| 摘要: |
| 波束形成在无线通信、雷达、声呐等阵列系统中具有广泛应用。数字波束形成通常是基于接收信号的阵列响应和协方差矩阵的估计设计。由于天线增益、相位、波达方向(Direction-of-Arrival，DOA)和协方差矩阵估计的误差会导致导向矢量(Steering Vector,SV)产生模型失配，而这种模型失配会导致波束形成性能的下降。针对以上问题，给出了基于精度矩阵收缩估计的方法，采用了线性脊估计结构且用数据驱动和留一交叉验证来选择参数。通过Matlab仿真，研究了当存在模型不确定性时，基于精度矩阵收缩估计的方法以及基于协方差矩阵收缩估计和干扰加噪声协方差矩阵重构等方法的鲁棒性。结果显示，当存在模型失配时，基于精度矩阵收缩的波束形成方法在低信噪比时具有更优的鲁棒性。 |
| 关键词: 自适应波束形成 协方差矩阵 精度矩阵 收缩估计 矩阵重构 |
| DOI： |
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| 基金项目:国家自然科学基金资助项目（61601325） |
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| Comparative study on several robust adaptive beamforming methods |
| XIAO Zhitao,WANG Jiahao,GENG Lei,ZHANG Fang,TONG Jun |
| (1.School of Electronics and Information Engineering,Tianjin Polytechnic University,Tianjin 300387,China;2.Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems,Tianjin 300387,China;2.Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems,Tianjin 300387,China;3.School of Electrical,Computer and Communication Engineering,University of Wollongong,NSW 2522,Australia) |
| Abstract: |
| Beamforming has been widely studied in wireless communications,radar,sonar,and other array systems.Digital beamforming is usually designed based on the array response and the estimation of the covariance matrix of the received signal.Due to the errors of antenna gain,phase,direction-of-arrival(DOA) and covariance matrix estimation,the steering vector(SV) will cause the model mismatch,which will lead to the degradation of beamforming performance.To solve above problems,a method based on precision matrix shrinkage estimation is presented.The linear ridge estimation structure is adopted and the parameters are selected by data-driven and leave one out cross-validation.By Matlab simulation,the method based on precision matrix shrinkage estimation and the method based on covariance matrix shrinkage estimation and interference plus noise covariance matrix reconstruction are studied.The results show that the beamforming method based on the precision matrix shrinkage has better robustness at low signal-to-noise ratio(SNR) when there is model mismatch. |
| Key words: adaptive beamforming covariance matrix precision matrix shrinkage estimation covariance matrix reconstruction |
