CN103353591A - 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

Bistatic radar localization dimensionality reduction clutter suppression method based on MIMO

Technical field

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

Background technology

Radar is requisite electronics in the modern life, and wherein bistatic radar also helps the detection Stealthy Target simultaneously because the structure that has adopted the Receiver And Transmitter system to split has hidden investigation, anti-interference, anti fading advantage.But also because of this geometry characteristics, the distribution of its clutter power spectrum changes with the variation of distance, presents apart from non-stationary property, and namely the clutter sampled data of different distance door does not satisfy the independent same distribution condition, and namely clutter spectrum has Range-dependent.Therefore, effectively filtering or clutter reduction are the key issues that the 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 in bistatic MIMO radar, can utilize MIMO technique to obtain the emission cone angle information, thereby make the clutter spectrum of MIMO radar can be at the three dimensions inner analysis of emission space frequency-reception spatial frequency-Doppler frequency, for the clutter of bistatic MIMO radar suppresses to open up a new way.Although because the clutter spectrum of bistatic MIMO radar still has Range-dependent, it necessarily is on the plane in the three dimensions, utilize this characteristic to have many methods to realize inhibition for clutter.

A kind of clutter suppression method based on bistatic MIMO radar is disclosed in the patent " based on the clutter suppression method of 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 that obtains and to new coordinate axis projection, to eliminate the clutter Range-dependent, is then utilized space-time adaptive to process and eliminate clutter, detects target.The deficiency that the method exists is, its implementation is complicated, needs to calculate the contrary of full dimension clutter covariance matrix, and computation complexity is higher.

JIANXIN WU etc. are at paper " Range-Dependent Clutter Suppression for Airborne Sidelooking Radar using MIMO Technique " (Aerospace and Electronic Systems, Volume:48, Issue:4) in introduced a kind of utilization and processed to realize the method that clutter suppresses based on the full dimension of minimum mean square error criterion.The deficiency of the method is that the calculated amount of using full dimension to process is larger, and the independent same distribution clutter number of samples that needs is more, can't realize real-time processing in the 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, suppress requirement to independent same distribution clutter number of samples with the computation complexity that reduces the radar ground clutter suppression and clutter, realize the real-time processing that detects on a surface target.

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

(1) utilizes the bistatic MIMO radar mode of positive side-looking, N antenna of radar receiver end processed the transmitted waveform that the echo data that receives in the interval is used respectively M emitting antenna array element once relevant

Carry out matched filtering; Echo data after each receiving antenna matched filtering is joined end to end data vector y when obtaining MNK * 1 dimension empty:

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

Wherein, m=1,2 ..., M, subscript * represents conjugation, K is once the relevant umber of pulse of processing in the interval, ρ _TBe the reflection coefficient of target,

Be the steering vector of target, a _t(f _{T, T}) be target 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 Expression Kronecker is long-pending, N _cBe the number of clutter point source, ρ _iBe the reflection coefficient of i clutter point,

Be the space-time two-dimensional steering vector of i 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 _wData vector during for noise empty;

(2) structure MNK * r _Mr _Nr _KRank localization dimensionality reduction matrix T:

$T=G_M\⊗G_N\⊗G_K,$

Wherein, r _M, r _N, r _KThe number of launching beam, received beam and the Doppler's passage of choosing during for structure dimensionality reduction matrix, $G_M=[a_t\left(f_{t,T-{\tilde{r}}_M}\right),\·\·\·,a_t\left(f_{t,T-1}\right),a_t\left(f_{t,T}\right),a_t\left(f_{t,T+1}\right),\·\·\·,a_t\left(f_{t,T+{\tilde{r}}_M}\right)]$ Be the component of dimensionality reduction matrix at emit field,

For near the target launching beam

The emission array steering vector of individual wave beam, $G_N=[a_r\left(f_{r,T-{\tilde{r}}_N}\right),\·\·\·,a_r\left(f_{r,T-1}\right),a_r\left(f_{r,T}\right),a_r\left(f_{r,T+1}\right),\·\·\·,a_r\left(f_{r,T+{\tilde{r}}_N}\right)]$ Be the component of this dimensionality reduction matrix at acceptance domain,

