CN104502907B - A kind of airborne radar ground sound target tenacious tracking method - Google Patents

Abstract

The present invention relates to a kind of airborne radar ground sound target tenacious tracking method, according to dynamic and static target characteristic, use transmitting nonlinear frequency modulation and stepped frequency signal simultaneously respectively dynamic and static target to be detected.NLFM signal is mainly for detection of moving-target, and stepped frequency signal is mainly for detection of quiet target.A scanning frame at radar can obtain the once some mark of ground moving target and quiet target simultaneously.Compared with traditional method, the present invention can pay close attention to ground moving target and quiet target, the corresponsively overall situation of Area Objects simultaneously, when target is by moving quiet or can persistently be followed the tracks of to time dynamic by quiet, it is ensured that the continuous-stable of the dynamic and static target in ground is followed the tracks of.

Description

A kind of airborne radar ground sound target tenacious tracking method

Technical field

Belong to the present invention Area Objects data processing method, be under the jurisdiction of Radar Signal Detection and technical field of data processing, It is specifically related to a kind of airborne radar ground sound target tenacious tracking method.

Background technology

There is notable difference in airborne radar multiple target tracking over the ground compared with tradition air search radar, technical difficulty is big.First, There is relative motion between airborne radar platform and target, target following is not only relevant with the kinestate of target, but also Relevant with the kinestate of carrier aircraft self；Secondly as following the tracks of target is ground target, there is the stronger land clutter back of the body Scape, makes detections of radar target difficult；Finally, due to ground static target and moving target, maneuvering target and non-maneuver Target exists simultaneously, makes target tenacious tracking difficulty dramatically increase.

(1) target travel environment: aerial target is moved at three dimensions, and ground target generally can equivalence in little scope For two dimensional motion, and, for the target of motion on road, motion in one dimension can be equivalent in certain stage, until meeting To road junction, now its direction of motion is it may happen that change.Additionally the moving region of Area Objects would generally be subject to More restriction, the most severe orographic condition makes target to pass through.Although aerial target also can run into massif etc. Stop, but its suffered external environment condition limits far less than ground target.

(2) target travel characteristic: aerial target, in addition to helicopter and dirigible, is all limited by minimum speed, is less than The target of this restriction will be unable to run well, and ground target then can accelerate, slows down, totally stationary or at one section Keep kinestate constant in time.Therefore the transmutability aerial target to be far above of ground target motion.

(3) heavy dense targets degree: unless some special circumstances, usual aerial target can keep certain safe distance.And ground Between Area Objects, can with the nearest distance motion, time static can also one connect a ground and park, therefore ground The closeness of target is far above aerial target.

(4) sensor detection probability: due to terrain shading, sensor possibly cannot observe ground target, additionally ground There is minimum detection radial velocity (MDV), when target is static or moves with relatively low velocity in moving-target instruction (GMTI) Sensor cannot detect, and therefore the detection of sensor is probably discontinuous.

(5) clutter: ground target is moved in the environment that clutter is the most serious, the clutter recognition used at present processes also nothing Method reaches close to preferable inhibition, and the reduction and false-alarm number purpose that cause detection probability are increased by the existence of clutter.

Airborne radar, when detecting on a surface target, needs to pay close attention to ground moving target and quiet target simultaneously.Traditional data Processing method is subject to processing level and technical conditions limit, and generally moving-target and quiet target is separately processed, and the method can not The most overall situation of Area Objects fully, especially when target by move quiet or by quiet to dynamic moving time, mesh can be caused Mark is lost.

Along with microelectric technique develops, chip processing capabilities improves constantly, and double-core, the continuous of multi-core CPU occur and answer With, limit the hardware bottleneck disappearance that multiple batches of ground target processes, develop a kind of ground sound target data processing method, Ensure that the dynamic and static in stable condition tracking of ground target is possibly realized.

