Dipietro R C, Fante R
L.IEEE Transactions on Aerospace and Electronic Systems,1999,35(1):188-200.
Define 10, the iterative shrinkage thresholding algorithm (LISTA) based on study
Iterative shrinkage thresholding algorithm based on study is a kind of algorithm based on e-learning, initially by Gregor K in
It is proposed on the basis of iterative shrinkage thresholding algorithm (ISTA) within 2010." the Learning fast that refer to document
approximations of sparse coding"[C]//Proceedings of the 27th International
Conference on International Conference on Machine Learning.Gregor K,LeCun
Y.Omnipress,2010:399-406.
Initializing SAR system parameter includes：Emit signal center frequency, is denoted as f0；Pulse recurrence frequency is denoted as PRF；Hair
Signal wavelength is penetrated, λ is denoted as；Emit signal sampling frequencies, is denoted as Fs；Transmitted signal bandwidth is denoted as BW；Emit signal pulsewidth, note
It is Tr；Port number is denoted as N；Emit signal chirp rate, is denoted as Kr；Platform speed is denoted as Vt；The light velocity is denoted as c；Channel spacing,
It is denoted as d；Distance is denoted as τ, τ=1,2 ..., N to the fast timer；Distance is counted to fast time sampling, is denoted as Nr；When orientation is slow
Between, it is denoted as η, η=1,2 ..., Na；The slow time sampling points of orientation, are denoted as Na；Moving-target distance is denoted as r to position；Dynamic mesh
Orientation position is marked, a is denoted as；Moving-target orientation speed, is denoted as va；Moving-target distance is denoted as v to speedr；Platform is to dynamic mesh
The most short oblique distance of target, is denoted as r0；Distance is denoted as f to frequencyr。
Define i-th of channel reception to echo-signal be
Wherein, i indicates that i-th of channel, α indicate the complex magnitude of signal, KrIndicate transmitting signal chirp rate, Ri(η) is indicated
Oblique distance history, η indicate that slow time, c indicate the light velocity, f0Indicate that transmitting signal center frequency, τ indicate the fast time.Oblique distance history is expressed asd、r0, τ and η be respectively antenna spacing, most short oblique distance, fast time
With the slow time.By oblique distance history in ηi=(a+ (i-1) d)/(Vt-va) at carry out the second Taylor series, obtain
Ri(η)=k0,i+k1,iη+k2,iη2 (5)
Wherein
Wherein, r0、Vt、a、r、va、vrRespectively initialize obtained most short oblique distance, platform speed, the orientation of moving-target
To, distance to position and orientation, distance to speed.
It is the solution of the present invention flow chart as shown in Figure 1, the technical scheme is that：A kind of accurate SAR moving-targets
Method for parameter estimation specifically includes following steps：
S1, Range compress is carried out to echo-signal；
According to standardization Range compress method, matched filter is transformed into frequency domain with echo-signal and is multiplied, obtain away from
It is from compressed echo-signal：
Wherein, f0And frFor initialization centre frequency and distance to frequency；Ri(η) is oblique distance history.
S2, clutter recognition processing is carried out to the echo-signal after Range compress；
According to standardization DPCA methods, clutter recognition is carried out to signal expression (7), is obtained
Wherein, αi=α (exp {-j4 π/λ ((i-1) dvr/Vt) -1), αiIndicate the amplitude of i-th of channel echo, d,
vr、Vt、f0、frIt is antenna spacing, moving-target distance to speed, platform speed, centre frequency and distance to frequency.R1(η) is root
According to the oblique distance history for first antenna that formula (5) is calculated.
It transforms to and is apart from time domain
Wherein, f0To emit signal center frequency, R1(η) is the oblique distance for first antenna being calculated according to formula (5)
History, αiIndicate that i-th of channel echo signal amplitude, δ indicate impulse function.
S3, the echo-signal that obtains after step S2 processing is converted using Radon, obtains the distance of moving-target to speed
Degree；Step S3 include it is following step by step：
S31, the Radon transform methods according to standard, using pre-set first search range and the first step-size estimation
Go out the coarse value θ at the signal amplitude inclination angle after Range compressm coar；
S32, the coarse value θ estimated according to step S31m coarIt determines the second search range, then the second step-length, institute is set
It states the second step-length and is less than the first step-length；Second search range value is specially：Less than the coarse value in the first search range
In all values, choose and lower limit of the value as the second search range of the difference absolute value minimum of the coarse value；In the first search
More than in all values of the coarse value in range, the value of the difference absolute value minimum of selection and the coarse value is as the second search model
The upper limit enclosed；Calculation amount can be mainly reduced by this step, improves estimated accuracy；Specific second search range value example
Such as：Setting search parameter collection is [1,2,3,4,5] for the first time, then it is 3 that estimation, which obtains coarse value,；Then again according to coarse value 3
Arrange parameter collection [2.5,2.6 ... 3.4,3.5] can thus be estimated to obtain exact value 3.1.
