CN106249209B - A kind of adaptive iteration method of estimation of anti-velocity gate deception interference - Google Patents

A kind of adaptive iteration method of estimation of anti-velocity gate deception interference Download PDF

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CN106249209B
CN106249209B CN201610544322.1A CN201610544322A CN106249209B CN 106249209 B CN106249209 B CN 106249209B CN 201610544322 A CN201610544322 A CN 201610544322A CN 106249209 B CN106249209 B CN 106249209B
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CN106249209A (en
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崔国龙
姬红敏
卢金伟
盛彪
孔令讲
张天贤
易伟
杨晓波
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University of Electronic Science and Technology of China
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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
    • G01S7/36—Means for anti-jamming, e.g. ECCM, i.e. electronic counter-counter measures
    • 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

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  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

A kind of adaptive iteration method of estimation of anti-velocity gate deception interference of the disclosure of the invention, is related to Anti-jamming Technology for Radar field, more particularly to Radar cross-section redaction adaptive iteration estimation technique.This method is prior information with receiving signal using radar emission signal, interference signal, for each doppler cells, utilize the target of the last iterative estimate and the doppler spectral of interference, target and the optimal linear filtering device of interference are separately designed, so that the output power of each doppler cells is minimum.Target and interference can be identified simultaneously to reach the algorithm, and the effect with estimation target can be effectively identified under high interfering energy.

Description

A kind of adaptive iteration method of estimation of anti-velocity gate deception interference
Technical field
The present invention relates to Anti-jamming Technology for Radar fields, more particularly to Radar cross-section redaction adaptive iteration estimation technique.
Background technology
Pulse Doppler radar have high range resolution and speed resoluting force, strong clutter reduction ability, can compared with Transient echo, therefore its critically important strategic position in present electronic warfare are told under strong clutter background.Pulse is more It is come resolution target and interference by relevant treatment that the general tradition for strangling radar, which receives processing method,.Digital RF reservoir (DRFM) The deception jammer of composition can generate formula versatile and flexible, right by zooming in and out, being delayed, modulating and forwarding to radar signal A variety of cheating interferences of resistance.Since cheating interference and radar emission signal have extremely strong coherence, radar receiving terminal is easy False target is formed, radar is made to be difficult to differentiate, seriously expends radar resource, stern challenge and threat are brought to radar.Cause This, for improve radar system interference free performance and detectivity, for radar active cheating interference Anti-Jamming Technique gradually Become the emphasis and hot spot of domestic and foreign scholars' research.
Adaptive iteration estimation technique is an effective measures for fighting radar speed cheating interference.2013, Zhang Jingdong A kind of anti-velocity gate deception interference method based on random initial phase train of pulse is proposed, sees document " New Antivelocity Deception Jamming Technique Using Pulses with Adaptive Initial Phase,IEEE Transactions on Aerospace and Electronic System,vol.49,no.2,pp.1290-1300, April 2013. " however, in article its using with high sidelobe level and performance under strong velocity gate deception interference by It is handled to the badly damaged matched filtering docking collection of letters number.Under high interference energy, the performance of matched filtering is by serious Damage, can not detect target.In order to which the target solved under high interference can not detect test problems, for random initial phase arteries and veins Punching string, the present invention proposes adaptive iteration estimation technique, it has a good anti-velocity gate deception jamming performance, and can be The detection and estimation to target are realized under high interference energy.From the point of view of the article published at present, adaptive iteration estimation skill Art has important researching value.
Invention content
The object of the present invention is to the target detection under high interference energy for pulse Doppler radar is asked with estimation Topic proposes to be suitable for the adaptive iteration estimation technique of anti-velocity gate deception interference.This method utilizes radar emission signal, interference letter Number it is prior information with receiving signal, for each doppler cells, utilizes target and the interference of the last iterative estimate Doppler spectral separately designs target and the optimal linear filtering device of interference, so that the output power of each doppler cells is minimum. Target and interference can be identified simultaneously to reach the algorithm, and can effectively be identified and estimation mesh under high interfering energy Target effect.