Summary of the invention

In place of the deficiencies in the prior art, the present invention proposes a kind of airborne radar ground sound target tenacious tracking Method

A kind of airborne radar ground sound target tenacious tracking method, it is characterised in that step is as follows:

Step 1: radar emission NLFM signal is used for detecting moving-target, launches stepped frequency signal and detects quiet target, A scanning frame at radar obtains the once some mark of ground moving target and quiet target simultaneously；

Step 2: the once some mark carrying out moving-target and quiet target respectively carries out secondary lobe and weighting agglomeration process；

Step 3: use track initiation method based on two-stage Hough transform to be built respectively by dynamic and quiet target congealing point Vertical respective alternative flight path；Alternative for former frame flight path is carried out motion compensation, compensates present frame carrier aircraft position；

Step 4: the position of prediction present frame flight path: $\hat{K}(k/k-1)=F\hat{X}(k-1/k-1),$ Wherein: $F=\left[\begin{array}{ccc}1& T& T^2/2\\ 0& 1& T\\ 0& 0& 1\end{array}\right],$ $X={\left[\begin{array}{ccc}x& \stackrel{\·}{x}& \stackrel{\·\·}{x}\end{array}\right]}^T,$ WithRespectively represent present frame flight path position, speed and Component of acceleration；

Step 5: repeat step 1～step 2, obtains the congealing point of next some mark；

Step 6: centered by the predicted position of flight path, is associated the metric data and flight path that fall into Bo Mennei, To correlation combiner；

If metric data does not falls within the Bo Mennei of any one flight path, set up a new flight path with these data；

If there is no observation station at the Bo Mennei of flight path, in two kinds of situation:

Situation 1: when moving-target flight path is the most uncorrelated with all moving-target congealing points, then carries out two hypothesis tracking, obtain Correlation combiner；

Assume 1: target is undetected, then flight path is extrapolated according to the characteristics of motion before；

Assume 2: target is static, then carry out between moving-target flight path to quiet target congealing point is relevant, if having relevant Point, then carry out flight path renewal with it, and without reference point, then the position keeping flight path original is motionless, and speed is zero；

Situation 2: when quiet targetpath is the most uncorrelated with all quiet target congealing points, then carry out two hypothesis tracking；

Assume 1: target is undetected, then the position keeping flight path original is motionless, and speed is zero, and target is the most static；

Assume 2: target transfers motion to, then carry out between quiet targetpath to moving-target congealing point is relevant, if had Reference point, then carry out flight path renewal with it, and estimates the speed of flight path, without reference point, then keeps flight path former The position come is motionless, waits the relevant of next frame, obtains correlation combiner；

The correlation combiner of all moving-target flight paths and quiet targetpath is participated in computing according to the following formula, finds an overall generation The optimum allocation that valency is minimum, carries out the final updated of flight path with it；

a^*(k)=arg min_a(k)C(k|a(k))

Wherein:

$C\left(k\right|a\left(k\right))={\mathrm{\Σ}}_{m=0_1,0_2,1}^{M\left(k\right)}{\mathrm{\Σ}}_{n=1}^{N(k-1)}\mathrm{\α}(k,m,n)c(k,m,n)$

Wherein:

C (k, m, n) be distribution a (k, m, cost value n): $c(k,m,n)=-\ln \left(\frac{\mathrm{\Φ}(k,m,n)}{\mathrm{\Φ}(k,m,0)}\right)$

When situation 1: Φ (k, m, n) be calculated as follows:

$\mathrm{\&Phi;}(k,m,n)=\left\{\begin{array}{cc}{P}_{D}P\left\{\right|v_r\left(k\right)|\&GreaterEqual;v_0\}\mathrm{\&Lambda;}(k,m,n)& m>0,n>0\\ \mathrm{\&lambda;}& m>0,n=0\\ (1-P_D)P\left\{\right|v_r\left(k\right)|\&GreaterEqual;v_0\}\mathrm{\&lambda;}& m=0_1,n>0\\ P\left\{\right|v_r\left(k\right)|<v_0\}\mathrm{\&lambda;}& m=0_2,n>0\end{array}\right.$

Wherein: m ＞ 0, n ＞ 0 is relevant to flight path for measuring；M ＞ 0, n=0 are for measuring and already present flight path not phase Close, for false-alarm；M=0₁, n ＞ 0 is relevant to flight path for assuming measurement 1；M=0₂, n ＞ 0 for assume to measure 2 with Flight path is correlated with；

Λ (k, m, n) be Interactive Multiple-Model estimate combined probability, v₀It is Minimum detectable, vr₍K) it is that kth is swept Retouch the radial velocity of frame (if kth scanning frame does not has measured value, vr₍K) it is to be recorded in advance by-1 scanning frame of kth Come).Assume speed Gaussian distributed, then can calculate P{ | v_r(k)|≥v₀And P{ | v_r(k) | ＜ v₀}；

