CN103777190B - A kind of angle estimating method of bistatic MIMO radar high speed highly maneuvering target - Google Patents

Abstract

The invention discloses the angle estimating method of bistatic MIMO radar high speed highly maneuvering target, the receiving array comprising bistatic MIMO radar receives the echoed signal of high speed highly maneuvering target; Receiving array echo be positioned at transmitting on different distance unit and carry out conjugate multiplication; In fast time domain and slow time domain, Fourier transform is carried out successively to data after conjugate multiplication; Target velocity is gone out according to the peak estimation in step 3; At the slow time frequency domain components of target that fast temporal frequency domain is extracted in different split tunnel along target Doppler frequency values; Realize forming virtual array data across multiple range gate by the splicing of the target frequency domain data on different distance door; Super resolution algorithm is utilized to estimate each objective emission angle and acceptance angle.The high motion of automobile of the high speed of target can be avoided the impact of MIMO radar channel separation, realize forming effective virtual array across multiple range gate, solve the angle on target Parameter Estimation Problem of the bistatic MIMO radar under high speed highly maneuvering target.

Description

A kind of angle estimating method of bistatic MIMO radar high speed highly maneuvering target

Technical field

The present invention relates to the application of multi-input multi-output radar system, particularly a kind of angle estimating method of bistatic MIMO radar high speed highly maneuvering target.

Background technology

The bistatic radar of bistatic has stronger Anti-antiradiation missile, Anti-amyloid-β antibody, anti-low-level penetration and anti-stealthy " four resist " ability, and by multiple-input and multiple-output (Multiple-InputMultiple-Output, MIMO) technology is applied in bistatic radar, can solve in traditional bistatic radar and receive and dispatch the synchronous problem of spatial beams.Therefore bistatic MIMO radar has a wide range of applications, and its target detection and parameter estimation have become a study hotspot of field of radar.The emission array of bistatic MIMO radar launches mutually orthogonal signal, and receiving array apart from each other can utilize the orthogonality transmitted to form virtual array by matched filtering method, then conventional super-resolution angle estimation algorithm is utilized can to estimate the emission angle (DirectionOfDeparture of target from virtual array, and acceptance angle (DirectionOfArrival DOD), DOA), thus the multiple target in implementation space without fuzzy cross bearing.

Modern radar is not only faced with the threat of high-speed flight guided missile and fighter plane in antiaircraft field, and in space industry, also need real time monitoring sky unoccupied orbital target, and therefore high speed highly maneuvering target is the new problem faced in modern radar target detection.Although DOD and the DOA Combined estimator algorithm of bistatic MIMO radar is widely studied, and emerges some effective algorithms, and most of algorithm does not consider the impact that the high-speed motion of target is estimated angle on target.In bistatic MIMO radar, effective formation of virtual array and the Chief Signal Boatswain time integral of echo are the keys that angle on target is estimated.The Doppler maximum frequency produced due to high-speed moving object can not be ignored the modulation transmitted within the matched filtering time, there is echoed signal serious distortion phenomenon, make matched filtering severe mismatch, thus cause MIMO radar effectively cannot form virtual array, cause traditional super resolution algorithm to be difficult to angle on target and estimate.Simultaneously, namely high-speed moving object can cross over multiple range unit at echo integration time in angle estimation process, namely target energy is dispersed on multiple range unit, therefore, when MIMO radar utilizes conventional super-resolution algorithm estimating target angle, first target energy must be focused on single range unit, otherwise the angle estimation precision of target can be affected.R.P.Perry etc. are distance calibration techniques conventional in a kind of radar in 188 pages to the 200 pages Keystone conversion proposed of IEEETransactionsonAerospaceandElectronicSystems periodical the 35th volume the 1st phase in 1999, it makes target echo envelope can align within long echo integration time by the change of scale of slow time shaft, due to still phase of echo relation can be retained in low signal-to-noise ratio situation, be therefore applicable to faint high-speed target and detect.But Keystone conversion can be lost efficacy when doppler ambiguity appears in target, but targeted cache motion will inevitably cause doppler ambiguity under the low-repetition-frequency restriction of radar signal, and Keystone conversion also cannot correct the range curvature caused by the radial acceleration of high speed highly maneuvering target, simultaneously because change of scale generally needs interpolation arithmetic to realize, therefore its operand is larger.Cascade Keystone conversion is applied in the multi-parameter estimation of multi-carrier frequency MIMO radar high-speed target at 2763 pages to 2768 pages of electronic letters, vol periodical the 38th volume the 12nd phase in 2010 by Qin Guodong, in order to avoid Keystone conversion was lost efficacy, the method is first carried out search to the doppler ambiguity number of high-speed moving object and is estimated, then the Doppler frequency difference utilizing Keystone transfer pair echo range walk respectively and cause in each split tunnel because transmitting carrier frequency is different corrects, thus solves MIMO radar to the Combined estimator of high-speed moving object multi-Dimensional parameters.But the Doppler frequency difference in different split tunnel caused by the acceleration of highly maneuvering target cannot be corrected by Keystone conversion, this can cause the virtual array of multi-carrier frequency MIMO radar effectively to be formed.Chen Jinli proposes a kind of method of bistatic MIMO radar high-speed moving object DOD and DOA electronics and information journal the 35th volume the 4th phase in 2013 859 pages to 864 pages, effectively add up to make the echo signal being dispersed in different distance unit, the method is averaged the sample covariance matrix that the object matching filtering be dispersed on different distance unit exports data, is improved the estimated accuracy of angle on target by the estimated accuracy improving covariance matrix.In order to avoid matched filter mismatch, the method expands its doppler tolerance by reducing matched filtering duration, but sacrifices the channel separation performance of matched filter, and the performance of the virtual array that MIMO radar is formed can not reach optimum.

