CN103353591B - Bistatic radar localization dimension reduction clutter suppression method based on MIMO - Google Patents

Abstract

The invention discloses a bistatic radar localization dimension reduction clutter suppression method based on MIMO. By using a current bistatic MIMO radar distance dependence clutter suppression method, an operation amount is large and the number of needed independent identically distributed samples is high. By using the method of the invention, the above problems are mainly solved. Realization steps are characterized in that (1) a transmitted waveform is used to carry out matched filtering on echo data of the radar; (2) a localization dimension reduction matrix is constructed and dimension reduction processing is performed on the received data; (3) the data after the dimension reduction is used to estimate a clutter covariance matrix; (4) according to a space-time adaptive processing principle, an optimal weight vector is obtained; (5) the optimal weight is used to weight the data after the dimension reduction, the background clutter is suppressed and a target signal is detected. By using the method of the invention, there are the advantages that a computation complexity is low; a requirement to the number of the independent identically distributed samples is low and clutter suppression performance is good. The method can be used in bistatic radar ground target detection of the MIMO.

Description

Based on the bistatic radar localization dimension reduction clutter suppression method of MIMO

Technical field

The invention belongs to Radar Technology field, further relate to the localization dimensionality reduction clutter suppression method of the bistatic multiple-input and multiple-output MIMO radar of positive side-looking, can be used for suppressing the dimensionality reduction of ground clutter, realize detection on a surface target.

Background technology

Radar is requisite electronics in the modern life, and wherein the structure that splits owing to have employed Receiver And Transmitter system of bistatic radar, has hidden investigation, anti-interference, anti fading advantage, also help detection Stealthy Target simultaneously.But also because this geometry feature, the distribution of its clutter power spectrum changes with the change of distance, present distance non-stationary property, namely the clutter sampled data of different distance door does not meet independent same distribution condition, and namely clutter spectrum has distance dependencies.Therefore, effective filtering or clutter reduction are the key issues that Bistatic Radar Detection target faces.

Jun Li etc. are at paper " Bistatic MIMO Radar Space-time Adaptive Processing " (2011IEEE Radar Conference, Westin Crown Center in Kansas City, Missouri, May2011) propose to utilize MIMO technique to obtain in bistatic MIMO radar in and launch cone angle information, thus enable the clutter spectrum of MIMO radar at the three dimensions inner analysis of emission space frequency-reception spatial frequency-Doppler frequency, for the clutter recognition of bistatic MIMO radar opens up a new way.Because although the clutter spectrum of bistatic MIMO radar still has Range-dependent, it is necessarily in a plane in three dimensions, utilizes this characteristic to have many methods to achieve suppression for clutter.

A kind of clutter suppression method based on bistatic MIMO radar is disclosed in patent " clutter suppression method based on bistatic MIMO radar " (application number 201110317530.5) of Xian Electronics Science and Technology University's application.The method is carried out rotation of coordinate to the echo data obtained and is projected to new coordinate axis, to eliminate clutter Range-dependent, then utilizes space-time adaptive process to eliminate clutter, detects target.The deficiency that the method exists is, its implementation is complicated, needs to calculate the inverse of full dimension clutter covariance matrix, and computation complexity is higher.

JIANXIN WU etc. are at paper " Range-Dependent Clutter Suppression for AirborneSidelooking Radar using MIMO Technique " (Aerospace and Electronic Systems, Volume:48, Issue:4) in describe a kind of utilization and realize the method for clutter recognition based on the full dimension process of minimum mean square error criterion.The deficiency of the method is, use the calculated amount of full dimension process comparatively large, and the independent same distribution clutter number of samples needed is more, cannot realize real-time process in practical application.

Summary of the invention

The object of the invention is to the deficiency for above-mentioned prior art, a kind of localization dimensionality reduction clutter suppression method based on bistatic MIMO radar is proposed, to reduce the computation complexity of radar ground clutter suppression and clutter recognition to the requirement of independent same distribution clutter number of samples, realize the real-time process detected on a surface target.

