CN106872954B - A kind of hypersonic platform clutter recognition and motive target imaging method - Google Patents
A kind of hypersonic platform clutter recognition and motive target imaging method Download PDFInfo
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- CN106872954B CN106872954B CN201710050665.7A CN201710050665A CN106872954B CN 106872954 B CN106872954 B CN 106872954B CN 201710050665 A CN201710050665 A CN 201710050665A CN 106872954 B CN106872954 B CN 106872954B
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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
- G01S7/414—Discriminating targets with respect to background clutter
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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
- G01S7/411—Identification of targets based on measurements of radar reflectivity
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Abstract
The invention belongs to Radar Technology field, a kind of hypersonic platform clutter recognition and motive target imaging method are disclosed, comprising: obtain the echo-signal of each receiving antenna；It carries out pulse compression and contracting of baroclining is gone in orientation, obtain distance domain-Azimuth Compression frequency domain echo-signal；First step coarse search is carried out to radial velocity, and obtains moving target steering vector and Clutter steering vector；Optimal weight vector is calculated, and carries out clutter recognition, obtains transient echo data；It carries out simplifying Radon transformation, obtains radial velocity fine estimation；Accurate compensation radial velocity, obtains movement destination image.The present invention solves the problems, such as that existing method clutter recognition and moving target parameter Estimation are inaccurate, improves the clutter recognition performance of hypersonic platform radar, improves the letter miscellaneous noise ratio of moving target.
Description
Technical field
The invention belongs to Radar Technology field more particularly to a kind of hypersonic platform clutter recognitions and motive target imaging
Method, clutter recognition and motive target imaging for hypersonic platform Multichannel radar.
Background technique
Hypersonic aircraft is a kind of novel optimal in structure of recent domestic research and development energetically, has high speed
High motor-driven feature, can allow current air defence system to be difficult to detect to it.Hypersonic aircraft flies in 20km-100km
Near space, flying speed is more than 5 times of velocities of sound, it might even be possible to reach 20 times of velocities of sound, and can be in 1 hour to the whole world
Sensitive target in range carries out precision strike.Therefore, it is multi-disciplinary to combine aerospace field crowd for hypersonic aircraft
New technology, represents the research and development direction of the following aerospace field, be considered as in military affairs after stealth technology again
One focus technology field becomes an important directions of 21 century Global Aerospace career development.
Currently, multiple countries including the U.S. and China are greatly developing hypersonic aircraft, however big portion
The R&D work divided concentrates on air force, propulsion and material etc., and near space hypersonic aircraft is in detection energy
There is blank for research in terms of power, that is, lack effective communication and information, monitoring, reconnaissance platforms.Existing airborne radar pair
Ground observation platform mostly uses aircraft and satellite, and carries out imaging and Ground moving target detection phase using hypersonic radar platform
Hypersonic platform radar, which can observe energy compared to spaceborne radar, to be had the advantage that for airborne and spaceborne radar platform
Fainter target；The observation scope of hypersonic platform radar is much larger than airborne radar；Hypersonic platform radar has height
Motor-driven feature can be avoided detected and strike；Hypersonic platform radar has filled up the blank of near space earth observation.
Therefore, the research detected over the ground for hypersonic platform radar, has very important significance.
Due to the high-speed motion of hypersonic radar platform, radar return can have doppler ambiguity, and move mesh
Mark is often submerged in the strong clutter in ground, therefore before motive target imaging, needs to carry out using Multichannel radar system miscellaneous
Wave inhibits.In existing imaging space and time adaptive processing (ISTAP) and chirp
In typical the multichannel clutter recognition and motive target imaging method such as Fourier transform (CFT), due to moving target
Unknown parameters, thus clutter recognition is carried out using arbitrary parameter, and motive target imaging is carried out using static target parameter, this
A little processing methods can all cause clutter recognition and motive target imaging performance to decline, and the letter for seriously reducing moving target miscellaneous is made an uproar
Than can also make subsequent moving object detection performance decline.Also, the estimation of moving target parameter is used in existing method
The method of direct search so that operand dramatically increases, and causes the decline of Parameter Estimation Precision.
Summary of the invention
For the deficiency of above-mentioned prior art, the invention proposes a kind of hypersonic platform clutter recognition and moving targets
Imaging method can effectively solve the problems, such as that existing method clutter recognition and moving target parameter Estimation are inaccurate, improve superb
The clutter recognition performance of velocity of sound platform radar improves the letter miscellaneous noise ratio of moving target.
In order to achieve the above objectives, the present invention is realised by adopting the following technical scheme.
