CN106093891A - Radar fence anti-crowding measure false target jamming profile method based on doppler velocity inspection - Google Patents

Abstract

The present invention proposes a kind of discrimination method based on target Doppler velocity estimation, primarily to solution radar fence is during differentiating crowding measure false target jamming profile, and the problem that identification result increases with false target dense degree and is deteriorated.First, selected reference radar also carries out measuring packet pretreatment, measurement based on positional information association will be carried out under other radar network target measurement conversions to benchmark radar local coordinate system, get rid of incoherent false measurement and clutter with preliminary, reduce amount of calculation simultaneously；Then, estimate target Doppler speed based on the positional information measured after Coordinate Conversion, measure with benchmark radar doppler velocity and test, to realize the discriminating of false target.With classical based on compared with positional information association mirror method for distinguishing, the inventive method ensure that the high detectability of true and false target in the case of distance multi-false targets dense degree is relatively big.

Description

Radar fence anti-crowding measure false target jamming profile method based on doppler velocity inspection

Technical field

The present invention is under the jurisdiction of radar data process field, it is adaptable to solves radar fence crowding measure false target jamming profile and differentiates to ask Topic.

Background technology

Along with the gradually development of modern electronic warfare technology, the mode of radar network composite is being increasingly being applied to target Follow the tracks of detection, and the conflicting mode for radar fence is constantly updated the most therewith.Deceiving interference stores by using digital RF Radar signal is replicated, modulates and forwards by the device of the advanced person such as device, it is possible to exchanges for less input and preferably disturbs effect Really, therefore Deceiving interference and countermeasure techniques thereof become the focus of Present Domestic outer expert research.

Cheating interference to distance by radar information is a kind of common cheating interference mode, is mainly docked by jamming equipment The radar illumination signal received carry out time delay modulation realize with amplification forwarding, apart from multi-false-target jamming be then to radar away from A kind of important way from information deception.During distance multi-false-target jamming implemented by jammer, radar, jammer are with empty Decoy is approximately on same straight line on radial distance direction, and false target is to be spacedly distributed in real goal two Side, and the motion feature that holding is close with real goal, great fascination.Discrimination method master currently for distance multi-false targets To be analyzed based on the position feature of true and false target.Classical arest neighbors method is the more effective distance multi-false targets of one Discrimination method, the method is built based on angle information, the statistic of range information, is realized the mirror of true and false target by X 2 test Not.But, it is currently based on the jamming equipment during the advanced persons such as digital radiofrequency memory by accurately answering radar emission signal System, modulate and forward and can effectively control false target quantity and spacing distance so that false target in spatial distribution more Close to real goal.Current classical arest neighbors method be capable of false target dense degree less in the case of true and false mesh Mark differentiate, and when distance to false target quantity be significantly increased, and false target dense degree increase time, only by analyze mesh Target positional information carries out the erroneous association rate of true and false target mirror method for distinguishing and will rise, and identification result will be deteriorated, and along with void When decoy dense degree increases further, identification result will drastically deteriorate.Accordingly, it would be desirable to introduce new aim parameter measurement information with Improve the distinguishing ability to false target.

For radar fence distance to cheating interference, jamming equipment by control forward radar signal time delay reality The deception of existing range information, and the doppler information modulation for false target does not take into account, this arises that false target Doppler velocity information move the unmatched situation of state, according to this characteristic, for possessing the radar of speed measuring function, Compare with the true and false target state estimated based on positional information by introducing the doppler velocity measurement information of target Relatively, analyze difference between the two, to realize the discriminating of true and false target, thus be effectively improved the distinguishing ability of radar fence.