The spatial density λ of false-alarm is

Wherein P_FABeing false-alarm probability, distance, orientation, the certainty of measurement of distance speed three-dimensional are respectively With

When situation 2, Φ (k, m, n) be calculated as follows:

$\mathrm{\&Phi;}(k,m,n)=\left\{\begin{array}{cc}{P}_{D}P\left\{\right|v_r\left(k\right)|=\&GreaterEqual;v_0\}\mathrm{\&Lambda;}(k,m,n)& m>0,n>0\\ \mathrm{\&lambda;}& m>0,n=0\\ (1-P_D)P\left\{\right|v_r\left(k\right)|=0\&GreaterEqual;\}\mathrm{\&lambda;}& m=0_1,n>0\\ P\left\{\right|v_r\left(k\right)|!=0\}\mathrm{\&lambda;}& m=0_2,n>0\end{array}\right.$

Situation 2 needs to calculate P{ | v_r(k) |=0} and P{ | v_r(k)|！=0}；

Described ripple door includes range gate, orientation Bo Men, pitching ripple door and Doppler's ripple door；

Step 7, filtering: according to the filtering method of alpha-beta-γ, flight path is filtered

$\hat{X}(k/k)=\hat{X}(k/k-1)+K[y\left(k\right)-H\hat{X}(k/k-1)]$

$\hat{X}(k/k-1)=F\hat{X}(k-1/k-1)$

Wherein gain matrix $K=\left[\begin{array}{c}\mathrm{\&alpha;}\\ \mathrm{\&beta;}/T\\ \mathrm{\&gamma;}/T^2\end{array}\right],$ Observing matrix H=[1 0 0]；

Step 8, flight path manage: when a flight path repeatedly do not have observation station cause repeatedly extrapolate time, by flight path delete； Repeat step 1～step 8, carry out sound target tenacious tracking.

Described range gate 20～50m.

Described orientation ripple door 1.5～2.5 degree.

Described pitching ripple door 2～4 degree.

Described Doppler's ripple door 3～6.

A kind of airborne radar ground sound target tenacious tracking method that the present invention proposes, according to dynamic and static target characteristic, Transmitting nonlinear frequency modulation and stepped frequency signal simultaneously is used respectively dynamic and static target to be detected.NLFM signal Mainly for detection of moving-target, stepped frequency signal is mainly for detection of quiet target.A scanning frame at radar can be same Time obtain the once some mark of ground moving target and quiet target.

Compared with traditional method, the present invention can pay close attention to ground moving target and quiet target simultaneously, corresponsively Area Objects Overall situation, when target is by moving quiet or can persistently be followed the tracks of to time dynamic by quiet, it is ensured that the dynamic and static target in ground continuous surely Fixed tracking.

Accompanying drawing explanation

Fig. 1: for static-dynamic-dynamic rate curve moved of target

Fig. 2: for static-dynamic-dynamic geometric locus moved of target, square frame is the position that target is static

Fig. 3: for the rate curve of target stationary-mobile-quiet motion

Fig. 4: for the geometric locus of target stationary-mobile-quiet motion, square frame is the position that target is static

Fig. 5: for the relation schematic diagram of carrier aircraft NED with carrier aircraft LOS coordinate system

Fig. 6: be the related procedure of two hypothesis tracking

Detailed description of the invention

In conjunction with embodiment, accompanying drawing, the invention will be further described:

Radar data processes, and is primarily directed to aerial target and naval target, and ground target mobility strong, clutter Interference is big, the influence factor such as target occlusion is more in targeted species scope many, same, to the detection of target, merger, Cohesion, build boat and be proposed higher requirement.Need on the basis of conventional radar data processing method, for ground Target characteristic, proposes one and is suitable for strong maneuvering target, and can method to sound target tenacious tracking simultaneously.The most right Fig. 1～Fig. 4 tetra-width figure, target is quiet again to dynamic by moving, or target by quiet to moving again to quiet, can tenacious tracking.

According to dynamic and static target characteristic, use and launch nonlinear frequency modulation and stepped frequency signal respectively to dynamic and static target simultaneously Detect.NLFM signal is mainly for detection of moving-target, and stepped frequency signal is mainly for detection of quiet target. A scanning frame at radar can obtain the once some mark of ground moving target and quiet target simultaneously.

