搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

风成噪声背景下垂直阵阵列信噪比随声源深度的变化规律

李明杨 赵航芳 孙超

引用本文:
Citation:

风成噪声背景下垂直阵阵列信噪比随声源深度的变化规律

李明杨, 赵航芳, 孙超

Variation of signal-to-noise ratio of vertical array with sound source depth under wind-generated noise background

Li Ming-Yang, Zhao Hang-Fang, Sun Chao
PDF
HTML
导出引用
  • 风成噪声是海洋中最广泛存在的环境噪声、是被动声纳处理性能的重要影响因素.它具有一个典型的物理性质是很大程度上只对应中高阶模态. 阵列信噪比计入了阵列采样辐射声强、背景噪声功率和阵处理增益, 是决定声纳阵列处理性能的关键物理量. 本文研究了受风成噪声模态结构影响, 典型夏季浅海环境中垂直阵阵列信噪比随声源深度的变化关系. 在简正波模深函数采样完整的假设条件下, 理论证明了阵列信噪比随声源深度的变化可近似为低阶模态幅度强度(模深函数模值的平方)随深度变化的线性叠加, 且模态阶数越低, 贡献越大; 并且, 在强风成噪声背景、显著负梯度环境下该变化规律可由1阶模态幅度强度随深度的变化近似独立表征. 以上结果表明, 在同一声源距离条件下, 声源置于水体下半部分时的阵列信噪比比置于海面附近更大, 并且在位于1阶模态峰值点所在深度附近时达到最大. 典型负声速梯度浅海环境中的仿真实验结果对理论分析进行了验证, 并表明在一定条件下阵列信噪比随声源深度的变化与声源距离近似无关.
    Wind-generated noise is ubiquitous in ocean environments and highly influences the passive sonar performance. Since it originates from sources near the ocean surface, one of its physical features is that it largely represents only the intermediate- and high-order modes. The array-level signal-to-noise ratio (SNR), which includes the array-sampled sound intensity, background noise power, and array gain, is an essential quantity determining the sonar array performance. What is investigated in this work is how the array-level SNR of the vertical line array (VLA) varies with the source depth in downward-refracting shallow water, contributed by the modal structure of the surface noise. On the assumption that the modes are well sampled, it is theoretically demonstrated that the SNR varying with the source depth can be approximated as a linear combination of the lower-order mode-amplitude intensities varying with the water depth. Particularly, when the surface noise especially dominates and the water channel is highly downward refractive, this variation can be represented nearly only by the 1st-order mode-amplitude intensity varying with depth. The structure is meaningful in practice. It suggests the SNR will be inherently larger when the source is submerged than it is near the ocean surface, and will be maximized at a source depth slightly below the 1st-order mode peak across different source ranges. The above assertions are demonstrated in a typical downward-refracting shallow-water channel; the effects from the dominant degree of the surface noise, sound speed gradient in water column, and array aperture are investigated numerically. The obtained results are shown below. 1) Under certain circumstances, the variation of SNR with source depth is nearly irrelevant to the source range. 2) When the surface noise is more significant, the largest SNR in a certain source range will be more significantly larger than the SNR for the source near the surface, the corresponding source depth will be closer to that presenting the 1st-order mode’s peak, and the variation of SNR with source depth is increasingly irrelevant to the source range. 3) A stronger downward-refracting sound speed also enhances this SNR superiority and irrelevance to the source range, but causes the source depth presenting the largest SNR to be more deviated from the 1st-order mode’s peak. 4) Although the structure is unraveled on the assumption that the VLA spans the full water column, it can be seen when the VLA does not but covers the low-order modes' main part; when the array aperture is insufficiently large it will become approximately periodic in the source range, with the source depth presenting the largest SNR fluctuating lightly and nearly periodically around the 1st-order mode peak.
      通信作者: 赵航芳, hfzhao@zju.edu.cn
    • 基金项目: 国家自然科学基金青年科学基金(批准号: 12004335)和国家自然科学基金(批准号: 62071429)资助的课题.
      Corresponding author: Zhao Hang-Fang, hfzhao@zju.edu.cn
    • Funds: Project supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 12004335) and the National Natural Science Foundation of China (Grant No. 62071429).
    [1]