Summary of the invention

For radar fence in crowding measure false target jamming profile discrimination process, identification result increases with false target dense degree The problem being deteriorated greatly, it is proposed that a kind of crowding measure false target jamming profile discrimination method estimated based on doppler velocity.First Selected reference radar carries out measuring packet pretreatment, by other radar network target measurement conversions to benchmark radar local coordinate system Under carry out measurement based on positional information association, reject incoherent false target measure with preliminary, reduce amount of calculation simultaneously；So After positional information based on the measurement after Coordinate Conversion estimate the doppler velocity of target, with benchmark radar doppler velocity amount Survey is tested, and i.e. realizes the discriminating of final true and false target.The present invention uses technical scheme steps as follows:

1. based on doppler velocity inspection radar fence anti-crowding measure false target jamming profile method, it is characterised in that include with Lower technical step:

The packet of step (), benchmark radar measurement and data compression；

Radar on the basis of radar 1 in selected radar network, it is assumed that the distance that k moment radar 1 i-th measures is ρ_i(k), side Parallactic angle is θ_iK (), the angle of pitch is ε_iK (), distance, azimuth and the angle of pitch that jth measures are respectively ρ_j(k)、θ_j(k)、ε_j (k).By (1) formula, radar 1 measurement is grouped:

${\mathrm{\&eta;}}_1\left(k\right)=\frac{{\left({\mathrm{\&theta;}}_i\right(k)-{\mathrm{\&theta;}}_j(k\left)\right)}^2}{2{\mathrm{\&sigma;}}_{\mathrm{\&theta;}}^2}+\frac{{\left({\mathrm{\&epsiv;}}_i\right(k)-{\mathrm{\&epsiv;}}_j(k\left)\right)}^2}{2{\mathrm{\&sigma;}}_{\mathrm{\&epsiv;}}^2}<F_{\mathrm{\&alpha;}},k=1,2,...,N---\left(1\right)$

WhereinBeing inspection thresholding, α is its significance level, and n=2 is degree of freedom, σ_θAnd σ_εRepresent radar respectively Azimuth and angle of pitch error in measurement standard deviation；If i and j of radar 1 measures meets (1) formula, then the two is measured and draw Normalizing group, other measurements are tested in this way according to (1) formula and any measurement being divided into a group, if meeting (1) Formula, then incorporate into this measurement in this group, if certain measure with all be grouped measurement be all unsatisfactory for (1) formula, then this measurement is put under One new group, according to this process, until all measurement judges to have divided；

Through measuring packet, azimuth each measurement identical with the angle of pitch is divided into one group；During each is grouped Aim parameter interception angle and the angle of pitch carry out data compression, it is considered to the measurement in each packet is all from same portion radar network, The arithmetic average that measuring after compression measures in being grouped for each, if having N in k moment the l packet_lK () individual measurement, then compress Rear accuracy in measurement improves

Step (two), Testing Association based on adjustment location information；

Set up mahalanobis distance statistic:

η₂(k)=Δ^T(k)(R_2to1(k)+R_l(k))^-1Δ(k) (2)

Then false target differentiates that problem can differentiate by following criterion:

H₀:Target measures as potential real goal；

H₁:Target measures as false target or clutter point；

Wherein, whereinFor decision threshold, α is significance level；Δ (k)=Z_2to1,ENU(k)-Z_l,ENU(k), Z_2to1,ENUK () is other radar network measurement conversions to the coordinates matrix in benchmark radar ENU coordinate system, Z_l,ENUOn the basis of (k) The coordinate of radar the l packet；R_2to1(k) and R_lK () respectively measures Z_2to1,ENU(k) and Z_l,ENUThe measurement covariance square of (k) Battle array；

Step (three), the estimation for target Doppler speed will be measured by the target of step (two) Testing Association, Doppler velocity to potential real goal is estimated；

Step (four), the potential real goal doppler velocity estimated value that step (three) is obtained and benchmark RADOP It is poor that velocity measurement is carried out, and constructs statistic of test, is realized the final discriminating of real goal by X 2 test；

Step (five), one the new set of composition of the positional information corresponding to measurement will checked by step (four):