1) two assume tracking

Two assume that the basic ideas of tracking are, when a target is when this frame is without observation station, assume to divide according to two kinds Cheng Liangge branch, finally finds one group of optimum allocation to carry out more fresh target in the most relevant distribution.

Situation one:

When a moving target does not detect at a certain frame, having two kinds of probabilities, one is due to environment or detection door The setting of limit, causes target undetected, and another kind is owing to target velocity is too small, less than Minimum detectable, Cannot be by moving-target detection detection, target occurs in quiet target detection.

Situation two:

When a static target does not detect at a certain frame, having two kinds of probabilities, one is due to environment or detection door The setting of limit, causes target undetected, and another kind is owing to target transfers motion to, the position before have left, mesh Mark in the detection of present moving-target.

For both the above situation, two hypothesis trackings can be used.

A) target travel and measurement model

t_kThe state value of moment target is

$X\left(t_k\right)=\left[\begin{array}{c}x\left(t_k\right)\\ \stackrel{\&CenterDot;}{x}\left(t_k\right)\\ y\left(t_k\right)\\ \stackrel{\&CenterDot;}{y}\left(t_k\right)\end{array}\right]---\left(1\right)$

Wherein x (t_k) and y (t_k) be respectively cartesian coordinate system x, the position of y-axis,WithIt is respectively x, y The speed of axle.

The state model of target is

X(t_k)=F (t_k)X(t_k-1)+Γ(t_k)v(t_k-1) (2)

Wherein F is state-transition matrix, and Γ is excitation matrix, v (t_k-1) it is process noise.

t_kMoment measures vector and comprises distance, azimuth-range speed i.e. doppler information.

$Z\left(t_k\right)=\left[\begin{array}{c}r\left(t_k\right)\\ \mathrm{\&theta;}\left(t_k\right)\\ \stackrel{\&CenterDot;}{r}\left(t_k\right)\end{array}\right]+W\left(t_k\right)---\left(3\right)$

Wherein W (t_k) it is to measure noise vector.

B) principle of two hypothesis trackings

Two assume that the subject matter that tracking is to be solved is, measured value M (k) of kth frame and the flight path of kth-1 frame The optimum attaching problem of T (k-1).It is minimum that optimum is exactly the overall associated costs realizing measuring between flight path.

Define binary system distribution variable a (k, m, n),

The complete or collected works making a (k) be distribution, then

$a\left(k\right)=\left\{\begin{array}{c}\mathrm{\&alpha;}(k,m,n):m=0_1,0_2,\mathrm{1,2},...,M\left(k\right);\\ n=\mathrm{0,1},...,N(k-1)\end{array}\right\}---\left(5\right)$

Wherein M (k) is the sum of sound target detection measured value, and N (k-1) is the number of flight path.

Comprise the first assume measure distribution a (k, 0₁, n) represent owing to being not detected by, flight path T_nK () surveys with any one Amount M (k) is the most uncorrelated.

Comprise the second assume measure distribution a (k, 0₂, n), represent owing to target is static or radial velocity is little in situation one Flight path T is caused in Minimum detectable_nK () measures the most uncorrelated with any one moving-target in M (k)；At situation two table Show and cause flight path T owing to target travel have left original position_nK in () and M (k), any one quiet target measurement is the most not Relevant.

Distribution a (k, m, 0) represents that measurement m is the most uncorrelated (assuming that it is a false-alarm with any one already present flight path Point).

Our purpose is to find an optimum allocation a^*K (), it can make overall situation associated costs minimum, i.e.

a^*(k)=arg min_a(k)C(k|a(k)) (6)

Wherein

$C\left(k\right|a\left(k\right))={\mathrm{\&Sigma;}}_{m=0_1,0_2,1}^{M\left(k\right)}{\mathrm{\&Sigma;}}_{n=1}^{N(k-1)}\mathrm{\&alpha;}(k,m,n)c(k,m,n)---\left(7\right)$

Wherein (k, m n) are distribution a (k, m, cost value n) to c.

