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基于子空间旋转变换的低复杂度波达角估计算法

闫锋刚 齐晓辉 刘帅 沈毅 金铭

闫锋刚, 齐晓辉, 刘帅, 沈毅, 金铭. 基于子空间旋转变换的低复杂度波达角估计算法[J]. 电子与信息学报, 2016, 38(3): 629-634. doi: 10.11999/JEIT150539
引用本文: 闫锋刚, 齐晓辉, 刘帅, 沈毅, 金铭. 基于子空间旋转变换的低复杂度波达角估计算法[J]. 电子与信息学报, 2016, 38(3): 629-634. doi: 10.11999/JEIT150539
YAN Fenggang, QI Xiaohui, LIU Shuai, SHEN Yi, JIN Ming. Low-complexity DOA Estimation via Subspace Rotation Technique[J]. Journal of Electronics & Information Technology, 2016, 38(3): 629-634. doi: 10.11999/JEIT150539
Citation: YAN Fenggang, QI Xiaohui, LIU Shuai, SHEN Yi, JIN Ming. Low-complexity DOA Estimation via Subspace Rotation Technique[J]. Journal of Electronics & Information Technology, 2016, 38(3): 629-634. doi: 10.11999/JEIT150539

基于子空间旋转变换的低复杂度波达角估计算法

doi: 10.11999/JEIT150539
基金项目: 

国家自然基金(61501142),山东省自然科学基金(ZR2014FQ003),中国博士后科学基金(2015M571414),中央高校基本科研业务费专项资金(HIT.NSRIF.2016102)

Low-complexity DOA Estimation via Subspace Rotation Technique

Funds: 

The National Natural Science Foundation of China (61501142), Shandong Provincial Natural Science Foundation (ZR2014FQ003), China Postdoctoral Science Foundation (2015M571414), The Fundamental Research Funds for the Central Universities (HIT.NSRIF.2016102)

  • 摘要: 多重信号分选(MUltiple SIgnal Classification, MUSIC)算法是波达方向(Direction-Of-Arrival, DOA)估计的最重要算法之一,但庞大的计算量使其工程实用性大打折扣。为降低MUSIC的计算量,该文基于子空间旋转(Subspace Rotation Technique, SRT)变换思想提出了一种高效改进算法,即SRT-MUSIC算法。SRT-MUSIC利用秩亏特性对噪声子空间矩阵按行分块并以旋转变换得到降维噪声子空间,进而基于该降维噪声子空间与导向矢量的正交性构造空间谱估计信号DOA。理论分析表明:SRT-MUSIC能有效避免空间谱搜索中的冗余运算,从而成倍降低算法的计算量。对于大阵元、少信号情况,所提算法计算效率优势更为明显。仿真实验证明了SRT-MUSIC的有效性和高效性。
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出版历程
  • 收稿日期:  2015-05-07
  • 修回日期:  2015-12-18
  • 刊出日期:  2016-03-19

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