Summary of the invention

For solving the problem, the invention discloses a kind of angle estimating method of bistatic MIMO radar high speed highly maneuvering target.

For achieving the above object, the method that the present invention adopts is: a kind of angle estimating method of bistatic MIMO radar high speed highly maneuvering target, comprises the steps:

(1) echoed signal of high speed highly maneuvering target, is received by the receiving array of bistatic MIMO radar;

(2), receiving array echo be positioned at transmitting on different distance unit and carry out conjugate multiplication;

(3), in fast time domain and slow time domain, Fourier transform is carried out successively to data after conjugate multiplication;

(4), target velocity is gone out according to the peak estimation in step 3 result;

(5), at the slow time frequency domain components of target that fast temporal frequency domain is extracted in different split tunnel along target Doppler frequency values;

(6), by the splicing of the target frequency domain data on different distance door, realize forming virtual array data across multiple range gate;

(7) super resolution algorithm, is utilized to estimate each objective emission angle and acceptance angle.

Beneficial effect:

The angle estimating method of a kind of bistatic MIMO radar high speed highly maneuvering target disclosed by the invention, compared with prior art tool has the following advantages:

(1) the high motion of automobile of the high speed of target causes conventional matched-filter severe mismatch, therefore bistatic MIMO radar effectively cannot form virtual array, thus make conventional super-resolution method be difficult to effective estimation of objective emission angle and reception, the inventive method is by carrying out the Fourier transform processing of fast time domain and slow time domain to data after receiving array echo and the conjugate multiplication that transmits, then the target frequency domain components in different split tunnel is extracted in, with the high motion of automobile of the high speed avoiding target on the impact of MIMO radar channel separation, virtual array is made to be able to effective formation.

(2) the present invention is by again splicing the target frequency domain components being dispersed in multiple range unit, thus can the target energy on different distance unit effectively be accumulated when angle on target is estimated, to improve the estimated accuracy of target DOD and DOA, and its operand is more much lower than existing range walk correction method, is conducive to Project Realization.

Accompanying drawing explanation

Fig. 1 is realization flow figure of the present invention;

Fig. 2 is bistatic MIMO radar structural representation of the present invention;

Fig. 3 is that the present invention carries out two-dimension fourier transform result figure to the data after conjugate multiplication that receiving array echo and different distance unit transmit;

The planisphere of Fig. 4 for utilizing traditional algorithm (ESPRIT algorithm) to estimate high-speed target angle;

Fig. 5 is the planisphere utilizing algorithm of the present invention to estimate high-speed target angle;

Fig. 6 is the angle estimation RMSE of target 1 and the graph of a relation of signal to noise ratio snr.

Embodiment

Below in conjunction with the drawings and specific embodiments, illustrate the present invention further, following embodiment should be understood and be only not used in for illustration of the present invention and limit the scope of the invention.It should be noted that, the word "front", "rear" of use is described below, "left", "right", "up" and "down" refer to direction in accompanying drawing, word " interior " and " outward " refer to the direction towards or away from particular elements geometric center respectively.

The angle estimating method of a kind of bistatic MIMO radar high speed highly maneuvering target of the present invention comprises the following steps:

Step 1, receives the echoed signal of high speed highly maneuvering target by the receiving array of bistatic MIMO radar.

Suppose that bistatic MIMO radar emission array and receiving array all adopt equidistant even linear array, be made up of M transmitting array element and N number of reception array element respectively, its array element distance is respectively d _tand d _r, as shown in Figure 2.Launch array element for M and launch mutually orthogonal cycle baseband phase coded signal, can be expressed as

$S(\tilde{t},t_l)={[S_1(\tilde{t},t_l)S_2(\tilde{t},t_l)\·\·\·S_M(\tilde{t},t_l)]}^T---\left(1\right)$

In formula, [] ^trepresent vector transposition; t _l=lT is the slow time, and wherein T is the repetition period of radar signal; wherein t is the fast time, 0≤t < T; be m and launch transmitting of array element.

Suppose to there is P high speed highly maneuvering target on identical initial Range resolution unit, its emission angle (DOD) is expressed as θ _t1, θ _t2..., θ _tP, acceptance angle (DOA) is expressed as θ _r1, θ _r2..., θ _rP, so (θ _tp, θ _rp) can represent p (p=1,2 ..., P) locus of individual target.P target makes uniformly accelrated rectilinear motion, makes v _p=v _tp+ v _rpand a _p=a _tp+ a _rpbe " radial velocity and " and " radial acceleration and " of p target, v _tpand v _rpbe p target relative to the radial velocity of emission array and receiving array, a _tpand a _rpbe p target relative to the radial acceleration of emission array and receiving array.The distance of high-speed target movement within echoed signal integration time is less than its distance from emission array and receiving array, and therefore the subtle change that occurs within echo integration time of target DOA and DOD is negligible.Receiving array base band echoed signal can be expressed as