$c(k,m,n)=-\ln \left(\frac{\mathrm{\&Phi;}(k,m,n)}{\mathrm{\&Phi;}(k,m,0)}\right)---\left(8\right)$

Situation one:

$\mathrm{\&Phi;}(k,m,n)=\left\{\begin{array}{cc}{P}_{D}P\left\{\right|v_r\left(k\right)|\&GreaterEqual;v_0\}\mathrm{\&Lambda;}(k,m,n)& m>0,n>0\\ \mathrm{\&lambda;}& m>0,n=0\\ (1-P_D)P\left\{\right|v_r\left(k\right)|\&GreaterEqual;v_0\}\mathrm{\&lambda;}& m=0_1,n>0\\ P\left\{\right|v_r\left(k\right)|<v_0\}\mathrm{\&lambda;}& m=0_2,n>0\end{array}\right.---\left(9\right)$

Wherein m ＞ 0, n ＞ 0 is relevant to flight path for measuring；M ＞ 0, n=0 are uncorrelated with already present flight path for measuring, I.e. false-alarm；M=0₁, n ＞ 0 is relevant to flight path (due to P for assuming measurement 1_D＜ 1)；M=0₂, n ＞ 0 is for assuming Measure 2 relevant to flight path (owing to Minimum detectable limits).

Λ (k, m, n) be Interactive Multiple-Model estimate combined probability, v₀It is Minimum detectable, v_rK () is that kth is swept Retouch the radial velocity of frame (if kth scanning frame does not has measured value, v_rK () is to be recorded in advance by-1 scanning frame of kth Come).Assume speed Gaussian distributed, then can calculate P{ | v_r(k)|≥v₀And P{ | v_r(k) | ＜ v₀}。

The spatial density λ of false-alarm is

$\mathrm{\&lambda;}=\frac{P_{\mathrm{FA}}}{{12}^{3/2}{\mathrm{\&sigma;}}_r{\mathrm{r\&sigma;}}_{\mathrm{\&theta;}}{\mathrm{\&sigma;}}_{\stackrel{\&CenterDot;}{r}}}---\left(10\right)$

Wherein P_FABeing false-alarm probability, distance, orientation, the certainty of measurement of distance speed three-dimensional are respectively With

Situation two:

$\mathrm{\&Phi;}(k,m,n)=\left\{\begin{array}{cc}{P}_{D}P\left\{\right|v_r\left(k\right)|=\&GreaterEqual;v_0\}\mathrm{\&Lambda;}(k,m,n)& m>0,n>0\\ \mathrm{\&lambda;}& m>0,n=0\\ (1-P_D)P\left\{\right|v_r\left(k\right)|=0\&GreaterEqual;\}\mathrm{\&lambda;}& m=0_1,n>0\\ P\left\{\right|v_r\left(k\right)|!=0\}\mathrm{\&lambda;}& m=0_2,n>0\end{array}\right.---\left(11\right)$

Situation two needs to calculate P{ | v_r(k) |=0} and P{ | v_r(k)|！=0}.

C) two assume the restrictive condition followed the tracks of

A () confirms.One measurement is only possible to relevant to a flight path, and must is fulfilled for

${[Z_m\left(t_k\right)-{\hat{Z}}_m\left(t_k\right)]}^{\&prime;}{S}_m{\left(t_k\right)}^{-1}[Z_m\left(t_k\right)-{\hat{Z}}_m\left(t_k\right)]\&le;\mathrm{\&gamma;}---\left(12\right)$

γ is to confirm thresholding,It is prediction measured value, S_m(t_k) it is covariance.

(b) man-to-man restriction.One flight path is the most relevant to a measurement, and assumes that flight path can be with the most Individual measurement is correlated with.Measure for one and at most distribute to a flight path, and assume to measure (m=0₁Or m=0₂) can divide The multiple flight path of dispensing.

C () non-NULL is correlated with.Assume that measurement can not be distributed to assume flight path.

D) state updates

Situation one:

Assume not measure in kth frame to update flight path, then obtain the state of flight path from the prediction of k-1 frame to k frameWith covariance P (k | k-1).Radial velocity obeys averageVariance is P_r(k | k-1) Gauss distribution.If flight path is relevant to assuming measurement 1 (being not detected by), then the state estimation of target current time It it is the predictive value of previous scanning frame.If flight path is relevant to assuming measurement 2 (Minimum detectable restriction), then The position of target remains stationary as, and speed is zero.

