Polarization-spatial Joint Null Broadening Beamforming

As a typical array spatial anti-jamming technology,adaptive beamforming algorithm is mainly applied in radar,sonar,communication and navigation systems by optimizing the weight vector with specific criteria.In recent years,the adaptive beamforming algorithm based on polarization sensitive array has been widely studied by many scholars because of better anti-jamming ability.However,most of the research on polarization sensitive array beamforming algorithms is based on non-high dynamic or static environment.In high dynamic environment,the narrow null formed by traditional adaptive beamforming algorithms in the interference area can not suppress the offset interference,which leads to the performance degradation or failure of polarization anti-jamming algorithms.In order to solve this problem,this thesis studies the polarization-sensitive array beamforming algorithm in a highly dynamic environment.The specific research content is as follows:Firstly,according to the polarization characterization of electromagnetic wave,the signal receiving model of the classical polarization sensitive array uniform linear array is established.On this basis,according to the needs of different engineering background,three classical polarization spatial joint beamforming algorithms are analyzed,and the characteristics of each algorithm are authenticated by simulation experiments.Secondly,the influence of the high dynamic environment on the signal direction is analyzed,and the classic scalar array null broadening algorithms such as the covariance matrix cone method,the projection transformation method and the matrix reconstruction method are studied.On this basis,for the polarization sensitive array,combining the polarization beamforming criteria such as minimum variance distortionless response,linear constraint minimum variance,and power inversion,a covariance matrix reconstruction method based on Capon spectrum reset is proposed,which realizes polarization-spatial joint null broadening.In addition,considering the real-time requirements of the algorithm in high dynamic environment,the reduced rank conjugate gradient method is adopted to solve the problem of high computational complexity caused by the polarization array,which counterbalances the shortcomings of the algorithm.The simulation experiments verify this fast algorithm's effectiveness.Finally,considering the influence of the inevitable array manifold error on the performance of the algorithm in practical engineering,two classical array manifold error models are established to improve the algorithm's ability in engineering environment: array gain-phase error model and array element position error model.In this thesis,a robust beamforming algorithm for polarization sensitive array in high dynamic environment based on ICA is proposed.Firstly,the array manifold error matrix is estimated from the separated mixed matrix by blind separation technique,and then the covariance matrix and the expected signal steering vector are corrected and reconstructed by using the matrix containing the array manifold error information,so that the array manifold error can be corrected.Simulation results show that the algorithm is robust to array manifold errors.