A kind of hypersonic platform clutter recognition and motive target imaging method, described method includes following steps:
Step 1, radar receiver obtains the echo-signal of k-th of receiving antenna, to the echo-signal of k-th of receiving antenna
The Fourier transformation for doing fast time dimension, obtain k-th of receiving antenna apart from frequency domain echo signal, and to k-th of receiving antenna
Apart from frequency domain echo signal using frequency domain reference signal carry out pulse compression, obtain k-th of receiving antenna apart from frequency domain-side
Position time domain echo-signal；
Step 2, oblique filter is removed in the orientation for constructing k-th of receiving antenna, according to the orientation of k-th of receiving antenna
Go oblique filter to carry out orientation to k-th receiving antenna apart from frequency domain-orientation time domain echo-signal and go contracting of baroclining, and successively into
The Fourier transformation of the slow time dimension of row and the inverse Fourier transform of fast time dimension, obtain the distance domain-orientation of k-th of receiving antenna
The echo-signal in compression frequency domain；
Step 3, k=1,2 ..., K are enabled, to respectively obtain the distance domain-Azimuth Compression frequency domain of K receiving antenna
Echo-signal；The distance domain of the K receiving antenna-Azimuth Compression frequency domain echo-signal is arranged successively, echo is obtained
Signal；
Step 4, estimated value range and the rough estimate interval for setting moving target radial velocity, to the radial speed of moving target
Degree carry out first step coarse search, obtain moving target radial velocity first step rough estimate value and corresponding moving target
Steering vector and Clutter steering vector；
Step 5, optimal weight vector coefficient required for clutter recognition is obtained, according to the optimal weight vector coefficient to search
Echo-signal carries out clutter recognition, the Moving Target Return data after obtaining clutter recognition；
Step 6, rough radial velocity penalty function is constructed, the Moving Target Return data after the clutter recognition are carried out
Distance dimension Fourier transformation and azimuth dimension inverse Fourier transform, obtain apart from frequency domain-orientation time domain echo-signal, then according to institute
Rough radial velocity penalty function is stated to compensate to described apart from the rough radial velocity of frequency domain-orientation time domain echo-signal,
Obtain the compensated echo-signal of rough radial velocity；Distance is carried out to the rough compensated echo-signal of radial velocity again
Inverse Fourier transform is tieed up, the two-dimensional time-domain echo-signal of moving target is obtained；
Step 7, Radon transformation is carried out to the two-dimensional time-domain echo-signal of the moving target, realizes that moving target is radial
The second step of speed is accurately estimated, the fine estimation of moving target radial velocity is obtained；
Step 8, distance dimension Fourier transformation is carried out to the two-dimensional time-domain echo-signal of the moving target, obtains distance frequency
Domain-orientation time domain Moving Target Return signal；Residual radial velocity penalty function is constructed, is mended according to the residual radial velocity
It repays function accurately to compensate the radial velocity of moving target, obtains accurate compensated echo-signal；
Step 9, to the accurate compensated echo-signal progress azimuth dimension Fourier transformation and apart from the inverse Fourier of dimension
Transformation, the moving target signal focused.
Hypersonic platform clutter recognition and motive target imaging method provided by the invention pass through the diameter to moving target
It carries out efficiently solving the radar system based on high ultrasonic platform due to moving target with accurate Two-step estimation roughly to speed
The problem of clutter recognition caused by unknown parameters and imaging performance decline, and improve the estimated accuracy of moving target parameter.
Specifically, compared with the prior art, the present invention has the following advantages:
First, it is miscellaneous due to carrying out multichannel using rough estimate radial velocity in the Clutter suppression algorithm that the present invention designs
Wave inhibits, and can reduce moving target unknown parameters and clutter recognition performance is caused to decline, the letter for effectively improving moving target miscellaneous is made an uproar
Than；
Second, the method for the present invention carries out Two-step estimation by the radial velocity to moving target, significantly mentions than existing methods
The high estimated accuracy of parameter, also provides better possibility for the detection of subsequent moving-target；
Third, in the two-step method operating process that the method for the present invention proposes, since the first step can be determined using rough estimate
The approximate range of moving target radial velocity, and effectively realize clutter recognition, so that second step accurately estimates that radial velocity can be with
It searches for and realizes in a small range, effectively reduce calculation amount than existing methods.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.
