期刊文献+

一种最差情况下性能最优化的特征分析自适应波束形成方法 被引量:13

Eigenanalysis-based adaptive beamforming using worst-case performance optimization
下载PDF
导出
摘要 自适应波束形成在弱目标检测和空域滤波中应用广泛。然而在实际海洋环境中,失配情况比较普遍,往往会导致传统自适应波束形成方法性能明显下降。针对此问题,本文基于特征分析重构观测信号协方差矩阵来抑制干扰对弱目标检测的影响,在此基础上进一步利用凸优化算法来提高波束形成方法的鲁棒性。数值仿真和海试数据处理结果表明,本文所提方法在抑制干扰对弱目标影响的基础上,在阵元位置平均误差不超过入射信号中心频率对应波长的40%的情况下,仍可以鲁棒地检测目标信号。同时,该方法显著提高了自适应波束形成方法的输出信干噪比,且受对角加载量取值的影响较小。 Robust adaptive beamforming is an efficient way for both spatial filtering and weak target detection in the presence of interference and noise, particularly in oceanic engineering where mismatch most often degrades the performance of conventional adaptive beamforming. In the proposed method, the covariance matrix is re-constructed based on eigenanalysis, using a more stable and practical criterion. Convex optimization is implemented on the re- constructed eovariance matrix to further improve the robustness. Numerical simulations and experimental results show that the proposed method can efficiently suppress the interference and robustly detect the weak target under the condition that average sensors' position error is less than 40% of incident signal wavelength. The proposed robust adaptive beamforming has higher output signal to interference plus noise ratio, and is less sensitive to the diagonal loading factor.
出处 《声学学报》 EI CSCD 北大核心 2015年第2期187-197,共11页 Acta Acustica
关键词 自适应波束形成 特征分析 目标信号 协方差矩阵 波束形成方法 空域滤波 信干噪比 海试 数据处理结果 波达方向 Beamforming Convex optimization Covariance matrix Numerical methods Signal detection Signal interference Signal to noise ratio
  • 相关文献

参考文献43

  • 1Chae C B,Hwang I,Heath R,Tarokh V.Interference aware-coordinated beamforming in a multi-cell system.IEEE Trans.Wireless Commun.,2012;11(10):3692-3703. 被引量:1
  • 2Tang,J S,Pan Y,Jiang X D.Postbeamformer weak signal extraction with a strong interference close to the signal's direction.In:Proc.IEEE Int Signal Process,Commun.and Comput.(ICSPCC)Conf.,2011:1-5. 被引量:1
  • 3Krim H,Viberg M.Two decades of array signal processing research:the parametric approach.IEEE Signal Process.Mag.,1996;13(4):67-94. 被引量:1
  • 4Svensson A,Jakobsson A.Adaptive detection of a partly known signal corrupted by strong interference.IEEE Signal Process.Lett,2011;18(12):729-732. 被引量:1
  • 5Mehdizadeh S,Austeng A,Johansen T,Holm S.Eigenspace based minimum variance beamforming applied to ultrasound imaging of acoustically hard tissues.IEEE Trans.Med.Imag.,2012;31(10):1912-1921. 被引量:1
  • 6Zhang L,Liu W.Robust beamforming for coherent signals in the presence of steering vector and correlation matrix errors.In:7th International ICST Conference on Communications and Networking in China(CHINACOM),2012:352-355. 被引量:1
  • 7Blomberg A,Austeng A,Hansen R,Synnes S.Improving sonar performance in shallow water using adaptive beamforming.IEEE J.Ocean.Eng.,2013;38(2):297-307. 被引量:1
  • 8桑怀胜,李峥嵘.智能天线的原理、自适应波束形成算法的研究进展与应用[J].国防科技大学学报,2001,23(6):83-89. 被引量:34
  • 9韩英臣,赵兴录,赵国庆.自适应波束形成技术的发展与现状研究[J].航天电子对抗,2009,25(2):61-64. 被引量:5
  • 10刘宪军,安红,张扬.一种改进的稳健波束形成算法[J].电子信息对抗技术,2011,26(6):18-21. 被引量:2

二级参考文献83

共引文献86

同被引文献87

引证文献13

二级引证文献28

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部