For near the target received beam The receiving array steering vector of individual wave beam, $G_K=[a_d\left(f_{d,T-{\tilde{r}}_K}\right),\·\·\·,a_d\left(f_{d,T-1}\right),a_d\left(f_{d,T}\right),a_d\left(f_{d,T+1}\right),\·\·\·,a_d\left(f_{d,T+{\tilde{r}}_K}\right)]$ Be the component of this dimensionality reduction matrix at Doppler domain,

For near the target Doppler passage

Doppler's steering vector of individual passage, ${\tilde{r}}_N=\mathrm{1,2},\·\·\·,(r_N-1)/2,$ ${\tilde{r}}_M=\mathrm{1,2},\·\·\·,(r_M-1)/2,$ ${\tilde{r}}_K=\mathrm{1,2},\·\·\·,(r_K-1)/2;$

Data vector y and goal orientation vector b when (3) multiply by sky with above-mentioned dimensionality reduction matrix T _T(f _{T, T}, f _{R, T}, f _{D, T}), obtain data vector z behind the dimensionality reduction and the goal orientation vector C behind the 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 ^HThe expression conjugate transpose;

(4) utilize the data vector z of a range gate 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 behind the dimensionality reduction of k range gate, range gate refers to take Receiver And Transmitter at the subpoint on ground as focus, and is bistatic apart from the one group elliptical ring of sum as fixed value to two take ground clutter o'clock;

(5) according to the 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,

Be echo covariance matrix value

Inverse matrix;

(6) the data vector z after utilizing above-mentioned optimum weight vector w to dimensionality reduction is weighted, and obtains the echo data for the target location clutter reduction, detects target.

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

(a) the present invention has utilized the unique features of MIMO radar arrangement, namely can obtain target in the method that receiving end is processed by signal with respect to the angle information of transmitter, 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 in the situation of the positive airborne bistatic MIMO radar of side-looking, three-dimensional clutter spectrum is concentrated on the plane.

(b) the present invention utilizes the localization dimension reduction method to carry out dimensionality reduction to the receive data after the coupling, method is implemented simple, reduce computation complexity, also reduced simultaneously the requirement to independent same distribution clutter number of samples, be conducive to realize the real-time processing that detects on a surface target.

Purpose of the present invention, feature, advantage can be described in detail by following accompanying drawing and example.

Description of drawings

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

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

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

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

Fig. 5 is that this number of samples of independent same distribution clutter is 2000 o'clock, the present invention and the optimal processing method of ideally eliminating Range-dependent and the existing improvement factor curve comparison figure that does not do the full dimension disposal route of dimension-reduction treatment;

Fig. 6 is that this number of samples of independent same distribution clutter is 600 o'clock, the present invention and the optimal processing method of ideally eliminating Range-dependent and the existing improvement factor curve comparison figure that does not do the full dimension disposal route of dimension-reduction treatment;

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

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 _rBe the subpoint of receiver at surface level, the x axle is the receiver speed v ₂Direction, the position coordinates of receiver is (0,0, h _r), O _tPoint is the subpoint of transmitter at 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 _bBe baseline O _rO _tLength, v _tThe speed of transmitter,

Be the angle of transmitter velocity and x axle, P is i clutter point in the given range gate, θ _{R, i}And θ _{T, i}Respectively azimuth firing angle and take over party's parallactic angle of this clutter point, φ _{R, i}And φ _{T, i}Respectively emission angular altitude and the reception angular altitude of this clutter point, ψ _{R, i}And ψ _{T, i}Respectively this clutter point with the line of transmitter with respect to the angle of transmitter heading and with the line of the receiver angle with respect to the receiver heading.

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

Step 1: the echo data to radar carries out matched filtering.