    Urick R J 1984 Ambient Noise in the Sea (Washington: Undersea Warfare Technology Office) pp2–30

    [2]

    Hamson R M 1985 J. Acoust. Soc. Am. 78 1702Google Scholar

    [3]

    Zakarauskas P 1986 Canadian Acoust. 14 3

    [4]

    Dahl P, Miller J, Cato D, Andrew R 2007 Acoust. Today 3 23Google Scholar

    [5]

    Jensen F B, Kuperman W A, Porter M B, Schmidt H 2000 Computational Ocean Acoustics (New York. USA: Springer-Verlag) chap 9, pp338–340

    [6]

    Cron B F, Sherman C H 1962 J. Acoust. Soc. Am. 34 1732Google Scholar

    [7]

    Kuperman W A, Ingenito F 1980 J. Acoust. Soc. Am. 67 1988Google Scholar

    [8]

    Liggett W S, Jacobson M J 1965 J. Acoust. Soc. Am. 38 303Google Scholar

    [9]

    Yang T C, Kwang Y 1997 J. Acoust. Soc. Am. 101 2541Google Scholar

    [10]

    周建波, 朴胜春, 刘亚琴, 祝捍皓 2017 物理学报 66 014301Google Scholar

    Zhou J B, Piao S C, Liu Y Q, Zhu H H 2017 Acta Phys. Sin. 66 014301Google Scholar

    [11]

    Jiang D, Li Z, Qin J, Peng Z, Shao H 2017 Sci. China Phys. Mech. 60 124321Google Scholar

    [12]

    蒋光禹, 孙超, 谢磊, 刘雄厚 2019 物理学报 68 024302Google Scholar

    Jiang G Y, Sun C, Xie L, Liu X H 2019 Acta Phys. Sin. 68 024302Google Scholar

    [13]

    Kay S 1993 Fundamentals of Statistical Signal Processing Volume II: Detection Theory (New Jersey: Prentice Hall) pp197–200, 478–479

    [14]

    Kong D Z, Sun C, Li M Y, Xie L 2021 Defence Technology 17 1414Google Scholar

    [15]

    Li M Y, Sun C, Zhao H, Willett P 2022 IEEE J. Ocean. Eng. 47 201Google Scholar

    [16]

    Baggeroer A B, Kuperman W A, Schmidt H 1987 J. Acoust. Soc. Am. 83 571Google Scholar

    [17]

    Buck J R, Preisig J C, Wage K E 1998 J. Acoust. Soc. Am. 103 1813Google Scholar

    [18]

    向龙凤, 孙超, 李明杨 2015 声学学报 40 779Google Scholar

    Xiang L F, Sun C, Li M Y 2015 Acta Acustica 40 779Google Scholar

    [19]

    Wang N, Liu J Z 2002 Chin. Phys. B 11 456Google Scholar

    [20]

    Kim K, Woojae S, Keunhwa L 2010 IEEE J. Ocean. Eng. 35 120Google Scholar

    [21]

    Van Trees H L 2002 Optimum Array Processing: Part IV of Detection, Estimation, and Modulation Theory (New York: John Wiley & Sons) pp449–450

    [22]

    Neilsen T B, Westwood E K 2002 J. Acoust. Soc. Am. 111 748Google Scholar

    [23]

    Porter M B 1991 The KRAKEN Normal Mode Program (La Spezia: SCALANT Undersea Research Center)

    [24]

    https://www.bksv.com/media/doc/bp0317.pdf

    [25]

    Wenz G M 1962 J. Acoust. Soc. Am. 34 1936Google Scholar

    [26]

    Yang T C 1987 J. Acoust. Soc. Am. 82 1736Google Scholar

    [27]

    李明杨, 孙超, 邵炫 2014 物理学报 63 204302Google Scholar

    Li M Y, Sun C, Shao X 2014 Acta Phys. Sin. 63 204302Google Scholar

  • 图 1  典型负声速梯度浅海环境

    Fig. 1.  Typical shallow sea environment with negative sound velocity gradient.

    图 2  200 Hz声源激发的18阶模态的形状

    Fig. 2.  Shapes of 18 modes excited by a 200 Hz source.