Situation two:

Assuming not measure in kth frame to update flight path, the most no matter flight path is relevant to assuming measurement 1 (being not detected by), Or relevant to assuming measurement 2 (target transfers motion to), the position all keeping target is motionless, and speed is zero.

Detailed description of the invention:

1) launch nonlinear frequency modulation and stepped frequency signal simultaneously, obtain the once some mark of ground moving target and quiet target；

2) target agglomeration process

Carry out moving-target respectively and agglomeration process that quiet target is once put, all include secondary lobe and weighting cohesion two steps.

● remove secondary lobe

First delimit a distance and the scope of speed, the line amplitude that clicks in the range of this compared, amplitude difference Excessive point is considered secondary lobe, is deleted.

$\frac{F\left(i\right)}{F\left(j\right)}>D---\left(13\right)$

● amplitude weighting

Owing to radar beam is when scanning continuously, wave beam lobe has one fixed width, and at least several pulses are swept continuously To target, the corresponding orientation values of each pulse, same target is caught in repeatedly, repeatedly during capture target Orientation values is the most different, and it is bigger that this has resulted in azimuthal splitting degree.It is thus desirable to mesh same in single pass The multiple Plot coherence of target becomes a some mark.

To delimit some M altogether at distance, orientation, pitching and Doppler four-dimension Bo Mennei, the amplitude of carrying out adds simultaneously Power.

The distance of the jth congealing point of the i-th frame is:

$r_i\left(j\right)=\frac{{\mathrm{\&Sigma;}}_{k=0}^{M}r\left(k\right)*F\left(k\right)}{{\mathrm{\&Sigma;}}_{k=0}^{M}F\left(k\right)}---\left(14\right)$

Wherein, M is once counting of four-dimensional Bo Mennei, and r (k) is the distance that kth is once put, and F (k) is kth once point Amplitude, r_iJ () is the distance of the jth congealing point of the i-th frame.

3) boat is built

The congealing point of dynamic and static target is set up alternative flight path；Use track initiation method based on two-stage Hough transform.

● choose displacement time as parameter, twice adjacent measurement done such as down conversion:

$\begin{array}{c}{\mathrm{\&Delta;}}_{\mathrm{\&rho;i}}\left[{\mathrm{\&theta;}}_n\right]={\mathrm{\&rho;}}_{i+1}\left[{\mathrm{\&theta;}}_n\right]-{\mathrm{\&rho;}}_i\left[{\mathrm{\&theta;}}_n\right]=(x_{i+1}-x_i){\cos \mathrm{\&theta;}}_n\\ +k(t_{i+1}-t_i)\sin {\mathrm{\&theta;}}_n\end{array}---\left(15\right)$

Wherein

${\mathrm{\&theta;}}_n=(n-\frac{1}{2}-\frac{N_{\mathrm{\&theta;}}}{2})\mathrm{\&pi;}/N_{\mathrm{\&theta;}},(n=\mathrm{1,2},...,N_{\mathrm{\&theta;}})---\left(16\right)$

N in formula_θSegmentation hop count for parameter θ.

K=(v_max+α_maxT)/12 is proportionality coefficient, v_maxAnd α_maxIt is respectively the maximal rate and the most greatly of target Speed, T is the sampling period.

Find θ_n=θ₀, (n=1,2 ..., N_θ) so that Δ ρ_i[θ_n]=0.

● first order Hough transform

First to x_iAnd y_iDo Hough transform based on kinestate.

If flight path meetsWithThen think that this flight path may be for reliable boat Mark, if be unsatisfactory for, then this flight path is false track, directly deletes from alternative flight path.

● second level Hough transform

Due at more than 1km, oblique distance r_iWith time t_iThe most linear, therefore can be to oblique distance r_iDo based on fortune The Hough transform of dynamic state, if flight path meetsThen this flight path can be initiateed.