$X(\tilde{t},t_l)=\underset{p=1}{\overset{P}{\mathrm{\&Sigma;}}}{a}_r\left({\mathrm{\&theta;}}_{\mathrm{rp}}\right){\mathrm{\&rho;}}_p{a}_t^T\left({\mathrm{\&theta;}}_{\mathrm{tp}}\right)S(\tilde{t}-\frac{v_p\tilde{t}}{c}-\frac{a_p\widetilde{t^2}}{2c},t_l)e^{-j2\mathrm{\&pi;}(f_{\mathrm{dp}}\tilde{t}+\frac{a_p}{2\mathrm{\&lambda;}}\widetilde{t^2})}+\mathrm{\&omega;}(\tilde{t},t_l)---\left(2\right)$

In formula, for the output echoed signal vector of receiving array; ρ _prepresent the scattering coefficient of p target; $a_r\left({\mathrm{\&theta;}}_{\mathrm{rp}}\right)={[1e^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;})d_r{\sin \mathrm{\&theta;}}_{\mathrm{rp}}}\&CenterDot;\&CenterDot;\&CenterDot;e^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;})(N-1)d_r{\sin \mathrm{\&theta;}}_{\mathrm{rp}}}]}^T$ To be size be receiving array steering vector that N × 1 ties up, λ is carrier wavelength; $a_r\left({\mathrm{\&theta;}}_{\mathrm{rp}}\right)={[1e^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;})d_r{\sin \mathrm{\&theta;}}_{\mathrm{rp}}}\&CenterDot;\&CenterDot;\&CenterDot;e^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;})(N-1)d_r{\sin \mathrm{\&theta;}}_{\mathrm{rp}}}]}^T$ To be size be emission array steering vector that M × 1 ties up; f _dpt () is the Doppler frequency of p target, can be expressed as f _dp=(v _tp+ v _rp)/λ=v _p/ λ; λ is wavelength; for the noise vector of receiving array, obey zero-mean, variance is multiple Gaussian distribution, namely wherein I _nfor the unit matrix of N × N.The envelope variation caused by acceleration within whole echo integration time is much smaller than range resolution, and be also very small by the envelope variation that target velocity is caused within the fast time, therefore by aimed acceleration within echo integration time and the envelope variation that causes within the fast time of target velocity can ignore.Therefore formula (2) can be reduced to

$X(\tilde{t},t_l)\&ap;\underset{p=1}{\overset{P}{\mathrm{\&Sigma;}}}{a}_r\left({\mathrm{\&theta;}}_{\mathrm{rp}}\right){\mathrm{\&rho;}}_p{a}_t^T\left({\mathrm{\&theta;}}_{\mathrm{tp}}\right)S(\tilde{t}-\frac{v_p{t}_l}{c},t_l)e^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}}t}\&CenterDot;e^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}}{t}_l}{e}^{{-\mathrm{j\&pi;a}}_p{{t_l}^2}_{}/\mathrm{\&lambda;}}+\mathrm{\&omega;}(\tilde{t},t_l)---\left(3\right)$

From formula (3), within long echo integration time, the distance change of high-speed moving object is often greater than the range resolution of radar, then target echo envelope can occur phenomenon of walking about within integration time; And the Doppler frequency variation range caused by aimed acceleration can be greater than Doppler's resolution element, then there are target Doppler diffusion phenomena, but because aimed acceleration causes caused phase place change to be very small within the fast time, therefore only consider the phase place change that aimed acceleration produces in slow time domain in formula (3) in the 3rd exponential term.The range walk of high-speed target and Doppler's diffusion phenomena cause target energy to be dispersed on multiple range unit and doppler cells.First exponential term in formula (3) represents that Doppler frequency can be modulated transmitting in the fast time, and the Doppler frequency due to high-speed moving object is often greater than the half of radar signal repetition frequency, namely the phase place change that then Doppler frequency is caused within the fast time be can not ignore, namely can there is serious distortion in echoed signal, cause the severe mismatch of matched filter, thus effectively cannot form virtual array, therefore bistatic MIMO radar is difficult to effectively estimate high speed highly maneuvering target DOD and DOA.

Step 2, receiving array echo be positioned at transmitting on different distance unit and carry out conjugate multiplication.

High speed highly maneuvering target produces Doppler maximum frequency and not only destroys the orthogonality between transmitting, and make the mismatch loss of matched filter serious, and the power dissipation of high speed highly maneuvering target is on different resolution elements, what this all can cause bistatic MIMO radar cannot form effective virtual array, and then affects the estimation of angle on target parameter.Make z _p(t _l) the range unit number crossed within the 1st cycle that transmits for p target, z _p(t _l) value is integer, wherein target and the Range resolution unit δ=c/B corresponding to the Distance geometry between emission array and receiving array, B is transmitted signal bandwidth, so

In formula, represent the smallest positive integral being more than or equal to b.Can to ignore the impact of echo envelope because the target range less than distance by radar resolution is walked about, therefore formula (3) can be reduced to

$X(\tilde{t},t_l)\&ap;\underset{p=1}{\overset{P}{\mathrm{\&Sigma;}}}{a}_r\left({\mathrm{\&theta;}}_{\mathrm{rp}}\right){\mathrm{\&rho;}}_p{a}_t^T\left({\mathrm{\&theta;}}_{\mathrm{tp}}\right)S(\tilde{t}-\frac{v_p{t}_l}{c},t_l)e^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}}t}\&CenterDot;e^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}}{t}_l}{e}^{{-\mathrm{j\&pi;a}}_p{{t_l}^2}_{}/\mathrm{\&lambda;}}+\mathrm{\&omega;}(\tilde{t},t_l)---\left(5\right)$

