CN106125039B - Improvement space-time adaptive Monopulse estimation method based on local Combined Treatment - Google Patents

Improvement space-time adaptive Monopulse estimation method based on local Combined Treatment Download PDF

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CN106125039B
CN106125039B CN201610414875.5A CN201610414875A CN106125039B CN 106125039 B CN106125039 B CN 106125039B CN 201610414875 A CN201610414875 A CN 201610414875A CN 106125039 B CN106125039 B CN 106125039B
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jdl
angle
doppler
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CN106125039A (en
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于佳
沈明威
纪存孝
胡佩
郑佳芝
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Hohai University HHU
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S3/00Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
    • G01S3/02Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using radio waves
    • G01S3/14Systems for determining direction or deviation from predetermined direction
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S13/00Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06Systems determining position data of a target
    • G01S13/42Simultaneous measurement of distance and other co-ordinates
    • G01S13/44Monopulse radar, i.e. simultaneous lobing
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S3/00Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
    • G01S3/02Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using radio waves
    • G01S3/04Details
    • G01S3/06Means for increasing effective directivity, e.g. by combining signals having differently oriented directivity characteristics or by sharpening the envelope waveform of the signal derived from a rotating or oscillating beam antenna

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

Abstract

The improvement space-time adaptive Monopulse estimation method based on local Combined Treatment that the invention discloses a kind of, in object space frequency and Doppler frequency mismatch simultaneously, Doppler frequency and azimuth of target by the target estimated, steering vector when iteration updates the Space-time domain dimensionality reduction matrix and target detection sky of JDL algorithm, it is less to solve multichannel onboard radar system channel, DOPPLER RESOLUTION is lower, the big problem of angle error.The present invention only needs two step iteration that can accurately estimate object space angle, is easy to engineering construction.