Z_real,q(k)={ (ρ_2to1,l,p(k),θ_2to1,l,p(k),ε_2to1,l,p(k)),(ρ_1,l(k),θ_1,l(k),ε_1,l(k))} (3)

Wherein (ρ_2to1,l,p(k),θ_2to1,l,p(k),ε_2to1,l,p(k)) represent that other radar network are changed to benchmark radar Pth target on corresponding benchmark radar the l packet direction measures, (ρ_1,l(k),θ_1,l(k),ε_1,l(k)) represent benchmark radar Real goal on the l packet direction measures；Z_real,qK subscript q of () represents that q-th real goal measures set；To pass through Two measurements after doppler velocity inspection are considered as the same real goal measurement that radar network detects；

Assume to gather Z_real,qK total L measurement in (), then this L measures is considered as that same target measures, for improving The certainty of measurement of radar fence, will gather Z_real,qK the measurement in () carries out based on a fusion treatment for mark synthesis, wherein true mesh Target doppler velocity measures and uses the doppler velocity of benchmark radar to measure v₁(k)；

For set Z_real,qMeasurement vector Z in (k)₁(k)、Z₂(k)、…、Z_L(k), corresponding error in measurement Covariance R₁(k)、R₂(k)、…、R_LK (), obtains new metric data and covariance data after carrying out fusion treatment:

$Z_{fusion}\left(k\right)=R_{fusion}\left(k\right)\underset{i=1}{\overset{L}{\&Sigma;}}{R}_i^{-1}\left(k\right)Z_i\left(k\right)---\left(4\right)$

$R_{fusion}\left(k\right)={\&lsqb;\underset{i=1}{\overset{L}{\&Sigma;}}{R}_i^{-1}\left(k\right)\&rsqb;}^{-1}---\left(5\right)$

Real goal after merging measures Z_fusion(k)=[ρ_fusion(k) θ_fusion(k) ε_fusion(k) v₁(k)]^TMake For measuring input, expanded Kalman filtration algorithm is utilized to realize the tenacious tracking of real goal.

Concrete, radar fence anti-crowding measure false target jamming profile based on doppler velocity inspection in described step (three) Method can be divided into the most again following steps:

(1) obtaining after potential real goal measures, it is contemplated that differentiating the non-thread during false target at radar fence Sexual factor, will carry out nonlinear filtering estimation by expanded Kalman filtration algorithm；State equation based on positional information is X₁ (k+1)=FX₁K ()+V (k), polar coordinate measurement equation is Z₁(k)=h₁(X₁(k))+W₁(k)；Wherein, X₁K () is that the k moment is potential True target state vector, F is state-transition matrix, and V (k) is process noise matrix, X₁(k+1) it is that the k+1 moment is potential truly Dbjective state vector, Z₁K () is the measurement vector of potential real goal, W₁K () is measurement noise, its covariance matrix is

(2) target location must be arrived according to the state equation of potential real goal with measurement equation to be estimated as Velocity estimation vector isTherefore change to benchmark radar target measure relative to base The direction vector of quasi-radar is:

(3) Doppler's estimating speed that potential real goal measures is velocity estimation?Projection on direction, i.e. The potential real goal doppler velocity changed to benchmark radar is estimated as:

The variance that doppler velocity is estimated isWherein, P is velocity estimation and the association side of location estimation in k moment Difference battle array,

Concrete, radar fence anti-crowding measure false target jamming profile based on doppler velocity inspection in described step (four) Method can be divided into the most again following steps:

(1) the potential real goal doppler velocity potential true mesh corresponding with benchmark radar that will estimate in step (three) Target doppler velocity measures and builds statistic:

${\mathrm{\&eta;}}_3\left(k\right)=\frac{\hat{V}\left(k\right)-v\left(k\right)}{{\mathrm{\&sigma;}}_{\hat{V}}^2+{\mathrm{\&sigma;}}_v^2}---\left(8\right)$

Wherein, v (k) is that the doppler velocity of the corresponding potential real goal of k moment benchmark radar measures,For range rate error Variance；

(2) according to constructed statistic, false target based on doppler velocity is differentiated that problem sets up judgement

H₀:Target measures and measures for real goal；

H₁:Target measures and measures for false target；

Wherein,For decision threshold, α is its significance level.