The range unit number that hypothetical target is crossed within echo integration time is in [-Z, Z], and wherein Z is integer.So be used in the reference signal on z (z ∈ [-Z, Z]) range unit at receiving end the echo of array element is received to n-th carry out conjugate multiplication, can the output of conjugate multiplication on z range unit be

$\begin{array}{c}{Y}_{\mathrm{mn}}(t,t_l,z)=\underset{p\&Element;C_{\mathrm{zl}}}{\overset{P}{\underset{p=1}{\mathrm{\&Sigma;}}}}{\mathrm{\&beta;}}_p{\left(z\right)e}^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;})(n-1)d_r{\sin \mathrm{\&theta;}}_{\mathrm{rp}}}{\&CenterDot;e^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;})\left(\text{m-1}\right)d_t{\sin \mathrm{\&theta;}}_{\mathrm{tp}}}e}^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}}\text{t}}\&CenterDot;e^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}}{t}_l}{e}^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}}{{t_l}^2}_{}/\mathrm{\&lambda;}}\\ +{\mathrm{\&phi;}}_{\mathrm{mn}}(t,t_l,z)+W_{\mathrm{mn}}(t,t_l,z)\end{array}---\left(6\right)$

Formula ⁱⁿ, C _zlfor p meets z _p(t _l)=z (p=1,2 ..., value p) ^collectionclose; ψ (z) represents the initial phase of target p echo on z range unit; in formula (6), Section 1 is owing to working as z _p(t _lduring)=z and formed, in fast time domain, Section 1 becomes sinusoidal signal, and wherein [] * represents and gets complex conjugate; Section 2 φ in formula (6) _mn(t, t _l, z) can be expressed as

$\begin{array}{c}{\mathrm{\&phi;}}_{\mathrm{mn}}(\tilde{t},t_l,z)=\underset{p\&Element;C_{\mathrm{zl}}}{\overset{P}{\underset{p=1}{\mathrm{\&Sigma;}}}}{\mathrm{\&beta;}}_p{\left(z\right)e}^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;}){(n-1)d}_r{\sin \mathrm{\&theta;}}_{\mathrm{rp}}}\&CenterDot;\underset{i\&NotEqual;m}{\overset{M}{\underset{i=1}{\mathrm{\&Sigma;}}}}{e}^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;}){(i-1)d}_r{\sin \mathrm{\&theta;}}_{\mathrm{tp}}}{S}_i(t+t_l-\frac{\mathrm{z\&delta;}}{c},t_l)S_m^{*}(t+t_l-\frac{\mathrm{z\&delta;}}{c},t_l)\\ \&CenterDot;e^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}}t}\&CenterDot;e^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}}{t}_l}{e}^{{-\mathrm{j\&pi;a}}_p{t_l}^2/\mathrm{\&lambda;}}+\underset{p\&NotElement;C_{\mathrm{zl}}}{\overset{P}{\underset{p=1}{\mathrm{\&Sigma;}}}}{\mathrm{\&beta;}}_p{e}^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;}){(N-1)d}_r{\sin \mathrm{\&theta;}}_{\mathrm{rp}}}{a_t}^T\left({\mathrm{\&theta;}}_{\mathrm{tp}}\right)\\ \&CenterDot;S(t+t_l-\frac{z_p\left(t_l\right)\mathrm{\&delta;}}{c},t_l)S_m^{*}(t+t_l-\frac{\mathrm{z\&delta;}}{c},t_l)e^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}}t}\&CenterDot;e^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}}{t}_l}{e}^{{-\mathrm{j\&pi;a}}_p{t_l}^2/\mathrm{\&lambda;}}\end{array}---\left(7\right)$

Step 3, carries out Fourier transform in fast time domain and slow time domain successively to data after conjugate multiplication.

In fast time domain to Y _mn(t, t _l, z) carry out Fourier transform, can obtain

$\begin{array}{c}{Y}_{\mathrm{mn}}(f,t_l,z)={\&Integral;}_0^T{Y}_{\mathrm{mn}}{(t,t_l)e}^{-j2\mathrm{\&pi;ft}}\mathrm{dt}\\ =\underset{p\&Element;C_{\mathrm{zl}}}{\overset{P}{\underset{p=1}{\mathrm{\&Sigma;}}}}{\mathrm{\&beta;}}_p{\left(z\right)e}^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;}){(n-1)d}_r{\sin \mathrm{\&theta;}}_{\mathrm{rp}}}\&CenterDot;e^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;}){(m-1)d}_t{\sin \mathrm{\&theta;}}_{\mathrm{tp}}}\&CenterDot;\frac{\sin \left[\mathrm{\&pi;}(f+f_{\mathrm{dp}})T\right]}{\mathrm{\&pi;}(f+f_{\mathrm{dp}})T}\\ \&CenterDot;e^{-\mathrm{j\&pi;}(f+f_{\mathrm{dp}})T}\&CenterDot;e^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}}{t}_l}{e}^{{-\mathrm{j\&pi;a}}_p{t_l}^2/\mathrm{\&lambda;}}+{\mathrm{\&phi;}}_{\mathrm{mn}}(f,t_l,z)+W_{\mathrm{mn}}(f,t_l,z)\end{array}----\left(8\right)$