Fig. 1 is a kind of stream of hypersonic platform clutter recognition and motive target imaging method provided in an embodiment of the present invention
Cheng Tu；
Fig. 2 (a) is the received echo signal diagram of radar；
Fig. 2 (b) is traditional ISTAP processing method clutter recognition result figure；
Fig. 2 (c) is traditional CFT processing method clutter recognition result figure；
Fig. 2 (d) is the method for the present invention clutter recognition result figure；
Fig. 3 is the clutter recognition performance comparison figure using traditional ISTAP, CFT method and the method for the present invention；
Fig. 4 (a) is traditional ISTAP processing method motive target imaging result figure；
Fig. 4 (b) is traditional CFT processing method motive target imaging result figure；
Fig. 4 (c) is the motive target imaging result figure using the method for the present invention；
Fig. 5 is the moving target radial velocity estimated accuracy pair using traditional ISTAP, CFT method and the method for the present invention
Than figure.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The embodiment of the present invention provides a kind of hypersonic platform clutter recognition and motive target imaging method, as shown in Figure 1,
Described method includes following steps:
Step 1, radar receiver obtains the echo-signal of k-th of receiving antenna, to the echo-signal of k-th of receiving antenna
The Fourier transformation for doing fast time dimension, obtain k-th of receiving antenna apart from frequency domain echo signal, and to k-th of receiving antenna
Apart from frequency domain echo signal using frequency domain reference signal carry out pulse compression, obtain k-th of receiving antenna apart from frequency domain-side
Position time domain echo-signal.
In step 1: radar receiver obtains the echo-signal s of k-th of receiving antennak(tr, ta) are as follows:
sk(tr, ta)=wr(tr-τk)wa(ta-t0)exp[j2πf0(tr-τk)]exp[jπγ(tr-τk)2]
Wherein, k=1,2 ..., K, K indicate receiving antenna number, trIndicate distance to fast time, taIndicate that orientation is slow
Time, wr() indicates echo-signal distance to time window function, wa() indicates echo-signal orientation time window function, t0
Indicate the center hold moment of moving target, j indicates imaginary unit, f0Indicate that transmitting signal carrier frequency, γ indicate transmitting signal tune
Frequency, τkIndicate the time delay of k-th of antenna, τk=2Rk(ta)/c, c indicate propagation velocity of electromagnetic wave, Rk(ta) indicate taWhen
K-th of antenna is carved the distance between to moving target,
R0Indicate the minimum distance between image scene center and hypersonic platform, vrIndicate the radial velocity of moving target, vaIt indicates
The tangential velocity of moving target, v indicate radar platform movement velocity, dkIndicate k-th of antenna and the 1st antenna it is opposite away from
From dk=(k-1) d, d indicate the relative distance of two neighboring antenna；
To the echo-signal s of k-th of receiving antennak(tr, ta) the Fast Fourier Transform (FFT) FFT that makees fast time dimension, obtain away from
Off-frequency domain echo-signal, and frequency domain reference signal H is used to the frequency domain echo signalr(fr) pulse compression is carried out, realize distance
With filtering, obtain k-th of receiving antenna apart from frequency domain-orientation time domain echo-signal sk(fr, ta) are as follows:
sk(fr, ta)=FFTr[sk(tr, ta)]×Hr(fr)
=Wr(fr)wa(ta-t0)exp(-j2π(f0+fr)τk)
Wherein, frIndicate frequency of distance, FFTrIndicate [] the FFT operation of fast time dimension, frequency domain reference signal Hr(fr)=
exp[jπ(f0+fr)2/ γ], Wr() indicates echo-signal apart from frequency domain window function.
Step 2, oblique filter is removed in the orientation for constructing k-th of receiving antenna, is gone according to the orientation of k-th of receiving antenna
Oblique filter carries out orientation apart from frequency domain-orientation time domain echo-signal and goes contracting of baroclining to k-th receiving antenna, and successively carries out
The slow Fourier transformation of time dimension and the inverse Fourier transform of fast time dimension, obtain the distance domain-orientation pressure of k-th of receiving antenna
The echo-signal of contracting frequency domain.
Step 2 specifically: oblique filter H is removed in the orientation of k-th of receiving antenna of constructionA, k(fr, ta):
To k-th receiving antenna apart from frequency domain-orientation time domain echo-signal sk(fr, ta) as orientation oblique compression processing is gone,
And successively carry out the Fourier transformation of slow time dimension and the inverse Fourier transform of fast time dimension, obtain k-th of receiving antenna away from
Delocalization-Azimuth Compression frequency domain echo-signal sk(tr, fa):
sk(tr, fa)=IFFTr[[FFTa[sk(fr, ta)×Ha, k (fr, ta)]]
=wr(tr-2R0/c)Wa(fa+2vr/λ-2v2t0/λR0)
exp(-j4πR0/λ)exp[-j2π(fa+2vr/λ)dk/v]
Wherein, vrIndicate the radial velocity of moving target, λ indicates radar emission signal carrier frequency, FFTa[] indicates the slow time
The FFT of dimension is operated, IFFTrIndicate [] the IFFT operation of fast time dimension, Wa() indicates echo-signal orientation frequency domain window function.
Step 3, k=1,2 ..., K are enabled, to respectively obtain the distance domain-Azimuth Compression frequency domain of K receiving antenna
Echo-signal；The distance domain of the K receiving antenna-Azimuth Compression frequency domain echo-signal is arranged successively, echo is obtained
Signal.
