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基于互相关协方差矩阵的改进多重信号分类高分辨波达方位估计方法

毛琳琳 张群飞 黄建国 史文涛 韩晶

毛琳琳, 张群飞, 黄建国, 史文涛, 韩晶. 基于互相关协方差矩阵的改进多重信号分类高分辨波达方位估计方法[J]. 电子与信息学报, 2015, 37(8): 1886-1891. doi: 10.11999/JEIT141208
引用本文: 毛琳琳, 张群飞, 黄建国, 史文涛, 韩晶. 基于互相关协方差矩阵的改进多重信号分类高分辨波达方位估计方法[J]. 电子与信息学报, 2015, 37(8): 1886-1891. doi: 10.11999/JEIT141208
Mao Lin-lin, Zhang Qun-fei, Huang Jian-guo, Shi Wen-tao, Han Jing . Improved Multiple Signal Classification Algorithm for Direction of Arrival Estimation Based on Covariance Matrix of Cross-correlation[J]. Journal of Electronics and Information Technology, 2015, 37(8): 1886-1891. doi: 10.11999/JEIT141208
Citation: Mao Lin-lin, Zhang Qun-fei, Huang Jian-guo, Shi Wen-tao, Han Jing . Improved Multiple Signal Classification Algorithm for Direction of Arrival Estimation Based on Covariance Matrix of Cross-correlation[J]. Journal of Electronics and Information Technology, 2015, 37(8): 1886-1891. doi: 10.11999/JEIT141208

基于互相关协方差矩阵的改进多重信号分类高分辨波达方位估计方法

doi: 10.11999/JEIT141208
基金项目: 

国家自然科学基金(61271415)

Improved Multiple Signal Classification Algorithm for Direction of Arrival Estimation Based on Covariance Matrix of Cross-correlation

  • 摘要: 针对经典高分辨波达方位(DOA)估计方法在低信噪比下分辨性能较差的问题,该文提出一种适用于主动探测系统的基于互相关矩阵的改进多重信号分类(MUSIC)高分辨方位估计方法(I-MUSIC)。该方法首先利用主动声呐发射信号已知的特性,将发射信号与阵元接收信号进行互相关,利用互相关序列形成新的空域协方差矩阵,再进行特征分解。理论分析表明,互相关处理在抑制噪声的同时保留了阵元之间的相位信息,可以得到比MUSIC方法更准确的子空间划分,进而提高低信噪比方位估计性能。在此基础上,提出一种基于相关时间门限的改进MUSIC高分辨方位估计(T-MUSIC)方法,通过对互相关序列设置时间门限进一步提高方位估计信噪比。仿真结果表明,与MUSIC方法相比,I-MUSIC与T-MUSIC可以分别使低信噪比时的估计性能提高3 dB和6 dB,相应平均估计误差分别为原方法的77%和53%。在阵元间接收噪声存在相关性时,T-MUSIC与I-MUSIC方法相比可获得8 dB的估计增益,估计性能更优。I-MUSIC与T-MUSIC应用于多目标主动探测,可大幅提高探测系统在低信噪比下的方位估计性能。
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出版历程
  • 收稿日期:  2014-09-17
  • 修回日期:  2015-04-16
  • 刊出日期:  2015-08-19

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