Description

Improvement space-time adaptive Monopulse estimation method based on local Combined Treatment
Technical field
The present invention relates to airborne radar Monopulse estimation fields, and in particular to a kind of improvement based on local Combined Treatment is empty When adaptive monopulse angle-measuring method.
Background technique
Work is regarded under airborne radar, land clutter seriously leads to dopplerbroadening, so that moving target is easy to be flooded by clutter, Influence radar target acquisition performance.
The it is proposeds such as Brennan in 1973 are using Space time pattern (STAP) come clutter reduction.STAP into The filtering of row space-time two-dimensional, by unit to be detected (CUT) adjacency unit selection training sample, adaptive polo placement filter Weight, has become the technology of a core, and is considered as the strong tools of airborne radar detection target while clutter reduction.
Although target detection performance can be improved using STAP technology, it is unable to estimate out target angle.Nickel is mentioned Adaptive monopulse technology out is a kind of High-precision angle estimation method, and this method can extend to space-time two-dimensional.STAP In sky, two-dimensional space realizes that self-adapting clutter inhibits the coherent accumulation with moving-target signal, and optimal place theoretically may be implemented Reason, but operand required for full dimension is handled is surprising, it is assumed that spatially and temporally hits is respectively N and K, and what is obtained is adaptive Weight needs to tie up NK × NK clutter correlation matrix and is estimated and inverted that operand is O (NK)3, processing is soft or hard in real time All there is huge difficulty on part.
The solution of problem is down to lower dimensional space, it can be achieved that system by the linear transformation to full dimension data by dimensionality reduction STAP The reduction of freedom degree.
Summary of the invention
The technical problem to be solved by the present invention is to provide a kind of based on office for defect involved in background technique The improvement space-time adaptive Monopulse estimation method of domain Combined Treatment, it is less to solve multichannel onboard radar system channel, more General Le resolution ratio is lower, the big problem of angle error.
The present invention uses following technical scheme to solve above-mentioned technical problem:
Improvement space-time adaptive Monopulse estimation method based on local Combined Treatment, includes the following steps:
Step 1) sets h=0, obtains each array element of airborne radar detecting distance unit according to the following formula and receives signal z:
Z=bs+n
Wherein, the complex envelope of b expression target, n expression clutter plus noise, steering vector when s is target empty,
For Kronecker product, st=[1 ej2πv ... ej2πv(K-1)]T, ss=[1 ej2πu ... ej2πu(N-1)]T, st、 ssTime domain steering vector and airspace steering vector are respectively corresponded, subscript T indicates transposition operation;
The target that v is indicated normalizes Doppler frequency, and u=d sin θ/λ indicates that target normalizes spatial frequency, and d is to show battle array First spacing, λ are wavelength, and θ is target bearing Space Angle, and N is radar antenna element number of array, and K is arteries and veins in a coherent accumulation period Rush number;
Step 2), steering vector s when angle-doppler cells detection sky where target to be detected0
Wherein,st0、ss0Point The time domain steering vector at doppler cells center to be detected and the airspace guiding arrow at angle-unit center to be detected are not corresponded to Amount;
v0Indicate the normalization Doppler frequency at doppler cells center to be detected, u0=d sin θ0/ λ indicates angle measurement to be checked Spend the normalization spatial frequency of unit center, θ0For transmitting antenna bearing sense angle;
Step 3) obtains local Combined Treatment (JDL) dimensionality reduction square of measuring angle-doppler cells to be checked according to the following formula Battle array:
Wherein, TtFor time domain dimensionality reduction matrix, TsFor airspace dimensionality reduction matrix:
Step 4) obtains the JDL dimensionality reduction data of measuring angle-doppler cells to be checked according to the following formula:
zT=THz
Wherein, subscriptHIndicate the operation of complex conjugate transposition;
Step 5) carries out Maximum-likelihood estimation acquisition JDL dimensionality reduction clutter as sample by neighbor distance unit and interference is added to make an uproar Sound covariance matrix RT
Step 6) calculates JDL and wave beam adaptive weight w according to the following formulaT
Wherein,Indicate steering vector when the detection of JDL dimensionality reduction is empty,
Step 7) calculates separately the orientation JDL difference beam adaptive weight and JDL time domain difference beam adaptive weight;
Step 8) calculates the estimated value of target normalization spatial frequency u according to the following formulaTarget normalizes Doppler The estimated value of frequency v
Wherein, ruFor orientation difference beam with and wave beam pulse ratio, μuFor ruOffset correction, rvIt is poor for time domain Wave beam with and wave beam pulse ratio, μvFor rvOffset correction;For the oblique of space-time adaptive pulse ratio Rate matrix;
Step 9) enablesH=h+1;
