主动声呐混响模型与抗混响信号处理
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摘要
本论文研究并分析了主动声呐混响模型以及抗混响信号处理。在已有的瑞利分布混响统计模型基础上，本文着重研究了非瑞利分布混响统计模型。通过对非瑞利分布混响统计模型的仿真和分析，本文提出了抗混响的两种基本途径：一是设计一个更好的主动声呐发射波形，以提高目标分辨能力；二是改善抗混响信号处理算法。论文的工作主要包括以下几个方面：
1．目前许多主动声呐系统通过发射宽带信号来改善距离分辨率、采用波束形成技术来增加信混比和方位分辨率，这会导致混响的统计模型不再服从瑞利分布。针对这一现象，论文分析并比较了非瑞利分布模型与瑞利分布模型的区别，验证拖尾现象对接收机工作性能的影响。
2．基于经典的统计检测理论，论文针对非瑞利分布混响背景下的信号检测进行了深入的研究，计算出几种典型混响统计分布模型下的接收机工作特性曲线，进一步验证了非瑞利分布混响对接收机工作性能的影响。
3．通过对非瑞利分布混响统计模型的仿真和分析，可以发现，要提高抗混响能力，必须要从和混响有直接关系的因素出发，也就是发射信号。因此本文还讨论了目前常用的单频脉冲信号和线性调频信号，计算其模糊度函数，讨论其时间分辨率和频率分辨率。此外，还研究了超低频大时间的几何梳状波形，也比较了其模糊度函数和分辨率。得出该波形具有非均匀的频率间隔，它可以提高频率分辨性能。
4．最后主要讨论了抗混响信号处理的另外一个途径，即抗混响信号处理算法。本文先基于单元散射体模型对混响信号的时频模型进行了仿真，然后利用此模型，对其进行分段预白化处理。仿真研究了白化前后的接收机工作特性曲线，结果表明预白化处理可以提高信混比约3～5dB。
This dissertation studies and analyses active sonar reverberation model and anti-reverberation signal processing. Based on the rayleigh-distributed reverberation model, the dissertation especially concentrates on the investigation of non-rayleigh-distributed reverberation model. Anti-reverberation approaches are proposed in this dissertation via the simulation and analysis of the non-rayleigh-distributed reverberation statistical model. The first is to design a better active sonar waveform for improving targets resolution. The second is to meliorate signal processing arithmetic. According to these approaches, the following are main contributions in this dissertation.
1. At present, many active sonar systems transmit broad bandwidth waveforms to improve range-resolution and use beamforming to increase signal-to-reverberation power ratio and bearing resolution. This may causes the reverberation statistical model no longer be rayleigh-distributed. According to this phenomena, the dissertation analyses and compares rayleigh-distribution and non-rayleigh-distribution, and then validates influence of receiver operating performance by the phenomena of heavier tail.
2. Based on the classical statistical detection theory, the dissertation lucubrates signal detection under non-rayleigh-distributed reverberation background. Through the simulation of receiver operating characteristic curves, influence of receiver operating performance under non-rayleigh-distributed reverberation background are validated again.