The Doppler frequency of high-speed moving object is often greater than the repetition frequency of radar signal, now there will be lack sampling phenomenon.In this case, the true Doppler frequency of target p can be expressed as

f _dp＝f _dp0+n _p/T(9)

In formula, f _dp0for not ambiguous Doppler frequency; n _pfor doppler ambiguity number.Formula (9) is substituted into formula (8), can obtain

$\begin{array}{c}{Y}_{\mathrm{mn}}(f,t_l,z)=\underset{p\&Element;C_{\mathrm{zl}}}{\overset{P}{\underset{p=1}{\mathrm{\&Sigma;}}}}{\mathrm{\&beta;}}_p{\left(z\right)e}^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;}){(n-1)d}_r{\sin \mathrm{\&theta;}}_{\mathrm{rp}}}\&CenterDot;e^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;}){(m-1)d}_t{\sin \mathrm{\&theta;}}_{\mathrm{tp}}}\&CenterDot;\frac{\sin \left[\mathrm{\&pi;}(f+f_{\mathrm{dp}})T\right]}{\mathrm{\&pi;}\left(f{+f}_{\mathrm{dp}}\right)T}\\ \&CenterDot;e^{-\mathrm{j\&pi;}(f+f_{\mathrm{dp}})T}\&CenterDot;e^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}0}{t}_l}\&CenterDot;e^{-j2\mathrm{\&pi;}(n_p/T)t_l}\&CenterDot;e^{{-\mathrm{j\&pi;a}}_p{t_l}^2/\mathrm{\&lambda;}}+{\mathrm{\&phi;}}_{\mathrm{mn}}(f,t_l,z)+W_{\mathrm{mn}}(f,f_l,z)\end{array}---\left(10\right)$

Due to 2 π (n in the 3rd exponential term in formula (10) the 2nd row _p/ T) t _lthe integral multiple of 2 π, namely therefore formula (10) can be expressed as again

$\begin{array}{c}{Y}_{\mathrm{mn}}(f,t_l,z)=\underset{p\&Element;C_{\mathrm{zl}}}{\overset{P}{\underset{p=1}{\mathrm{\&Sigma;}}}}{\mathrm{\&beta;}}_p{\left(z\right)e}^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;}){(n-1)d}_r{\sin \mathrm{\&theta;}}_{\mathrm{rp}}}\&CenterDot;e^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;}){(m-1)d}_t{\sin \mathrm{\&theta;}}_{\mathrm{tp}}}\&CenterDot;\frac{\sin \left[\mathrm{\&pi;}(f+f_{\mathrm{dp}})T\right]}{\mathrm{\&pi;}\left(f{+f}_{\mathrm{dp}}\right)T}\\ \&CenterDot;e^{-\mathrm{j\&pi;}(f+f_{\mathrm{dp}})T}\&CenterDot;e^{{-j2\mathrm{\&pi;f}}_{\mathrm{dp}0}{t}_l}\&CenterDot;\&CenterDot;e^{{-\mathrm{j\&pi;a}}_p{t_l}^2/\mathrm{\&lambda;}}+{\mathrm{\&phi;}}_{\mathrm{mn}}(f,t_l,z)+W_{\mathrm{mn}}(f,f_l,z)\end{array}---\left(11\right)$

Suppose that the signal energy of p target on z range unit appears at the repetition period and be numbered l=L _pmin, L _pmin+ 1 ..., L _pmaxmoment in, in slow time domain to formula (8) about t _lcarry out Fourier transform, can be obtained by the resident theorem of phase place,

$\begin{array}{c}{Y}_{\mathrm{mn}}(f,f_l,z)\&ap;\underset{p\&Element;C_{\mathrm{zl}}\&Element;}{\overset{P}{\underset{p=1}{\mathrm{\&Sigma;}}}}{\mathrm{\&beta;}}_p{\left(z\right)e}^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;}){(n-1)d}_r{\sin \mathrm{\&theta;}}_{\mathrm{rp}}}\&CenterDot;e^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;}){(m-1)d}_r{\sin \mathrm{\&theta;}}_{\mathrm{tp}}}\&CenterDot;\frac{\sin \left[\mathrm{\&pi;}(f+f_{\mathrm{dp}})T\right]}{\mathrm{\&pi;}(f+f_{\mathrm{dp}})T}{e}^{-\mathrm{j\&pi;}(f+f_{\mathrm{dp}})T}\\ \&CenterDot;\mathrm{rect}\left[\frac{f_l+f_{\mathrm{dp}0}}{(L_{\mathrm{pamx}}-L_{p\min })T\&CenterDot;a_p/\mathrm{\&lambda;}}\right]e^{\mathrm{j\&pi;}{(f_t+f_{\mathrm{dp}0})}^2/\left({a_p/\mathrm{\&lambda;}}_{}\right)}{e}^{-\mathrm{j\&pi;f}1(L_{\mathrm{pamx}}+L_{p\min })T}+{\mathrm{\&xi;}}_{\mathrm{mn}}(f,f_l,z)\end{array}---\left(12\right)$

In formula, ζ _mn(f, fl, z)=φ _mn(f, f _l, z)+W _n(f, f _l, z).From formula (12), due to the existence of aimed acceleration, the frequency spectrum of target in slow time domain is made to there will be broadening phenomenon.

Step 4, goes out target velocity according to the peak estimation in step 2 result.