    图 3  垂直阵覆盖全水深时风成噪声协方差矩阵特征向量与模态采样的对应关系 (a)归一化特征值; (b) 特征向量与模态采样的相关系数

    Fig. 3.  Corresponding relation analysis between eigenvectors of the surface noise covariance matrix and sampled modes for the vertical line array spanning the full water column: (a) Normalized eigenvalues; (b) correlations between eigenvectors and sampled modes.

    图 4  归一化SNR随声源深度的变化结果 (a) 不同声源距离; (b)${r_{\rm{s}}} = 10\;{\rm{km}}$(在每个声源范围内, SNR由该范围内的最大SNR归一化)

    Fig. 4.  Normalized SNR versus source depths: (a) Different source ranges; (b) ${r_{\rm{s}}} = 10\;{\rm{km}}$ (at each source range the SNR is normalized by the greatest SNR at that range).

    图 5  阵列覆盖全水深时不同特征向量 (a)关于SNR的权值; (b)对SNR的贡献随声源深度的变化(关于图中最大值进行了归一化)

    Fig. 5.  For the vertical line array spanning the full water column different eigenvectors': (a) Weights to SNR; (b) contributions to SNR versus source depths(normalized by the greatest value).

    图 6  声源距离10 km上归一化SNR随声源深度的变化结果 (a)不同风成噪声强度; (b) $\alpha = 1000$时SNR随声源深度与1阶模态幅度强度随深度变化对比

    Fig. 6.  Normalized SNR versus source depths at ${r_{\rm{s}}} = 10\;{\rm{km}}$: (a) Different α; (b) comparison of source depths and the 1 st-order mode-amplitude intensity varying with water depths for $\alpha = 1000$.

    图 7  $\alpha = 1$时不同声源距离上归一化SNR随声源深度的变化结果

    Fig. 7.  Normalized SNR versus source depths across different source ranges for $\alpha = 1$.

    图 8  不同声源距离上归一化SNR随声源深度的变化结果 (a) g = -0.05 s–1; (b) g = –0.07 s–1; (c) g = –0.10 s–1; (d) g = –0.30 s–1

    Fig. 8.  Normalized SNR versus source depths at different source ranges: (a) g = –0.05 s–1; (b) g = –0.07 s–1; (c) g = –0.10 s–1; (d) g = –0.30 s–1.

    图 9  不同声速梯度环境中归一化SNR随声源深度的变化结果(${r_{\rm{s}}} = 10\;{\rm{km}}$)

    Fig. 9.  Normalized SNR versus source depths at ${r_{\rm{s}}} = 10\;{\rm{km}}$ in various gradient cases.

    图 10  垂直阵覆盖10—100 m时不同声源距离上归一化SNR随声源深度的变化关系

    Fig. 10.  Normalized SNR versus source depths across different source ranges for the vertical line array spanning from 10 to 100 m in depth.

    图 11  垂直阵覆盖50—100 m时(a)不同声源距离上SNR随声源深度的变化结果和(b) 最大SNR对应的声源深度(红色虚线为1阶模态峰值点所在深度)

    Fig. 11.  For the vertical line spanning from 50 to 100 m in depth: (a) Normalized SNR versus source depths; (b) the source depth presenting the largest SNR at different source ranges(The red dashed line is the depth of the peak point of the first-order mode).

    图 12  垂直阵覆盖50—100 m时影响SNR的模态采样分析 (a) 模态采样与特征向量相关系数); (b) 不同特征向量对SNR的归一化权值, 通过第11个特征向量的归一化

    Fig. 12.  Analysis of mode’s contribution to the SNR for the vertical line array spanning from 50 to 100 m in depth: (a) The correlation between sampled modes and eigenvectors; (b) the weights of different eigenvectors to the SNR, normalized by that of the 11 th eigenvector.

