| 引用本文: | 陈鹏,景晓簪,陈洋,王威.稳健的特征空间基变换自适应波束形成[J].哈尔滨工业大学学报,2023,55(5):71.DOI:10.11918/202112102 |
| CHEN Peng,JING Xiaozan,CHEN Yang,WANG Wei.Robust eigenspace bases transition technique for adaptive beamforming[J].Journal of Harbin Institute of Technology,2023,55(5):71.DOI:10.11918/202112102 |
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| 摘要: |
| 针对现有自适应波束形成器在阵元位置误差、幅相误差以及信号来波方向误差耦合时干扰抑制能力下降的问题,提出了一种稳健的基于特征空间基变换的自适应波束形成算法。首先,对导向向量中阵元位置误差、幅相误差以及信号来波方向误差的影响进行了建模；然后,通过利用真实信号子空间与导向矢量张成空间相同的特性,引入子空间距离的概念量化两个子空间相似程度,并构建出一个最小化空间距离的多维非线性优化问题；在此基础上,结合遗传算法与拟牛顿法的特点形成一种混合优化策略,在解除最优化问题后,得到信号子空间的一组非正交基；最后,将估计的信号子空间与噪声子空间组合为特征空间,通过对特征空间进行基变换提取出准确的干扰加噪声协方差矩阵,并对期望信号导向向量进行了修正。数值仿真结果表明:所提混合优化算法随着迭代数提高能够显著降低子空间距离,迭代数达到100次时,能够将子空间距离降低至1以下；在信号来波方向误差、阵元位置误差以及幅相误差同时存在,且输入信噪比为10 dB的情况下,所提算法的输出信干噪比与现有方法相比提高约14 dB。 |
| 关键词: 特征空间 基变换 混合优化 自适应波束形成 干扰抑制 |
| DOI：10.11918/202112102 |
| 分类号:TB56 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(9,7) |
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| Robust eigenspace bases transition technique for adaptive beamforming |
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CHEN Peng,JING Xiaozan,CHEN Yang,WANG Wei
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(School of Information Engineering, Chang’an University, Xi’an 710064, China)
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| Abstract: |
| Considering that the interference suppression capability of the existing adaptive beamformer decreases when coupling the array element position error, amplitude and phase error, and signal arrival direction error, a robust adaptive beamforming algorithm based on eigenspace bases transition was proposed. First, the influence of the array element position error, amplitude and phase error, and signal arrival direction error of the steering vectors was modeled. Then, on the basis of the characteristics that the real signal subspace was the same as the space spanned by the steering vectors, the concept of subspace distance was introduced to quantify the similarity of two subspaces, and a multi-dimensional nonlinear optimization problem that minimized the spatial distance was constructed. Next, a hybrid optimization strategy was formed by combining the characteristics of the genetic algorithm and the quasi-Newton method, and after solving the optimization problem, a set of non-orthogonal bases of the signal subspace were obtained. Finally, the estimated signal subspace and the noise subspace were combined into an eigenspace. The accurate interference-plus-noise covariance matrix was extracted by the bases transition of the eigenspace, and the steering vector of the desired signal was corrected. Numerical simulation results show that the proposed hybrid optimization algorithm could significantly reduce the subspace distance as the number of iterations increased. When the number of iterations reached 100, the subspace distance reduced to less than 1. When the array element position error, amplitude and phase error, and signal arrival direction error occurred at the same time, and the input signal-to-noise ratio was 10 dB, the output signal-to-interference noise of the proposed algorithm was about 14 dB higher than that of the existing methods. |
| Key words: eigenspace bases transition hybrid optimization adaptive beamforming interference suppression |