Step 3 specifically: by the distance domain of K obtained receiving antenna-Azimuth Compression frequency domain echo-signal s1(tr,
fa), s2(tr, fa) ..., sK(tr, fa) arranged in sequence, obtain echo-signal matrix s (tr, fa)=[s1(tr, fa),
s2(tr, fa) ..., sK(tr, fa)]T, wherein subscript T indicates transposition operation, faIndicate orientation frequency.
Step 4, estimated value range and the rough estimate interval for setting moving target radial velocity, to the radial speed of moving target
Degree carry out first step coarse search, obtain moving target radial velocity first step rough estimate value and corresponding moving target
Steering vector and Clutter steering vector.
Step 4 specifically includes following sub-step:
The maximum estimated value v of (4a) setting moving target radial velocityr_rangeWith rough estimate interval vr_step, and obtain
Need the total degree P=ceil (v of rough searchr_range/vr_step), wherein ceil () expression, which rounds up, counts operation；
(4b) initializes the number of iterations p=1；
(4c) carries out first step rough estimate to the radial velocity of moving target, obtains velocity estimation median vr_temp=-
vr_range/2+p×vr_step；
(4d) enables the value of p add 1 if p < P, and returns to sub-step (4c), otherwise to all velocity estimations of acquisition among
Value, seeks the corresponding moving target energy of each velocity estimation median；
(4e) is selected so that the maximum velocity estimation median of moving target energy, the as moving target radial velocity
One step rough estimate value vr0, i.e.,WhereinIndicate to obtain corresponding v when maximum valuer_tempValue；
Wherein,
(4f) acquires moving target steering vectorAre as follows:
(4g) acquires Clutter steering vector aC(fa) are as follows:
aC(fa)=[exp (- j2 π fad1/v)…exp(-j2πfadK/v)]T。
Step 5, optimal weight vector coefficient required for clutter recognition is obtained, according to the optimal weight vector coefficient to search
Echo-signal carries out clutter recognition, the Moving Target Return data after obtaining clutter recognition.
Step 5 specifically includes following sub-step:
(5a) is according to the echo-signal matrix s (tr, fa), covariance matrix R (f is calculateda)=E [s (tr, fa)sH
(tr, fa)], wherein E [] expression takes desired operation, and subscript H indicates conjugate transposition；
(5b) is according to optimization problem:
Acquire optimal weight vector coefficient required for clutter recognitionAre as follows:
WhereinIt indicates to obtain corresponding when minimum value
(5c) is by the optimal weight vector coefficientWith the echo-signal matrix s (tr, fa) be multiplied, it obtains pair
Moving Target Return data after the clutter recognition answeredAre as follows:
Step 6, rough radial velocity penalty function is constructed, the Moving Target Return data after the clutter recognition are carried out
Distance dimension Fourier transformation and azimuth dimension inverse Fourier transform, obtain apart from frequency domain-orientation time domain echo-signal, then according to institute
Rough radial velocity penalty function is stated to compensate to described apart from the rough radial velocity of frequency domain-orientation time domain echo-signal,
Obtain the compensated echo-signal of rough radial velocity；Distance is carried out to the rough compensated echo-signal of radial velocity again
Inverse Fourier transform is tieed up, the two-dimensional time-domain echo-signal of moving target is obtained.
Step 6 specifically includes following sub-step:
Construct rough radial velocity penalty functionAre as follows:
Obtain the two-dimensional time-domain echo-signal of moving targetAre as follows:
Wherein IFFTaIndicate [] the IFFT operation of slow time dimension, vr_resIt indicates to rough radial velocity vr0It compensates
Residual radial velocity afterwards, vr_res=vr-vr0。
Step 7, Radon transformation is carried out to the two-dimensional time-domain echo-signal of the moving target, realizes that moving target is radial
The second step of speed is accurately estimated, the fine estimation of moving target radial velocity is obtained.
It sets and the search range of second step precise search is carried out as [v to the radial velocity of moving targetr0-vr_step/ 2, vr0
+vr_step/ 2] Radon transformation, and in the search range is carried out, residual radial velocity v is acquiredr_res, and obtain moving target diameter
To the fine estimation v of speedr_est=vr0+vr_res。
The search range of second step precise search is carried out as [v to the radial velocity of moving target specifically, settingr0-vr_step/ 2,
vr0+vr_step/ 2], the basis and in the search range
Radon transformation is carried out, wherein ρ is the radius of Radon transformation, and θ is the angle of Radon transformation, and δ () is delta function.It seeks
The peak value of Radon transformation, the Radon transformation angle at peak value is θ0, and according to θ0Acquire residual radial velocity vr_res=Δ
trcotθ0/cΔta, wherein Δ trResolution cell width, Δ t are tieed up for distanceaFor azimuth dimension resolution cell width.According to remaining diameter
To speed vr_resThe fine estimation v of moving target radial velocity is calculatedr_est=vr0+vr_res。
Step 8, distance dimension Fourier transformation is carried out to the two-dimensional time-domain echo-signal of the moving target, obtains distance frequency
Domain-orientation time domain Moving Target Return signal；Residual radial velocity penalty function is constructed, is mended according to the residual radial velocity
It repays function accurately to compensate the radial velocity of moving target, obtains accurate compensated echo-signal.