For achieving the above object, disposal route of the present invention comprises the steps:

(1) utilize the bistatic MIMO radar pattern of positive side-looking, the echo data received in a coherent processing inteval the N number of antenna of radar receiver end uses the transmitted waveform of M emitting antenna array element respectively carry out matched filtering; Echo data after each receiving antenna matched filtering is joined end to end, obtains the spatial-temporal data vector y that MNK × 1 is tieed up:

$y={\mathrm{\ρ}}_T{b}_T(f_{t,T},f_{r,T},f_{d,T})+\underset{i=0}{\overset{N_c-1}{\mathrm{\Σ}}}{\mathrm{\ρ}}_i{b}_i(f_{t,i},f_{r,i},f_{d,i})+y_w,$

Wherein, m=1,2 ..., M, subscript * represents conjugation, and K is the umber of pulse in a coherent processing inteval, ρ _tfor the reflection coefficient of target, for the steering vector of target, a _t(f _t,T) be objective emission array steering vector, a _r(f _r,T) accept array steering vector, a for target _d(f _d,T) be target Doppler steering vector, symbol represent that Kronecker amasss, N _cfor the number of clutter point source, ρ _ibe the reflection coefficient of i-th clutter point, be the space-time two-dimensional steering vector of i-th clutter point, a _t(f _t,i) be the emission array steering vector of target, a _r(f _r,i) accept array steering vector, a for target _d(f _d,i) be Doppler's steering vector of target, y _wfor the spatial-temporal data vector of noise;

(2) MNK × r is constructed _mr _nr _krank localization dimensionality reduction matrix T:

$T=G_M\⊗G_N\⊗G_K,$

Wherein, r _m, r _n, r _kfor the number of launching beam, received beam and Doppler's passage chosen during structure dimensionality reduction matrix, $G_M=[a_t\left(f_{t,T-{\tilde{r}}_M}\right),\·\·\·,a_t\left(f_{t,T-1}\right),a_t\left(f_{t,T}\right),a_t\left(f_{t,T+1}\right),\·\·\·,a_t\left(f_{t,T+{\tilde{r}}_M}\right)]$ For dimensionality reduction matrix is at the component of emit field, for near objective emission wave beam the emission array steering vector of individual wave beam, $G_N=[a_r\left(f_{r,T-{\tilde{r}}_N}\right),\·\·\·,a_r\left(f_{r,T-1}\right),a_r\left(f_{r,T}\right),a_r\left(f_{r,T+1}\right),\·\·\·,a_r\left(f_{r,T+{\tilde{r}}_N}\right)]$ For this dimensionality reduction matrix is at the component of acceptance domain, for near intended recipient wave beam the receiving array steering vector of individual wave beam, $G_K=[a_d\left(f_{d,T-{\tilde{r}}_K}\right),\·\·\·,a_d\left(f_{d,T-1}\right),a_d\left(f_{d,T}\right),a_d\left(f_{d,T+1}\right),\·\·\·,a_d\left(f_{d,T+{\tilde{r}}_K}\right)]$ For this dimensionality reduction matrix is at the component of Doppler domain, for target Doppler passage proximate doppler's steering vector of individual passage, ${\tilde{r}}_N=\mathrm{1,2},\·\·\·,(r_N-1)/2,$ ${\tilde{r}}_M=\mathrm{1,2},\·\·\·,(r_M-1)/2,$ ${\tilde{r}}_K=\mathrm{1,2},\·\·\·,(r_K-1)/2;$

(3) spatial-temporal data vector y and goal orientation vector b is multiplied by by above-mentioned dimensionality reduction matrix T _t(f _t,T, f _r,T, f _d,T), obtain the goal orientation vector C after the data vector z after dimensionality reduction and dimensionality reduction _t(f _t,T, f _r,T, f _d,T):

z=T ^Hy，

c _T(f _t,T,f _r,T,f _d,T)=T ^Hb _T(f _t,T,f _r,T,f _d,T)，

Wherein, subscript ^hrepresent conjugate transpose;

(4) the data vector z of a range gate is utilized to calculate echo covariance matrix R:R=zz ^h, and to 2 × r _mr _nr _kthe covariance matrix of individual range gate is averaged, and obtains its estimated value

$\hat{R}=\frac{1}{2\×r_M{r}_N{r}_K}\underset{k=0}{\overset{2\×r_M{r}_N{r}_K-1}{\mathrm{\Σ}}}{z}_k{z}_k^H,$

