南京大学学报(自然科学版) ›› 2017, Vol. 53 ›› Issue (4): 661–.

• • 上一篇    下一篇

 基于欠定盲分离的广义逆简正波过滤方法

 张寅权1,张 爽2*,高思宇1,李国富2   

  • 出版日期:2017-08-02 发布日期:2017-08-02
  • 作者简介: 1.国家海洋信息中心,天津,300171;2.国家海洋技术中心,天津,300112
  • 基金资助:
     基金项目:中国科学院水声环境特性重点实验室开放课题,国家自然科学基金(41376013,41376015,41306006,41541041,41506039),国家973计划(2013CB430304),国家863计划(2013AA09A505),全球变化与海气相互作用专项(GASI-01-01-12,GASI-IPOVAI-04)
    收稿日期:2016-10-01
    *通讯联系人,E-mail:maymayed2007@126.com

 Acoustic pseudo-inverse mode filtering based on under determined blind source separation

 Zhang Yinquan1,Zhang Shuang2*,Gao Siyu1,Li Guofu2   

  • Online:2017-08-02 Published:2017-08-02
  • About author: 1.National Marine Date and Information Service,Tianjin,300171,China;
    2.National Ocean Technology Center,Tianjin,300112,China

摘要:  水声传播信号是多号简正波的叠加,通过简正波过滤分离各号简正波,是水声领域常用的一种技术手段,也是匹配模目标定位、声源信号重构等诸多应用的基础.对于垂直阵接收信号,广义逆方法是最常用的一种简正波过滤方法.广义逆方法的一个关键问题是如何确定接收信号中包含的简正波的号数,采用的简正波号数与实际号数偏差越大,简正波过滤的效果越差.针对上述问题,提出一种利用欠定盲分离技术获取垂直阵接收信号中包含的简正波号数的方法,并且通过在理想波导和夏季波导环境下的数值仿真对该方法进行检验,仿真结果表明:在一定的信噪比条件下,本文方法可以从垂直阵接收信号中准确提取简正波号数信息.该方法有助于减小简正波号数未知引起的广义逆简正波过滤的偏差,在基于简正波过滤技术的目标定位、识别等水声应用领域具有一定的应用前景.

Abstract:  Underwater sound propagation signal can be regarded as the composition of normal modes.Acoustic mode filtering is employed to separate each mode from the received signal and has been widely used in many practical applications,such as matched mode processing(MMP)for target localization,reconstruction of target signal,and so on.For a vertical line array,pseudo-inverse method is a popular and suitable way to implement mode filtering.A key problem for the pseudo-inverse method is to determine how many normal modes should be adopted to construct the coefficient matrix.Once the number of normal modes used by the pseudo-inverse method diverges from the actual value,performance of the mode filtering would decrease.In view of the above question,a method based on underdetermined blind source separation(UBSS)is proposed in this paper,aiming to search the number of normal modes contained in the received signal of a vertical line array.Therefore,traditional acoustic pseudo-inverse mode filtering can be decomposed in two steps.Firstly,one should search the number of normal modes by the present method.Then,one could filter each mode by the traditional way of pseudo-inverse mode filtering.To verify the present method,acoustic pressure field in two kinds of waveguide,ideal waveguide and shallow water waveguide in summer,has been simulated numerically.Results of the numerical simulation show that:(1)one can extract the number of the normal modes contained in the received signal of vertical line array by the proposed method when the signal to noise ratio(SNR)is high;(2)the performance of the method will decrease as the SNR reduces.It is assumed that the present method can be used to diminish the deviation of mode filtering caused by the uncertainty of the number of normal modes.And the method has potential use in practical applications based on mode filtering,for instance,target localization and identification.

 [1] Tindle C T,Guthrie K M,BoldG E J,et al.Measurements of the frequency dependence of normal modes.The Journal of the Acoustical Society of America,1978,64(4):1178-1185.
[2] Lo E C,Zhou J X,Shang E C.Normal mode filtering in shallow water.The Journal of the Acoustical Society of America,1983,74(6):1833-1836.
[3] Wilson G R,Koch R A,Vidmar P J.Matched mode localization.The Journal of the Acoustical Society of America,1988,84(1):310-320.
[4] Buck J R,Preisig J C,Wage K E.A unified framework for mode filtering and the maximum a posteriori mode filter.The Journal of the Acoustical Society of America,1998,103(4):1813-1824.
[5] 郭国强,孙 超,杨益新.基于垂直阵模态分解的低频水声信号盲解卷处理研究.声学学报,2011,36(1):8-19.(Guo G Q,Sun C,Yang Y X.Blind deconvolution of low frequency acoustic signals based on mode decomposition using vertical linear array in shallow water.Acta Acustica,2011,36(1):8-19.)
[6] Shang E C.An efficient high-resolution method of source localization processing in mode space.The Journal of the Acoustical Society of America,1989,86(5):1960-1964.
[7] 肖 鹏,雷 波,杨坤德.模态滤波匹配定位方法研究.声学技术,2013,32(6):81-82.(Xiao P,Lei B,Yang K D.Experiment research on modal filtering localization method.Technical Acoustics,2013,32(6):81-82.)
[8] Shang E C.Source depth estimation in waveguides.The Journal of the Acoustical Society of America,1985,77(4):1413-1418.
[9] 高天赋,陈耀明,杨怡青.短垂直阵简正波匹配的声源定位.声学学报,1996,21(S4):493-505.(Gao T F,Chen Y M,YangY Q.Source localization by the MMP of a short vertical array.Acta Acustica,1996,21(S4):493-505.)
[10] Yang T C.A method of range and depth estimation by modal decomposition.The Journal of the Acoustical Society of America,1987,82(5):1736-1745.
[11] 张苏弦,刘海林.基于稀疏特性的欠定盲信号分离算法.南京大学学报(自然科学),2011,47(5):566-570.(Zhang S X,Liu H L.Underdetermined blind source separation algorithm based on sparse representation.Journal of Nanjing University(Natural Sciences),2011,47(5):566-570.)
[12] 陶襄樊,陈美霞,魏建辉.欠定盲分离方法预报水下双层圆柱壳辐射声场.舰船科学技术,2012,34(11):8-13,58.(Tao X F,Chen M X,Wei J H.Prediction of radiated acoustic field for double cylindrical shell under water using underdeter-mined blind source separation.Ship Science and Technology,2012,34(11):8-13,58.)
[13] Karvanen J,Cichocki A.Measuring sparseness of noisy signals.In:Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation.Nara,Japan:Riken,2003:125-130.
[14] Chen S S,Donoho D L,Saunders M A.Atomic decompositionby basis pursuit.Society for Industrial and Applied Mathematics,2001,43(1):129-159.
[15] Donoho D L.For most large underdetermined systems of linear equations the minimal l1-norm solution is also the sparsest solution.Communi-cations on Pure and Applied Mathematics,2006,59(6):797-829.
[16] Donoho D L.Compressed sensing.IEEE Transactions on Information Theory,2006,52(4):1289-1306. 第53卷 第4期,2017年7月南京大学学报(自然科学),JOURNAL OF NANJING UNIVERSITY,(NATURAL SCIENCE)Vol.53, No.4,July,2017
No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!