The present invention provides a kind of adaptive iteration methods of estimation of anti-velocity gate deception interference, it includes the following steps：
Step 1：Iterations m=0 is initialized, carrying out slow time sampling to the reception signal for containing N number of pulse is connect The dis-crete sample values y of the collection of letters number carries out slow time sampling to the transmitting pulse signal for containing N number of pulse and obtains transmitting pulse signal Dis-crete sample values sT, the disturbing pulse signal for containing N number of pulse is carried out slow time sampling obtain disturbing pulse signal from Dissipate sampled value sJ；Signal will be received and carry out matched filtering with transmitting signal, and Fourier transformation is carried out to matched filtering result, Doppler's initial estimation of target when obtaining iterations m=0⊙ is dot product, and (0) represents iteration time Number is 0；Signal will be received and carry out matched filtering with interference signal, and Fourier transformation is carried out to matched filtering result, obtained Doppler's initial estimation of interference
Step 2：Iterations add one, enable m=m+1,
Step 3：It calculates：
WhereinThe Doppler for being the target that the m-1 times iteration obtains on first Doppler sample point estimation,The Doppler for being the interference that the m-1 times iteration obtains on first Doppler sample point estimation, diag MATLAB The middle function for generating diagonal matrix, (m-1) represents iterations as m-1, | |2For take absolute value and square, K for normalize it is how general Strangle frequency (- 0.5,0.5] uniform sampling points,It serves as reasonsThe diagonal matrix of composition, It serves as reasonsThe diagonal matrix of composition；
And construct the correlation matrix R of following the m times iteration(m)：
Wherein matrix FT=diag (sT) F, matrix FJ=diag (sJ) F, F be DFT transform matrix, σ2For multiple Gauss zero-mean The covariance of white noise, I are unit battle array；
Step 4：Obtain Doppler's estimation of the target of the m times iteration of targetWith the interference of the m times iteration of interference Doppler estimation
Doppler estimation of the target that the m times iteration obtains on k-th of Doppler sample pointIt can be by following formula It can be calculated
Wherein fT,kFor matrix FTKth row, H be matrix conjugate transposition, (R(m))-1For matrix R(m)It is inverse, y for receive The dis-crete sample values of signal；Change k=1,2 ..., K, the target Doppler estimation of the m times iteration can be obtained
Doppler estimation of the interference that the m times iteration obtains on k-th of Doppler sample pointIt can be by following formula It can be calculated
Wherein fJ,kFor matrix FJKth row, H be matrix conjugate transposition, (R(m))-1For matrix R(m)It is inverse, y for receive The dis-crete sample values of signal.Change k=1,2 ..., K, the interference Doppler estimation of the m times iteration can be obtained
Step 5：IfWithIt is satisfied by, then exporting target is It is with interferenceThe parameter for the control convergence that wherein ε is set for us, size determine according to actual conditions,For The target Doppler estimation of the m times iteration,For the interference Doppler estimation of the m times iteration,For the m-1 times iteration Target Doppler estimation,For the interference Doppler estimation of the m-1 times iteration, | | | | it is two norms；Otherwise, repeat step 2~ 4, it is straight to cause convergence.
The innovative point of the present invention：A kind of adaptive iteration algorithm for estimating of anti-velocity gate deception interference is provided, it can be simultaneously Target and interference are estimated, there is low sidelobe level, and can effectively be identified and estimation target under high interfering energy.
The present invention provides a kind of adaptive iteration algorithm for estimating of anti-velocity gate deception interference, this method utilizes radar emission Signal, interference signal, reception signal are prior information, for each doppler cells, utilize the mesh of the last iterative estimate Mark and the doppler spectral of interference, separately design target and the optimal linear filtering device of interference, to reach output power each more All minimum on general Le unit, i.e., interference and the energy of noise are suppressed in the Doppler of target estimates spectrum, in the how general of interference The energy of target and noise in estimation spectrum is strangled to be suppressed.The algorithm can not only identify target and interference simultaneously, there is low secondary lobe Level, and can effectively be identified under high interfering energy and estimation target.