The invention has the beneficial effects as follows:

Contrast existing association discrimination method based on positional information, checking based on doppler velocity described in the technical program Radar fence anti-crowding measure false target jamming profile method, have the beneficial effects that:

1) false target dense degree ensure that the high detectability of true and false target time big.When false target quantity is big, close During collection degree height, the erroneous association rate of association discrimination method based on positional information becomes big, it is impossible to realize the correct of real goal Differentiate；The present invention first passes through Testing Association based on positional information and realizes a part of false target of preliminary rejecting, in terms of reducing Calculation amount, is then carried out doppler velocity and estimates to realize final true and false mesh the potential real goal associated by positional information Mark differentiates.

2) remain to keep the high detectability of true and false target during the change of radar site parameter measurement precision.When radar site parameter When certainty of measurement reduces, the erroneous association rate of association discrimination method based on positional information becomes big, and identification result is deteriorated；The present invention By introducing doppler velocity information, doppler velocity dimension aspect adds a re-association inspection, has been effectively ensured good Identification result.

Accompanying drawing explanation

The method step flow chart of accompanying drawing 1 present invention；

Accompanying drawing 2 is crowding measure false target jamming profile schematic diagram；

Accompanying drawing 3 be false target dense degree detectability correct on real goal affect changing trend diagram；

Accompanying drawing 4 is that radar ranging accuracy change is correct with based on positional information correlating method real goal to the inventive method Detectability affect comparison diagram；

Accompanying drawing 5 is that radar angle measurement accuracy change is correct with based on positional information correlating method real goal to the inventive method Detectability affect comparison diagram.

Detailed description of the invention

Below in conjunction with the accompanying drawings, describing technical scheme in detail, referring to the drawings 1, the concrete steps of the present invention include:

The packet of step (), benchmark radar measurement and data compression；

Radar on the basis of radar 1 in selected radar network, it is assumed that the distance that k moment radar 1 i-th measures is ρ_i(k), side Parallactic angle is θ_iK (), the angle of pitch is ε_iK (), distance, azimuth and the angle of pitch that jth measures are respectively ρ_j(k)、θ_j(k)、ε_j (k).By (9) formula, radar 1 measurement is grouped:

$\begin{array}{c}{\mathrm{\&eta;}}_1\left(k\right)=\frac{{\left({\mathrm{\&theta;}}_i\right(k)-{\mathrm{\&theta;}}_j(k\left)\right)}^2}{2{\mathrm{\&sigma;}}_{\mathrm{\&theta;}}^2}+\frac{{\left({\mathrm{\&epsiv;}}_i\right(k)-{\mathrm{\&epsiv;}}_j(k\left)\right)}^2}{2{\mathrm{\&sigma;}}_{\mathrm{\&epsiv;}}^2}<F_{\mathrm{\&alpha;}}\\ k=1,2,\mathrm{...},N\end{array}---\left(9\right)$

WhereinBeing inspection thresholding, α is its significance level, and n=2 is degree of freedom, σ_θAnd σ_εRepresent radar respectively Azimuth and angle of pitch error in measurement standard deviation；If i and j of radar 1 measures meets (9) formula, then the two is measured and draw Normalizing group, other measurements are tested in this way according to (9) formula and any measurement being divided into a group, if meeting (9) Formula, then incorporate into this measurement in this group, if certain measure with all be grouped measurement be all unsatisfactory for (9) formula, then this measurement is put under One new group, according to this process, until all measurement judges to have divided；

Through measuring packet, azimuth each measurement identical with the angle of pitch is divided into one group；During each is grouped Aim parameter interception angle and the angle of pitch carry out data compression, it is considered to the measurement in each packet is all from same portion radar network, The arithmetic average that measuring after compression measures in being grouped for each, if having N in k moment the l packet_lK () individual measurement, then compress Rear accuracy in measurement improves