It obtains apart from frequency domain-orientation time domain Moving Target Return signalAre as follows:
Construct residual radial velocity penalty functionAre as follows:
Obtain accurate compensated echo-signal s (fr, ta) are as follows:
Step 9, to the accurate compensated echo-signal progress azimuth dimension Fourier transformation and apart from the inverse Fourier of dimension
Transformation, the moving target signal focused.
The moving target signal s (t focusedr, fa) are as follows:
So far, that is, the movement destination image data of focusing are obtained, hypersonic platform provided in an embodiment of the present invention is miscellaneous
Wave inhibits and motive target imaging method terminates.
Hypersonic platform clutter recognition and motive target imaging method provided in an embodiment of the present invention pass through to movement mesh
Target radial velocity carries out efficiently solving the radar system based on high ultrasonic platform due to fortune with accurate Two-step estimation roughly
The problem of clutter recognition caused by moving-target unknown parameters and imaging performance decline, and improve the estimation of moving target parameter
Precision.Specifically, compared with the prior art, the present invention has the following advantages:
First, it is miscellaneous due to carrying out multichannel using rough estimate radial velocity in the Clutter suppression algorithm that the present invention designs
Wave inhibits, and can reduce moving target unknown parameters and clutter recognition performance is caused to decline, the letter for effectively improving moving target miscellaneous is made an uproar
Than；
Second, the method for the present invention carries out Two-step estimation by the radial velocity to moving target, significantly mentions than existing methods
The high estimated accuracy of parameter, also provides better possibility for the detection of subsequent moving-target；
Third, in the two-step method operating process that the method for the present invention proposes, since the first step can be determined using rough estimate
The approximate range of moving target radial velocity, and effectively realize clutter recognition, so that second step accurately estimates that radial velocity can be with
It searches for and realizes in a small range, effectively reduce calculation amount than existing methods.
Hereinafter, being described further by emulation experiment to the above-mentioned beneficial effect of the present invention:
1) simulated conditions:
It is emulated using hypersonic platform multichannel SAR GMTI system, and 4 antenna channels (i.e. M=4) is set,
1st channel emission signal, all channels receives echo-signal simultaneously, is divided into d=0.5m, the fortune of radar platform between adjacent antenna
Dynamic speed is v=1700m/s (5Mach)；1st channel emission linear waveform signal emits the bandwidth and pulsewidth difference of signal
For Br=200MHz and Tp=12us, transmitting signal carrier frequency are f0=10GHz, pulse recurrence frequency PRF=1800Hz, frequency modulation
Rate is γ=Br/Tp.The nearest oblique distance at radar platform and image scene center is 65km.It is provided in radar imagery scene center
One moving target point, tangentially and radially speed is respectively 0m/s and 10m/s to moving target.Emulation be also provided with 8 it is static miscellaneous
Wave point, position be respectively (- 100,100), (0,100), (100,100), (- 100,0), (100,0), (- 100, -100),
(0, -100), (100, -100).Simulation result is illustrated in emulation content below.
2) emulation content and simulation result:
Emulation 1: simulation comparison is carried out to clutter recognition processing using the method for the present invention and traditional ISTAP and CFT method.
Simulation result is as shown in Figure 2, wherein Fig. 2 (a) is using traditional ISTAP processing method clutter recognition result figure；Fig. 2 (b) is
Using traditional CFT processing method clutter recognition result figure；Fig. 2 (c) is using the method for the present invention clutter recognition result figure.
Emulation 2: using the clutter recognition performance comparison figure of traditional ISTAP, CFT method and the method for the present invention.Emulation knot
Fruit is as shown in Figure 3.
Emulation 3: simulation comparison is carried out to motive target imaging using the method for the present invention and traditional ISTAP and CFT method.
Simulation result is as shown in Figure 4, wherein Fig. 4 (a) is using traditional ISTAP processing method motive target imaging result figure；Fig. 4
It (b) is using traditional CFT processing method motive target imaging result figure；Fig. 4 (c) is the movement mesh using the method for the present invention
Mark imaging results figure.