Step 10), judges whether h is less than m, if h < m, m be it is pre-set be greater than 1 integer, will be in step 1 Steering vector s when detection is empty0It is modified toWherein:
And by the T in the JDL dimensionality reduction matrix T in step 1tAnd TsIt is modified to:
Step 11) repeats step 4) to step 10), until h=m;
Step 12) calculates the estimated value of target bearing Space Angle θ according to the following formula
Wherein, arcsin () is arcsine operation;
Step 13) exports the estimated value of target bearing Space Angle.
Further optimize as the improvement space-time adaptive Monopulse estimation method the present invention is based on local Combined Treatment Scheme, the m in the step 10) are equal to 2.
Further optimize as the improvement space-time adaptive Monopulse estimation method the present invention is based on local Combined Treatment Scheme, the difference beam of JDL orientation described in step 7) adaptive weight and JDL time domain difference beam adaptive weight calculation formula difference It is as follows:
Wherein, dT,u=THdu, dT,v=THdv,
Diagonal matrix DN=diag (λ π i [0 1 ... N-1]/d), DK=diag (2 π i [0 1 ... K -1]).
Further optimize as the improvement space-time adaptive Monopulse estimation method the present invention is based on local Combined Treatment Scheme, r in the step 8)v、μv、ru、μuWithThe calculation formula of middle each element is respectively:
Further optimize as the improvement space-time adaptive Monopulse estimation method the present invention is based on local Combined Treatment Scheme, R described in step 5)TEstimated valueFor:
Wherein, xTi=THxiRepresent i-th of training sample xiOutput after dimensionality reduction matrix T carries out dimension-reduction treatment, L is sample This number.
Further optimize as the improvement space-time adaptive Monopulse estimation method the present invention is based on local Combined Treatment Scheme, L=27.
The invention adopts the above technical scheme compared with prior art, has the following technical effects:
1. this method is by estimating the Doppler of target frequently in object space frequency and Doppler frequency mismatch simultaneously Steering vector when rate and azimuth iteration update the Space-time domain dimensionality reduction matrix and target empty of JDL algorithm, can reduce Doppler across It more loses, and then improves output letter miscellaneous noise ratio, can get angle measurement accuracy more higher than conventional adaptive monopulse.
2. fast convergence rate is easy to engineering construction.
Detailed description of the invention
Fig. 1 is the improvement space-time adaptive Monopulse estimation method flow diagram based on JDL;
Fig. 2 is that JDL-STAM algorithm target angle is estimated with the number of iterations change curve;
Fig. 3 is JDL-STAM and JDL-MSTAM algorithm target angle is estimated with the number of iterations change curve;
Fig. 4 is that the normalization target Doppler frequency that JDL-STAM and JDL-MSTAM algorithm is estimated changes with the number of iterations Curve;
Fig. 5 is JDL-STAM and JDL-MSTAM algorithm target angle estimates RMSE with SCNR change curve;
Fig. 6 is that target angle of the JDL-MSTAM algorithm under different pulse number estimates RMSE with SCNR change curve.
Specific embodiment
Technical solution of the present invention is described in further detail with reference to the accompanying drawing:
The improvement space-time adaptive Monopulse estimation method based on local Combined Treatment that the invention discloses a kind of, in target Spatial frequency and Doppler frequency simultaneously mismatch when, pass through the Doppler frequency and azimuth of target of the target estimated, iteration Steering vector when updating the Space-time domain dimensionality reduction matrix and target detection sky of JDL algorithm can significantly reduce Doppler and cross over loss, And then output letter miscellaneous noise ratio is improved, this method only needs two step iteration that can accurately estimate object space angle.
Assuming that radar antenna has, array element is N number of, each array-element antenna isotropic, and umber of pulse is K in a coherent accumulation period, Then the radar signal doppler cells signal model of its detection unit can be expressed as form:
Z=bs+n
Wherein, z indicates that array of detection units receives signal phasor, and b indicates that the complex envelope of target, n indicate clutter plus noise; Assuming that it is 0 that clutter plus noise n, which obeys mean value, covariance is the Gaussian Profile of R, and clutter, noise and target are irrelevant;S is mesh Steering vector when mark is empty:
Wherein, st=[1 ej2πv ... ej2πv(K-1)]T, ss=[1 ej2πu ... ej2πu(N-1)]T, st、ssWhen respectively corresponding Domain steering vector and airspace steering vector, subscript T indicate transposition operation, and v indicates that target normalizes Doppler frequency, u=d sin θ/λ indicates that target normalizes spatial frequency, and d is to show array element spacing, and λ is wavelength, and θ is target bearing Space Angle.
Steering vector s when angle-doppler cells detection sky where target to be detected0For:
Wherein,st0、ss0Point The time domain steering vector at doppler cells center to be detected and the airspace guiding arrow at angle-unit center to be detected are not corresponded to Amount, v0Indicate the normalization Doppler frequency at doppler cells center to be detected, u0=d sin θ0/ λ indicates measuring angle list to be checked The normalization spatial frequency at first center, θ0For transmitting antenna bearing sense angle.