According to Fig. 3, utilize the bistatic MIMO pattern of positive side-looking, the waveform that the transmitting antenna array emission is mutually orthogonal is with the echo data y of receiver _nConjugation with the transmitted waveform complex envelope

Carry out matched filtering as inner product, namely Owing to be the MIMO radar, so can obtain target with respect to the angle information of transmitting antenna array at receiving end, so the echo data after the matched filtering is joined end to end, can obtain the sufficient statistic of the MNK of echo * 1 dimension 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, and 2 ..., N, M are emitting antenna array element number, m=1, and 2 ..., M, K are once the relevant umber of pulse of processing in the interval, ρ _TBe the reflection coefficient of target, Be the steering vector of target, a _t(f _{T, T}) be target 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, T}Be the normalization emission space frequency of target, f _{R, T}Be the normalization reception spatial frequency of target, f _{D, T}Be the normalization Doppler frequency of target, symbol

Expression Kronecker is long-pending, N _cBe the number of clutter point source, y _wData vector during for noise empty, ρ _iBe the reflection coefficient of i clutter point,

Be the space-time two-dimensional steering vector of i clutter point, a _t(f _{T, i}) be target 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 normalization emission space frequency of i clutter point, The normalization that is i clutter point receives spatial frequency, $f_{d,i}=\frac{{\mathrm{<figure-callout\; id="1"\; label="v"\; filenames="HDA00003366364800031.png"\; state="\{\{state\}\}">v</figure-callout>}}_1}{\mathrm{\&lambda;f}}\cos {\mathrm{\&theta;}}_{r,i}\cos {\mathrm{\&phi;}}_{r,i}+\frac{v_2}{\mathrm{\&lambda;f}}\cos {\mathrm{\&theta;}}_{t,i}\cos {\mathrm{\&phi;}}_{t,i}=\frac{{\mathrm{<figure-callout\; id="1"\; label="v"\; filenames="HDA00003366364800031.png"\; state="\{\{state\}\}">v</figure-callout>}}_1}{\mathrm{\&lambda;f}}\cos {\mathrm{\&psi;}}_{r,i}+\frac{v_2}{\mathrm{\&lambda;f}}\cos {\mathrm{\&psi;}}_{t,i}$ Be the normalization Doppler frequency of i 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, i}And θ _{T, i}, φ _{R, i}And φ _{T, i}, ψ _{R, i}And ψ _{T, i}All are parameters of Fig. 2 indication.Be that P is i clutter point in the given range gate, θ _{R, i}And θ _{T, i}Respectively azimuth firing angle and take over party's parallactic angle of this clutter point, φ _{R, i}And φ _{T, i}Respectively emission angular altitude and the reception angular altitude of this clutter point, ψ _{R, i}And ψ _{T, i}Respectively this clutter point with the line of transmitter with respect to the angle of transmitter heading and with the line of the receiver angle with respect to the receiver heading.

The bistatic MIMO pattern of described positive side-looking, the transmitter and receiver that the refers to radar different location that is placed in, and heading and antenna normal perpendicular direction separately, produce a plurality of transmission channels at transmitting terminal by the mutually orthogonal signal of a plurality of transmission antennas transmit, in the echoed signal of receiving end with a plurality of antenna reception targets, the radar clutter spectrum is positioned on the three-dimensional plane of emission space frequency-reception spatial frequency-Doppler frequency.

Step 2: construct localization dimensionality reduction matrix and receive data is carried out dimension-reduction treatment.

The situation of all moving for transmitter and receiver, corresponding clutter spectrum is many three-dimensional curves in the space that emission space frequency-reception spatial frequency-Doppler frequency forms, it can change along with the variation of distance, namely has Range-dependent, but because all clutter points all in same three-dimensional planar, can utilize above-mentioned sufficient statistic to process according to y estimation clutter covariance matrix.But the operand of directly data being processed and the independent same distribution clutter number of samples of requirement are too large, thereby can't realize real-time processing, cause detecting hydraulic performance decline.So, before estimating clutter covariance matrix, need to adopt the localization dimension reduction method that receive data is carried out dimension-reduction treatment, its dimensionality reduction step is as follows:

2.a) structure MNK * r _Mr _Nr _KRank localization dimensionality reduction matrix is:

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

Wherein, r _M, r _N, r _KThe number of launching beam, received beam and the Doppler's passage of choosing during for structure dimensionality reduction matrix, $G_M=[a_t\left(f_{t,T-{\tilde{r}}_M}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_t\left(f_{t,T-1}\right),a_t\left(f_{t,T}\right),a_t\left(f_{t,T+1}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_t\left(f_{t,T+{\tilde{r}}_M}\right)]$ Be the component of dimensionality reduction matrix at emit field,

