| Compared to the traditional phased-array radar,multiple-input multiple-output(MIMO)radar can achieve better performance in parameter identification,interference mitigation and target detection by waveform diversity,attracting significant interest from radar researchers.By exploiting the advantages of waveform diversity,the research of MIMO radar beamforming includes transmit beamforming and adaptive beamforming.Although many achievements about MIMO radar beamforming have been acquired by many scholars,there are some problems to be solved according to different operating environments.At the transmitter,when there are transmit steering vector mismatches,the transmit beampttern will be distorted,casuing performance degradation of transmit beampattern design algorithms.For the joint optimization of transmit and receive beamforming,not only interference or clutter mitigation,but also range sidelobe suppression and power constraints of the transmit signals should be considered.At receiver,the performance of adaptive beamforming will be degraded,when there are non-stationary interference and mainlobe interference.To solve the above problems,this dissertation focuses on the key technologies of beamforming for MIMO radar,and the work are illustrated as follows:1.Robust transmit beampattern design for MIMO radar via minimizing ISLFor the problem of existing mismatches between the actual and the presumed steering vectors,robust transmit beampattern design is studied.The integrated side-lobe level(ISL)is used as the criterion and the radiated power in the main lobe is constrained according to the steering vector error.Firstly,a robust transmit beampattern design method of MIMO radar based on covariance matrix is given.Since the covariance matrix is a semi-definite and Hermitian matrix,the optimization problem can be converted to a second-order cone programming(SOCP)problem.Then,by exploiting transmit beamspace processing(TBP),a robust transmit beampattern design method of MIMO radar based on transmit weighting matrix is presented.By TBP,a linear combination of orthogonal waveforms is emitted at each transmit array element to obtain the coherent processing gain,which separates transmit beamforming and waveform design.Since the problem is non-convex,an algorithm based on semi-definite relaxation(SDR)and linearization method is proposed to convert it to two optimization problems,which are repectively based on semi-definite programming(SDP)and SOCP.Simulation results show that the two methods can design the worst-case beampatterns according to different steering vector errors,and the obtained worst-case ISL is lower than that of the non-robust method.2.Joint optimization of transmit and receive beamforming for MIMO radar in presence of interferenceThe detection performance can be improved by joint optimization of transmit and receive beamforming for MIMO radar,with the prior information of target and interference.Firstly,for the problem that the direction of the target is uncertain,a modified joint optimization method of transmit and receive beamforming for MIMO radar based on waveform design is presented.Considering the constant modulus constraint and the similarity constraint of waveform,maximizing the worst-case signal-to-interference-plus-noise ratio(SINR)is used as the criterion to construct the objective function,and a sequential algorithm based on SDR is given to obtain the optimal waveform and the spatial filter.Simulations show that the optimized waveform with constant envelope improves the worst-case output SINR.Moreover,the similarity constraint balances the coherent gain of the transmit beampattern and the performance of pulse compression.Then,by exploiting transmit beamspace processing(TBP),joint optimization of transmit and receive beamforming based on transmit weighting matrix design is proposed in presence of signal-dependent interference.Considering the constraint of peak-to-average power ratio(PAPR)of transmit array elements,the objective function is constructed by maximizing the output SINR.A sequential optimization algorithm based on the Quasi-Newton Method is proposed to acquire the optimal weighting matrix.The optimized weighting matrix improves the SINR performance effectively,providing better performance than traditional phased-array radar and omni-directional MIMO radar.3.MIMO radar beamforming for mainlobe interference suppression in spectrum-sharing environmentTo suppress the main-lobe communication interference in spectrum-sharing environment,a beamforming method for MIMO radar based on the preprocessing of the waveform initial phase is studied.To suppress the mainlobe interference,Minimum Variance Distortionless Response(MVDR)beamformer is used as the spatial filter at the output of the matched filters and maximizing the output SINR is employed as the criterion to optimize the waveform initial phase.Since the optimization problem is unimodular quadratic programming problem,three optimization algorithms,which are respectively based on SDR,power method like iterations and the phase-only variable metric,are given to trackle it.The proposed method is validated by the simulations of beampattern and SINR performance.4.Robust beamforming for MIMO radar for non-stationary interference suppressionIn order to suppress non-stationary interference,robust beamforming based on direct data domain(DDD)is studied.Since DDD beamforming is a single snapshot beamforming method,when there are mismatches between the actual and the presumed signal steering vectors,the performance of direct data domain(DDD)approach will be extremely degraded,causing target self-nulling and high sidelobe level.To solve this problem,the worst-case performance optimization algorithm based on norm constraint(WCPO-NC)is proposed firstly.By adding the norm constraint of weighting vector,the algorithm can effectively reduce the sidelobe level while solving the problem of target self-nulling.Since the expression of adaptive beamforming is similar to that of space-time adaptive processing(STAP),the above algorithm is applied to DDD STAP of MIMO radar. |
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