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海洋环境中,在水下目标的线谱频率未知或者目标辐射噪声的连续谱很弱时,很难实现水中弱目标的准确检测,本文提出基于广义Duffing振子检测系统的水下目标辐射噪声检测方法.通过对传统周期扰动的Duffing振子信号检测系统的分析和推广,提出了一种可输入非周期、非平稳信号的广义Duffing振子检测系统,可检测输入的无先验信息目标信号.为实现广义Duffing振子系统运动状态的精确、有效判断,提出了一种相空间图形的离散分布列计算方法,通过类网格函数实现了利用统计复杂度对系统输出的嵌入式表征,从而实现了无先验信息时的水中弱目标的嵌入式检测.相同条件下与传统检测方法仿真对比可知,本文提出的方法可以检测到更低信噪比下的目标,并能满足水中检测实时性要求.
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关键词:
- 水中目标检测 /
- 广义Duffing振子系统 /
- 统计复杂度 /
- 相空间
In the marine environment, when the line spectra of underwater target radiated signal are unknown or the continuous spectra are weak, it is extremely hard to accurately detect the underwater weak target. The line spectrum based method commonly requires spectrum information for detection, and the continuous spectrum based energy method is hard to achieve accurate detection in long distance. In this paper, an underwater radiated noise detection method based on generalized Duffing oscillator detection system is proposed. Firstly, a generalized Duffing oscillator detection system for non-periodic and non-stationary input signal is proposed through deducing the traditional Duffing oscillator detection system that is perturbed by periodic signal. And the proposed generalized Duffing oscillator detection system is able to detect the signals of targets without needing prior information. Secondly, when the target radiated signal (non-periodic and non-stationary signal) is input into the generalized Duffing oscillator, a special form of output phase space (a special state of motion) is discovered and the differences in output phase space among different input signals (periodic stationary signals, nonperiodic non-stationary signals and the target radiated signals) are analyzed. It is found that the special phase space has different form from the output phase spaces of other kinds of signals; accordingly the underwater targets can be detected through the representation of the difference between special phase space and ordinary phase space. Thirdly, a discrete distribution sequence calculation method based on phase space is proposed for the precise and efficient judgment of system motion. The proposed calculation method defines a similar-grid function, based on which, the distribution sequence calculation method of output phase space is deduced, and the distribution sequences of different kinds of output phase spaces are calculated. The method realizes an embedded expression of system output by using the statistical complexity, therefore achieving the embedded underwater target detection when the line spectra of underwater target radiated signal are unknown or the continuous spectra are weak. The analysis result indicates that the method is of low-computation. Finally, the experimental results in the sea are described and the lowest signalto-noise ratio (SNR) of the method is calculated to be -9.133 dB. Simulation and experimental results have shown that the proposed method can detect target successfully in a lower SNR than traditional detection method, and the real-time performance can meet the demand for underwater detection. The method in this paper provides new ideas and ways of thinking for underwater target detection, and has very important reference value for low SNR long-distance target detection under real condition.-
Keywords:
- underwater target detection /
- generalized Duffing oscillator system /
- statistical complexity /
- phase space
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[11] Lai Z H, Leng Y G, Sun J Q, Fan S B 2012 Acta Phys. Sin. 61 050503 (in Chinese) [赖志慧, 冷永刚, 孙建桥, 范胜波 2012 物理学报 61 050503]
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[14] Li Y, Shi Y W, Ma H T, Yang B J 2004 Acta Electron. Sin. 32 87 (in Chinese) [李月, 石要武, 马海涛, 杨宝俊 2004 电子学报 32 87]
[15] Lorenz E N 1995 The Essence of Chaos (Seattle: University of Washington Press) p186
[16] Chen G, Lai D 1998 Int. J. Bifurcat. Chaos 8 1585
[17] Xue Y J, Yang S Y 2003 Chaos Soliton. Fract. 17 717
[18] Bandt C, Pompe B 2002 Phys. Rev. Lett. 88 174102
[19] Grassberger P, Procaccia I 2004 The Theory of Chaotic Attractors (New York: Springer) pp189-208
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[1] Li Q H, Li M, Yang X T 2008 Acta Acoust. 33 193 (in Chinese) [李启虎, 李敏, 杨秀庭 2008 声学学报 33 193]
[2] Li Q H, Li M, Yang X T 2008 Acta Acoust. 33 289 (in Chinese) [李启虎, 李敏, 杨秀庭 2008 声学学报 33 289]
[3] Antoni J, Hanson D 2012 IEEE J. Ocean. Eng. 37 478
[4] Zhou G L, Li G H, Cheng J 2009 Comput. Simulat. 7 337 (in Chinese) [周关林, 李钢虎, 成静 2009 计算机仿真 7 337]
[5] Liu H B, Wu D W, Jin W, Wang Y Q 2013 Acta Phys. Sin. 62 050501 (in Chinese) [刘海波, 吴德伟, 金伟, 王永庆 2013 物理学报 62 050501]
[6] Cong C, Li X K, Song Y 2014 Acta Phys. Sin. 63 064301 (in Chinese) [丛超, 李秀坤, 宋扬 2014 物理学报 63 064301]
[7] Zhang X Y, Luo L Y 2015 Acta Acoust. 40 511 (in Chinese) [张晓勇, 罗来源 2015 声学学报 40 511]
[8] Kedar S 2011 Comptes Rendus Geosci. 343 548
[9] Cato D H 2012 AIP Conf. Proc. 1495 242
[10] Hinich M J, Marandino D, Sullivan E J 1989 J. Acoust. Soc. Am. 85 1512
[11] Lai Z H, Leng Y G, Sun J Q, Fan S B 2012 Acta Phys. Sin. 61 050503 (in Chinese) [赖志慧, 冷永刚, 孙建桥, 范胜波 2012 物理学报 61 050503]
[12] He M J, Xu W, Sun Z K 2014 Sci. Sin.: Phys. Mech. Astron. 44 981 (in Chinese) [何美娟, 徐伟, 孙中奎 2014 中国科学: 物理学 力学 天文学 44 981]
[13] Bao F, Li C, Wang X, Wang Q, Du S 2010 J. Acoust. Soc. Am. 128 206
[14] Li Y, Shi Y W, Ma H T, Yang B J 2004 Acta Electron. Sin. 32 87 (in Chinese) [李月, 石要武, 马海涛, 杨宝俊 2004 电子学报 32 87]
[15] Lorenz E N 1995 The Essence of Chaos (Seattle: University of Washington Press) p186
[16] Chen G, Lai D 1998 Int. J. Bifurcat. Chaos 8 1585
[17] Xue Y J, Yang S Y 2003 Chaos Soliton. Fract. 17 717
[18] Bandt C, Pompe B 2002 Phys. Rev. Lett. 88 174102
[19] Grassberger P, Procaccia I 2004 The Theory of Chaotic Attractors (New York: Springer) pp189-208
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