Research On Models And Algorithms Of Airborne Multiple-input Multiple-output Radar Space-time Adaptive Processing

As a rising radar system,multiple-input multiple-output(MIMO)radar owns a lot of potentials to improve the capabilities of traditional radar as well as a wide range of applications,which has attracted extensive and sustaining attention by the military and academia at home and abroad.As a core technology of the new generation airborne early warning radar,space-time adaptive processing(STAP)can effectively realize the functions of ground clutter suppression and ground moving target indication(GMTI).Nowadays,the organic integration of the airborne MIMO radar system and STAP technology has been further achieved,and MIMO radar STAP immediately becomes one of the research hotspots in the international radar field.Aiming at the STAP technology of airborne MIMO radar,this dissertation focuses on the contents including the non-homogeneous sample detection,the algorithm realization in the error condition and the jamming environment,as well as the MIMO-STAP models and algorithms under the transmit beamspace and polarization cases.The main work and innovations of this dissertation are summarized as follow:1.The performance of target detection in MIMO radar STAP decreases when the covariance matrix is estimated with training samples contaminated by target-like signals.To solve the problem,a knowledge-aided(KA)generalized inner product(GIP)method for non-homogeneous samples detection is proposed.Firstly,two kinds of the clutter subspace knowledge are utilized to construct the clutter covariance matrix offline.One is estimated by prolate spheroidal wave functions(PSWF),and the other is off-line constructed based on the system parameters.Then,the GIP non-homogeneity detector(GIP NHD)is integrated to realize the effective selection of training samples,which eliminates the effect of the target-like signals in training samples on target detection.The simulation results show that compared with the conventional GIP method,the KA-GIP method can screen out contaminated training samples more effectively and improve the target detection performance of MIMO radar STAP.Thus the proposed KA-GIP method is more valuable for practical engineering application.2.To solve the problem of the mismatch errors between the actual and presumed signal steering vectors in airborne MIMO radar STAP,a robust reduced-dimension MIMO-STAP method based on tri-iterative algorithm(TRIA)and second-order cone programming(SOCP)is proposed.Firstly,the MIMO-STAP weight vector is decomposed into the Kronecker product of the transmit,the receive and the Doppler weight vectors.Then,by imposing a bound on the errors between the actual transmit,receive and Doppler steering vectors and the presumed steering vectors,respectively,the optimization of the worst case performance is executed and transformed into the SOCP formulation.Further,the TRIA is utilized to resolve the three low dimension weight vectors,and finally the full dimension MIMO-STAP weight vector is synthesized.The proposed method can significantly decrease the training sample requirement and the computational complexity while maintaining the robust STAP performance of airborne MIMO radar,which is more valuable for practical engineering application.3.Airborne MIMO radar will confront the jamming environment when operating in practice.Aiming at the above problem,a reduced-rank(RR)MIMO-STAP method for simultaneous clutter plus jamming suppression and a reduced-dimension(RD)MIMO-STAP method for cascaded clutter plus jamming suppression are proposed,respectively.In the RR MIMO-STAP method,the total data covariance matrix is expressed as the sum of a low-rank clutter covariance matrix and a block-diagonal jamming-plus-noise covariance matrix.Then,through utilizing the zero-forcing method and combined with the convenient off-line clutter subspace,the simplified calculation form of the weight vector can be obtained based on the matrix inversion lemma.Meanwhile,the accurate estimation of the low-dimension jamming plus noise covariance matrix can be achieved by an auxiliary channel allocated with the matched filter orthogonal to all the transmit waveforms of MIMO radar.The proposed RR MIMO-STAP method can effectively realize the simultaneous clutter plus jamming suppression.The approximate full-dimension optimum performance can be provided,and the computational burden can be significantly alleviated.The proposed RD MIMO-STAP method proceeds in two steps based on the different signal characteristics between jamming and clutter,for the sake of separate jamming and clutter suppression.Firstly,the orthogonal complementary subspace of jamming is obtained,and then it is utilized as the transformation matrix to cancel the jamming,while the receive dimension is reduced.Secondly,the TRIA is utilized to suppress the clutter combining the remaining receive DOF with the transmit DOF and the Doppler DOF,and further dimension reduction is implemented.Based on the above two steps,the proposed method can effectively achieve the consequence of cascaded jamming and clutter elimination.Moreover,the training sample number and the computational complexity are significantly decreased.4.The output signal-to-clutter-plus-noise ratio(SCNR)of traditional airborne MIMO radar STAP decreases because of the transmit power dispersion.To solve this problem,a MIMO-STAP method based on transmit beamspace(TB)-TRIA is proposed.Firstly,the signal model of the TB-based MIMO radar STAP is established.Two optimizing criterions for designing the TB weight matrix based on the spheroidal sequence and SOCP,respectively,are proposed to focus all transmit power within the desired spatial sector.Then,the clutter-to-noise ratio(CNR)of the TB-based MIMO radar is analyzed to show its relationship with the total transmit power.The calculation result is further provided to illustrate that the CNR of the TB-based MIMO radar is reduced compared with that of the traditional MIMO radar with uniform omni-directional transmission.Furthermore,in order to decrease the training sample requirement and the computational complexity of the TB-based MIMO-STAP,the TRIA is utilized to resolve the reduced-dimension weight vectors.The theoretical analysis and simulation results show that,through the corresponding tri-iterative reduced-dimension processing,the TB-based MIMO-STAP can achieve the improvement of the output SCNR,compared to the traditional MIMO-STAP with uniform omni-directional transmission.Moreover,the computational burden is further decreased.5.In order to further improve the capability of clutter suppression and target detection of traditional MIMO-STAP in the low Doppler frequency region,the polarization-space-time adaptive processing(PSTAP)method based on polarization array MIMO radar is proposed.Firstly,the signal model of airborne polarization array MIMO radar PSTAP is established.Then based on the idea of resolution grid,an equivalent expression of the covariance matrix in polarization array MIMO radar PSTAP is obtained.Next,combined with the equivalent covariance matrix,the SCNR performance of the polarization array MIMO radar PSTAP is derived and analyzed.The theoretical analysis and simulation results illustrate that through utilizing the additional polarization information,the polarization array MIMO radar PSTAP can achieve significant improvement of the clutter suppression performance compared to the traditional MIMO-STAP,which is beneficial for the detection of the moving target with low-speed.