CN105807267B - A kind of MIMO radar extends mesh object detection method - Google Patents
A kind of MIMO radar extends mesh object detection method Download PDFInfo
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Abstract
A kind of MIMO radar extension mesh object detection method of the present invention, it is therefore intended that utilize the band-wise processing advantage of MIMO radar so that the extension target in Compound-Gaussian Clutter can be detected preferably.The core concept of this method is：The target echo received according to MIMO radar, the estimation of the parameters of target motion and clutter parameter is carried out, then using GLRT general principles, obtain test statistics, and be finally completed detection.Because target Doppler mismatch, Compound-Gaussian Clutter form parameter etc. can all have an impact to GLRT detection performance, the method for using maximal possibility estimation (MLE) first, the Doppler of target and the estimate of clutter form parameter are obtained, then carries out target detection.Finally, using the advantage of MIMO radar band-wise processing, the accumulation of target echo energy is realized, so as to greatly improve the performance of GLRT detectors, the raising of performance is relevant with the number of MIMO radar dual-mode antenna.
Description
【Technical field】
The invention belongs to traditional Radar Targets'Detection field, and in particular to currently in multiple-input and multiple-output (Multi-
Input Multi-output, MIMO) anti-clutter and target detection technique under radar system.It is compound for further
In Gaussian Clutter, for the MIMO radar using broadband signals such as linear frequency modulations, it is proposed that one kind extension mesh object detection method.
【Background technology】
Conventional radar is launched using individual antenna and reception signal, carries out target acquisition；And MIMO radar uses multiple hairs
Penetrate antenna and multiple reception antennas carry out target acquisition, thus possess good space diversity characteristic and waveform diversity advantage.
In general, MIMO radar can be divided into distributed and two kinds of centralization.To different configuration modes, currently mainly arrowband is used
Signal, the point target detecting method under Gaussian Clutter is studied.But when the bandwidth of MIMO radar transmission signal increases
Add, resolution ratio is constantly lifted, and the characteristic of extension is presented in the distribution of target scattering point, and it is true that point target model has been difficult to accurate simulation
Target signature, using extension object module will be more accurate.In addition, under high-resolution background, low target is visited
During survey, there is serious hangover in the statistical distribution of clutter echo, deviate from conventional Gaussian distribution model.In low grazing angle
In the case of, the clutter distribution character under high-resolution background can be described more truly using complex Gaussian distribution.Compound height
This distribution is (usual by the speckle component (being usually zero-mean gaussian process) and the texture component of slow time change of fast time change
For non-negative real random process) it is described.Because wideband MIMO radar employs transmitted wide band signal, possesses high-resolution energy
Power, Compound-Gaussian Clutter model considers the correlation properties between sample, and analytic properties are good, is more suitable for describing wideband MIMO thunder
Up to the clutter environment faced.Currently, broadband signal has been widely used, and research wideband MIMO radar is in Compound-Gaussian Clutter
Object detection method in environment, there is highly important application value.
In field of radar, for target detection problems, based on Generalized Likelihood Ratio (generalized likelihood
Ratio test, GLRT) method can obtain good performance.It is right using GLRT general principles in Compound-Gaussian Clutter
Extension target component estimated and carry out target detection method it is relatively common.But under MIMO radar system, with
The increase of receiver treatment channel number, GLRT methods become more complicated, and the characteristic of target and clutter is different, detector
Processing mode also shows the characteristics of different.To utilize the advantage of MIMO radar band-wise processing, in Compound-Gaussian Clutter
Extension target, it is proposed that the MIMO radar object detection method based on GLRT.
【The content of the invention】
The purpose of this method is the band-wise processing advantage using MIMO radar so that the extension in Compound-Gaussian Clutter
Target can be detected preferably.The core concept of this method is：The target echo received according to MIMO radar, carry out target
The estimation of kinematic parameter and clutter parameter, then using GLRT general principles, test statistics is obtained, and be finally completed detection.
