Search

Article

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

The measure of environmental sensitivity in detection performance degradation

Liu Zong-Wei Sun Chao Du Jin-Yan

The measure of environmental sensitivity in detection performance degradation

Liu Zong-Wei, Sun Chao, Du Jin-Yan
PDF
Get Citation
  • Existing detection methods have mismatch problem when applyed to the real uncertain ocean, which will lead to the detection performance degradation. However, there has been little work on defining the practical quantitative measures of environmental sensitivity. In this article we define a measure of environmental sensitivity for target detection performance loss in an uncertain ocean for realistic uncertainties in various environmental parameters (water-column sound speed profile and seabed geoacoustic properties). The Monte Carlo approach is used to transfer the environment uncertainty through the forward problem and quantify the resulting variability in the detection performance loss. The computer simulation is based on the Malta Plateau, a well-studied shallow-water region of the Mediterranean Sea. The simulation result shows that 1) the sensitivity is range and depth dependent and in the sound channel the sensitivity is much smaller than in other regions of the ocean; 2) the sound speed profile and the upper seabed layer are most sensitive parameters for the detection performance loss; 3) the sensitivity is frequency dependent. The seabed layer properties such as sediment thickness, density and attenuation coefficient have less influence on the detection as the frequency increases.
    • Funds: Project supported by the Major Basic Project of National Security of China (Grant No. 613110020101) and the National Natural Science Foundation of China (Grant No. 11274252).
    [1]

    Baggeroer A B, Kuperman W A, Mikhalevsky P N 1993 IEEE J. Ocean. Eng. 18 401

    [2]

    Pace N G, Jensen F B 2002 Impact of Littoral Environmental Variability of Acoustic Predictions and Sonar Performance (La Spezia, Italy: Kluwer Academic Publishers) p507

    [3]

    Sha L W, Nolte L W 2005 J. Acoust. Soc. Am. 117 1942

    [4]

    Schmidt H, Baggeroer A B, Kuperman W A, Scheer E K 1990 J. Acoust. Soc. Am. 88 1851

    [5]

    Krolik J L 1992 J. Acoust. Soc. Am. 92 1408

    [6]

    Lee N, Zurk L M, Ward J 1999 Signals, Systems and Computers, 1999 Conference Record of the Thirty-Third Asilomar Conference on Pacific Grove California, October 24-27, 1999 p876

    [7]

    Richardson A M, Nolte L W 1991 J. Acoust. Soc. Am. 89 2280

    [8]

    Shorey J A, Nolte L W, Krolik J L 1994 J. Comput. Acoust. 2 285

    [9]

    Sibul L H 2006 J. Acoust. Soc. Am. 119 3342

    [10]

    Culver R L, Camin H J 2008 J. Acoust. Soc. Am. 124 3619

    [11]

    Ballard J A, Culver R L 2009 IEEE J. Ocean. Eng. 34 128

    [12]

    Walker S C, Roux P, Kuperman W A 2005 J. Acoust. Soc. Am. 118 1518

    [13]

    Wang H Z, Wang N, Gao D Z 2011 Chin. Phys. Lett. 28 114302

    [14]

    Del Balzo D R, Feuillade C, Rowe M M 1988 J. Acoust. Soc. Am. 83 2180

    [15]

    Tolstoy A 1989 J. Acoust. Soc. Am. 85 2394

    [16]

    Zhao H F, Li J L, Gong X Y 2011 J. Harbin Eng. Univ. 32 200 (in Chinese) [赵航芳, 李建龙, 宫先仪 2011 哈尔滨工程大学学报 32 200]

    [17]

    Kessel R T 1999 J. Acoust. Soc. Am. 105 122

    [18]

    Dosso S E, Giles P M, Brooke G H, McCammon D F, Pecknold S, Hines P C 2007 J. Acoust. Soc. Am. 121 42

    [19]

    Dosso S E, Morley M G, Giles P M, Brooke G H, McCammon D F, Pecknold S, Hines P C 2007 J. Acoust. Soc. Am. 122 2560

    [20]

    Pecknold S P, Masui K W, Hines P C 2008 J. Acoust. Soc. Am. 124 EL110

    [21]

    Finette S 2005 J. Acoust. Soc. Am. 117 997

    [22]

