南京大学学报(自然科学版) ›› 2017, Vol. 53 ›› Issue (4): 621–.

• •    下一篇

声矢量圆阵宽带相干信号的方位估计

安妍妍1，李　赢1，时胜国1，2*，时　洁1，2   

  • 发布日期:2017-08-01
  • 作者简介:1.哈尔滨工程大学水声工程学院，哈尔滨，150001；2.哈尔滨工程大学水声技术重点实验室，哈尔滨，150001
  • 基金资助:
    基金项目：长江学者和创新团队发展计划(IRT_16R17)，国家自然科学基金(11404076) 收稿日期：2016－09－02 *通讯联系人，E－mail：shishengguo@hrbeu.edu.cn

The direction－of－arrival estimation for wideband coherent sources using the circular acoustic vector sensor array

An Yanyan1，Li Ying1，Shi Shengguo1，2*，Shi Jie1，2   

  • Published:2017-08-01
  • About author:1.College of Underwater Acoustic Engineering，Harbin Engineering University，Harbin，150001，China； 2．Science and Technology on Underwater Acoustic Laboratory，Harbin Engineering University，Harbin，150001，China

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摘要： 针对水下目标的远程被动探测问题，提出了一种声矢量圆阵的宽带相干目标方位估计方法．首先，基于子带分解原理将宽带划分为若干不重叠窄带，根据圆阵模式空间变换理论，将声矢量圆阵转换成与频率无关的虚拟直线阵，并采用声压P与振速(Vr＋Vφ)联合处理方法构建了每个窄带的互协方差矩阵，通过求和平均实现了宽带接收信号的互协方差矩阵估计；其次，引入一种修正的矢量奇异值分解算法，对接收相干信号的互协方差矩阵进行重构处理，用于解决相干声源的空间分辨问题；最后，利用MUSIC算法实现了声矢量圆阵宽带相干目标的方位估计．理论分析及仿真结果表明，修正的矢量奇异值分解算法较修正前具有更强的空间分辨能力；P×(Vr＋Vφ)声压振速联合处理方法较同阵型的声压阵及其他声压振速联合处理方法(即(P＋Vc)×Vc、P×Vc)具有更好的背景噪声抑制能力；将P×(Vr＋Vφ)声压振速联合处理方法与修正的矢量奇异值分解算法有机地结合起来，可提高宽带相干源的方位估计性能．水池实验结果进一步验证了算法的有效性．

关键词: 声矢量圆阵, 模式空间变换, 修正奇异值分解, 方位估计

Abstract: With the development of the acoustic vector sensor，DOA(direction－of－arrival)estimation methods of the wideband signals with high spatial resolution based on the acoustic vector array have been widely concerned.When sources are correlated or coherence，the detection performance of the high resolution DOA estimation methods will degrade.In order to solve the problem of distinguishing from coherent wideband targets，a new DOA estimation algorithm for a UCAVSA(uniform circular acoustic vector sensor array)is proposed in this paper.Firstly，by extending the concept of the sub－band decomposition to the UCAVSA，the wideband received signals of the UCAVSA are decomposed into a number of narrowband signals.The mode space transformation principle further transforms the UCAVSA to a virtual uniform linear array which removes the frequency dependency of the response of the UCAVSA.For every narrowband signals，the cross－covariance matrixes between the acoustic pressure P and the acoustic particle velocity (Vr＋Vφ) of the virtual uniform linear array are constructed，and then they are averaged to obtain the covariance matrix of wideband signals.In addition，a modified singular value decomposition algorithm，which is used to restore the rank of the covariance matrix by reconstructing the cross covariance matrix，is applied to solve distinguishing from coherent sources.Finally，the spatial spectrum formulation for MUSIC based on the modified singular value decomposition has been derived.Theoretical analyses and simulation results show that the spatial resolution of the modified singular value decomposition algorithm is higher than that of the non－modified singular value decomposition algorithm.Meanwhile，the combined processing method of P×(Vr＋Vφ) can improve the DOA estimation performance compared to the same manifold of traditional uniform circular pressure sensor array and other combined processing of the acoustic pressure and the acoustic particle velocity(such as (P＋Vc)×Vc and P×Vc)．It is also discovered that the proposed method combined P×(Vr＋Vφ) with the modified singular value decomposition algorithm can effectively resolve the coherent sources and reduce the SNR(signal－to－noise ratio)threshold.The effectiveness of the proposed method is verified by the pool experimental results.In addition，the proposed method has a widely application in radar system and air acoustics.

Key words: circular acoustic vector sensor array, mode space transformation, modified singular value decomposition, direction－of－arrival estimation

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