Owing to there is the echoed signal of each target on initial distance door z=0, frequency domain data Y on initial distance door therefore can be utilized _mn(f, f _l, z=0) and (m=1,2, ..., M, n=1,2, ..., N) Doppler frequency of estimating target and ambiguous Doppler frequency, in order to improve the main secondary lobe of target peak than to be conducive to target detection, can combine the frequency domain data that all about difference launches array element and receive array element and estimating, namely the Doppler frequency of target p and ambiguous Doppler frequency are estimated by following formula

$(\widehat{f_{\mathrm{dp}}},\widehat{f_{\mathrm{dp}0}})=\underset{f,f_l}{\arg \max }\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}\underset{n-1}{\overset{N}{\mathrm{\&Sigma;}}}\left|Y_{\mathrm{mn}}(-f,{-f}_{l}z=0)\right|---\left(13\right)$

In engineer applied, for reducing operand, Fourier transform is replaced by fast fourier transform.Due to estimated value be the integral multiple of radar signal repetition frequency, therefore can not utilize estimated value with separate target velocity fuzzy, therefore " radial velocity and " estimated value of target velocity target p only by conversion obtains,

$\widehat{v_p}=\mathrm{\&lambda;}\&CenterDot;\widehat{f_{\mathrm{dp}}}---\left(14\right)$

Step 5, at the slow time frequency domain components of target that fast temporal frequency domain is extracted in different split tunnel along target Doppler frequency values.

In by fast temporal frequency domain, extract target at slow time frequency domain components along target Doppler frequency values, can be expressed as

$Y_{\mathrm{mn}}(-\stackrel{}{v_{\text{p}}}/\mathrm{\&lambda;},f_l,z)=e^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;}){(n-1)d}_r{\sin \mathrm{\&theta;}}_{\mathrm{rp}}}\&CenterDot;e^{-j(2\mathrm{\&pi;}/\mathrm{\&lambda;}){(m-1)d}_t{\sin \mathrm{\&theta;}}_{\mathrm{tp}}}\&CenterDot;H_p(-\widehat{v_p}/\mathrm{\&lambda;}{,f}_l,z)+{\mathrm{\&xi;}}_{\mathrm{mn}}(-\widehat{v_p}/\mathrm{\&lambda;},f_l,z),p\&Element;C_{\mathrm{zl}}---\left(15\right)$

In formula,

$H_p(-\widehat{v_p}/\mathrm{\&lambda;},f_l,z)={\mathrm{\&beta;}}_p{\left(z\right)e}^{-\mathrm{j\&pi;}(\widehat{v_p}/\mathrm{\&lambda;}+f_{\mathrm{dp}})T}\&CenterDot;\mathrm{rect}\left[\frac{f_l+f_{\mathrm{dp}0}}{(L_{p\max }-L_{p\min })T\&CenterDot;a_p/\mathrm{\&lambda;}}\right]\&CenterDot;e^{-\mathrm{j\&pi;}{\left(f_l{+f}_{\mathrm{dp}0}\right)}^2/(a_p/\mathrm{\&lambda;})}{e}^{-j\mathrm{\&pi;}{f}_t(L_{p\max }+L_{p\min })T}.$

mn the channel components that the target p echoed signal on distribution z range unit is formed through above-mentioned process in fact, m=1,2 ..., M, n=1,2 ..., N.So can obtain according to same method and be distributed in the component of signal of target p echoed signal in other split tunnels on z range unit, then on z range unit, the signal of target p in all MN split tunnel can be expressed as

$(-\widehat{v_p},\mathrm{\&lambda;},f_l,z)=({\mathrm{\&theta;}}_{\mathrm{rp}},{\mathrm{\&theta;}}_{\mathrm{tp}})H_P(-\widehat{v_p}/\mathrm{\&lambda;},f_l,z)+\mathrm{\&xi;}(-\widehat{v_p}/\mathrm{\&lambda;},f_l,z),C_{\mathrm{zl}}---\left(16\right)$

In formula, $Y(-\widehat{v_p}/\mathrm{\&lambda;},f_l,z)={[Y_1(-\widehat{v_p}/\mathrm{\&lambda;},f_l,z),Y_2(-\widehat{v_p}/\mathrm{\&lambda;},f_l,z),...,Y_{\mathrm{MN}}(-\widehat{v_p}/\mathrm{\&lambda;},f_l,z)]}^T;$ A (θ _rp, θ _tp)= for Kronecker amasss; be be MN × 1 n dimensional vector n, be made up of the mutual distracter of the noise after channel separation and echo signal. be exactly that target p is distributed in the virtual array that the echoed signal on z range unit formed after above-mentioned process and exports data in fact.

Step 6, by the splicing of the target frequency domain data on different distance door, realizes forming virtual array data across multiple range gate.