  • [1]

    Urick R J 1984 Ambient Noise in the Sea (Washington: Undersea Warfare Technology Office) pp2–30

    [2]

    Hamson R M 1985 J. Acoust. Soc. Am. 78 1702Google Scholar

    [3]

    Zakarauskas P 1986 Canadian Acoust. 14 3

    [4]

    Dahl P, Miller J, Cato D, Andrew R 2007 Acoust. Today 3 23Google Scholar

    [5]

    Jensen F B, Kuperman W A, Porter M B, Schmidt H 2000 Computational Ocean Acoustics (New York. USA: Springer-Verlag) chap 9, pp338–340

    [6]

    Cron B F, Sherman C H 1962 J. Acoust. Soc. Am. 34 1732Google Scholar

    [7]

    Kuperman W A, Ingenito F 1980 J. Acoust. Soc. Am. 67 1988Google Scholar

    [8]

    Liggett W S, Jacobson M J 1965 J. Acoust. Soc. Am. 38 303Google Scholar

    [9]

    Yang T C, Kwang Y 1997 J. Acoust. Soc. Am. 101 2541Google Scholar

    [10]

    周建波, 朴胜春, 刘亚琴, 祝捍皓 2017 物理学报 66 014301Google Scholar

    Zhou J B, Piao S C, Liu Y Q, Zhu H H 2017 Acta Phys. Sin. 66 014301Google Scholar

    [11]

    Jiang D, Li Z, Qin J, Peng Z, Shao H 2017 Sci. China Phys. Mech. 60 124321Google Scholar

    [12]

    蒋光禹, 孙超, 谢磊, 刘雄厚 2019 物理学报 68 024302Google Scholar

    Jiang G Y, Sun C, Xie L, Liu X H 2019 Acta Phys. Sin. 68 024302Google Scholar

    [13]

    Kay S 1993 Fundamentals of Statistical Signal Processing Volume II: Detection Theory (New Jersey: Prentice Hall) pp197–200, 478–479

    [14]

    Kong D Z, Sun C, Li M Y, Xie L 2021 Defence Technology 17 1414Google Scholar

    [15]

    Li M Y, Sun C, Zhao H, Willett P 2022 IEEE J. Ocean. Eng. 47 201Google Scholar

    [16]

    Baggeroer A B, Kuperman W A, Schmidt H 1987 J. Acoust. Soc. Am. 83 571Google Scholar

    [17]

    Buck J R, Preisig J C, Wage K E 1998 J. Acoust. Soc. Am. 103 1813Google Scholar

    [18]

    向龙凤, 孙超, 李明杨 2015 声学学报 40 779Google Scholar

    Xiang L F, Sun C, Li M Y 2015 Acta Acustica 40 779Google Scholar

    [19]

    Wang N, Liu J Z 2002 Chin. Phys. B 11 456Google Scholar

    [20]

    Kim K, Woojae S, Keunhwa L 2010 IEEE J. Ocean. Eng. 35 120Google Scholar

    [21]

    Van Trees H L 2002 Optimum Array Processing: Part IV of Detection, Estimation, and Modulation Theory (New York: John Wiley & Sons) pp449–450

    [22]

    Neilsen T B, Westwood E K 2002 J. Acoust. Soc. Am. 111 748Google Scholar

    [23]

    Porter M B 1991 The KRAKEN Normal Mode Program (La Spezia: SCALANT Undersea Research Center)

    [24]

    https://www.bksv.com/media/doc/bp0317.pdf

    [25]

    Wenz G M 1962 J. Acoust. Soc. Am. 34 1936Google Scholar

    [26]

    Yang T C 1987 J. Acoust. Soc. Am. 82 1736Google Scholar

    [27]