Description of the drawings
Fig. 1 is to emit pulse with postponing the disturbing pulse schematic diagram of i PRI；
Fig. 2 is that the Doppler interfered single goal and two estimates schematic diagram；Fig. 2 (a) is that Doppler's estimation of target is shown It is intended to, Fig. 2 (b) is that the Doppler of interference estimates schematic diagram；
Fig. 3 is that multiple target and the Doppler more interfered estimate schematic diagram；Fig. 3 (a) is that the Doppler of target estimates schematic diagram, Fig. 3 (b) is that the Doppler of interference estimates schematic diagram.
Specific embodiment
After initialization, we constantly iteration until meeting the condition of convergence, can obtain Doppler's estimation of targetWithParticularly, in the m times iteration, it would be desirable to be estimated using the Doppler of the m-1 timesWithTo calculateWithTherefore, secondary loop iteration algorithm can carry out.
Input：sT、sJ、y
Output：Doppler's estimation of targetDoppler's estimation of interference
Step 1：The Doppler of initialized target and interference estimation
Step 1-1：Obtain discrete sT、sJ、y
Assuming that single train of pulse of the Doppler radar transmitting in base containing N number of pulse, different pulses contains different random Initial phase, then the transmitting pulse signal of n-th of pulse can be expressed as
Wherein TrFor pulse recurrence interval (PRI),For random initial phase, independently of each other, and obey (- π, π] it is equal Even same distribution, u (t) are as follows for unit jump function
Assuming that there is Q target, they contain different frequencies, and (are delayed in identical range cell and are τ0), then the successive objective echo-signal of n-th of pulse can be expressed as
Wherein τ0For the round trip time delay of target, σT,q, q=1 ..., Q are the complex amplitude of the radar cross section (RCS) of target, fT,q=r 2vT,qNormalization Doppler frequencies of the T/ λ for q-th of target, vT,qFor the radial velocity of q-th of target, λ is radar Carrier wavelength.
Assuming that DRFM intercepts and captures radar emission signal, and generate at least one PRI of interference needs.Assuming that have P interference, they Containing different frequencies, identical range cell is in target, and (i.e. delay is τ0), disturbing pulse delay transmitting pulse i A PTIs, principle such as Fig. 1, then the stepwise derivation echo-signal of n-th of pulse be
Wherein σJ,p、τ0、fJ,p=2vJ,pTr/ λ and vJ,pThe respectively complex amplitude of interference echo, round trip time delay, p-th of interference Normalization all come frequency and p-th interference radial velocity.
Therefore, the reception signal y of n-th of pulsen(t) it can represent as follows：
Wherein vn(t) to receive the multiple zero mean Gaussian white noise in band, covariance σ2。
By slow time sampling, receives echo-signal yn(t) it is τ in time delay0The discrete form of range cell can represent For
Here we with K point general (- 0.5,0.5] normalization Doppler frequency uniform sampling, and be defined as f=[f1, f2,…,fK]T.Define dT=[dT(1),…,dT(K)]TAnd dJ=[dJ(1),…,dJ(K)]TRespectively target is in Doppler domain Estimation is with interfering the estimation in Doppler domain.As normalization Doppler frequency fT,qWhen on k-th of Doppler's point, dT(k)= σT,qThere is target appearance, otherwise dT(k)=0 without target.Similarly, this is also to dJ(k) it is applicable in.In the present invention, for moving-target Test problems, our primary interests are velocity informations, thus our main purposes be estimation dTWith dJ.For this purpose, we It is y=[y (1), y (2) ..., y (N)] by discrete return pulse signalTIt can be expressed as again
Y=FTdT+FJdJ+v (1-7)
Wherein
●dT=[dT(1),dT(1),…,dT(K)]TFor Doppler's estimation of target, dJ=[dJ(1),dJ(1),…,dJ (K)]TFor interference Doppler estimate,
●FTWith FJMatrix for N × K represents as follows respectively：
FT=diag (sT)F,FJ=diag (sJ)F (1-8)
Wherein：Discrete transmitting pulse signal isDiscrete disturbing pulse signal isF can represent as follows for DFT transform matrix：
