文章摘要
梁国龙,张柯,王逸林*,范展.声矢量阵相干源方位估计算法[J].声学技术,2013,32(6):464~468
声矢量阵相干源方位估计算法
DOA estimation of coherent signals based on acoustic vector array
投稿时间:2013-03-04  修订日期:2013-05-07
DOI:10.3969/j.issn1000-3630.2013.06.004
中文关键词: 声矢量阵  质点速度场平滑  矩阵平方平滑  相干源  波达方向估计
英文关键词: acoustic vector array  particle velocity field smoothing  matrix square smoothing  coherent source  DOA estimation
基金项目:国家自然科学基金(51279043、51209059、61201411)和水声技术国家级重点实验室基金资助项目(9140C200203110C2003)
作者单位E-mail
梁国龙 哈尔滨工程大学水声技术重点实验室, 哈尔滨 150001  
张柯 哈尔滨工程大学水声技术重点实验室, 哈尔滨 150001  
王逸林* 哈尔滨工程大学水声技术重点实验室, 哈尔滨 150001 Wang10.W10@gmail.com 
范展 哈尔滨工程大学水声技术重点实验室, 哈尔滨 150001  
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中文摘要:
      基于声矢量阵的质点速度场平滑(Particle Velocity Field Smoothing, PVFS)算法是一种有效的解相干算法,但是当存在大量相干源时,该算法性能急剧下降甚至失效。在PVFS算法的基础上,提出了矩阵平方平滑 (Matrix Square Smoothing, MSS)-PVFS算法,该算法是对PVFS算法的改进,通过对PVFS算法构造的数据协方差矩阵进行平方、矩阵分块以及矩阵块间交叉相乘等数学运算,增强了PVFS算法解相干的能力,并大大增加了其分辨相干源的数目。计算机仿真结果表明,MSS-PVFS算法的效果与空间平滑(Spatial Smoothing, SS)-PVFS算法大致相同,但在低信噪比条件下,该方法具有更高的DOA估计精度。
英文摘要:
      PVFS (Particle Velocity Field Smoothing) algorithm based on acoustic vector sensor array is an effective decorrelation algorithm. However, the performance will seriously degrade or even fails when there are a large number of coherent sources. Based on PVFS, the MSS (Matrix Square Smoothing) algorithm is proposed as the amelioration of PVFS. The proposed algorithm first squared and partitioned the data covariance matrix constructed by PVFS. Then, the partitioned matrix was cross-multiplied by each other. Finally, the decorrelation ability of PVFS algorithm was enhanced and more coherent sources can be distinguished. Computer simulation indicated that the proposed algorithm achieved a similar performance as the Spatial Smoothing PVFS algorithm. Moreover, the DOA estimation accuracy of the proposed algorithm was much higher when the signal-to-noise ratio was low.
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