S33, the Radon transform methods according to standard estimate Range compress using the second search range and the second step-length
The exact value θ at signal amplitude inclination angle afterwardsm deli；
S34, the exact value θ obtained according to step S33m deliThe distance of moving-target is calculated to speed；It is calculated according to formula (10)
The distance of moving-target is to speed：
It can be obtained orientation speed vr, it is expressed as vr est；
Wherein, PRF and FsFor pulse recurrence frequency and sample frequency；θm deliThe letter obtained for the transformation estimations of Radon twice
Number amplitude inclination angle.
S4, migration correction is carried out to the echo-signal that obtains after step S2 processing, obtains the distance of moving-target to position；
According to standard FFST migration alignment techniques, the signal expression (8) after adjust the distance compression and DPCA carries out migration school
Just, it obtains
For the slow time after transformation：
Center Doppler frequency fdt0With linear frequency modulation rate γdFor
Wherein,It is fuzzy for PRF；vr、a、λ、η、τ、r0、PRF、VtRespectively moving-target distance
To speed, moving-target orientation position, wavelength, slow time, fast time, most short oblique distance, pulse recurrence frequency and platform speed.
The distance that range gate where signal after being corrected according to migration can be obtained moving-target is denoted as r to position rest。
Echo-signal after S5, migration of being adjusted the distance according to LVD correction carries out parameter Estimation, obtains the orientation position of moving-target
It sets and orientation speed；Specifically：According to standard LVD technologies, parameter Estimation is carried out to formula (11), parameter therein can be obtained
fdt0And γd.According to the two parameters and its expression formula (12), simultaneous equations can be obtained moving-target orientation position a and orientation
To speed va, it is expressed as aestAnd va est。
S6, using LISTA to the distance of moving-target to speed, distance to position, orientation position and orientation speed
It is refined.Step S6 specifically include it is following step by step：
The maximum N ' of echo signal amplitude of S61, interception after step S2 clutter recognitionsrThe data of a range gate merge
At a column vector conduct
Intercept the DPCA and the maximum total N ' of echo data (9) formula amplitude after Range compress in i-th of channelrA range gate
Data, be merged into a column vector conductI.e.
Wherein,Indicate rest-N′rEcho data after the DPCA of/2 range gates, restFor step
The moving-target distance that rapid S4 is obtained is to position, N 'rFor the signal distance door number of interception, Na, τ, η be the obtained distance of initialization to
Sampling number, fast time and slow time.
The moving-target orientation speed that S62, the moving-target distance obtained according to step S3 are obtained to speed and step S5
vaest, construct the first parameter set, the first parameter set includes moving-target distance to speed parameter collectionWith moving-target orientation
Speed parameter collectionThe first parameter matrix is constructed according to the first parameter set；
Wherein, pk=[aest,rest,vak；vr k；] indicate k-th of target component being refined, aestIt is obtained for step S5
Moving-target orientation position, restThe moving-target distance obtained for step S5 to position,
For an element in parameter set.
According to parameter matrix formula (14), the echo frequency-region signal expression formula after pulse pressure is constructedIt recycles
Distance is transformed to time-domain signal to Fourier transformation
S63, calculation matrix is constructed according to the parameter matrix of step S62 constructions；
S64, moving-target distance is obtained to velocity estimation value and orientation using standard LISTA methods according to calculation matrix
Velocity estimation value；
According to standard LISTA methods, have
It is acquired using LISTAMoving-target distance be can be obtained to velocity estimation value vr LISTA estWith moving-target orientation speed
Spend estimated value va LISTA est。
S65, the moving-target distance obtained according to step S4 are to position restThe moving-target orientation position obtained with step S5
aest, the second parameter set is constructed, the second parameter set includes：Moving-target distance is to location parameter collectionWith moving-target orientation
Location parameter collectionThe second parameter matrix is constructed according to the second parameter set；
Wherein, pkIndicate k-th of target component being refined, pk=[ak,rk,va LISTA est；vr LISTA est；],
va LISTA estAnd vr LISTA estFor the moving-target orientation speed that step S64 is obtained, ak,rkFor an element in parameter set,
According to parameter matrix formula (17), the echo frequency-region signal expression formula after pulse pressure is constructedIt recycles
Distance is transformed to time-domain signal to Fourier transformation
S66, the second calculation matrix is constructed according to the second parameter matrix of step S65 constructions；
S67, moving-target distance is obtained to position estimation value and side using standard LISTA methods according to the second calculation matrix
Position is to position estimation value.
According to standard LISTA methods, have
It is acquired using LISTAIt can be obtained moving-target position estimation value aLISTA estAnd rLISTA est。
To solve in va＜ ＜ VtaThe larger problem of error under conditions of (η) is invalid, the present invention use reRT methods；Root
The orientation speed estimated according to step S5 carries out clutter recognition processing to the echo-signal after Range compress；It is then back to
Step S3, by re-starting clutter recognition processing, intimate study plot has carried out DPCA, will not introduce extra phase.
