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作 者:刘磊 陈模江[2] LIU Lei;CHEN Mojiang(The sixth military science representative office of Naval Equipment Department in Beijing,Beijing,100088,China;Institute of Acoustics,Chinese Academy of Sciences,Beijing,100190,China)
机构地区:[1]海装驻北京地区第六军事代表室,北京100088 [2]中国科学院声学研究所,北京100190
出 处:《网络新媒体技术》2023年第5期51-56,共6页Network New Media Technology
摘 要:精确知道导向向量与噪声(包括干扰)协方差矩阵的情况下,MVDR波束形成算法可保证期望信号无失真的同时最大限度地抑制干扰。对于实际的声呐系统,导向向量误差和采样协方差矩阵误差导致MVDR波束形成算法性能严重下降。充分利用导向向量误差椭圆的稳健波束形成算法能够解决或改善此种性能劣化问题,但是该稳健算法需要运用牛顿迭代法或者二阶锥规划求解,计算效率较低。针对这一问题,本文在分析理想方向向量与实际方向向量关系的基础上,通过将理想方向向量投影到数据协方差矩阵的某一个特征向量上,提出了一种形式简单、计算量低的改进的稳健自适应波束形成算法。仿真分析表明,所提出的改进稳健算法明显提高了计算效率,且对信号方向向量的适配具有良好的稳健性。湖上实验数据处理结果,进一步证实了该算法的有效性。In the case of precisely knowing the covariance matrix between the steering vector and noise(including interference),the MVDR beamforming algorithm can guarantee the desired signal without distortion while minimizing interference.For the actual sonar system,the steering vector error and sampling covariance matrix error cause the performance of MVDR beamforming algorithm to degrade seriously.The robust beamforming algorithms that make full use of steering vector error ellipses can solve or improve this performance degradation problem,but these robust algorithms need to use Newton-Raphson method or second-order cone programming to solve,and the computational efficiency is slow.To solve this problem,based on the analysis of the relationship between the ideal direction vector and the actual direction vector,an improved robust adaptive beamforming algorithm with simple form and low computation is proposed by projecting the ideal direction vector onto a feature vector of the data covariance matrix.Simulation results show that the proposed improved robust algorithm can improve the computational efficiency significantly and has good robustness for the adaptation of signal steering vector.The experimental data processing results on the lake further confirm the effectiveness of the proposed algorithm.
关 键 词:MVDR 波束形成算法 导向向量误差 采样协方差矩阵
分 类 号:TN911.7[电子电信—通信与信息系统]
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