Because target Doppler mismatch, Compound-Gaussian Clutter form parameter etc. all can produce shadow to GLRT detection performance
Ring, first using maximal possibility estimation (MLE) method, obtain the Doppler of target and the estimate of clutter form parameter, so
After carry out target detection.Finally, using the advantage of MIMO radar band-wise processing, the accumulation of target echo energy is realized, so as to
The performance of GLRT detectors is greatly improved, the raising of performance is relevant with the number of MIMO radar dual-mode antenna.To realize above-mentioned mesh
Detection process is marked, this method is realized using following steps：
Step 1：The signal that MIMO radar is received is pre-processed：
First, the signal that receiver receives is filtered and low noise amplification etc. pretreatment.Consider centralized MIMO radar,
With M transmitting antenna and N number of reception antenna, transmission signal is using M mutually orthogonal broadband signals, pulse number K.It is right
In each reception antenna, comprising M matched filter, the target echo received is subjected to matched filtering, then each reception antenna
M echo can be obtained, N number of reception antenna can obtain M × N roads echo-signal altogether.Assuming that the transmission signal of m-th of transmitting antenna
After n-th of reception antenna carries out matched filtering, echo-signal x is obtainedm,n.If once being sampled to each pulse,
xm,nFor the vector of K × 1.For extending target, ignore the influence of noise and Range cell migration, when the scattering unit of target
When number is L, the Hypothesis Testing Problem of t-th of target scattering unit can be expressed as follows：
H0:xm,n,t=cm,n,tT=1 ..., L+R
H0Represent that range cell to be detected does not have target, H1Target be present in expression.Wherein, xm,n,tIt is t-th of scattering unit
Echo-signal, cm,n,tIt is noise signal；αtIt is target scattering coefficient；fdFor the Doppler frequency of target；Here, dtWith drRespectively
Expression is the spacing between transmitting antenna and reception antenna, θtmWithIt is transmitting antenna and reception antenna and horizontal angle,
TpRepresent the pulse repetition period；m∈[1,M]；n∈[1,N].Because MIMO radar is centralization, it is believed that each launch day
Line target scattering coefficient α corresponding with reception antennatIt is identical, and the scattering coefficient between each scattering unit is different, so as to αtBy
L is determined；R is auxiliary unit number, only includes noise signal, to try to achieve accurate clutter covariance matrix, usually requires that R
≥K。
Under MIMO radar system, the clutter vector c of t-th of scattering unitm,n,tUsing complex Gaussian model, can represent
For
Wherein, τtIt is the texture component of t-th of scattering unit, the component changes slowly, can describe different distance list
The clutter power of member rises and falls；ηtIt is the speckle component of t-th of scattering unit, is independent identically distributed multiple Gauss stochastic variable, line
Manage component and speckle component is separate.
For t-th of scattering unit, clutter covariance matrix CtIt can be expressed as
Wherein, ()HThe conjugate transposition computing of representing matrix；
Scattering unit is not limited, if texture component τ meets that Gamma is distributed, its probability density function can be expressed as
Wherein, b is scale parameter, represents the size of clutter mean power；V is form parameter；Γ (v) is Gamma functions；
Exp () is exponent arithmetic.Form parameter v characterizes the non-gaussian degree of clutter amplitude, and v is smaller, and clutter amplitude distribution is sharper
Sharp, clutter fluctuation characteristic is more violent, and non-gaussian degree is bigger；Otherwise clutter amplitude distribution is closer to Gaussian Profile.
In H0And H1Under assuming that, and joint probability density function p (x | τt,H0) and p (x | τt,αt,fd,H1) can be expressed as
Wherein, Φm,n,t(αt,fd)=xm,n,t-αtsm,n,t(fd)；Det () is determinant computing；(·)HFor conjugate transposition
Computing；Remaining each parameter is with reference to definition above.
Step 2：Parameter Estimation is carried out to the signal received, prepared for further object detection.Parameter Estimation
Method is as follows：
According to target echo and Compound-Gaussian Clutter feature, in H0Under the conditions of (target is not present), clutter can be obtained by (5) formula
Texture componentFor
In H1Under the conditions of (target presence), target Doppler, target scattering coefficient and clutter texture component can be obtained by (6) formula
MLE can be expressed as successivelyWith
Wherein, xm,n,tIt is that the transmission signal of m-th of transmitting antenna corresponding to t-th of scattering unit of target connects by n-th
After receiving antenna match filtering, echo-signal is obtained；sm,n,t(fd) represent to contain target Doppler information and signal guide vector
Echo-signal；Because target Doppler information is identical corresponding to each pair dual-mode antenna, and same target is in different scattering units
Doppler information also immobilize, therefore f can be used heredRepresent the Doppler of target.