Emulation 4: the moving target radial velocity using the method for the present invention and traditional ISTAP and CFT method processing is estimated
Accuracy comparison.Simulation result is as shown in Figure 5.
3) analysis of simulation result:
Emulation 1: as can be seen that carrying out clutter suppression using traditional ISTAP and CFT method from Fig. 2 (a) and Fig. 2 (b)
System, there are certain losses for moving target energy, and clutter is not totally constrained；As can be seen that adopting from Fig. 2 (c)
Clutter recognition is carried out with the method for the present invention, moving target is fully retained, and clutter is totally constrained.From the comparison of Fig. 2
As a result as can be seen that the method for the present invention is more preferable than traditional ISTAP and CFT method clutter recognition effect in.
Emulation 2: from figure 3, it can be seen that the radial velocity in moving target is the clutter of the method for the present invention at 10m/s
Inhibit letter miscellaneous noise ratio higher, and traditional ISTAP and CFT method letter miscellaneous noise ratio is lower.
Emulation 3: from Fig. 4 (a) and Fig. 4 (b) as can be seen that using traditional ISTAP and CFT method to moving target into
Row imaging, imaging results are diffused as multiple points, i.e., moving target is not fully focused；As can be seen that using from Fig. 4 (c)
Moving target is imaged in the method for the present invention, and imaging results are focused to a point, this demonstrate that the method for the present invention is to high ultrasound
The validity of fast radar platform motive target imaging.
Emulation 3: from figure 5 it can be seen that high using the moving target radial velocity estimated accuracy that the method for the present invention obtains
In the moving target radial velocity estimated accuracy obtained using traditional ISTAP, CFT method.
Those of ordinary skill in the art will appreciate that: realize that all or part of the steps of above method embodiment can pass through
The relevant hardware of program instruction is completed, and program above-mentioned can store in computer-readable storage medium, which exists
When execution, step including the steps of the foregoing method embodiments is executed；And storage medium above-mentioned includes: ROM, RAM, magnetic or disk
Etc. the various media that can store program code.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can easily think of the change or the replacement, and should all contain
Lid is within protection scope of the present invention.Therefore, protection scope of the present invention should be based on the protection scope of the described claims.
Claims (7)
1. a kind of hypersonic platform clutter recognition and motive target imaging method, which is characterized in that the method includes as follows
Step:
Step 1, radar receiver obtains the echo-signal of k-th of receiving antenna, does fastly to the echo-signal of k-th of receiving antenna
The Fourier transformation of time dimension, obtain k-th of receiving antenna apart from frequency domain echo signal, and to k-th receiving antenna away from
Off-frequency domain echo-signal carry out pulse compression, obtain k-th of receiving antenna apart from frequency domain-orientation time domain echo-signal；
Step 2, oblique filter is removed in the orientation for constructing k-th of receiving antenna, goes tiltedly to filter according to the orientation of k-th of receiving antenna
Wave device carries out orientation apart from frequency domain-orientation time domain echo-signal and goes contracting of baroclining to k-th receiving antenna, and when successively carrying out slow
Between the inverse Fourier transform of Fourier transformation and fast time dimension tieed up, obtain distance domain-Azimuth Compression frequency of k-th of receiving antenna
The echo-signal in rate domain；
Step 2 specifically:
It is H that oblique filter is removed in the orientation for constructing k-th of receiving antennaa,k(fr,ta):
Wherein, j indicates imaginary unit, f0Indicate transmitting signal carrier frequency, frIndicate frequency of distance, v indicates radar platform movement speed
Degree, taIndicate orientation slow time, dkIndicate the relative distance of k-th of antenna and the 1st antenna, c indicates Electromagnetic Wave Propagation speed
Degree, R0Indicate the minimum distance between image scene center and hypersonic platform；
To k-th receiving antenna apart from frequency domain-orientation time domain echo-signal sk(fr,ta) as orientation go oblique compression processing, and according to
The inverse Fourier transform of the secondary Fourier transformation for carrying out slow time dimension and fast time dimension, obtains the distance domain-of k-th of receiving antenna
The echo-signal s of Azimuth Compression frequency domaink(tr,fa):
sk(tr,fa)=IFFTr[FFTa[sk(fr,ta)×Ha,k(fr,ta)]]
=wr(tr-2R0/c)Wa(fa+2vr/λ-2v2t0/λR0)
exp(-j4πR0/λ)exp[-j2π(fa+2vr/λ)dk/v]
Wherein, wr() indicates echo-signal distance to time window function, trIndicate distance to fast time, t0Indicate moving target
The center hold moment, vrIndicate the radial velocity of moving target, λ indicates radar emission signal wavelength, FFTaWhen [] indicates slow
Between tie up FFT operation, IFFTrIndicate [] the IFFT operation of fast time dimension, Wa() indicates echo-signal orientation frequency domain window letter
Number, faIndicate orientation frequency；