For near the target launching beam The emission array steering vector of individual wave beam, $G_N=[a_r\left(f_{r,T-{\tilde{r}}_N}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_r\left(f_{r,T-1}\right),a_r\left(f_{r,T}\right),a_r\left(f_{r,T+1}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_r\left(f_{r,T+{\tilde{r}}_N}\right)]$ Be the component of this dimensionality reduction matrix at acceptance domain,

For near the target received beam

The receiving array steering vector of individual wave beam, $G_K=[a_d\left(f_{d,T-{\tilde{r}}_K}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_d\left(f_{d,T-1}\right),a_d\left(f_{d,T}\right),a_d\left(f_{d,T+1}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_d\left(f_{d,T+{\tilde{r}}_K}\right)]$ Be the component of this dimensionality reduction matrix at Doppler domain,

For near the target Doppler passage

Doppler's steering vector of individual passage, ${\tilde{r}}_N=\mathrm{1,2},\&CenterDot;\&CenterDot;\&CenterDot;,(r_N-1)/2,$ ${\tilde{r}}_M=\mathrm{1,2},\&CenterDot;\&CenterDot;\&CenterDot;,(r_M-1)/2,$ ${\tilde{r}}_K=\mathrm{1,2},...,(r_K-1)/2;$

2.b) data vector y and goal orientation vector b when multiply by sky with above-mentioned dimensionality reduction matrix T _T(f _{T, T}, f _{R, T}, f _{D, T}), obtain data vector z behind the dimensionality reduction and the goal orientation vector C behind the 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 ^HThe expression conjugate transpose.

After sufficient statistic done above-mentioned dimension-reduction treatment according to y, if estimate clutter covariance matrix with the data z behind the dimensionality reduction, the dimension of covariance matrix was reduced 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 _KTherefore, greatly reduce operand and to the requirement of independent same distribution clutter number of samples.

Step 3: estimate clutter covariance matrix.

Utilize the data vector z of a range gate 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 behind the dimensionality reduction of k range gate, range gate refers to take Receiver And Transmitter at the subpoint on ground as focus, and is bistatic apart from the one group elliptical ring of sum as fixed value to two take ground clutter o'clock.

Step 4: obtain optimum weight vector.

According to the space-time adaptive handling principle, by above-mentioned echo covariance matrix value

Obtain optimum weight vector w:

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

Wherein, μ is a scalar, Be echo covariance matrix value

Inverse matrix, c _T(f _{T, T}, f _{R, T}, f _{D, T}) steering vector when being the target empty behind the above-mentioned dimensionality reduction.

Step 5: data behind the dimensionality reduction are weighted.

Data vector z after utilizing above-mentioned optimum weight vector w to dimensionality reduction is weighted, and obtains the echo data for the target location clutter reduction, detects target.

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

One. experimental situation

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

The bistatic MIMO radar parameter of table 1

Parameter name	Concrete value
		Emission array number M	5
Receive array number N	8
		Coherent pulse is counted L	8
Wavelength	0.3m
		Pulse repetition rate f r	2000Hz
Base length L b	100km
		The receiver height H 2	9km
The receiver speed v 2	100m/s
		The receiver heading	90 ° (with respect to x axle)
Transmitter angle of pitch γ	30°
		The transmitter height H 1	10km
The transmitter speed v 1	100m/s
		The transmitter heading	90 ° (with respect to x axle)

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 described positive side-looking of embodiment, with the transmitted waveform of M transmission antenna unit the echo data of radar is carried out matched filtering, obtain receive data y, with the three-dimensional clutter spectrum of receive data y structure, its result as shown in Figure 4.Wherein, Fig. 4 (a) is that the longitudinal axis is the normalization Doppler frequency, two axles of surface level are the three-dimensional clutter spectrum of normalization receive frequency and normalization transmission frequency, and Fig. 4 (b) rotates three-dimensional clutter spectrum behind certain visual angle with the clutter spectrum among Fig. 4 (a).