Wherein, z _krepresent the data vector after the dimensionality reduction of a kth range gate, range gate refers to the subpoint of Receiver And Transmitter on ground for focus, the one group of elliptical ring being fixed value to two bistatic distance sums with ground clutter o'clock;

(5) according to space-time adaptive handling principle, by above-mentioned echo covariance matrix value obtain optimum weight vector:

$w=\mathrm{\μ}{\hat{R}}^{-1}{c}_T(f_{t,T},f_{r,T},f_{d,T}),$

Wherein, μ is a scalar, for echo covariance matrix value inverse matrix;

(6) utilize above-mentioned optimum weight vector w to be weighted the data vector z after dimensionality reduction, obtain, for the echo data of target location clutter reduction, detecting target.

The present invention compared with prior art, has the following advantages:

A () present invention utilizes the unique features of MIMO radar structure, namely the angle information of target relative to transmitter can be obtained at receiving end by the method for signal transacting, therefore the clutter spectrum of radar has not been traditional space-time two-dimensional clutter spectrum, but the three-dimensional clutter spectrum of emission space frequency-reception spatial frequency-Doppler frequency, and when the airborne bistatic MIMO radar of positive side-looking, three-dimensional clutter spectrum is concentrated in a plane.

B () the present invention carries out dimensionality reduction to the reception data separate localization dimension reduction method after coupling, method is implemented simple, reduce computation complexity, also reduce the requirement to independent same distribution clutter number of samples simultaneously, be conducive to the real-time process realizing detecting on a surface target.

Object of the present invention, feature, advantage are described in detail by following accompanying drawing and example.

Accompanying drawing explanation

Fig. 1 is process flow diagram of the present invention;

Fig. 2 is the geometric configuration figure of the present invention's airborne bistatic MIMO radar of positive side-looking used;

Fig. 3 is the process block diagram of receiving end matched filtering of the present invention;

Fig. 4 is the three-dimensional clutter spectrum of the present invention's airborne bistatic MIMO radar of positive side-looking used;

Fig. 5 is this number of samples of independent same distribution clutter when being 2000, the present invention with ideally eliminate the optimal processing method of Range-dependent and the existing improvement factor curve comparison figure not doing the full dimension disposal route of dimension-reduction treatment;

Fig. 6 is this number of samples of independent same distribution clutter when being 600, the present invention with ideally eliminate the optimal processing method of Range-dependent and the existing improvement factor curve comparison figure not doing the full dimension disposal route of dimension-reduction treatment;

Fig. 7 is the present invention and the existing change curve comparison diagram of improvement factor with independent same distribution clutter number of samples not doing the full dimension disposal route of dimension-reduction treatment.

Embodiment

The geometric configuration of the bistatic MIMO radar of positive side-looking that the present invention is used as shown in Figure 2, coordinate origin O _rfor receiver is at the subpoint of surface level, x-axis is receiver speed v ₂direction, the position coordinates of receiver is (0,0, h _r), O _tpoint is for transmitter is at the subpoint of surface level, and the position coordinates of transmitter is (L _bcos γ, L _bsin γ, h _t), γ is the position angle of transmitter, L _bfor baseline O _ro _tlength, v _tthe speed of transmitter, be the angle of transmitter velocity and x-axis, P is i-th clutter point in given range gate, θ _r,iand θ _t,iazimuth firing angle and take over party's parallactic angle of this clutter point respectively, φ _r,iand φ _t,itransmitting angular altitude and the reception angular altitude of this clutter point respectively, ψ _r,iand ψ _t,ibe respectively this clutter point and transmitter line relative to transmitter heading angle and with the line of the receiver angle relative to receiver heading.

With reference to Fig. 1, specific implementation step of the present invention is as follows:

Step 1: matched filtering is carried out to the echo data of radar.