Step 3, k=1,2 ..., K are enabled, to respectively obtain distance domain-Azimuth Compression frequency domain echo of K receiving antenna
Signal；The distance domain of the K receiving antenna-Azimuth Compression frequency domain echo-signal is arranged successively, echo-signal is obtained
Matrix；
Step 4, set moving target radial velocity estimated value range and rough estimate interval, to moving target radial velocity into
Row first step coarse search obtains the first step rough estimate value of moving target radial velocity, and corresponding moving target guiding
Vector sum Clutter steering vector；
Step 5, optimal weight vector coefficient required for clutter recognition is obtained, according to the optimal weight vector coefficient to echo-signal
Matrix carries out clutter recognition, the Moving Target Return data after obtaining clutter recognition；
Step 6, rough radial velocity penalty function is constructed, distance is carried out to the Moving Target Return data after the clutter recognition
Fourier transformation and azimuth dimension inverse Fourier transform are tieed up, is obtained apart from frequency domain-orientation time domain echo-signal, then according to described thick
Slightly the radial velocity penalty function rough radial velocity of frequency domain-orientation time domain echo-signal of adjusting the distance compensates, and obtains rough
The compensated echo-signal of radial velocity；Distance is carried out to the rough compensated echo-signal of radial velocity again to tie up in inverse Fu
Leaf transformation obtains the two-dimensional time-domain echo-signal of moving target；
Step 6 specifically includes following sub-step:
Construct rough radial velocity penalty functionAre as follows:
Obtain the two-dimensional time-domain echo-signal of moving targetAre as follows:
Wherein, IFFTaIndicate [] the IFFT operation of slow time dimension, vr_resIndicate the first step rough estimate value to radial velocity
vr0Residual radial velocity after compensating, vr_res=vr-vr0；
Step 7, Radon transformation is carried out to the two-dimensional time-domain echo-signal of the moving target, realizes moving target radial velocity
Second step accurately estimate, obtain the fine estimation of moving target radial velocity；
Step 8, distance dimension Fourier transformation is carried out to the two-dimensional time-domain echo-signal of the moving target, obtained apart from frequency domain-
The Moving Target Return signal of orientation time domain；Residual radial velocity penalty function is constructed, is compensated according to the residual radial velocity
Function accurately compensates the radial velocity of moving target, obtains accurate compensated echo-signal；Wherein remaining radial speed
Degree is the difference of the radial velocity of moving target and the first step rough estimate value of moving target radial velocity；
In step 8:
It obtains apart from frequency domain-orientation time domain Moving Target Return signalAre as follows:
Construct residual radial velocity penalty functionAre as follows:
Obtain accurate compensated echo-signal s (fr,ta) are as follows:
Wherein, Wr() indicates echo-signal apart from frequency domain window function, wa() indicates echo-signal orientation time window function；
Step 9, azimuth dimension Fourier transformation is carried out to the accurate compensated echo-signal and apart from dimension inverse Fourier transform,
The moving target signal focused.
2. a kind of hypersonic platform clutter recognition according to claim 1 and motive target imaging method, feature exist
In in step 1:
Radar receiver obtains the echo-signal s of k-th of receiving antennak(tr,ta) are as follows:
sk(tr,ta)=wr(tr-τk)wa(ta-t0)exp[j2πf0(tr-τk)]exp[jπγ(tr-τk)2]
Wherein, k=1,2 ..., K, K indicate receiving antenna number, trIndicate distance to fast time, taIndicate the orientation slow time,
wr() indicates echo-signal distance to time window function, wa() indicates echo-signal orientation time window function, t0Indicate fortune
The center hold moment of moving-target, j indicate imaginary unit, f0Indicate that transmitting signal carrier frequency, γ indicate transmitting signal frequency modulation rate, τk
Indicate the time delay of k-th of receiving antenna, τk=2Rk(ta)/c, c indicate propagation velocity of electromagnetic wave, Rk(ta) indicate taMoment
The distance between k-th of receiving antenna and moving target,
R0Indicate image scene center with it is hypersonic
Minimum distance between platform, vrIndicate the radial velocity of moving target, vaIndicate the tangential velocity of moving target, v indicates superb
Velocity of sound platform movement velocity, dkIndicate the relative distance of k-th of receiving antenna and the 1st receiving antenna, dk=(k-1) d, d expression
The relative distance of two neighboring receiving antenna；
Determine frequency domain reference signal Hr(fr)=exp [j π (f0+fr)2/ γ], and using frequency domain reference signal to k-th of reception day
Line apart from frequency domain echo signal carry out pulse compression, obtain k-th of receiving antenna apart from frequency domain-orientation time domain echo-signal
sk(fr,ta) are as follows:
sk(fr,ta)=FFTr[sk(tr,ta)]×Hr(fr)
=Wr(fr)wa(ta-t0)exp(-j2π(f0+fr)τk)
Wherein, frIndicate frequency of distance, FFTrIndicate [] the Fast Fourier Transform FFT operation of fast time dimension, Wr() indicates
Echo-signal is apart from frequency domain window function.