Step 3：According in H0And H1Under the conditions of echo data, by the joint probability density function (5) that is previously obtained and
(6) and GLRT criterions, can be examined statistic is
Wherein, γ is the detection threshold under certain false-alarm probability.
Step 4：The relevant parameter estimate that step 2 is obtained substitutes into (11) formula and abbreviation, can obtain
Computing of taking the logarithm is carried out to formula (12), can be examined statistic is
Wherein, γ '=ln (γ), by threshold judgement, when test statistics T is more than thresholding γ ', it is believed that detection
To target, otherwise do not detect target.
Test statistics and target Doppler frequency can be seen that according to (13) formulaRadar transmit-receive antenna number M and N, letter
Number pulse number K and target scattering unit number L is relevant.Target Doppler information is typically unknown, if by other means obtain
There is deviation in the Doppler frequency taken, it will cause GLRT hydraulic performance declines, it is therefore necessary to which Doppler is estimated.In addition,
Under Compound-Gaussian Clutter, clutter amplitude acuity that different form parameter v is obtained is different, when v is smaller clutter amplitude compared with
To be sharp, to reach certain false-alarm probability, detection threshold will improve, and pass through clutter covariance matrix Σ's in (13) formula
Effectively estimation, using in detector, echo x can be reducedm,n,tThe sharp clutter of middle amplitude is to detection
The influence of performance.For MIMO radar, the increase of dual-mode antenna number can make GLRT obtain enough energy accumulations, so as to improve
Detection performance, the raising of another aspect radar resolution can also increase target scattering unit number, can equally improve detection
Energy.
The beneficial effects of the present invention are：
First, using MLE, the estimation of target and clutter unknown parameter information is effectively realized, is provided well for detection
Basis, corresponding method of estimation can also be applied in the Radar Targets'Detection problem of other systems.
Second, detector is designed under the background of Compound-Gaussian Clutter, therefore, it is possible to adapt under different shape parameter
Compound-Gaussian Clutter type, there is well adapting to property and application.For different form parameters, detection performance also can
There is certain difference.
3rd, because MIMO radar is using wideband orthogonal signal, the transmission signal between different antennae is mutually orthogonal,
Therefore, when each reception antenna carries out matched filtering, the influence that adjacent antenna signal is brought can be eliminated, ensures each antenna hair
Penetrate the independence of signal.Using broadband signal, it is possible to increase the resolution capability of MIMO radar, target are changed into extending mesh from point target
Mark, the scattering properties of different scattering units are different so that detector can adapt to different target properties.
4th, using the advantage of MIMO radar MIMO, the energy accumulation effect of detector is greatly improved, so as to reach
Preferable detection performance.Therefore, under different dual-mode antenna configuration modes, the detection performance of MIMO radar is also different.
According to the expression formula of detector, in the timing of dual-mode antenna number sum one, detection performance reaches when dual-mode antenna number is equal
It is optimal.
5th, the general principle of this method can extend to the other application scene of MIMO radar target detection, only need root
According to different noise performances, corresponding detector is derived.
【Brief description of the drawings】
Fig. 1 is that overall procedure is realized in the detection of this method.
Fig. 2 is M matched filtering processing procedure of n-th of antenna.
Fig. 3 is Doppler's estimated bias that MLE algorithms obtain under different antennae configuration mode.
Fig. 4 a are clutter amplitude distribution situations corresponding to different shape parameter v.
Fig. 4 b are 2 × 2MIMO radar detedtion probability curves in the case of v under different shape parameter.
2 × 2MIMO radar detedtion probabilities curve when Fig. 5 is Doppler mismatch.
Fig. 6 is the MIMO radar detection probability curve under different antennae configuration mode.
【Embodiment】
This method is applied to the various MIMO radars using broadband signal.With reference to shown in accompanying drawing 1-6, below to this method
Specific steps and effect are further explained.Mainly comprise the following steps：
Step 1：Simulation parameter is set first：MIMO radar transmitted signal bandwidth 200MHz；PRF is 500Hz；Pulse
Number K is 16；False-alarm probability isAssuming that target only has orientation extension, scattering unit number is 4, corresponding scattering
Coefficient is set to αt=[1.2 2.3 3.1 2.5]；The speed of target is 25m/s.The signal that N number of reception antenna obtains is carried out down
Frequency conversion, intermediate-freuqncy signal is obtained, prepared for the matched filtering of next step.