According to Fig. 3, utilize the bistatic MIMO mode of positive side-looking, transmitting antenna array launches mutually orthogonal waveform, with the echo data y of receiver _nwith the conjugation of transmitted waveform complex envelope matched filtering is carried out, namely as inner product owing to being MIMO radar, therefore can obtain the angle information of target relative to transmitting antenna array at receiving end, so joined end to end by the echo data after matched filtering, the sufficient statistic that MNK × 1 that can obtain echo is tieed up is according to being:

$y={\mathrm{\ρ}}_T{b}_T(f_{t,T},f_{r,T},f_{d,T})+\underset{i=0}{\overset{N_c-1}{\mathrm{\Σ}}}{\mathrm{\ρ}}_i{b}_i(f_{t,i},f_{r,i},f_{d,i})+y_w,$

Wherein, subscript * represents conjugation, and N is receiving antenna array element number, n=1,2 ..., N, M are emitting antenna array element number, m=1,2 ..., M, K are the umber of pulse in a coherent processing inteval, ρ _tfor the reflection coefficient of target, for the steering vector of target, a _t(f _t,T) be objective emission array steering vector, a _r(f _r,T) accept array steering vector, a for target _d(f _d,T) be target Doppler steering vector, f _t,Tfor the normalized emission spatial frequency of target, f _r,Tfor the normalization of target receives spatial frequency, f _d,Tfor the normalization Doppler frequency of target, symbol represent that Kronecker amasss, N _cfor the number of clutter point source, y _wfor the spatial-temporal data vector of noise, ρ _ibe the reflection coefficient of i-th clutter point, be the space-time two-dimensional steering vector of i-th clutter point, a _t(f _t,i) be objective emission array steering vector, a _r(f _r,i) accept array steering vector, a for target _d(f _d,i) be target Doppler steering vector, be the normalized emission spatial frequency of i-th clutter point, be the normalization reception spatial frequency of i-th clutter point, $f_{d,i}=\frac{v_1}{\mathrm{\λf}}\cos {\mathrm{\θ}}_{r,i}\cos {\mathrm{\φ}}_{r,i}+\frac{v_2}{\mathrm{\λf}}\cos {\mathrm{\θ}}_{t,i}\cos {\mathrm{\φ}}_{t,i}=\frac{v_1}{\mathrm{\λf}}\cos {\mathrm{\ψ}}_{r,i}+\frac{v_2}{\mathrm{\λf}}\cos {\mathrm{\ψ}}_{t,i}$ Be the normalization Doppler frequency of i-th clutter point, d ₁and d ₂be respectively the array element distance of transmitting terminal and receiving end, λ is carrier wavelength, and f is pulse repetition rate, parameter θ _r,iand θ _t,i, φ _r,iand φ _t,i, ψ _r,iand ψ _t,iall parameters of Fig. 2 indication.Namely P is i-th clutter point in given range gate, θ _r,iand θ _t,iazimuth firing angle and take over party's parallactic angle of this clutter point respectively, φ _r,iand φ _t,itransmitting angular altitude and the reception angular altitude of this clutter point respectively, ψ _r,iand ψ _t,ibe respectively this clutter point and transmitter line relative to transmitter heading angle and with the line of the receiver angle relative to receiver heading.

The described bistatic MIMO mode of positive side-looking, refer to that the transmitter and receiver of radar is placed in different location, and heading is vertical with respective antenna normal direction, multiple transmission channel is produced by the signal that multiple transmission antennas transmit is mutually orthogonal at transmitting terminal, in the echoed signal of receiving end with multiple antenna receiving target, radar clutter spectrum is positioned in a three-dimensional plane of emission space frequency-reception spatial frequency-Doppler frequency.

Step 2: structure localization dimensionality reduction matrix also carries out dimension-reduction treatment to reception data.

For the situation that transmitter and receiver all moves, corresponding clutter spectrum is many bar three-dimensional curves in the space of emission space frequency-reception spatial frequency-Doppler frequency composition, it can change along with the change of distance, namely there is distance dependencies, but because all clutter points are all in same three-dimensional planar, above-mentioned sufficient statistic can be utilized to estimate that clutter covariance matrix processes according to y.But the independent same distribution clutter number of samples of the direct operand to data processing and requirement is too large, thus cannot realize real-time process, causes detection perform to decline.So before estimation clutter covariance matrix, need to adopt localization dimension reduction method to carry out dimension-reduction treatment to reception data, its dimensionality reduction step is as follows:

2.a) construct MNK × r _mr _nr _krank localization dimensionality reduction matrix is:

$T=G_M\⊗G_N\⊗G_K,$

Wherein, r _m, r _n, r _kfor the number of launching beam, received beam and Doppler's passage chosen during structure dimensionality reduction matrix, $G_M=[a_t\left(f_{t,T-{\tilde{r}}_M}\right),\·\·\·,a_t\left(f_{t,T-1}\right),a_t\left(f_{t,T}\right),a_t\left(f_{t,T+1}\right),\·\·\·,a_t\left(f_{t,T+{\tilde{r}}_M}\right)]$ For dimensionality reduction matrix is at the component of emit field, for near objective emission wave beam the emission array steering vector of individual wave beam, $G_N=[a_r\left(f_{r,T-{\tilde{r}}_N}\right),\·\·\·,a_r\left(f_{r,T-1}\right),a_r\left(f_{r,T}\right),a_r\left(f_{r,T+1}\right),\·\·\·,a_r\left(f_{r,T+{\tilde{r}}_N}\right)]$ For this dimensionality reduction matrix is at the component of acceptance domain, for near intended recipient wave beam the receiving array steering vector of individual wave beam, $G_K=[a_d\left(f_{d,T-{\tilde{r}}_K}\right),\·\·\·,a_d\left(f_{d,T-1}\right),a_d\left(f_{d,T}\right),a_d\left(f_{d,T+1}\right),\·\·\·,a_d\left(f_{d,T+{\tilde{r}}_K}\right)]$ For this dimensionality reduction matrix is at the component of Doppler domain, for target Doppler passage proximate doppler's steering vector of individual passage, ${\tilde{r}}_N=\mathrm{1,2},\·\·\·,(r_N-1)/2,$ ${\tilde{r}}_M=\mathrm{1,2},\·\·\·,(r_M-1)/2,$ ${\tilde{r}}_K=\mathrm{1,2},...,(r_K-1)/2;$

2.b) be multiplied by spatial-temporal data vector y and goal orientation vector b by above-mentioned dimensionality reduction matrix T _t(f _t,T, f _r,T, f _d,T), obtain the goal orientation vector C after the data vector z after dimensionality reduction and dimensionality reduction _t(f _t,T, f _r,T, f _d,T):

z=T ^Hy，

c _T(f _t,T,f _r,T,f _d,T)=T ^Hb _T(f _t,T,f _r,T,f _d,T)，

Wherein, subscript ^hrepresent conjugate transpose.

After doing above-mentioned dimension-reduction treatment to sufficient statistic according to y, if estimate clutter covariance matrix with the data z after dimensionality reduction, the dimension of covariance matrix reduces to r by MNK _mr _nr _k, then corresponding inversion operation amount is by O [(MNK) ³] reduce to O [(r _mr _nr _k) ³], make the requirement of independent same distribution clutter number of samples reduce to 2 × r by 2 × MNK _mr _nr _k, therefore greatly reduce operand and the requirement to independent same distribution clutter number of samples.

Step 3: estimate clutter covariance matrix.

The data vector z of a range gate is utilized to calculate echo covariance matrix R:R=zz ^h, and to 2 × r _mr _nr _kthe covariance matrix of individual range gate is averaged, and obtains its estimated value

$\hat{R}=\frac{1}{2\×r_M{r}_N{r}_K}\underset{k=0}{\overset{2\×r_M{r}_N{r}_K-1}{\mathrm{\Σ}}}{z}_k{z}_k^H,$

Wherein, z _krepresent the data vector after the dimensionality reduction of a kth range gate, range gate refers to the subpoint of Receiver And Transmitter on ground for focus, the one group of elliptical ring being fixed value to two bistatic distance sums with ground clutter o'clock.

Step 4: obtain optimum weight vector.

According to space-time adaptive handling principle, by above-mentioned echo covariance matrix value obtain optimum weight vector w:

$w=\mathrm{\μ}{\hat{R}}^{-1}{c}_T(f_{t,T},f_{r,T},f_{d,T}),$

Wherein, μ is a scalar, for echo covariance matrix value inverse matrix, c _t(f _t,T, f _r,T, f _d,T) be steering vector during target empty after above-mentioned dimensionality reduction.

Step 5: data after dimensionality reduction are weighted.