Step (two), Testing Association based on adjustment location information；

Set up mahalanobis distance statistic:

η₂(k)=Δ^T(k)(R_2to1(k)+R_l(k))^-1Δ(k) (10)

Then false target differentiates that problem can differentiate by following criterion:

H₀:Target measures as potential real goal；

H₁:Target measures as false target or clutter point；

Wherein, whereinFor decision threshold, α is significance level；Δ (k)=Z_2to1,ENU(k)-Z_l,ENU(k), Z_2to1,ENUK () is other radar network measurement conversions to the coordinates matrix in benchmark radar ENU coordinate system, Z_l,ENUOn the basis of (k) The coordinate of radar the l packet；R_2to1(k) and R_lK () respectively measures Z_2to1,ENU(k) and Z_l,ENUThe measurement covariance square of (k) Battle array；

Step (three), obtaining after potential real goal measures, it is contemplated that differentiating during false target at radar fence Non-linear factor, nonlinear filtering estimation will be carried out by expanded Kalman filtration algorithm；State equation based on positional information For X₁(k+1)=FX₁K ()+V (k), polar coordinate measurement equation is Z₁(k)=h₁(X₁(k))+W₁(k)；Wherein, X₁K () is to dive in the k moment At true target state vector, F is state-transition matrix, and V (k) is process noise matrix, X₁(k+1) it is that the k+1 moment is potential truly Dbjective state vector, Z₁K () is the measurement vector of potential real goal, W₁K () is measurement noise, its covariance matrix is

State equation according to potential real goal and measurement equation must arrive target location and be estimated as: Velocity estimation vector is:Therefore change to benchmark radar target measure relative to base The direction vector of quasi-radar is:

The doppler velocity that potential real goal measures is estimated as estimating speed?Projection on direction, i.e. turns Shift to the potential real goal doppler velocity after benchmark radar be estimated as:

The variance that doppler velocity is estimated isWherein, P is velocity estimation and the association of location estimation in k moment Variance matrix,

Step (four), the potential real goal doppler velocity that estimates in step (three) is estimated corresponding with benchmark radar The doppler velocity of potential real goal measures and builds statistic:

${\mathrm{\&eta;}}_3\left(k\right)=\frac{\hat{V}\left(k\right)-v\left(k\right)}{{\mathrm{\&sigma;}}_{\hat{V}}^2+{\mathrm{\&sigma;}}_v^2}---\left(13\right)$

Wherein, v (k) is that the doppler velocity of the corresponding potential real goal of k moment benchmark radar measures,For range rate error Variance；

False target based on doppler velocity differentiating, problem is set up adjudicate:

H₀:Target measures and measures for real goal；

H₁:Target measures and measures for false target；

Wherein,For decision threshold, α is its significance level；

Step (five), one the new set of composition of the positional information corresponding to measurement will checked by step (four):

Z_{Real, q}(k)={ (ρ_2to1,l,p(k),θ_2to1,l,p(k),ε_2to1,l,p(k)),(ρ_1,l(k),θ_1,l(k),ε_1,l(k))} (14)

Wherein (ρ_2to1,l,p(k),θ_2to1,l,p(k),ε_2to1,l,p(k)) represent that other radar network are changed to benchmark radar Pth target on corresponding benchmark radar the l packet direction measures, (ρ_1,l(k),θ_1,l(k),ε_1,l(k)) represent benchmark radar Real goal on the l packet direction measures；Z_real,qK subscript q of () represents that q-th real goal measures set；To pass through Two measurements after doppler velocity inspection are considered as the same real goal measurement that radar network detects；