Step 2：The signal received is subjected to matched filtering processing.MIMO radar uses MIMO system, Mei Gefa
Penetrate between the transmission signal of antenna and keep orthogonal property.Therefore, M transmission signal can be received in receiving terminal, each receiver
And signal, using M matched filter, the echo-signal that M filtering exports can be obtained respectively., can for N number of reception antenna
To obtain M × N number of filtering output.
Step 3：The covariance square of the echo-signal calculating clutter of range cell acquisition is closed in target using MIMO radar
Battle array Σ, then according to above-mentioned MLE algorithms, calculate target and clutter relevant parameter.
Fig. 3 be in the case where dual-mode antenna is 1 × 3,2 × 2 and 2 × 3 MIMO radar background, according to MLE algorithms (formula (8)),
Obtained target Doppler estimated bias.It can be found that the algorithm for estimating in this method is estimated after signal to noise ratio (SCR) reaches 10dB
Meter deviation can reach less level.
According to MLE algorithms, after Doppler's estimate is obtained, estimating for target scattering coefficient can be calculated using formula (9)
Evaluation, result of calculation here areActual value is contrasted, can be with
The estimate for thinking scattering coefficient is more accurately.Using the parameter estimation result of the above, target detection can be carried out.
Step 4：According to the false-alarm probability of setting, detection threshold is obtained, then utilizes parameter estimation result and echo-signal
Detector output is obtained, threshold judgement is carried out, finally obtains testing result.
To illustrate the importance for the parameter Estimation mentioned in the validity of this method and method implementation process, according to above
Simulation parameter, in the case where dual-mode antenna is 2 × 2 MIMO radar background, give first in clutter form parameter difference, according to
The target detection curve that flow chart shown in Fig. 1 obtains, as a result as shown in Figure 4 b.It can be found that under different clutter form parameters,
Detector remains to preferably detect target, and smaller in clutter form parameter, more sharp (such as Fig. 4 a of clutter amplitude distribution
It is shown) in the case of, detection performance still increases.
Fig. 5 is the target detection curve under target Doppler mismatch condition, it can be found that being about in Doppler mismatch
During 2Hz, with SCR increase, detection performance remains to reach 1.When Doppler mismatch reaches 6Hz, detection performance finally can only
It is maintained at 0.2 or so.It can be seen that the performance of detector will be had a strong impact on to the accuracy of target Doppler estimation.Therefore, having must
Target Doppler is accurately estimated by MLE algorithms, to ensure the performance of detector.
Fig. 6 is the target detection curve of MIMO radar under the different antennae configuration mode that this method obtains.From simulation result
It can be found that as number of antennas increases, the detection performance of MIMO radar effectively improves, because when number of antennas increases
Added-time, target echo can effectively be accumulated so that test statistics increases and thresholding is constant, therefore 2 × 3 MIMO thunders
The performance reached is better than 1 × 3 situation.In addition, under identical dual-mode antenna number (M+N is fixed), as M=N, detection performance will
More excellent than under other configurations, because when dual-mode antenna number is equal, M × N reaches maximum, therefore in simulation result, 2
The detection performance of × 2 MIMO radar is better than the detection performance under 1 × 3 configuration mode.
By contrasting the detection performance known to Doppler and under unknown situation, it is believed that when Doppler is unknown, by MLE
Doppler's estimate that algorithm obtains is more accurate, can ensure GLRT detection performance.Fig. 6 simulation result, Ke Yiwei
For MIMO radar in the problem of extension target detection under Compound-Gaussian Clutter, the arrangement of dual-mode antenna provides foundation,
In the case that number of antennas is certain, make dual-mode antenna number equal, enable to the detection performance of MIMO radar optimal.