4), when next frame once puts mark arrival, the cohesion of dynamic and static target is carried out the most respectively；

5) alternative for former frame flight path is carried out motion compensation, compensate present frame carrier aircraft position；

The history point mark of flight path includes two steps (with reference to Fig. 5) to the carrier aircraft NED down conversion of this frame: (1) oblique distance compensates: Oblique distance should compensate according to displacement rather than distance.It is true that need the displacement compensated should be carrier aircraft two frames it Between air line distance between corresponding moment NED coordinate system (for treating compensation point mark) initial point, according still further to sine Calculating the oblique distance of target under current carrier aircraft NED, this computing is also obtained the azimuth deviation introduced by carrier aircraft displacement.Real On border, this displacement calculating means is, by all previous move distance of all inertial guidance data between two frame initial times to this displacement to (being determined by the yaw angle of two frame initial times) projects and sues for peace in amount direction.(2) orientation compensates: need to enter in two steps OK, the orientation values of some mark is firstly the need of (for treating compensation point mark, being phase by driftage declinate filtered between two frames The yaw angle difference of adjacent frame corresponding moment NED) deduct, its secondary azimuth deviation carrier aircraft displacement introduced compensates.

6) prediction

The characteristics of motion according to flight path, it was predicted that the position of present frame flight path；

$\hat{X}(k*k-1)=F\hat{X}(k-1/k-1)---\left(17\right)$

Wherein $F=\left[\begin{array}{ccc}1& T& T^2/2\\ 0& 1& T\\ 0& 0& 1\end{array}\right],$ $X={\left[\begin{array}{ccc}x& \stackrel{\&CenterDot;}{x}& \stackrel{\&CenterDot;\&CenterDot;}{x}\end{array}\right]}^T,$ Here,WithRepresent position respectively, speed and adding Velocity component.

7) relevant

Centered by the predicted position of flight path, setpoint distance, orientation, pitching and Doppler relevant ripple door, ripple will be fallen into Metric data and flight path in Men are associated, and this metric data is probably the new observation of this flight path correspondence target, it is possible to Can be false-alarm, it is also possible to be the initial of a fresh target, finally determining of these problems obtains more observation by the time Carry out again after data.If metric data does not falls within the Bo Mennei of any one flight path, then these data directly produce one Individual new flight path.If there is no observation station at the Bo Mennei of flight path, then carry out course extrapolation.

When moving-target flight path is the most uncorrelated with all moving-target congealing points, then carry out two hypothesis tracking.Assume a target not It is detected, then flight path is extrapolated according to the characteristics of motion before；Assume that two targets are static, then carry out moving-target boat Relevant between mark to quiet target congealing point, if there being reference point, then carries out flight path renewal with it, without relevant Point, then the position keeping flight path original is motionless, and speed is zero.

When quiet targetpath is the most uncorrelated with all quiet target congealing points, then carry out two hypothesis tracking.Assume a target not Be detected, then the position keeping flight path original is motionless, and speed is zero, and target is the most static；Assume that two targets transfer fortune to Dynamic, then carry out between quiet targetpath to moving-target congealing point is relevant, if there being reference point, then carries out flight path with it Updating, and estimate the speed of flight path, without reference point, then the position keeping flight path original is motionless, waits next Being correlated with of frame.

The correlation combiner of all moving-target flight paths and quiet targetpath is participated in computing, finds an overall situation according to formula 6 The optimum allocation of Least-cost, carries out the final updated of flight path with it.

8) filtering

According to alpha-beta-γ filtering method, flight path is filtered.

$\hat{X}(k/k)=\hat{X}(k/k-1)+K[y\left(k\right)-H\hat{X}(k/k-1)]---\left(18\right)$

$\hat{X}(k/k-1)=F\hat{X}(k-1/k-1)---\left(19\right)$

Wherein gain matrix $K=\left[\begin{array}{c}\mathrm{\&alpha;}\\ \mathrm{\&beta;}/T\\ \mathrm{\&gamma;}/T^2\end{array}\right],$ Observing matrix H=[1 0 0].

9) flight path management

When a flight path does not repeatedly have observation station repeatedly to extrapolate, flight path is deleted.

10) flight path is newly-built

The point mark shut mutually, sets up new alternative flight path.

11) 4 are repeated)～10).