Utilize above-mentioned optimum weight vector w to be weighted the data vector z after dimensionality reduction, obtain, for the echo data of target location clutter reduction, detecting target.

Effect of the present invention can be further illustrated by following emulation experiment.

One. experimental situation

With reference to Fig. 2, example of the present invention various parameters used are as table 1

The bistatic MIMO radar parameter of table 1

Parameter name	Concrete value
		Launch array number M	5
Receive array number N	8
		Coherent pulse number L	8
Wavelength	0.3m
		Pulse repetition rate f r	2000Hz
Base length L b	100km
		Receiver height H 2	9km
Receiver speed v 2	100m/s
		Receiver heading	90 ° (relative to x-axis)
Transmitter angle of pitch γ	30°
		Transmitter height H 1	10km
Transmitter speed v 1	100m/s
		Transmitter heading	90 ° (relative to x-axis)

Two. emulation content and result

Experiment one: the emulation of clutter Range-dependent character

This experiment is for the situation of the airborne bistatic MIMO radar of the positive side-looking described in embodiment, with the transmitted waveform of M transmission antenna unit, matched filtering is carried out to the echo data of radar, obtain receiving data y, by the three-dimensional clutter spectrum receiving data y structure, its result as shown in Figure 4.Wherein, Fig. 4 (a) is the longitudinal axis is normalization Doppler frequency, two axles of surface level are the three-dimensional clutter spectrum of normalization receive frequency and normalized emission frequency, and the clutter spectrum in Fig. 4 (a) is rotated the three-dimensional clutter spectrum behind certain visual angle by Fig. 4 (b).

As can be seen from Fig. 4 (a), the present invention is when the airborne bistatic MIMO radar of positive side-looking, its clutter spectrum is many bar three-dimensional curves in the space of emission space frequency-reception spatial frequency-Doppler frequency composition, different distance is corresponding different spectral line respectively, and therefore it has Range-dependent characteristic.

As can be seen from Fig. 4 (b), the clutter spectrum of all clutter range gate is all at same three-dimensional planar, and it is feasible for illustrating that the present invention carries out dimension-reduction treatment to it.

Experiment two: the emulation of clutter recognition performance

2.1) set range gate number as 2000, the emission space frequency of target is f _t,T=0, reception spatial frequency is f _r,T=0, miscellaneous noise ratio is 40dB, r _m=3, r _n=5, r _k=3, other parameter is in table 1.

Under these conditions, its clutter recognition performance is emulated by the inventive method, and process these two kinds of methods make clutter recognition performance comparison with the optimal processing method and existing full dimension of not doing dimension-reduction treatment of eliminating Range-dependent in the ideal case, its comparing result is as shown in Figure 5.The horizontal ordinate of Fig. 5 is normalization Doppler frequency, and ordinate is improvement factor.

As can be seen from Figure 5, identical geometrical configuration, same hardware configuration and same data rate condition under, independent same distribution clutter number of samples and range gate number are when 2000>2 × MNK, though performance of the present invention, a little less than there is not the optimal processing method of clutter Range-dependent and not doing the full dimension disposal route of dimension-reduction treatment, greatly reduces operand.

2.2) set range gate number as 600, the emission space frequency of target is f _t,T=0, reception spatial frequency is f _r,T=0, miscellaneous noise ratio is 40dB, r _m=3, r _n=5, r _k=3, other parameter is in table 1.

Under these conditions, its clutter recognition performance is emulated by the inventive method, and process these two kinds of methods make clutter recognition performance comparison with the optimal processing method and existing full dimension of not doing dimension-reduction treatment of eliminating Range-dependent in the ideal case, its comparing result is as shown in Figure 6.The horizontal ordinate of Fig. 6 is normalization Doppler frequency, and ordinate is improvement factor.

As can be seen from Figure 6, identical geometrical configuration, same hardware configuration and same data rate condition under, independent same distribution clutter number of samples and range gate number are when 600<2 × MNK, performance of the present invention lower than do not exist clutter Range-dependent optimal processing method but higher than the full dimension disposal route not doing dimension-reduction treatment, and greatly reduce operand, thus the demand that proof The present invention reduces independent same distribution clutter number of samples, the clutter recognition better performances when sample number is not enough.