Claims (4)
1. a kind of MIMO radar extends mesh object detection method, it is characterised in that comprises the following steps：
Step 1：The signal that MIMO radar is received is pre-processed：
First, the signal that receiver receives is filtered and low noise amplification pretreatment；
For extending target, ignore the influence of noise and Range cell migration, when the scattering unit number of target is L, t-th
The Hypothesis Testing Problem of target scattering unit is expressed as follows：
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H0Represent that range cell to be detected does not have target, H1Target be present in expression；Wherein, xm,n,tIt is the echo of t-th of scattering unit
Signal, cm,n,tIt is noise signal；αtIt is target scattering coefficient；fdFor the Doppler frequency of target；Here, dtWith drRespectively
Expression is the spacing between transmitting antenna and reception antenna, θtmWithIt is transmitting antenna and reception antenna and horizontal angle,
TpRepresent the pulse repetition period；m∈[1,M]；n∈[1,N]；R is auxiliary unit number, only includes noise signal；
Under MIMO radar system, the clutter vector c of t-th of scattering unitm,n,tUsing complex Gaussian model, it is expressed as
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Wherein, τtIt is the texture component of t-th of scattering unit, the component changes slowly, describes the clutter work(of different distance unit
Rate rises and falls；ηtIt is the speckle component of t-th of scattering unit, is independent identically distributed multiple Gauss stochastic variable, texture component is with dissipating
Spot component is separate；
For t-th of scattering unit, clutter covariance matrix CtIt is expressed as
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Wherein, b is scale parameter, represents the size of clutter mean power；V is form parameter；Γ (v) is Gamma functions；exp
() is exponent arithmetic；Form parameter v characterizes the non-gaussian degree of clutter amplitude, and v is smaller, and clutter amplitude distribution is more sharp,
Clutter fluctuation characteristic is more violent, and non-gaussian degree is bigger；Otherwise clutter amplitude distribution is closer to Gaussian Profile；
In H0And H1Under assuming that, and joint probability density function p (x | τt,H0) and p (x | τt,αt,fd,H1) be expressed as
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</mrow>
<mi>L</mi>
</munderover>
<munderover>
<mo>&Pi;</mo>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>M</mi>
</munderover>
<munderover>
<mo>&Pi;</mo>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<mrow>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>&pi;&tau;</mi>
<mi>t</mi>
</msub>
<mo>)</mo>
</mrow>
<mi>K</mi>
</msup>
<mi>det</mi>
<mrow>
<mo>(</mo>
<mi>&Sigma;</mi>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<mi>exp</mi>
<mo>(</mo>
<mo>-</mo>
<mfrac>
<mrow>
<msubsup>
<mi>x</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
<mi>H</mi>
</msubsup>
<msup>
<mi>&Sigma;</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<msub>
<mi>x</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
</mrow>
<msub>
<mi>&tau;</mi>
<mi>t</mi>
</msub>
</mfrac>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>5</mn>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<mtable>
<mtr>
<mtd>
<mrow>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>|</mo>
<msub>
<mi>&tau;</mi>
<mi>t</mi>
</msub>
<mo>,</mo>
<msub>
<mi>&alpha;</mi>
<mi>t</mi>
</msub>
<mo>,</mo>
<msub>
<mi>f</mi>
<mi>d</mi>
</msub>
<mo>,</mo>
<msub>
<mi>H</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mo>=</mo>
<munderover>
<mo>&Pi;</mo>
<mrow>
<mi>t</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>L</mi>
</munderover>
<munderover>
<mo>&Pi;</mo>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>M</mi>
</munderover>
<munderover>
<mo>&Pi;</mo>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<mrow>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>&pi;&tau;</mi>
<mi>t</mi>
</msub>
<mo>)</mo>
</mrow>
<mi>K</mi>
</msup>
<mi>det</mi>
<mrow>
<mo>(</mo>
<mi>&Sigma;</mi>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<mi>exp</mi>
<mo>(</mo>
<mrow>
<mo>-</mo>
<mfrac>
<mrow>
<msub>
<mi>&Phi;</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>&alpha;</mi>
<mi>t</mi>
</msub>
<mo>,</mo>
<msub>
<mi>f</mi>
<mi>d</mi>
</msub>
<mo>)</mo>
</mrow>
<mi>H</mi>
</msup>
<msup>
<mi>&Sigma;</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<msub>
<mi>&Phi;</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>&alpha;</mi>
<mi>t</mi>
</msub>
<mo>,</mo>
<msub>
<mi>f</mi>
<mi>d</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
<msub>
<mi>&tau;</mi>
<mi>t</mi>
</msub>
</mfrac>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
</mtr>
</mtable>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>6</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, Φm,n,t(αt,fd)=xm,n,t-αtsm,n,t(fd)；Det () is determinant computing；(·)HTransported for conjugate transposition