Can find out from Fig. 4 (a), the present invention is in the situation of the positive airborne bistatic MIMO radar of side-looking, its clutter spectrum is many three-dimensional curves in the space that emission space frequency-reception spatial frequency-Doppler frequency forms, different distance is corresponding different spectral lines respectively, so it has the Range-dependent characteristic.

Can find out that from Fig. 4 (b) clutter spectrum of all clutter range gate illustrates that all at same three-dimensional planar it is feasible that the present invention carries out dimension-reduction treatment to it.

Experiment two: the emulation of clutter rejection

2.1) to establish the range gate number be 2000, the emission space frequency of target is f _{T, T}=0, the reception spatial frequency is f _{R, T}=0, miscellaneous noise ratio is 40dB, r _M=3, r _N=5, r _K=3, other parameter sees Table 1.

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

As can be seen from Figure 5, under the condition of identical geometrical configuration, same hardware configuration and same data rate, independent same distribution clutter number of samples is that the range gate number is 2000〉during 2 * MNK, though performance of the present invention is a little less than the optimal processing method that does not have the clutter Range-dependent and do not do the full dimension disposal route of dimension-reduction treatment, has greatly reduced operand.

2.2) to establish the range gate number be 600, the emission space frequency of target is f _{T, T}=0, the reception spatial frequency is f _{R, T}=0, miscellaneous noise ratio is 40dB, r _M=3, r _N=5, r _K=3, other parameter sees Table 1.

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

As can be seen from Figure 6, under the condition of identical geometrical configuration, same hardware configuration and same data rate, independent same distribution clutter number of samples is that the range gate number is when 600＜2 * MNK, performance of the present invention is lower than the optimal processing method that does not have the clutter Range-dependent but is higher than the full dimension disposal route of not doing dimension-reduction treatment, and greatly reduced operand, thereby proof the present invention has reduced the demand to independent same distribution clutter number of samples, and the clutter rejection when sample number is not enough is better.

2.3) the emission space frequency of establishing target is f _{T, T}=0, the reception spatial frequency is f _{R, T}=0, miscellaneous noise ratio is 40dB, r _M=3, r _N=5, r _K=3, other parameter sees Table 1.

Under these conditions, with the change curve of its clutter rejection of the inventive method emulation with independent same distribution clutter number of samples, and process these two kinds of methods with the optimal processing method of eliminating in the ideal case Range-dependent and the existing full dimension of not doing dimension-reduction treatment and compare, 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 the configuration of identical geometrical configuration, same hardware and same data rate the clutter rejection of the inventive method with the speed of convergence of independent clutter number of samples obviously faster than the existing full dimension disposal route of not doing dimension-reduction treatment, obtain in the true clutter environment of a large amount of independent same distribution numbers of samples being difficult to, the present invention has better clutter and suppresses ability.

In sum, the present invention is based on its clutter spectrum and be the bistatic MIMO pattern of positive side-looking on the three-dimensional plane that is positioned at emission space frequency-reception spatial frequency-Doppler frequency, utilized the localization dimension reduction method that receive data is carried out dimensionality reduction, again clutter is suppressed, realize detection on a surface target.The inventive method is under the condition of identical geometrical configuration, same hardware configuration and same data rate, compare with the existing full dimension disposal route of not doing dimension-reduction treatment, reduced computation complexity, also reduced the requirement to the independent same distribution number of samples simultaneously, had better clutter and suppress ability.

Claims (3)

1. the bistatic radar localization dimensionality reduction clutter suppression method based on MIMO comprises the steps:

(1) utilizes the bistatic MIMO radar mode of positive side-looking, N antenna of radar receiver end processed the transmitted waveform that the echo data that receives in the interval is used respectively M emitting antenna array element once relevant

Carry out matched filtering; Echo data after each receiving antenna matched filtering is joined end to end data vector y when obtaining MNK * 1 dimension empty:

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

Wherein, m=1,2 ..., M, subscript * represents conjugation, K is once the relevant umber of pulse of processing in the interval, ρ _TBe the reflection coefficient of target, $b_T(f_{t,T},f_{r,T},f_{d,T})=a_t\left(f_{t,T}\right)\&CircleTimes;a_r\left(f_{r,T}\right)\&CircleTimes;a_d\left(f_{d,T}\right)$ Be the steering vector of target, a _t(f _{T, T}) be target 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