● v=[v (1), v (2) ..., v (N)]TFor multiple Gauss zero-mean white noise, its covariance matrix is σ2I。
Step 1-2：Signal will be received and carry out matched filtering with transmitting signal, and Fourier is carried out to matched filtering result Transformation obtains the initial estimation of target：
Signal will be received and carry out matched filtering with interference signal, and Fourier transformation is carried out to matched filtering result, done The initial estimation disturbed：
Step 2：Iterations add one, i.e. m=m+1
Step 3：It calculatesWithConstruct correlation matrix R(m)
Step 3-1：
Assuming that dT、dJIt is mutual indepedent with v, and it is zero it is expected, i.e. E { dT}=E { dJ}=E { v }=0.Then receive signal Covariance matrix R can represent as follows：
Wherein：Again due to dT、dJIt is mutual indepedent with v, and expectation is Zero, then DTWith DJIt is diagonal matrix.In addition, usual DTWith DTUnknown, we are represented with single matrix herein, as follows
Step 3-2：
By last time estimationWithAs a result, it calculates the m-1 timesWithIt is as follows
ByWithR in the m times iteration can be obtained(m)For
Step 4：Calculate the target Doppler estimation of the m times iterationWith interference Doppler's estimation
Step 4-1：
It receives signal y and passes through linear filter wT(k), wherein y and wT,kIt is the vector of N × 1, k-th of target can be obtained The estimation of Doppler's pointFor
According to minimum output power criterion
W can be obtainedT,kFor
Then, in the m times iteration, optimal linear filterIt can represent as follows
Step 4-2：
Therefore it can obtain, the target Doppler estimation of the m times iterationSuch as following formula：
Wherein fT,kFor FTKth row,The optimal linear filtering device of k-th of doppler cells during for the m times iteration. Change k=1,2 ..., K, the target Doppler estimation of the m times iteration can be obtained
Step 4-3：
It receives signal y and passes through linear filter wJ(k), wherein y and wJ,kIt is the vector of N × 1, k-th of target can be obtained The estimation of Doppler's pointFor
According to minimum output power criterion
W can be obtainedJ,kFor
Then, in the m times iteration, optimal linear filterIt can represent as follows
Step 4-4：
Therefore it can obtain, the interference Doppler estimation of the m times iterationSuch as following formula：
Wherein fJ,kFor FJKth row,The optimal linear filtering of k-th of doppler cells during for the m times iteration Device.Change k=1,2 ..., K, the interference Doppler estimation of the m times iteration can be obtained
Step 5：
The setting condition of convergence is meets simultaneously：
Wherein ε is convergence parameter,For the target Doppler estimation of the m times iteration,Interference for the m times iteration Doppler's estimation,For the target Doppler estimation of the m-1 times iteration,Interference Doppler for the m-1 times iteration estimates Meter, | | | | it is two norms.
When Doppler's estimation of Doppler's estimation with the interference of target is satisfied by (1-26), then stops iteration, otherwise weigh Multiple step 2~4 are until convergence.
Simulation parameter
The simulation parameter of Fig. 2 is：Pulse number is N=64, Doppler domain sampling number K=1024, the σ of noise2=1, Iterations are n=20.Assuming that there are one real goal, normalization Doppler frequency is fT,1=0.2, | σT,1|2=20dB；Two A interference, normalization Doppler frequency are fJ,1=0.19, fJ,2=0.21, | σJ,1|2=| σJ,2|2=50dB.Fig. 2 (a) can be obtained： Adaptive iteration proposed by the present invention estimation (AIE) algorithm can beDoppler domain detect target peak, and have The peak sidelobe (PSL) of 15dB.However, for traditional filtering (MF) algorithm, target is produced completely by high interference Raw sidelobe level is flooded, and can not be detected.In Fig. 2 (b), AIE'sIn, two interference are accurately estimated, and There is the PSL of about 25dB, detection performance has significant advantage than matched filtering.