Calculate；
Step 2：Parameter Estimation is carried out to the signal received, prepared for further object detection；The method of parameter Estimation
It is as follows：
According to target echo and Compound-Gaussian Clutter feature, under the conditions of target is not present, as H0When, clutter line is obtained by (5) formula
Manage the MLE of componentFor
<mrow>
<msub>
<mover>
<mi>&tau;</mi>
<mo>^</mo>
</mover>
<mrow>
<mi>t</mi>
<mo>,</mo>
<msub>
<mi>H</mi>
<mn>0</mn>
</msub>
</mrow>
</msub>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mrow>
<mi>M</mi>
<mi>N</mi>
<mi>K</mi>
</mrow>
</mfrac>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>M</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<msubsup>
<mi>x</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
<mi>H</mi>
</msubsup>
<msup>
<mi>&Sigma;</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<msub>
<mi>x</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>7</mn>
<mo>)</mo>
</mrow>
</mrow>
Under target existence condition, as H1When, target Doppler, target scattering coefficient and clutter texture component are obtained by (6) formula
MLE is represented sequentially asWith
<mrow>
<msub>
<mover>
<mi>f</mi>
<mo>^</mo>
</mover>
<mi>d</mi>
</msub>
<mo>=</mo>
<mi>arg</mi>
<munder>
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
<msub>
<mi>f</mi>
<mi>d</mi>
</msub>
</munder>
<mo>{</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>M</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<mfrac>
<mrow>
<mo>|</mo>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>s</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>(</mo>
<msub>
<mi>f</mi>
<mi>d</mi>
</msub>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mi>H</mi>
</msup>
<msup>
<mi>&Sigma;</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<msub>
<mi>x</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<msup>
<mo>|</mo>
<mn>2</mn>
</msup>
</mrow>
<mrow>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>s</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>(</mo>
<msub>
<mi>f</mi>
<mi>d</mi>
</msub>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mi>H</mi>
</msup>
<msup>
<mi>&Sigma;</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<mrow>
<mo>(</mo>
<msub>
<mi>s</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>(</mo>
<msub>
<mi>f</mi>
<mi>d</mi>
</msub>
<mo>)</mo>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<mo>}</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>8</mn>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<msub>
<mover>
<mi>&alpha;</mi>
<mo>^</mo>
</mover>
<mi>t</mi>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>s</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>(</mo>
<msub>
<mover>
<mi>f</mi>
<mo>^</mo>
</mover>
<mi>d</mi>
</msub>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mi>H</mi>
</msup>
<msup>
<mi>&Sigma;</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<msub>
<mi>x</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
</mrow>
<mrow>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>s</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>(</mo>
<msub>
<mover>
<mi>f</mi>
<mo>^</mo>
</mover>
<mi>d</mi>
</msub>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mi>H</mi>
</msup>
<msup>
<mi>&Sigma;</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<mrow>
<mo>(</mo>
<msub>
<mi>s</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>(</mo>
<msub>
<mover>
<mi>f</mi>
<mo>^</mo>
</mover>
<mi>d</mi>
</msub>
<mo>)</mo>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>9</mn>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<msub>
<mover>
<mi>&tau;</mi>
<mo>^</mo>
</mover>
<mrow>
<mi>t</mi>
<mo>,</mo>
<msub>
<mi>H</mi>
<mn>1</mn>
</msub>
</mrow>
</msub>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mrow>
<mi>M</mi>
<mi>N</mi>
<mi>K</mi>
</mrow>
</mfrac>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>M</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<msub>
<mi>&Phi;</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mover>
<mi>&alpha;</mi>
<mo>^</mo>
</mover>
<mi>t</mi>
</msub>
<mo>,</mo>
<msub>
<mover>
<mi>f</mi>
<mo>^</mo>
</mover>
<mi>d</mi>
</msub>
<mo>)</mo>
</mrow>
<mi>H</mi>
</msup>
<msup>
<mi>&Sigma;</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<msub>
<mi>&Phi;</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mover>
<mi>&alpha;</mi>
<mo>^</mo>
</mover>
<mi>t</mi>
</msub>
<mo>,</mo>
<msub>
<mover>
<mi>f</mi>
<mo>^</mo>
</mover>
<mi>d</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>10</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, xm,n,tBe m-th of transmitting antenna corresponding to t-th of scattering unit of target transmission signal by n-th reception day
After lines matching filtering, echo-signal is obtained；sm,n,t(fd) represent to contain time of target Doppler information and signal guide vector