Signal data transforms to angle-Doppler by bidimensional discrete Fourier transform (DFT) when JDL algorithm is first empty Domain.It is in observed direction that angle is more since radar emission energy is concentrated mainly on observed direction in angle Doppler domain General Le unit is grouped, and every group becomes a local processing region (LPR).Assuming that radar array antenna has N column, and primary phase Time domain impulse number is K in dry-cure interval.There are 3 angle-units and 3 doppler cells in setting LPR, is then mapped to formulation The transformation of LPR is realized with matrix T.Wherein T is a series of airspaces and the dimensionality reduction turn that time domain steering vector Kronecker product is constituted Matrix is set, is defined as:
In formula,For Kronecker product;TtFor time domain dimensionality reduction matrix, i.e.,:
TsFor airspace dimensionality reduction matrix, i.e.,:
It is assumed herein that clutter and noise obey the Gaussian Profile that mean value is 0 and clutter plus noise covariance matrix is defined as R. After matrix T operation, the conversion of data is realized simultaneously with dimensionality reduction, and wherein angle domain is divided into the interval 1/N, and Doppler domain divides For the interval 1/K, that is, it is equivalent to the bidimensional DFT transform of JDL algorithm.
After conversion, the JDL dimensionality reduction data z of measuring angle-doppler cells to be checkedT=THZ, clutter add interference noise covariance Matrix RT=E { zTzT H, E { } indicates mathematic expectaion operation, subscriptHIndicate the operation of complex conjugate transposition, JDL and wave beam are adaptive WeightWhereinIndicate steering vector when the detection of JDL dimensionality reduction is empty;It is practical since miscellaneous characteristic of making an uproar is unknown The above formula covariance matrix R inTCalculating by its Maximum-likelihood estimation formInstead of:
Wherein xTi=THxiRepresent i-th of training sample xiOutput after dimensionality reduction matrix T carries out dimension-reduction treatment.L is sample Number, to guarantee estimated accuracy, sample needs statistically to meet independent same distribution condition with the miscellaneous component of making an uproar of unit to be detected, can Take L=27 independent same distribution training sample.
If the normalization Doppler frequency of target is strictly limited to detection unit center Doppler frequency, while target is returned One changes spatial frequency also at corresponding detection unit center, then steering vector is when sky in angle-Doppler domain
sT=[0 ... 010 ... 0]T
Wherein, " 1 " represents detection angles-doppler cells, and remaining element is " 0 ".However, when there are deviation, also When being target Doppler and the equal offset detection unit center of angle, JDL transition matrix T and when transformed target empty, are oriented to time domain Inevitable mismatch.The loss of target Doppler across loss and output signal-to-noise ratio is further resulted in, subsequent target detection error increases Greatly.That is, to further promote target angle measurement accuracy compensation need to be modified to target Doppler and angle parameter.
Data are handled through JDL, and it is corresponding to calculate separately space-time adaptive pulse in measuring angle-doppler cells to be checked Empty, time domain difference beam adaptive weight.The then orientation JDL difference beam adaptive weight and JDL time domain difference beam adaptive weight point It is not:
Wherein, dT,u=THdu, dT,v=THdv,Diagonal matrix DN= Diag (λ π i [0 1 ... N -1]/d), DK=diag (2 π i [0 1 ... K -1]).
The formula of the target bearing Space Angle and Doppler frequency estimated by space-time adaptive pulse is as follows:
WhereinWithThe estimated value of respectively target normalization spatial frequency u and the v of target normalization Doppler frequency, ruFor airspace difference beam with and wave beam pulse ratio, μuFor ruOffset correction, calculation formula is respectively:
rvFor time domain difference beam with and wave beam pulse ratio, μvFor rvOffset correction, calculation formula difference For:
For the slope matrix of space-time adaptive pulse ratio, each element calculation formula is respectively:
In the case where variable determines, the space-time adaptive pulse (abbreviated here as JDL-STAM) based on JDL is available In the estimation of target Doppler frequency and space angle.However, when target Doppler frequency departure detects doppler cells center When frequency and in the case where spatial frequency while mismatch, the angle error of JDL-STAM algorithm is increased accordingly.JDL-STAM is realized JDL treated detection steering vector matching, but there is no the Doppler of compensation target across loss.Multistep pulse can be with Further decrease the deviation of estimated value and true value.It, should be able to be according to the spatial frequency of estimation in order to further increase angle measurement accuracy Steering vector s when updating detection sky simultaneously with Doppler frequency0With the Space-time domain dimensionality reduction matrix T of JDL algorithm, i.e. the present invention proposes Based on JDL improve space-time adaptive single burst algorithm (JDL-MSTAM) with given observed direction spatial frequency and normalizing After change Doppler-frequency estimation goes out u and v, as new setting initial value u0And v0, update detection time domain steering vector st0 With airspace steering vector ss0, and dimensionality reduction matrix when redesigning the sky of JDL algorithmI.e.:
Steering vector s when modified detection is empty0ForWherein:
According to update detection it is empty when steering vector and JDL dimensionality reduction matrix reevaluate sample covariance matrix and it is corresponding from Adapt to the weight with wave beam, time-domain adaptive difference beam and space domain self-adapted difference beam, and iterative estimate space-time adaptive simple venation Punching estimation object space angle and Doppler frequency, had not only improved target Doppler coherent accumulation gain, but also to reduce target more The general mismatch loss for strangling cross-domain loss with steering vector when sky, therefore can get better angle measurement accuracy.The simulation experiment result table It is bright:By two step interative computations, target normalization spatial frequency u and normalization Doppler frequency v can be accurately estimated.Estimation Target bearing Space Angle is
θ=arcsin (λ u/d)
Wherein arcsin () is arcsine operation.
To sum up, the improvement space-time adaptive Monopulse estimation method concrete signal flow chart proposed by the present invention based on JDL See Fig. 1.Computer Simulation assessment algorithm performance is carried out below based on radar clutter simulation data.Radar system parameters are referring under Table:
A target to be detected is injected in distance unit to be detected, normalizes Doppler frequency v=0, how general target place is Strangle the normalization center Doppler frequency v of unit0=1/2K, and LPR is 3 × 3.
Fig. 2 gives JDL-STAM algorithm in the angle of target Doppler frequency offset detection unit center Doppler frequency Estimation figure.As shown in Figure 1, by two step iteration, JDL-STAM algorithm is in the case where deviating the smallest situation, i.e. when v=0.004, estimates The angle of meter is most accurate.However, when target normalization Doppler frequency v off center normalization Doppler frequency, target angle Degree estimated accuracy reduces immediately, and as Doppler shift amount increases, angle estimation error accordingly becomes larger.
As v=0.002, JDL-STAM and two kinds of algorithms of JDL-MSTAM each iteration angle estimation result such as Fig. 3 institute Show.Unlike JDL-STAM algorithm, the angle estimation error of JDL-MSTAM algorithm is smaller.JDL-MSTAM algorithm it is high-precision Degree has benefited from its Combined estimator target Doppler frequency and director space angle, updates JDL transition matrix by iteration, amendment is empty When steering vector reduce target Doppler across loss and steering vector matching error.Fig. 4 gives JDL-STAM and JDL- The target of two kinds of each iterative estimates of algorithm of MSTAM normalizes Doppler frequency.As shown in figure 4, the estimation of JDL-MSTAM algorithm Target Doppler frequency is more accurate.
Using the angle estimation for the adaptive monopulse processor that root-mean-square error (RMSE) is studied herein come quantitative analysis Precision.Root-mean-square error is defined as
In formula, M is Monte Carlo experiment number,Indicate the m times azimuth of target estimated, θ indicates practical mesh Mark azimuth.Following result is 3 step space-time adaptive pulse iteration, the average value of 200 independent Monte Carlo experiments.Two kinds The RMSE of target bearing Space Angle estimated by method is as shown in Figure 5 with signal noise noise ratio (SCNR) change curve.Target Doppler frequency v=0.002 is normalized, SCNR changes to 30dB from -10dB.As can be seen from the figure two kinds of algorithm angle estimations RMSE reduces with the increase of SCNR, but the error of JDL-MSTAM algorithm is smaller.
It is assumed that target Doppler frequency departure detects doppler cells centre frequency 40%, Fig. 6 gives JDL-MSTAM calculation Method is in different pulse number condition, i.e. K=128, and 64 and 32, target angle estimates RMSE with SCNR change curve.It can be with from figure Find out, when umber of pulse is more, DOPPLER RESOLUTION is improved, and JDL-MSTAM algorithm can obtain higher angle measurement accuracy.
Those skilled in the art can understand that unless otherwise defined, all terms used herein (including skill Art term and scientific term) there is meaning identical with the general understanding of those of ordinary skill in fields of the present invention.Also It should be understood that those terms such as defined in the general dictionary should be understood that have in the context of the prior art The consistent meaning of meaning will not be explained in an idealized or overly formal meaning and unless defined as here.
Above-described specific embodiment has carried out further the purpose of the present invention, technical scheme and beneficial effects It is described in detail, it should be understood that being not limited to this hair the foregoing is merely a specific embodiment of the invention Bright, all within the spirits and principles of the present invention, any modification, equivalent substitution, improvement and etc. done should be included in the present invention Protection scope within.