Assume to gather Z_real,qK total L measurement in (), then this L measures is considered as that same target measures, for improving The certainty of measurement of radar fence, will gather Z_real,qK the measurement in () carries out based on a fusion treatment for mark synthesis, wherein true mesh Target doppler velocity measures and uses the doppler velocity of benchmark radar to measure v₁(k)；

For set Z_real,qMeasurement vector Z in (k)₁(k)、Z₂(k)、…、Z_L(k), corresponding error in measurement Covariance R₁(k)、R₂(k)、…、R_LK (), obtains new metric data and covariance data after carrying out fusion treatment:

$Z_{fusion}\left(k\right)=R_{fusion}\left(k\right)\underset{i=1}{\overset{L}{\&Sigma;}}{R}_i^{-1}\left(k\right)Z_i\left(k\right)---\left(15\right)$

$R_{fusion}\left(k\right)={\&lsqb;\underset{i=1}{\overset{L}{\&Sigma;}}{R}_i^{-1}\left(k\right)\&rsqb;}^{-1}---\left(16\right)$

Real goal after merging measures Z_fusion(k)=[ρ_fusion(k) θ_fusion(k) ε_fusion(k) v₁(k)]^TMake For measuring input, expanded Kalman filtration algorithm is utilized to realize the tenacious tracking of real goal.

The effect of the present invention can be further illustrated by following matlab emulation experiment:

Emulation experiment scene setting

Assuming to possess radar on the basis of the radar 1 of speed measuring function, its geographical coordinate is north latitude 37.0 °, east longitude 120 °, highly 100m, the geographical coordinate of radar 2 is north latitude 37.5 °, east longitude 120 °, highly 300m.The range accuracy of two radars is 100m, Azimuth, pitch angle measurement precision are 0.1 °, and doppler velocity certainty of measurement is 1m/s, and the sampling period is 1s；Truly Target original position is north latitude 37.3 °, east longitude 121.3 °, highly 10000m, the fortune on tri-directions of E, N, U of relative radar 1 Dynamic speed is respectively 340m/s ,-200m/s ,-25m/s；Radar fence is to target Continuous Observation 200s, and target detection probability is 1.

Assuming the self-contained jamming equipment of real goal, jamming equipment, by capturing the signal of radar network, is carried out simultaneously Replicating, modulate and forward, it is possible to implement effective crowding measure false target deceptive jamming, jammer produces false target in modulation During, false target doppler information moves state and the phenomenon of " not mating " occurs, this phenomenon produce many General Le velocity deviation is set to 10m/s；In interfering process, jamming equipment produces a void in real goal both sides at interval of 1300m Decoy, every side produces 10, totally 20 false targets.Monte Carlo simulation number of times is 500 times.

Simulation result and analysis: in the case of other simulated conditions are constant, change false target dense degree, by accompanying drawing 3 it can be seen that along with distance constantly increases to the dense degree of false target, is based only upon discrimination method correct of positional information There is the trend declined to a great extent in discrimination, and the inventive method remains higher correct recognition rata.Analyze its reason to understand, When false target dense degree is less, it is spaced relatively big, between distance multi-false targets between radar network aim parameter measuring point mutually The probability being successfully associated improves therewith, therefore can effectively identify real goal and false mesh based on the positional information method of inspection Mark；And false target dense degree is when being gradually increased, the interval between distance multi-false targets diminishes therewith so that radar network mesh The probability associated that makes a mistake between scalar measuring point is greatly increased, and is based only upon positional information and would become hard to distinguish true and false aim parameter Survey, therefore cause correct recognition rata to be greatly reduced；And the inventive method is on the basis of target position information, by the thunder that will test the speed The target Doppler velocity information reached and the doppler velocity estimated based on positional information carry out making poor, structure inspected number Carry out statistical decision, by making screening further based on the multipair measurement combination existed after positional information Testing Association, finally real The differentiation of existing true and false target, thereby ensures that the real goal discrimination in the case of distance multi-false targets dense degree is relatively big. In the case of other simulated conditions are constant, change radar network range accuracy and angle measurement accuracy respectively, by accompanying drawing 4 and accompanying drawing 5 It can be seen that when false target dense degree is bigger, the inventive method still is able to keep higher correct recognition rata, and based on The discrimination of positional information correlating method is significantly lower than context of methods.Analyze its reason understand, when false target dense degree relatively Time big, only by effective discriminating of the positional information true and false target the most relatively difficult to achieve of target, and the inventive method is in target position Introduce doppler velocity information on the basis of confidence breath, make target measure and add new quantity of information, from there through bound site Confidence has ceased with doppler velocity information assurance identification result.