Ripple signal；Because target Doppler information is identical corresponding to each pair dual-mode antenna, and same target is in the more of different scattering units
General Le information also immobilizes, therefore uses fdRepresent the Doppler of target；
Step 3：According in H0And H1Under the conditions of echo data, by the joint probability density function (5) being previously obtained and (6) and
GLRT criterions, obtaining test statistics is
<mrow>
<mi>G</mi>
<mi>L</mi>
<mi>R</mi>
<mo>=</mo>
<mfrac>
<mrow>
<munder>
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
<mrow>
<msub>
<mi>&tau;</mi>
<mi>t</mi>
</msub>
<mo>,</mo>
<msub>
<mi>&alpha;</mi>
<mi>t</mi>
</msub>
<mo>,</mo>
<msub>
<mi>f</mi>
<mi>d</mi>
</msub>
</mrow>
</munder>
<mrow>
<mo>(</mo>
<mi>p</mi>
<mo>(</mo>
<mrow>
<mi>x</mi>
<mo>|</mo>
<msub>
<mi>&tau;</mi>
<mi>t</mi>
</msub>
<mo>,</mo>
<msub>
<mi>&alpha;</mi>
<mi>t</mi>
</msub>
<mo>,</mo>
<msub>
<mi>f</mi>
<mi>d</mi>
</msub>
<mo>,</mo>
<msub>
<mi>H</mi>
<mn>1</mn>
</msub>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<munder>
<mi>max</mi>
<msub>
<mi>&tau;</mi>
<mi>t</mi>
</msub>
</munder>
<mrow>
<mo>(</mo>
<mi>p</mi>
<mo>(</mo>
<mrow>
<mi>x</mi>
<mo>|</mo>
<msub>
<mi>&tau;</mi>
<mi>t</mi>
</msub>
<mo>,</mo>
<msub>
<mi>H</mi>
<mn>0</mn>
</msub>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<munderover>
<mtable>
<mtr>
<mtd>
<mo>></mo>
</mtd>
</mtr>
<mtr>
<mtd>
<mo><</mo>
</mtd>
</mtr>
</mtable>
<msub>
<mi>H</mi>
<mn>0</mn>
</msub>
<msub>
<mi>H</mi>
<mn>1</mn>
</msub>
</munderover>
<mi>&gamma;</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>11</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, γ is the detection threshold under certain false-alarm probability；
Step 4：The relevant parameter estimate that step 2 is obtained substitutes into (11) formula and abbreviation, obtains
Computing of taking the logarithm is carried out to formula (12), obtaining test statistics is
<mrow>
<mtable>
<mtr>
<mtd>
<mrow>
<mi>T</mi>
<mo>=</mo>
<mi>M</mi>
<mi>N</mi>
<mi>K</mi>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>t</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>L</mi>
</munderover>
<mrow>
<mo>(</mo>
<mi>ln</mi>
<mo>(</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>M</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<msubsup>
<mi>x</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
<mi>H</mi>
</msubsup>
<msup>
<mi>&Sigma;</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<msub>
<mi>x</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mo>-</mo>
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<mrow>
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<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>m</mi>
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<mn>1</mn>
</mrow>
<mi>M</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>n</mi>
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<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<msubsup>
<mi>x</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
<mi>H</mi>
</msubsup>
<msup>
<mi>&Sigma;</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<msub>
<mi>x</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>-</mo>
<mfrac>
<mrow>
<mo>|</mo>
<msub>
<mi>s</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mover>
<mi>f</mi>
<mo>^</mo>
</mover>
<mi>d</mi>
</msub>
<mo>)</mo>
</mrow>
<mi>H</mi>
</msup>
<msup>
<mi>&Sigma;</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<msub>
<mi>x</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<msup>
<mo>|</mo>
<mn>2</mn>
</msup>
</mrow>
<mrow>
<msub>
<mi>s</mi>
<mrow>
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Wherein, γ '=ln (γ), by threshold judgement, when test statistics T is more than thresholding γ ', it is believed that target is detected,
Otherwise do not detect target；
Found out according to (13) formula, test statistics and target Doppler frequencyRadar transmit-receive antenna number M and N, signal pulse
Number K and target scattering unit number L is relevant；Target Doppler information is unknown, if Doppler's frequency that by other means obtain
There is deviation in rate, it will cause GLRT hydraulic performance declines, it is therefore necessary to which Doppler is estimated；It is in addition, miscellaneous in complex Gaussian
Under ripple, the clutter amplitude acuity that different form parameter v is obtained is different, and clutter amplitude is more sharp when v is smaller, to reach
Certain false-alarm probability, detection threshold will improve, and be utilized in (13) formula by clutter covariance matrix Σ effective estimation
In detector, reduce echo xm,n,tInfluence of the sharp clutter of middle amplitude to detection performance；For
MIMO radar, the increase of dual-mode antenna number can make GLRT obtain enough energy accumulations, so as to improve detection performance, the opposing party
The raising of face radar resolution can also increase target scattering unit number, can equally improve detection performance.