If target p is away from radar motion, known according to formula (13), its range unit crossed within echo integration time is respectively z _p=0,1 ..., Z _p, the virtual array data be distributed in by target p on all range units are spliced by formula (17),

$\widetilde{Y_{\mathrm{pl}}}=[Y(-\widehat{v_p}/\mathrm{\&lambda;},f_l,0)Y(-\widehat{v_p/\mathrm{\&lambda;},f_l,1}),...,Y(-\widehat{v_p}/\mathrm{\&lambda;},f_l,Z_p)]---\left(17\right)$

The output data of virtual array after splicing covariance matrix be

$R_p=\frac{1}{Z_{p}L}\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}\widetilde{Y_{\mathrm{pl}}}\&CenterDot;\widetilde{Y_{\mathrm{pl}}^H}=\frac{1}{Z_p}\underset{z=0}{\overset{Z_p}{\mathrm{\&Sigma;}}}\frac{1}{L}\&CenterDot;\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}Y(-\widehat{v_p}/\mathrm{\&lambda;},f_l,z)Y^H(-\widehat{v_p}/\mathrm{\&lambda;},f_l,z)---\left(18\right)$

In formula, () ^hrepresent conjugate transpose; L is the fast umber of beats for estimate covariance matrix.After the virtual array data of target p on all range units are spliced by formula (17), its fast umber of beats becomes Z _pl, therefore can improve the estimated accuracy of covariance matrix, thus the estimated accuracy of the emission angle of target p and acceptance angle also can be improved thereupon.If target p is towards radar motion, known according to formula (13), its range unit crossed within echo integration time is respectively z _p=0 ,-1 ... ,-Z _p, the virtual array data be distributed in by target p on all range units carry out similar splicing, namely

$\widetilde{Y_{\mathrm{pl}}}=[Y(-\widehat{v_p}/\mathrm{\&lambda;},f_l,0)Y(-\widehat{v_p/\mathrm{\&lambda;},f_l,1}),...,Y(-\widehat{v_p}/\mathrm{\&lambda;},f_l,{-Z}_p)]---\left(19\right)$

The output data of virtual array after splicing covariance matrix be

$R_p=\frac{1}{Z_{p}L}\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}\widetilde{Y_{\mathrm{pl}}}\&CenterDot;\widetilde{Y_{\mathrm{pl}}^H}=\frac{1}{Z_p}\underset{z=-Z}{\overset{0}{\mathrm{\&Sigma;}}}\frac{1}{L}\&CenterDot;\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}Y(-\widehat{v_p}/\mathrm{\&lambda;},f_l,z)Y^H(-\widehat{v_p}/\mathrm{\&lambda;},f_l,z)---\left(20\right)$

Step 7, utilizes super resolution algorithm to estimate each objective emission angle and acceptance angle.

To covariance matrix R _pcarry out feature decomposition to have

$R_p=U_s{\mathrm{\&Sigma;}}_S{U_s}^H+U_n{\mathrm{\&Sigma;}}_n{U_n}^H---\left(21\right)$

In formula, Σ _sfor scalar, the large eigenwert of corresponding target p, this is because virtual array exports data in only there is target p; Σ _nfor diagonal matrix, diagonal element is made up of little eigenwert; with be respectively signal subspace and the noise subspace of virtual array.U _s=A (θ _rp, θ _tp) T, when there is single target, T is scalar.Order so A'(θ _rp, θ _tp) can by A (θ _rp, θ _tp) obtain through several times line translation, so adopt identical line translation can from U _sin can obtain U' _s, suppose U _s1and U _s2be respectively U _sbefore (N-1) M capable and rear (N-1) M capable; And U' _s1and U' _s2be respectively U' _sbefore (M-1) N capable and rear (M-1) N capable.Order

$r_{\mathrm{rp}}=\frac{1}{M(N-1)}\underset{i=1}{\overset{M(N-1)}{\mathrm{\&Sigma;}}}\frac{U_{s2}\left(i\right)}{U_{\mathrm{sl}}\left(i\right)}---\left(22\right)$

$r_{\mathrm{rp}}=\frac{1}{N(M-1)}\underset{i=1}{\overset{N(M-1)}{\mathrm{\&Sigma;}}}\frac{{U^{\&prime;}}_{s2}\left(i\right)}{{U^{\&prime;}}_{\mathrm{sl}}\left(i\right)}---\left(23\right)$

In formula, U _s1(i) and U _s2i () is U respectively _s1and U _s2in i-th row element; U' _s1(i) and U' _s2i () is respectively U' _s1and U' _s2in i-th row element.So DOA θ of target p _rpwith DOD θ _tpestimated value is respectively

$\widehat{{\mathrm{\&theta;}}_{\mathrm{rp}}}=\arcsin (-\mathrm{\&lambda;}\&CenterDot;\frac{\mathrm{angle}\left(r_{\mathrm{rp}}\right)}{{2\mathrm{\&pi;d}}_r})---\left(24\right)$

$\widehat{{\mathrm{\&theta;}}_{\mathrm{rp}}}=\arcsin (-\mathrm{\&lambda;}\&CenterDot;\frac{\mathrm{angle}\left(r_{\mathrm{tp}}\right)}{{2\mathrm{\&pi;d}}_t})---\left(25\right)$

The acceptance angle of other targets and emission angle also can adopt same method to obtain.

Technique effect of the present invention can be further illustrated by following simulation result.

Radar system parameters describes: the carrier frequency of bistatic MIMO radar is f ₀=10GHz, launches array number M=6, receives array number N=8, transmitting and receiving array element distance d _t=d _r=1.5cm.The each array element of emission array launches mutually orthogonal Gold coded signal, symbol width τ=0.1 _{μ s}, the phase encoding length within the cycle is 1023, radar signal cycle T=102.3 _{μ s}signal repetition period number L=128 within echo integration time.

Emulation content 1: the Fourier transform results of data in fast time domain and slow time domain after conjugate multiplication.