    李明杨, 孙超, 邵炫 2014 物理学报 63 204302Google Scholar

    Li M Y, Sun C, Shao X 2014 Acta Phys. Sin. 63 204302Google Scholar

  • [1] 周玉媛, 孙超, 谢磊, 刘宗伟. 基于波束-波数域非相干匹配的浅海运动声源深度估计方法. 物理学报, 2023, 72(8): 084302. doi: 10.7498/aps.72.20222361
    [2] 李晓彬, 孙超, 刘雄厚. 浅海负跃层中利用互相关输出峰值迁移曲线的声源深度判别. 物理学报, 2022, 71(13): 134302. doi: 10.7498/aps.71.20211987
    [3] 朱启轩, 孙超, 刘雄厚. 利用海底弹射区角度-距离干涉结构特征实现声源深度估计. 物理学报, 2022, 71(18): 184301. doi: 10.7498/aps.71.20220746
    [4] 张少东, 孙超, 谢磊, 刘雄厚, 王宣. 浅海波导环境不确定性对声源功率估计的影响. 物理学报, 2021, 70(24): 244301. doi: 10.7498/aps.70.20210852
    [5] 李明杨, 赵航芳, 孙超. 风成噪声背景下垂直阵阵列信噪比随声源深度的变化规律. 物理学报, 2021, (): . doi: 10.7498/aps.70.20211654
    [6] 蒋光禹, 孙超, 李沁然. 涡旋对深海风成噪声垂直空间特性的影响. 物理学报, 2020, 69(14): 144301. doi: 10.7498/aps.69.20200059
    [7] 史平, 马健, 钱轩, 姬扬, 李伟. 铷原子气体自旋噪声谱测量的信噪比分析. 物理学报, 2017, 66(1): 017201. doi: 10.7498/aps.66.017201
    [8] 张揽月, 丁丹丹, 杨德森, 时胜国, 朱中锐. 阵元随机均匀分布球面阵列联合噪声源定位方法. 物理学报, 2017, 66(1): 014303. doi: 10.7498/aps.66.014303
    [9] 江鹏飞, 林建恒, 孙军平, 衣雪娟. 考虑噪声源深度分布的海洋环境噪声模型及地声参数反演. 物理学报, 2017, 66(1): 014306. doi: 10.7498/aps.66.014306
    [10] 夏麾军, 马远良, 刘亚雄. 海洋环境噪声场对称性分析及噪声消除方法. 物理学报, 2016, 65(14): 144302. doi: 10.7498/aps.65.144302
    [11] 郭晓乐, 杨坤德, 马远良, 杨秋龙. 一种基于简正波模态消频散变换的声源距离深度估计方法. 物理学报, 2016, 65(21): 214302. doi: 10.7498/aps.65.214302
    [12] 戚聿波, 周士弘, 张仁和, 任云. 一种基于β-warping变换算子的被动声源距离估计方法. 物理学报, 2015, 64(7): 074301. doi: 10.7498/aps.64.074301
    [13] 苏林, 马力, 宋文华, 郭圣明, 鹿力成. 声速剖面对不同深度声源定位的影响. 物理学报, 2015, 64(2): 024302. doi: 10.7498/aps.64.024302
    [14] 焦尚彬, 任超, 李鹏华, 张青, 谢国. 乘性和加性α稳定噪声环境下的过阻尼单稳随机共振现象. 物理学报, 2014, 63(7): 070501. doi: 10.7498/aps.63.070501
    [15] 戚聿波, 周士弘, 张仁和, 张波, 任云. 水平变化浅海声波导中模态特征频率与声源距离被动估计. 物理学报, 2014, 63(4): 044303. doi: 10.7498/aps.63.044303
    [16] 韩云, 钟圣伦, 叶正圣, 陈启军. 基于视角无关转换的深度摄像机定位技术. 物理学报, 2014, 63(7): 074211. doi: 10.7498/aps.63.074211
    [17] 刘小龙, 黄建国, 雷开卓. 水下等离子体声源的冲击波负压特性. 物理学报, 2013, 62(20): 204301. doi: 10.7498/aps.62.204301
    [18] 周泽民, 曾新吾, 龚昌超, 赵云, 田章福. 大功率调制气流声源阵列的相干合成实验研究. 物理学报, 2013, 62(13): 134305. doi: 10.7498/aps.62.134305
    [19] 张宣妮, 张淳民, 艾晶晶. 四分束风成像偏振干涉仪信噪比的研究. 物理学报, 2013, 62(3): 030701. doi: 10.7498/aps.62.030701
    [20] 郭冠军, 苏 林, 毕思文. 风成海面的极化辐射. 物理学报, 2005, 54(5): 2448-2452. doi: 10.7498/aps.54.2448
计量
  • 文章访问数:  2730
  • PDF下载量:  60
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-09-06
  • 修回日期:  2021-10-14
  • 上网日期:  2022-02-14
  • 刊出日期:  2022-02-20

/

返回文章
返回