Claims (3)

1. radar fence anti-crowding measure false target jamming profile method based on doppler velocity inspection, it is characterised in that include following Step:

Step (one), selected reference radar, and carry out being grouped and data compression by benchmark radar measurement；

Step (two), based on aim parameter survey positional information build mahalanobis distance statistic, carry out true and false target by X 2 test Differentiate, reject the measurement of incoherent false target with preliminary, reduce amount of calculation simultaneously, will be considered as diving by the target of Testing Association At real goal；

Step (three), the estimation for target Doppler speed will be measured by the target of step (two) Testing Association, be dived Doppler velocity at real goal is estimated；

Step (four), the potential real goal doppler velocity estimated value that step (three) is obtained and benchmark radar doppler velocity It is poor that measurement is carried out, and constructs statistic of test, is realized the final discriminating of real goal by X 2 test；

Step (five), the real goal of each radar network checked by step (four) is measured carry out fusion treatment, and will melt Target after conjunction measures as measuring input, is filtered by Kalman filtering algorithm and estimates, finally realizing real goal Tenacious tracking.

Radar fence anti-crowding measure false target jamming profile method based on doppler velocity inspection the most according to claim 1, It is characterized in that, step (three) specifically includes following sub-step:

(1) obtaining after potential real goal measures, it is contemplated that non-linear differentiate during false target at radar fence Factor, will carry out nonlinear filtering estimation by expanded Kalman filtration algorithm；State equation based on positional information is X₁(k+ 1)=FX₁K ()+V (k), polar coordinate measurement equation is Z₁(k)=h₁(X₁(k))+W₁(k)；Wherein, X₁K () is that the k moment is potential very Real dbjective state vector, F is state-transition matrix, and V (k) is process noise matrix, X₁(k+1) it is k+1 moment potential true mesh Mark state vector, Z₁K () is the measurement vector of potential real goal, h₁(X₁(k)) be

W₁K () is measurement noise, its covariance matrix is

(2) target location must be arrived according to the state equation of potential real goal with measurement equation to be estimated as Velocity estimation vector isTherefore change to benchmark radar target measure relative to base The direction vector of quasi-radar is:

(3) doppler velocity that potential real goal measures is estimated as estimating speed?Projection on direction, i.e. changes Potential real goal doppler velocity to benchmark radar is estimated as

The variance that doppler velocity is estimated isWherein, P is velocity estimation and the covariance of location estimation in k moment Battle array,

Radar fence anti-crowding measure false target jamming profile method based on doppler velocity inspection the most according to claim 1, It is characterized in that, step (four) specifically includes following sub-step:

(1) by the potential real goal doppler velocity potential real goal corresponding with benchmark radar that estimate in step (three) Doppler velocity measures and builds statistic:

${\mathrm{\&eta;}}_3\left(k\right)=\frac{\hat{V}\left(k\right)-v\left(k\right)}{{\mathrm{\&sigma;}}_{\hat{V}}^2+{\mathrm{\&sigma;}}_v^2}$

Wherein, v (k) is that the doppler velocity of the corresponding potential real goal of k moment benchmark radar measures,For range rate error variance；

(2) according to constructed statistic, false target based on doppler velocity is differentiated, and problem is set up and adjudicates:

H₀:Target measures and measures for real goal；

H₁:Target measures and measures for false target；

Wherein,For decision threshold, α is its significance level.