A kind of 2. MIMO radar extension mesh object detection method according to claim 1, it is characterised in that：The MIMO thunders
Up to for centralization, having M transmitting antenna and N number of reception antenna, transmission signal is using M mutually orthogonal broadband signals, arteries and veins
It is K to rush number；For each reception antenna, comprising M matched filter, the target echo received is subjected to matched filtering, then
Each reception antenna obtains M echo, and N number of reception antenna obtains M × N roads echo-signal altogether.
A kind of 3. MIMO radar extension mesh object detection method according to claim 1, it is characterised in that：If m-th of hair
The transmission signal of antenna is penetrated after n-th of reception antenna carries out matched filtering, obtains echo-signal xm,n；If to each pulse
Once sampled, then xm,nFor the vector of K × 1.
A kind of 4. MIMO radar extension mesh object detection method according to claim 1, it is characterised in that：Because of MIMO radar
For centralization, then it is assumed that each transmitting antenna target scattering coefficient α corresponding with reception antennatIt is identical, and each scattering unit
Between scattering coefficient it is different, so as to αtDetermined by L；R is auxiliary unit number, only includes noise signal, to try to achieve accurately
Clutter covariance matrix, it is desirable to R >=K.
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| CN107102302B (en) * | 2017-04-27 | 2020-01-24 | 中国人民解放军海军航空大学 | Radar target fusion detection method based on non-Gaussian parameters |
| CN108896967B (en) * | 2018-05-11 | 2020-11-17 | 清华大学 | Method and device for detecting distance extended target based on clutter covariance matrix estimation |
| CN109683141B (en) * | 2019-01-15 | 2021-03-23 | 西安电子科技大学 | Multi-input multi-output radar emission waveform design method based on Bayesian framework |
| WO2021056332A1 (en) * | 2019-09-26 | 2021-04-01 | 深圳市速腾聚创科技有限公司 | Laser radar signal processing method and apparatus, and computer device and storage medium |
| CN110865362A (en) * | 2019-11-29 | 2020-03-06 | 桂林电子科技大学 | Low-slow small target detection method based on FDA-MIMO radar |
| CN111123233B (en) * | 2019-12-19 | 2021-09-17 | 中国电波传播研究所（中国电子科技集团公司第二十二研究所） | Sea clutter texture estimation method based on correlation |
| CN111751811B (en) * | 2020-05-20 | 2023-07-25 | 西安电子科技大学 | Distance expansion target detection method under multi-base station radar configuration |
| CN111999714B (en) * | 2020-09-02 | 2022-04-01 | 中国人民解放军海军航空大学 | Self-adaptive fusion detection method based on multi-scattering point estimation and clutter knowledge assistance |
| CN112929086A (en) * | 2021-01-19 | 2021-06-08 | 武汉研光通科技有限公司 | Dynamic range expansion method of radio frequency signal optical fiber transmission module based on electro-absorption |
| CN112946654B (en) * | 2021-01-27 | 2023-06-23 | 中国人民解放军国防科技大学 | Method, device, computer system and storage medium for filtering dynamic clutter by radar |
| CN113189556B (en) * | 2021-04-13 | 2022-05-03 | 电子科技大学 | MIMO radar moving target detection method under composite Gaussian clutter environment |
| CN113687325B (en) * | 2021-07-08 | 2024-02-06 | 西安电子科技大学 | Method for detecting shielding small target based on LP and HRRP models |
| CN113267759B (en) * | 2021-07-16 | 2021-09-24 | 中国人民解放军空军预警学院 | FDA-MIMO radar moving target detection method and system |
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