    Porter M B 1991 The Kraken Normal Mode Program (La Spezia, Italy: SACLANT Underwater Acoustic Research Center)

    [23]

    Jensen F B, Kuperman W A, Portor M B, Schmidt H 2000 Computational Ocean Acoustics (New York: American Institute of Physics) p67

    [24]

    Kay S M 1993 Fundamentals of Statistical Signal Processing, Volume II: Detection Theory (Upper Saddle River, New Jersey: Prentice Hall) p34

  • [1]

    Baggeroer A B, Kuperman W A, Mikhalevsky P N 1993 IEEE J. Ocean. Eng. 18 401

    [2]

    Pace N G, Jensen F B 2002 Impact of Littoral Environmental Variability of Acoustic Predictions and Sonar Performance (La Spezia, Italy: Kluwer Academic Publishers) p507

    [3]

    Sha L W, Nolte L W 2005 J. Acoust. Soc. Am. 117 1942

    [4]

    Schmidt H, Baggeroer A B, Kuperman W A, Scheer E K 1990 J. Acoust. Soc. Am. 88 1851

    [5]

    Krolik J L 1992 J. Acoust. Soc. Am. 92 1408

    [6]

    Lee N, Zurk L M, Ward J 1999 Signals, Systems and Computers, 1999 Conference Record of the Thirty-Third Asilomar Conference on Pacific Grove California, October 24-27, 1999 p876

    [7]

    Richardson A M, Nolte L W 1991 J. Acoust. Soc. Am. 89 2280

    [8]

    Shorey J A, Nolte L W, Krolik J L 1994 J. Comput. Acoust. 2 285

    [9]

    Sibul L H 2006 J. Acoust. Soc. Am. 119 3342

    [10]

    Culver R L, Camin H J 2008 J. Acoust. Soc. Am. 124 3619

    [11]

    Ballard J A, Culver R L 2009 IEEE J. Ocean. Eng. 34 128

    [12]

    Walker S C, Roux P, Kuperman W A 2005 J. Acoust. Soc. Am. 118 1518

    [13]

    Wang H Z, Wang N, Gao D Z 2011 Chin. Phys. Lett. 28 114302

    [14]

    Del Balzo D R, Feuillade C, Rowe M M 1988 J. Acoust. Soc. Am. 83 2180

    [15]

    Tolstoy A 1989 J. Acoust. Soc. Am. 85 2394

    [16]

    Zhao H F, Li J L, Gong X Y 2011 J. Harbin Eng. Univ. 32 200 (in Chinese) [赵航芳, 李建龙, 宫先仪 2011 哈尔滨工程大学学报 32 200]

    [17]

    Kessel R T 1999 J. Acoust. Soc. Am. 105 122

    [18]

    Dosso S E, Giles P M, Brooke G H, McCammon D F, Pecknold S, Hines P C 2007 J. Acoust. Soc. Am. 121 42

    [19]

    Dosso S E, Morley M G, Giles P M, Brooke G H, McCammon D F, Pecknold S, Hines P C 2007 J. Acoust. Soc. Am. 122 2560

    [20]

    Pecknold S P, Masui K W, Hines P C 2008 J. Acoust. Soc. Am. 124 EL110

    [21]

    Finette S 2005 J. Acoust. Soc. Am. 117 997

    [22]

    Porter M B 1991 The Kraken Normal Mode Program (La Spezia, Italy: SACLANT Underwater Acoustic Research Center)

    [23]

    Jensen F B, Kuperman W A, Portor M B, Schmidt H 2000 Computational Ocean Acoustics (New York: American Institute of Physics) p67

    [24]

    Kay S M 1993 Fundamentals of Statistical Signal Processing, Volume II: Detection Theory (Upper Saddle River, New Jersey: Prentice Hall) p34