Simulated conditions: suppose to there are 3 high-speed targets on same initial Range resolution unit, their emission angle and acceptance angle are respectively (θ _t1, θ _r1)=(30 °, 60 °), (θ _t2, θ _r2)=(5 °, 40 °), (θ _t3, θ _r3)=(25 °, 10 °), the radial velocity of 3 targets and be respectively 7500m/s, 9000m/s, 6500m/s, radial acceleration and be respectively 400m/s ², 500m/s ², 450m/s ², the signal to noise ratio snr=-30dB of three high-speed targets.In simulations by receiving array echoed signal respectively be positioned at transmitting on different distance unit and carry out conjugate multiplication, then carry out fast Fourier transform (FFT) process in fast time domain and slow time domain, result is as shown in Figure 3.As can be seen from Figure 3, existence 3 high-speed targets in radar detection area, the signal energy of one of them target is dispersed in z=0, on 1,2 range units, namely 3 range units are spanned at echo internal object integration time, and the signal energy of two objects is dispersed in z=0,1,2 in addition, on 3 range units, namely span 4 range units at echo internal object integration time; Target echo signal energy conversion can be represented in fast time speed-slow time Speed Two Dimensions region by context of methods process, can without the speed of 3 of a blur estimation high-speed target according to fast time speed territory, wherein the fast time velocity estimation value of 3 targets is respectively 7625.8m/s, 9092.3m/s, 6452.6m/s, but cause speed estimation error comparatively large because speed resolution is lower, relative error is respectively 1.7%, 1.03%, 0.73%.But there is fuzzy problem in the target velocity of carrying out estimated by FFT process in slow time domain.

Emulation content 2: bistatic MIMO radar utilizes traditional algorithm and algorithm of the present invention to estimate the planisphere of high-speed target angle.

Simulated conditions: target component is arranged with emulation content 1.Bistatic MIMO radar utilizes DOD and DOA of traditional algorithm and algorithm estimating target of the present invention respectively, the ESPRIT algorithm being applied to bistatic MIMO radar that traditional algorithm adopts Chen Duofang to propose at the 44th phase the 12nd volumes in 2008 the 770th page to 771 pages of ElectronicsLetters periodical.Fig. 4 and Fig. 5 is respectively the parameter planisphere that bistatic MIMO radar utilizes traditional algorithm and the inventive method to estimate, in figure, "+" represents the actual position of target, carries out 150 MonteCarlo experiments.From Figure 4 and 5, traditional algorithm has been difficult to the parameter estimation of high-speed moving object under the impact such as range migration and matched filter mismatch; Algorithm of the present invention effectively can form virtual array, and can accumulate target inband energy across range gate, therefore can effectively estimate DOD and DOA of high speed highly maneuvering target and accurately match, can the multiple high speed highly maneuvering target of effective location.

Emulation content 3: the relation of high-speed target angle estimation RMSE and signal to noise ratio snr.

Simulated conditions: suppose that the signal to noise ratio snr of three high-speed targets changes between-30dB ~ 0dB, other simulation parameters are with emulation content 1.The root-mean-square error of objective definition angle estimation is wherein θ _rwith θ _tbe respectively estimated value and the actual value of intended recipient angle DOA and emission angle DOD.Independently carry out 200 Monte-Carlo experiment, when the bistatic MIMO radar of Fig. 6 utilizes the inventive method and classic method, the variation relation of target 1 angle estimation root-mean-square error and target signal to noise ratio as shown.There is acceleration in target in the inventive method, target emulates without acceleration and namely only do not utilize initial distance door to form virtual array data estimation angle on target situation across range gate estimating target angle under respectively, and classic method has acceleration (target component arrange with emulation content 1) and target low speed and without emulating in acceleration situation at targeted cache respectively, wherein target low speed is set to 55m/s respectively without 3 target velocities during acceleration situation, 0m/s, 100m/s, other parameters are with emulation content 1.As can be seen from Figure 6, the inventive method effectively can estimate emission angle and the acceptance angle parameter of high speed highly maneuvering target, its angle estimation precision close to classic method at target low-speed situations namely without the angle estimation precision in the situations such as range walk and matched filter mismatch, but classic method exist target range walk about and matched filter mismatch time can lose efficacy, be namely unable to estimate the angle parameter of high speed highly maneuvering target; The angle estimation performance of the inventive method affects less by aimed acceleration; The inventive method is by carrying out data splicing the target frequency domain components of destination scatter in multiple range gate, realize forming virtual array data across multiple range gate, therefore its angle estimation precision is apparently higher than the precision only utilizing the target frequency domain data in single range gate to carry out angle estimation.

Technological means disclosed in the present invention program is not limited only to the technological means disclosed in above-mentioned technological means, also comprises the technical scheme be made up of above technical characteristic combination in any.The above is the specific embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications are also considered as protection scope of the present invention.

Claims (1)

1. an angle estimating method for bistatic MIMO radar high speed highly maneuvering target, is characterized in that: comprise the steps:

(1) echoed signal of high speed highly maneuvering target, is received by the receiving array of bistatic MIMO radar;

(2), receiving array echo be positioned at transmitting on different distance unit and carry out conjugate multiplication;

(3), in fast time domain and slow time domain, Fourier transform is carried out successively to data after conjugate multiplication;

(4), target velocity is gone out according to the peak estimation in step 3 result;

(5), at the slow time frequency domain components of target that fast temporal frequency domain is extracted in different split tunnel along target Doppler frequency values; (6), by the splicing of the target frequency domain data on different distance door, realize forming virtual array data across multiple range gate;

(7) super resolution algorithm, is utilized to estimate each objective emission angle and acceptance angle.