Claims (5)

1. the improvement space-time adaptive Monopulse estimation method based on local Combined Treatment, which is characterized in that include the following steps:
Step 1) sets h=0, obtains each array element of airborne radar detecting distance unit according to the following formula and receives signal z:
Z=bs+n
Wherein, the complex envelope of b expression target, n expression clutter plus noise, steering vector when s is target empty,
For Kronecker product, st=[1 ej2πv ... ej2πv(K-1)]T, ss=[1 ej2πu ... ej2πu(N-1)]T, st、ssPoint Time domain steering vector and airspace steering vector are not corresponded to, and subscript T indicates transposition operation;
The target that v is indicated normalizes Doppler frequency, and u=dsin θ/λ indicates that target normalizes spatial frequency, and d is between showing array element Away from λ is wavelength, and θ is target bearing Space Angle, and N is radar antenna element number of array, and K is umber of pulse in a coherent accumulation period;
Step 2), steering vector s when angle-doppler cells detection sky where target to be detected0
Wherein,st0、ss0It is right respectively Answer the time domain steering vector at doppler cells center to be detected and the airspace steering vector at angle-unit center to be detected;
v0Indicate the normalization Doppler frequency at doppler cells center to be detected, u0=dsin θ0/ λ indicates measuring angle list to be checked The normalization spatial frequency at first center, θ0For transmitting antenna bearing sense angle;
Step 3) obtains local Combined Treatment (JDL) dimensionality reduction matrix of measuring angle-doppler cells to be checked according to the following formula:
Wherein, TtFor time domain dimensionality reduction matrix, TsFor airspace dimensionality reduction matrix:
Step 4) obtains the JDL dimensionality reduction data of measuring angle-doppler cells to be checked according to the following formula:
zT=THz
Wherein, subscript H indicates the operation of complex conjugate transposition;
Step 5) carries out Maximum-likelihood estimation acquisition JDL dimensionality reduction clutter as sample by neighbor distance unit and interference noise is added to assist Variance matrix RT
Step 6) calculates JDL and wave beam adaptive weight w according to the following formulaT
Wherein,Indicate steering vector when the detection of JDL dimensionality reduction is empty,
Step 7) calculates separately the orientation JDL difference beam adaptive weight and JDL time domain difference beam adaptive weight;
Step 8) calculates the estimated value of target normalization spatial frequency u according to the following formulaTarget normalizes Doppler frequency v Estimated value
Wherein, ruFor orientation difference beam with and wave beam pulse ratio, μuFor ruOffset correction, rvFor time domain difference beam with With the pulse ratio of wave beam, μvFor rvOffset correction;For the slope matrix of space-time adaptive pulse ratio;
Step 9) enablesH=h+1;
Step 10), judges whether h is less than m, if h < m, m be it is pre-set be greater than 1 integer, by the detection in step 1 Steering vector s when empty0It is modified toWherein:
And by the T in the JDL dimensionality reduction matrix T in step 1tAnd TsIt is modified to:
Step 11) repeats step 4) to step 10), until h=m;
Step 12) calculates the estimated value of target bearing Space Angle θ according to the following formula
Wherein, arcsin () is arcsine operation;
Step 13) exports the estimated value of target bearing Space Angle.
2. the improvement space-time adaptive Monopulse estimation method according to claim 1 based on local Combined Treatment, special Sign is that the m in the step 10) is equal to 2.
3. special based on the improvement space-time adaptive Monopulse estimation method described in claim 1 based on local Combined Treatment Sign is that the difference beam of JDL orientation described in step 7) adaptive weight and JDL time domain difference beam adaptive weight calculation formula are divided It is not as follows:
Wherein, dT,u=THdu, dT,v=THdv,
Diagonal matrix DN=diag (λ π i [0 1 ... N-1]/d), DK=diag (2 π i [0 1 ... K-1]).
4. special based on the improvement space-time adaptive Monopulse estimation method described in claim 1 based on local Combined Treatment Sign is, R described in step 5)TEstimated valueFor:
Wherein, xTi=THxiRepresent i-th of training sample xiOutput after dimensionality reduction matrix T carries out dimension-reduction treatment, L are sample Number.
5. special based on the improvement space-time adaptive Monopulse estimation method as claimed in claim 4 based on local Combined Treatment Sign is, L=27.
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CN107167803A (en) * 2017-05-25 2017-09-15 河海大学 The robust Beam Domain Adaptive beamformer method estimated based on steering vector mismatch
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0704713A1 (en) * 1994-09-28 1996-04-03 Rockwell International Corporation Radar terrain bounce jamming detection using ground clutter tracking
US6229475B1 (en) * 1987-04-27 2001-05-08 Raytheon Company Pulse doppler radar system with improved cluster target resolution capability
CN101042435A (en) * 2006-03-23 2007-09-26 欧姆龙株式会社 Radar device and radar method

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP3829659B2 (en) * 2001-07-02 2006-10-04 三菱電機株式会社 Radar equipment
US7671789B1 (en) * 2008-10-03 2010-03-02 Lockheed Martin Corporation Method and system for target detection and angle estimation based on a radar signal

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6229475B1 (en) * 1987-04-27 2001-05-08 Raytheon Company Pulse doppler radar system with improved cluster target resolution capability
EP0704713A1 (en) * 1994-09-28 1996-04-03 Rockwell International Corporation Radar terrain bounce jamming detection using ground clutter tracking
CN101042435A (en) * 2006-03-23 2007-09-26 欧姆龙株式会社 Radar device and radar method

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