2.3) set the emission space frequency of target as f _t,T=0, reception spatial frequency is f _r,T=0, miscellaneous noise ratio is 40dB, r _m=3, r _n=5, r _k=3, other parameter is in table 1.

Under these conditions, the change curve of its clutter recognition performance with independent same distribution clutter number of samples is emulated by the inventive method, and process these two kinds of methods compare with the optimal processing method and existing full dimension of not doing dimension-reduction treatment of eliminating Range-dependent in the ideal case, its comparing result is as shown in Figure 7.The horizontal ordinate of Fig. 7 is independent same distribution clutter number of samples, and ordinate is improvement factor.

As can be seen from Figure 7, under the condition of identical geometrical configuration, same hardware configuration and same data rate the clutter recognition performance of the inventive method with the speed of convergence of independent clutter number of samples obviously faster than the existing full dimension disposal route not doing dimension-reduction treatment, be difficult to obtain in the true clutter environment of a large amount of independent same distribution numbers of samples, the present invention has better clutter suppression capability.

In sum, the present invention is based on its clutter spectrum is be positioned at the bistatic MIMO mode of positive side-looking in a three-dimensional plane of emission space frequency-reception spatial frequency-Doppler frequency, make use of localization dimension reduction method and dimensionality reduction is carried out to reception data, again to clutter recognition, realize detection on a surface target.The inventive method identical geometrical configuration, same hardware configuration and same data rate condition under, compared with the existing full dimension disposal route not doing dimension-reduction treatment, reduce computation complexity, also reduce the requirement to independent same distribution number of samples simultaneously, there is better clutter suppression capability.

Claims (3)

1., based on a bistatic radar localization dimension reduction clutter suppression method of MIMO, comprise the steps:

(1) utilize the bistatic MIMO radar pattern of positive side-looking, the echo data received in a coherent processing inteval the N number of antenna of radar receiver end uses the transmitted waveform of M emitting antenna array element respectively carry out matched filtering; Echo data after each receiving antenna matched filtering is joined end to end, obtains the spatial-temporal data vector y that MNK × 1 is tieed up:

$y={\mathrm{\&rho;}}_T{b}_T(f_{t,T},f_{r,T},f_{d,T})+\underset{i=0}{\overset{N_c-1}{\mathrm{\&Sigma;}}}{\mathrm{\&rho;}}_i{b}_i(f_{t,i},f_{r,i},f_{d,i})+y_w,$

Wherein, m=1,2 ..., M, subscript * represents conjugation, and K is the umber of pulse in a coherent processing inteval, ρ _tfor the reflection coefficient of target, $b_T(f_{t,T},f_{r,T},f_{d,T})=a_t\left(f_{t,T}\right)\&CircleTimes;a_r\left(f_{r,T}\right)\&CircleTimes;a_d\left(f_{d,T}\right)$ For the steering vector of target, a _t(f _t,T) be objective emission array steering vector, a _r(f _r,T) accept array steering vector, a for target _d(f _d,T) be target Doppler steering vector, symbol represent that Kronecker amasss, N _cfor the number of clutter point source, ρ _ibe the reflection coefficient of i-th clutter point, $b_i(f_{t,i},f_{r,i},f_{d,i})=a_t\left(f_{t,i}\right)\&CircleTimes;a_r\left(f_{r,i}\right)\&CircleTimes;a_d\left(f_{d,i}\right)$ Be the space-time two-dimensional steering vector of i-th clutter point, a _t(f _t,i) be the emission array steering vector of target, a _r(f _r,i) accept array steering vector, a for target _d(f _d,i) be Doppler's steering vector of target, y _wfor the spatial-temporal data vector of noise;

(2) MNK × r is constructed _mr _nr _krank localization dimensionality reduction matrix T:

$T=G_M\&CircleTimes;G_N\&CircleTimes;G_K,$

Wherein, r _m, r _n, r _kfor the number of launching beam, received beam and Doppler's passage chosen during structure dimensionality reduction matrix, $G_M=[a_t\left(f_{t,T-{\tilde{r}}_M}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_t\left(f_{t,T-1}\right),a_t\left(f_{t,T}\right),a_t\left(f_{t,T+1}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_t\left(f_{t,T+{\tilde{r}}_M}\right)]$ For dimensionality reduction matrix is at the component of emit field, for near objective emission wave beam the emission array steering vector of individual wave beam, $G_N=[a_r\left(f_{r,T-{\tilde{r}}_N}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_r\left(f_{r,T-1}\right),a_r\left(f_{r,T}\right),a_r\left(f_{r,T+1}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_r\left(f_{r,T+{\tilde{r}}_N}\right)]$ For this dimensionality reduction matrix is at the component of acceptance domain, for near intended recipient wave beam the receiving array steering vector of individual wave beam, $G_K=[a_d\left(f_{d,T-{\tilde{r}}_K}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_d\left(f_{d,T-1}\right),a_d\left(f_{d,T}\right),a_d\left(f_{d,T+1}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_d\left(f_{d,T+{\tilde{r}}_K}\right)]$ For this dimensionality reduction matrix is at the component of Doppler domain, for target Doppler passage proximate doppler's steering vector of individual passage, ${\tilde{r}}_N=\mathrm{1,2},\&CenterDot;\&CenterDot;\&CenterDot;,(r_N-1)/2,$ ${\tilde{r}}_M=\mathrm{1,2},\&CenterDot;\&CenterDot;\&CenterDot;,(r_M-1)/2,$ ${\tilde{r}}_K=\mathrm{1,2},\&CenterDot;\&CenterDot;\&CenterDot;,(r_K-1)/2;$

(3) spatial-temporal data vector y and goal orientation vector b is multiplied by by above-mentioned dimensionality reduction matrix T _t(f _t,T, f _r,T, f _d,T), obtain the goal orientation vector C after the data vector z after dimensionality reduction and dimensionality reduction _t(f _t,T, f _r,T, f _d,T):

z＝T ^Hy，

c _T(f _t,T,f _r,T,f _d,T)＝T ^Hb _T(f _t,T,f _r,T,f _d,T)，

Wherein, subscript ^hrepresent conjugate transpose;

(4) the data vector z of a range gate is utilized to calculate echo covariance matrix R:R=zz ^h, and to 2 × r _mr _nr _kthe covariance matrix of individual range gate is averaged, and obtains its estimated value

$\hat{R}=\frac{1}{2\&times;r_M{r}_N{r}_K}\underset{k=0}{\overset{2\&times;r_M{r}_N{r}_K-1}{\mathrm{\&Sigma;}}}{z}_k{z}_k^H,$

Wherein, z _krepresent the data vector after the dimensionality reduction of a kth range gate, range gate refers to the subpoint of Receiver And Transmitter on ground for focus, the one group of elliptical ring being fixed value to two bistatic distance sums with ground clutter o'clock;

(5) according to space-time adaptive handling principle, by above-mentioned echo covariance matrix value obtain optimum weight vector:

$w=\mathrm{\&mu;}{\hat{R}}^{-1}{c}_T(f_{t,T},f_{r,T},f_{d,T}),$

Wherein μ is a scalar, for echo covariance matrix value inverse matrix;

(6) utilize above-mentioned optimum weight vector w to be weighted the data vector z after dimensionality reduction, obtain, for the echo data of target location clutter reduction, detecting target.

2. the bistatic radar localization dimension reduction clutter suppression method based on MIMO according to claim 1, the bistatic MIMO mode of positive side-looking wherein described in step (1), refer to that the transmitter and receiver of radar is placed in different location, and heading is vertical with respective antenna normal direction, multiple transmission channel is produced by the signal that multiple transmission antennas transmit is mutually orthogonal at transmitting terminal, in the echoed signal of receiving end with multiple antenna receiving target, radar clutter spectrum is positioned in a three-dimensional plane of emission space frequency-reception spatial frequency-Doppler frequency.

3. the bistatic radar localization dimension reduction clutter suppression method based on MIMO according to claim 1, the echo data received in a coherent processing inteval the N number of antenna of radar receiver end wherein described in step (1) uses the transmitted waveform of M emitting antenna array element respectively carrying out matched filtering, is the echo data y of the n-th antenna with receiver _nwith the conjugation of the transmitted waveform complex envelope of transmitter m emitting antenna make inner product namely wherein n=1,2 ..., N, m=1,2 ..., M.