The simulation parameter of Fig. 3 is：Pulse number is N=64, Doppler domain sampling number K=1024, the σ of noise2=1, Iterations are n=20.There are 5 real goals, normalization Doppler frequency is fT,1=-0.3, fT,2=-0.1, fT,3=0, fT,4=0.3, fT,5=0.45, | σT,1|2=30dB, | σT,2|2=20dB, | σT,3|2=15dB, | σT,4|2=40dB, | σT,5|2 =50dB；There are 10 interference, normalization Doppler frequency is fJ,1=-0.31, fJ,2=-0.29, fJ,3=-0.11 fJ,4=- 0.09、fJ,5=-0.01, fJ,6=0.01, fJ,7=0.29, fJ,8=0.31, fJ,9=0.44, fJ,10=0.46, | σJ,p|2= 50dB, p=1 ..., 10.Fig. 3 (a) can be obtained：In AIE algorithmsDoppler estimation in, multiple targets can be examined accurately It measures, and has certain peak sidelobe (PSL).However, for traditional filtering (MF) algorithm, target is similary It is complete by high interference generate sidelobe level flood, can not be detected.In Fig. 3 (b), ten interference are accurately estimated, And there is the PSL of about 25dB, detection performance has significant advantage than matched filtering.
It can be obtained by the specific implementation of the present invention：The adaptive algorithm of anti-velocity gate deception interference proposed by the present invention, Target and interference can be accurately detected simultaneously, and has low sidelobe level, under strong jamming, still can be detected and be estimated Count target.

Claims (1)

1. a kind of adaptive iteration method of estimation of anti-velocity gate deception interference, it includes the following steps：
Step 1：Iterations m=0 is initialized, carrying out slow time sampling to the reception signal for containing N number of pulse obtains reception letter Number dis-crete sample values y, the transmitting pulse signal for containing N number of pulse is carried out slow time sampling obtain transmitting pulse signal from Dissipate sampled value sT, the discrete of disturbing pulse signal is obtained to the slow time sampling of disturbing pulse signal progress for containing N number of pulse and is adopted Sample value sJ；Signal will be received and carry out matched filtering with transmitting pulse signal, and Fourier transformation is carried out to matched filtering result, Doppler's initial estimation of target when obtaining iterations m=0⊙ is dot product, and (0) represents iteration time Number is 0；Signal will be received and carry out matched filtering with disturbing pulse signal, and Fourier transformation is carried out to matched filtering result, Obtain Doppler's initial estimation of interference
Step 2：Iterations add one, enable m=m+1,
Step 3：It calculates：
WhereinThe Doppler for being the target that the m-1 times iteration obtains on first Doppler sample point estimation,The Doppler for being the interference that the m-1 times iteration obtains on first Doppler sample point estimation, diag MATLAB The middle function for generating diagonal matrix, (m-1) represents iterations as m-1, | |2For take absolute value and square, K for normalize it is more It is general strangle frequency (- 0.5,0.5] uniform sampling points,It serves as reasonsThe diagonal matrix of composition,It serves as reasonsThe diagonal matrix of composition；
And construct the correlation matrix R of following the m times iteration(m)：
Wherein matrix FT=diag (sT) F, matrix FJ=diag (sJ) F, F be DFT transform matrix, σ2For multiple Gauss zero-mean white noise The covariance of sound, I are unit battle array；
Step 4：Obtain Doppler's estimation of the target of the m times iteration of targetIt is more with the interference of the m times iteration of interference Pu Le estimates
Doppler estimation of the target that the m times iteration obtains on k-th of Doppler sample pointIt can be calculated by following formula
Wherein fT,kFor matrix FTKth row, H be matrix conjugate transposition, (R(m))-1For matrix R(m)It is inverse, y for receive signal Dis-crete sample values；Change k=1,2 ..., K, the target Doppler estimation of the m times iteration can be obtained
Doppler estimation of the interference that the m times iteration obtains on k-th of Doppler sample pointIt can be calculated by following formula
Wherein fJ,kFor matrix FJKth row, H be matrix conjugate transposition, (R(m))-1For matrix R(m)It is inverse, y for receive signal Dis-crete sample values；
Change k=1,2 ..., K, the interference Doppler that can obtain the m times iteration is estimated as：
Step 5：IfWithIt is satisfied by, then exporting target isAnd interference ForWherein ε is the parameter of the control convergence of setting, and size is determined according to actual conditions,For the m times iteration Target Doppler estimation,For the interference Doppler estimation of the m times iteration,How general target for the m-1 times iteration is Strangle estimation,For the interference Doppler estimation of the m-1 times iteration, | | | |2For two norms；Otherwise, step 2~4 are repeated, directly To convergence.
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