  • [1] Liu Zong-Wei, Sun Chao, Xiang Long-Feng, Yi Feng. Robust source localization based on mode subspace reconstruction in uncertain shallow ocean environment. Acta Physica Sinica, 2014, 63(3): 034304. doi: 10.7498/aps.63.034304
    [2] Li Qian-Qian, Yang Fan-Lin, Zhang Kai, Zheng Bing-Xiang. Moving source parameter estimation in an uncertain environment. Acta Physica Sinica, 2016, 65(16): 164304. doi: 10.7498/aps.65.164304
    [3] Xia Hui-Jun, Ma Yuan-Liang, Liu Ya-Xiong. Analysis of the symmetry of the ambient noise and study of the noise reduction. Acta Physica Sinica, 2016, 65(14): 144302. doi: 10.7498/aps.65.144302
    [4] Li He, Guo Xin-Yi, Ma Li. Estimating structure and geoacoustic parameters of sub-bottom by using spatial characteristics of ocean ambient noise in shallow water. Acta Physica Sinica, 2019, 68(21): 214303. doi: 10.7498/aps.68.20190824
    [5] Jiang Peng-Fei, Lin Jian-Heng, Sun Jun-Ping, Yi Xue-Juan. Ocean ambient noise model considering depth distribution of source and geo-acoustic inversion. Acta Physica Sinica, 2017, 66(1): 014306. doi: 10.7498/aps.66.014306
    [6] Zhao Xian-Bin, Yan Wei, Wang Ying-Qiang, Lu Wen, Ma Shuo. Simulation study on the design of key technical parameters in marine environment sounding with fully polarimetric synthetic aperture radar based on ocean surface scattering model. Acta Physica Sinica, 2014, 63(21): 218401. doi: 10.7498/aps.63.218401
    [7] Liang Xiao, Wang Rui-Li. Sensitivity analysis and validation of detonation computational fluid dynamics model. Acta Physica Sinica, 2017, 66(11): 116401. doi: 10.7498/aps.66.116401
    [8] Gao Dang-Li, Li Lan-Xing, Feng Xiao-Juan, Chong Bo, Xin Hong, Zhao Jin, Zhang Xiang-Yu. Regulation of sensitivity of Yb concentration to power-dependent upconversion luminescence colors. Acta Physica Sinica, 2018, 67(22): 223201. doi: 10.7498/aps.67.20181167
    [9] Liu Jing-Jing, Sun Jun-Jun, Hu Hai-Yun, Xing Xiu-San. The life prediction for materials under the corrosion of seawater. Acta Physica Sinica, 2005, 54(5): 2414-2417. doi: 10.7498/aps.54.2414
    [10] Zhang Wei-Hong, Niu Zhong-Ming, Wang Feng, Gong Xiao-Bo, Sun Bao-Hua. Uncertainties of nucleo-chronometers from nuclear physics inputs. Acta Physica Sinica, 2012, 61(11): 112601. doi: 10.7498/aps.61.112601
  • Citation:
Metrics
  • Abstract views:  674
  • PDF Downloads:  577
  • Cited By: 0
Publishing process
  • Received Date:  15 August 2012
  • Accepted Date:  20 September 2012
  • Published Online:  20 March 2013

The measure of environmental sensitivity in detection performance degradation

  • 1. Institute of Acoustic Engineering, Northwestern Polytechnical University, Xi’an 710072, China
Fund Project:  Project supported by the Major Basic Project of National Security of China (Grant No. 613110020101) and the National Natural Science Foundation of China (Grant No. 11274252).

Abstract: Existing detection methods have mismatch problem when applyed to the real uncertain ocean, which will lead to the detection performance degradation. However, there has been little work on defining the practical quantitative measures of environmental sensitivity. In this article we define a measure of environmental sensitivity for target detection performance loss in an uncertain ocean for realistic uncertainties in various environmental parameters (water-column sound speed profile and seabed geoacoustic properties). The Monte Carlo approach is used to transfer the environment uncertainty through the forward problem and quantify the resulting variability in the detection performance loss. The computer simulation is based on the Malta Plateau, a well-studied shallow-water region of the Mediterranean Sea. The simulation result shows that 1) the sensitivity is range and depth dependent and in the sound channel the sensitivity is much smaller than in other regions of the ocean; 2) the sound speed profile and the upper seabed layer are most sensitive parameters for the detection performance loss; 3) the sensitivity is frequency dependent. The seabed layer properties such as sediment thickness, density and attenuation coefficient have less influence on the detection as the frequency increases.

Reference (24)

Catalog

    /

    返回文章
    返回