Claims (5)

1. an airborne radar ground sound target tenacious tracking method, it is characterised in that step is as follows:

Step 1: radar emission NLFM signal is used for detecting moving-target, launches stepped frequency signal and detects quiet target, and a scanning frame at radar obtains the once some mark of ground moving target and quiet target simultaneously；

Step 2: the once some mark carrying out moving-target and quiet target respectively carries out secondary lobe and weighting agglomeration process；

Step 3: use track initiation method based on two-stage Hough transform that dynamic and quiet target congealing point is set up respective alternative flight path respectively；Alternative for former frame flight path is carried out motion compensation, compensates present frame carrier aircraft position；

Step 4: the position of prediction present frame flight path:Wherein:x、WithRepresenting the position of present frame flight path respectively, speed and component of acceleration, T is the sampling period；

Step 5: repeat step 1～step 2, obtains the congealing point of next some mark；

Step 6: centered by the predicted position of flight path, is associated the metric data and flight path that fall into Bo Mennei, obtains correlation combiner；

If metric data does not falls within the Bo Mennei of any one flight path, set up a new flight path with these data；

If there is no observation station at the Bo Mennei of flight path, in two kinds of situation:

Situation 1: when moving-target flight path is the most uncorrelated with all moving-target congealing points, then carries out two hypothesis tracking, obtain correlation combiner；

Assume 1: target is undetected, then flight path is extrapolated according to the characteristics of motion before；

Assume 2: target is static, then carry out between moving-target flight path to quiet target congealing point is relevant, if there being reference point, then carries out flight path renewal with it, and without reference point, then the position keeping flight path original is motionless, and speed is zero；

Situation 2: when quiet targetpath is the most uncorrelated with all quiet target congealing points, then carry out two hypothesis tracking；

Assume 1: target is undetected, then the position keeping flight path original is motionless, and speed is zero, and target is the most static；

Assume 2: target transfers motion to, then carry out between quiet targetpath to moving-target congealing point is relevant, if there being reference point, then carry out flight path renewal with it, and estimate the speed of flight path, without reference point, then the position keeping flight path original is motionless, wait the relevant of next frame, obtain correlation combiner；

The correlation combiner of all moving-target flight paths and quiet targetpath is participated in computing according to the following formula, finds the optimum allocation of an overall Least-cost, carry out the final updated of flight path with it；

a^*(k)=arg min_a(k)C(k|a(k))

Wherein:

Wherein:

C (k, m, n) be distribution a (k, m, cost value n):

A (k) is the complete or collected works of distribution, and a (k, m, be n) that binary system distributes variable, and M (k) is the sum of sound target detection measured value, and N (k-1) is the number of flight path, 0₁、0₂For sound target detection measured value；

When situation 1: Ф (k, m, n) be calculated as follows:

Wherein: m ＞ 0, n ＞ 0 is relevant to flight path for measuring；M ＞ 0, n=0 are uncorrelated with already present flight path, for false-alarm for measuring；M=0₁, n ＞ 0 is relevant to flight path for assuming measurement 1；M=0₂, n ＞ 0 is relevant to flight path for assuming measurement 2；

Λ (k, m, n) be Interactive Multiple-Model estimate combined probability, v₀It is Minimum detectable, v_rK () is that the radial velocity of kth scanning frame is not (if kth scanning frame has measured value, v_rK () is to be got by-1 scanning frame prediction of kth), it is assumed that speed Gaussian distributed, then can calculate P{ | v_r(k)|≥v₀And P{ | v_r(k) | ＜ v₀}；

The spatial density λ of false-alarm is:

Wherein P_FABeing false-alarm probability, distance, orientation, the certainty of measurement of distance speed three-dimensional are respectivelyWith

When situation 2, Ф (k, m, n) be calculated as follows:

Situation 2 needs to calculate P{ | v_r(k) |=0} and P{ | v_r(k)|！=0}；

Described ripple door includes range gate, orientation Bo Men, pitching ripple door and Doppler's ripple door；

Step 7, filtering: according to the filtering method of alpha-beta-γ, flight path is filtered

Wherein gain matrixObserving matrix H=[1 0 0]；

Step 8, flight path manage: when a flight path repeatedly do not have observation station cause repeatedly extrapolate time, by flight path delete；Repeat step 1～step 8, carry out sound target tenacious tracking.

Airborne radar ground sound target tenacious tracking method the most according to claim 1, it is characterised in that: described range gate 20～50m.

Airborne radar ground sound target tenacious tracking method the most according to claim 1, it is characterised in that: described orientation ripple door 1.5～2.5 degree.

Airborne radar ground sound target tenacious tracking method the most according to claim 1, it is characterised in that: described pitching ripple door 2～4 degree.

Airborne radar ground sound target tenacious tracking method the most according to claim 1, it is characterised in that: described Doppler's ripple door 3～6.