Expression Kronecker is long-pending, N _cBe the number of clutter point source, ρ _iBe the reflection coefficient of i clutter point, Be the space-time two-dimensional steering vector of i 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 _wData vector during for noise empty;

(2) structure MNK * r _Mr _Nr _KRank localization dimensionality reduction matrix T:

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

Wherein, r _M, r _N, r _KThe number of launching beam, received beam and the Doppler's passage of choosing during for structure dimensionality reduction matrix, $G_M=[a_t\left(f_{t,T-{\tilde{r}}_M}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_t\left(f_{t,T-1}\right),a_t\left(f_{t,T}\right),a_t\left(f_{t,T+1}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_t\left(f_{t,T+{\tilde{r}}_M}\right)]$ Be the component of dimensionality reduction matrix at emit field, For near the target launching beam

The emission array steering vector of individual wave beam, $G_N=[a_r\left(f_{r,T-{\tilde{r}}_N}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_r\left(f_{r,T-1}\right),a_r\left(f_{r,T}\right),a_r\left(f_{r,T+1}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_r\left(f_{r,T+{\tilde{r}}_N}\right)]$ Be the component of this dimensionality reduction matrix at acceptance domain,

For near the target received beam

The receiving array steering vector of individual wave beam, $G_K=[a_d\left(f_{d,T-{\tilde{r}}_K}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_d\left(f_{d,T-1}\right),a_d\left(f_{d,T}\right),a_d\left(f_{d,T+1}\right),\&CenterDot;\&CenterDot;\&CenterDot;,a_d\left(f_{d,T+{\tilde{r}}_K}\right)]$ Be the component of this dimensionality reduction matrix at Doppler domain,

For near the target Doppler passage

Doppler's steering vector of individual passage, ${\tilde{r}}_N=\mathrm{1,2},\&CenterDot;\&CenterDot;\&CenterDot;,(r_N-1)/2,$ ${\tilde{r}}_M=\mathrm{1,2},\&CenterDot;\&CenterDot;\&CenterDot;,(r_M-1)/2,$ ${\tilde{r}}_K=\mathrm{1,2},\&CenterDot;\&CenterDot;\&CenterDot;,(r_K-1)/2;$

Data vector y and goal orientation vector b when (3) multiply by sky with above-mentioned dimensionality reduction matrix T _T(f _{T, T}, f _{R, T}, f _{D, T}), obtain data vector z behind the dimensionality reduction and the goal orientation vector C behind the 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 ^HThe expression conjugate transpose;

(4) utilize the data vector z of a range gate 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 behind the dimensionality reduction of k range gate, range gate refers to take Receiver And Transmitter at the subpoint on ground as focus, and is bistatic apart from the one group elliptical ring of sum as fixed value to two take ground clutter o'clock;

(5) according to the 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, Be echo covariance matrix value

Inverse matrix;

(6) the data vector z after utilizing above-mentioned optimum weight vector w to dimensionality reduction is weighted, and obtains the echo data for the target location clutter reduction, detects target.

2. the localization dimensionality reduction clutter suppression method based on bistatic MIMO radar according to claim 1, the bistatic MIMO pattern of the described positive side-looking of step (1) wherein, the transmitter and receiver that the refers to radar different location that is placed in, and heading and antenna normal perpendicular direction separately, produce a plurality of transmission channels at transmitting terminal by the mutually orthogonal signal of a plurality of transmission antennas transmit, in the echoed signal of receiving end with a plurality of antenna reception targets, the radar clutter spectrum is positioned on the three-dimensional plane of emission space frequency-reception spatial frequency-Doppler frequency.

3. the localization dimensionality reduction clutter suppression method based on bistatic MIMO radar according to claim 1, wherein step (1) is described processes the transmitted waveform that the echo data that receives in the interval is used respectively M emitting antenna array element to N antenna of radar receiver end once relevant

Carrying out matched filtering, is the echo data y with n antenna of receiver _nConjugation with the transmitted waveform complex envelope of m emitting antenna of transmitter

Make inner product namely

N=1 wherein, 2 ..., N, m=1,2 ..., M.

Images