3. a kind of hypersonic platform clutter recognition according to claim 2 and motive target imaging method, feature exist
In step 3 specifically:
K=1,2 ..., K are enabled, to respectively obtain distance domain-Azimuth Compression frequency domain echo-signal s of K receiving antenna1
(tr,fa),s2(tr,fa),…,sK(tr,fa), then the distance domain of K obtained receiving antenna-Azimuth Compression frequency domain is returned
Wave signal s1(tr,fa),s2(tr,fa),…,sK(tr,fa) arranged in sequence, obtain echo-signal matrix s (tr,fa)=
[s1(tr,fa),s2(tr,fa),...,sK(tr,fa)]T, wherein subscript T indicates transposition operation, faIndicate orientation frequency.
4. a kind of hypersonic platform clutter recognition according to claim 3 and motive target imaging method, feature exist
In step 4 specifically includes following sub-step:
The maximum estimated value v of (4a) setting moving target radial velocityr_rangeWith rough estimate interval vr_step, and obtain needing thick
Total degree P=ceil (the v slightly searched forr_range/vr_step), wherein ceil () expression, which rounds up, counts operation；
(4b) initializes the number of iterations p=1；
(4c) carries out first step rough estimate to the radial velocity of moving target, obtains velocity estimation median vr_temp=-
vr_range/2+p×vr_step；
(4d) enables the value of p add 1 if p < P, and returns to sub-step (4c), otherwise to all velocity estimation medians of acquisition, asks
Take the corresponding moving target energy of each velocity estimation median；
(4e) is selected so that the maximum velocity estimation median of moving target energy, the first step as moving target radial velocity
Rough estimate value vr0, i.e.,WhereinIt indicates to obtain corresponding when moving target Energy maximum value
Velocity estimation median vr_temp；
(4f) acquires moving target steering vectorAre as follows:
(4g) acquires Clutter steering vector aC(fa) are as follows:
aC(fa)=[exp (- j2 π fad1/v) … exp(-j2πfadK/v)]T。
5. a kind of hypersonic platform clutter recognition according to claim 4 and motive target imaging method, feature exist
In step 5 specifically includes following sub-step:
(5a) is according to the echo-signal matrix s (tr,fa), covariance matrix R (f is calculateda)=E [s (tr,fa)sH(tr,
fa)], wherein E [] expression takes desired operation, and subscript H indicates conjugate transposition；
(5b) is according to optimization problem:
Acquire optimal weight vector coefficient required for clutter recognitionAre as follows:
WhereinIndicate to obtain corresponding optimal weight vector coefficient when minimum value
(5c) is by the optimal weight vector coefficientWith the echo-signal matrix s (tr,fa) be multiplied, it obtains corresponding
Moving Target Return data after clutter recognitionAre as follows:
6. a kind of hypersonic platform clutter recognition according to claim 5 and motive target imaging method, feature exist
In step 7 specifically:
It sets and the search range of second step precise search is carried out as [v to the radial velocity of moving targetr0-vr_step/2,vr0+
vr_step/ 2] Radon transformation, and in the search range is carried out, residual radial velocity v is acquiredr_res, and obtain moving target diameter
To the fine estimation v of speedr_est=vr0+vr_res。
7. a kind of hypersonic platform clutter recognition according to claim 6 and motive target imaging method, feature exist
In, in step 9,
The moving target signal s focusedimage(tr,fa) are as follows:
simage(tr,fa)=IFFTr[FFTa[s(fr,ta)]]
=wr(tr-2R0/c)Wa(fa-2v2t0/λR0)exp(-j4πR0/λ)。
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| CN108051809B (en) * | 2017-11-14 | 2019-12-24 | 石家庄铁道大学 | Moving target imaging method and device based on Radon transformation and electronic equipment |
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| CN109298412B (en) * | 2018-09-30 | 2022-06-14 | 北京航空航天大学 | Target two-dimensional speed measurement method based on double-frequency coherent radar |
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| CN112946650B (en) * | 2021-04-15 | 2023-08-15 | 中山大学 | One-station fixed double-station low-frequency ultra-wideband SAR moving target detection and imaging method |
| CN113687356B (en) * | 2021-09-16 | 2023-10-20 | 中国科学院空天信息创新研究院 | Airborne multichannel circular SAR moving target detection and estimation method |
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