Then LISTA is carried out again, you can obtains accurate moving-target estimates of parameters.
The method of the present invention is compressed by carrying out the laggard row distance of clutter recognition to original echoed signals, is become using Radon
The distance of moving-target is got in return to speed vr, then by FFST progress migration corrections, the position after correction, which can calculate, sets out mesh
Target distance is to position r；Then it utilizes LVD to obtain the relevant parameter of the linear FM signal of moving-target, and passes through these parameters
Acquire the orientation position y and orientation speed v of moving-targeta.These parameters estimated are refined using LISTA, are obtained
More accurate value.Then to prevent estimated difference away from too big situation, keep parameter more accurate using reRT.
Those of ordinary skill in the art will understand that the embodiments described herein, which is to help reader, understands this hair
Bright principle, it should be understood that protection scope of the present invention is not limited to such specific embodiments and embodiments.For ability
For the technical staff in domain, the invention may be variously modified and varied.All within the spirits and principles of the present invention, made by
Any modification, equivalent substitution, improvement and etc. should be included within scope of the presently claimed invention.
Claims (6)
1. a kind of accurate SAR moving target parameter estimation methods, which is characterized in that including：
S1, Range compress is carried out to echo-signal；
S2, clutter recognition processing is carried out to the echo-signal after Range compress；
S3, the echo-signal that obtains after step S2 processing is converted using Radon, obtains the distance of moving-target to speed；
S4, migration correction is carried out to the echo-signal that obtains after step S2 processing, obtains the distance of moving-target to position；
Echo-signal after S5, migration of being adjusted the distance according to LVD correction carries out parameter Estimation, obtain the orientation position of moving-target with
Orientation speed；
S6, the distance of moving-target is carried out to speed, distance to position, orientation position and orientation speed using LISTA
Refinement.
2. a kind of accurate SAR moving target parameter estimation methods according to claim 1, which is characterized in that the step
S3 include it is following step by step：
S31, the Radon transform methods according to standard, using pre-set first search range and the first step-length estimate away from
Coarse value from compressed signal amplitude inclination angle；
S32, the second search range is determined according to the coarse value of step S31 estimations, then the second step-length, second step-length is set
Less than the first step-length；
S33, the Radon transform methods according to standard, after estimating Range compress using the second search range and the second step-length
The exact value at signal amplitude inclination angle；
S34, the exact value obtained according to step S33 calculate the distance of moving-target to speed.
3. a kind of accurate SAR moving target parameter estimation methods according to claim 2, which is characterized in that described second
Search range value is specially：In the first search range less than the coarse value all values in, choose with the coarse value it
Lower limit of the value of poor absolute value minimum as the second search range；It is more than all values of the coarse value in the first search range
In, it chooses and the upper limit of the value as the second search range of the difference absolute value minimum of the coarse value.
4. a kind of accurate SAR moving target parameter estimation methods according to claim 3, which is characterized in that step S4 institutes
The distance for stating to obtain moving-target is specially to position：Range gate where echo-signal after being corrected according to migration obtains moving-target
Distance is to position.
5. a kind of accurate SAR moving target parameter estimation methods according to claim 4, which is characterized in that step S6 tools
Body include it is following step by step：
The maximum N of echo signal amplitude of S61, interception after step S2 clutter recognitionsrThe data of ' a range gate, are merged into a row
Vectorial conduct
The moving-target orientation speed that S62, the moving-target distance obtained according to step S3 are obtained to speed and step S5, construction the
One parameter set, to the first parameter matrix of construction；
S63, calculation matrix is constructed according to the parameter matrix of step S62 constructions；
S64, moving-target distance is obtained to velocity estimation value and orientation speed using standard LISTA methods according to calculation matrix
Estimated value；
The moving-target orientation position that S65, the moving-target distance obtained according to step S4 are obtained to position and step S5, construction the
Two parameter sets, to the second parameter matrix of construction；
S66, the second calculation matrix is constructed according to the second parameter matrix of step S65 constructions；
S67, moving-target distance is obtained to position estimation value and orientation using standard LISTA methods according to the second calculation matrix
Position estimation value.
6. a kind of accurate SAR moving target parameter estimation methods according to claim 5, which is characterized in that if through step
When moving-target orientation speed after S6 refinements is more than the 1/15 of platform speed, further include：The side estimated according to step S5
Position carries out clutter recognition processing to speed to the echo-signal after Range compress；Then step S3 is executed.
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| CN110646774A (en) * | 2019-09-30 | 2020-01-03 | 中国人民解放军战略支援部队信息工程大学 | Maneuvering target coherent detection method and device based on product variable-scale periodic Lu distribution |
| CN111398960A (en) * | 2020-04-16 | 2020-07-10 | 北京理工大学重庆创新中心 | GEO satellite-borne SAR bistatic configuration design method based on moving target detection |
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