3. Through the simulating and analyzing of non-rayleigh-distributed reverberation statistical model, we can clearly see that in order to enhance the ability of anti-reverberation, research of active sonar waveform is important. So we first discuss several transmitting signal like continuous wave pulse(CWP) and linear frequency-modulated pulse(LFM), and then compute signal ambiguity function to analyze time-resolution and frequency-resolution. Furthermore, the dissertation introduces a new super-low-frequency and large-time geometric comb waveform. It
4. At the end of this dissertation, the arithmetic of signal processing is investigated. In this part, time-frequency model of reverberation is simulated based on the
1．目前许多主动声呐系统通过发射宽带信号来改善距离分辨率、采用波束形成技术来增加信混比和方位分辨率，这会导致混响的统计模型不再服从瑞利分布。针对这一现象，论文分析并比较了非瑞利分布模型与瑞利分布模型的区别，验证拖尾现象对接收机工作性能的影响。
2．基于经典的统计检测理论，论文针对非瑞利分布混响背景下的信号检测进行了深入的研究，计算出几种典型混响统计分布模型下的接收机工作特性曲线，进一步验证了非瑞利分布混响对接收机工作性能的影响。
3．通过对非瑞利分布混响统计模型的仿真和分析，可以发现，要提高抗混响能力，必须要从和混响有直接关系的因素出发，也就是发射信号。因此本文还讨论了目前常用的单频脉冲信号和线性调频信号，计算其模糊度函数，讨论其时间分辨率和频率分辨率。此外，还研究了超低频大时间的几何梳状波形，也比较了其模糊度函数和分辨率。得出该波形具有非均匀的频率间隔，它可以提高频率分辨性能。
4．最后主要讨论了抗混响信号处理的另外一个途径，即抗混响信号处理算法。本文先基于单元散射体模型对混响信号的时频模型进行了仿真，然后利用此模型，对其进行分段预白化处理。仿真研究了白化前后的接收机工作特性曲线，结果表明预白化处理可以提高信混比约3～5dB。
This dissertation studies and analyses active sonar reverberation model and anti-reverberation signal processing. Based on the rayleigh-distributed reverberation model, the dissertation especially concentrates on the investigation of non-rayleigh-distributed reverberation model. Anti-reverberation approaches are proposed in this dissertation via the simulation and analysis of the non-rayleigh-distributed reverberation statistical model. The first is to design a better active sonar waveform for improving targets resolution. The second is to meliorate signal processing arithmetic. According to these approaches, the following are main contributions in this dissertation.
1. At present, many active sonar systems transmit broad bandwidth waveforms to improve range-resolution and use beamforming to increase signal-to-reverberation power ratio and bearing resolution. This may causes the reverberation statistical model no longer be rayleigh-distributed. According to this phenomena, the dissertation analyses and compares rayleigh-distribution and non-rayleigh-distribution, and then validates influence of receiver operating performance by the phenomena of heavier tail.
2. Based on the classical statistical detection theory, the dissertation lucubrates signal detection under non-rayleigh-distributed reverberation background. Through the simulation of receiver operating characteristic curves, influence of receiver operating performance under non-rayleigh-distributed reverberation background are validated again.
3. Through the simulating and analyzing of non-rayleigh-distributed reverberation statistical model, we can clearly see that in order to enhance the ability of anti-reverberation, research of active sonar waveform is important. So we first discuss several transmitting signal like continuous wave pulse(CWP) and linear frequency-modulated pulse(LFM), and then compute signal ambiguity function to analyze time-resolution and frequency-resolution. Furthermore, the dissertation introduces a new super-low-frequency and large-time geometric comb waveform. It
4. At the end of this dissertation, the arithmetic of signal processing is investigated. In this part, time-frequency model of reverberation is simulated based on the
引文
[1] A. D. Whalen, Detection of Signals in Noise. Academic Press, 1971
[2] 奥里雪夫斯基，海洋混响的统计特性。科学出版社，1977
[3] 奥里雪夫斯基，声呐统计方法。国防工业出版社，1984
[4] 陈亚勇，MATLAB信号处理详解。人民邮电出版社，2001
[5] 蔡平、梁国龙、葛凤翔、惠俊英，界面混响信号的仿真研究。哈尔滨工程大学学报，vol．21．NO．4，Aug．2000
[6] 蔡平、梁国龙、葛凤翔、惠俊英，WVD-HT用于混响背景中检测多普勒目标回波的仿真研究。哈尔滨工程大学学报。vol．21．NO．3，Jun．2000
[7] Douglas A. Abraham. Statistical Normalization of Non-rayleigh Reverberation. Proc. OCEANS'97 conf., Halifax, NS, Canada, Oct. 1997, pp. 500-505
[8] D. A. Abraham, Modeling Non-Rayleigh Reverberation. SR-266, SACLANT Und. Res. Cen. May. 1997
[9] D. A. Abraham, Choosing a Non-Rayleigh Reverberation Model. Proc. OCEANS'99 conf., Nov. 1999, pp. 284-288
[10] Douglas A. Abraham. Signal Excess in K-Distributed Reverberation. IEEE J. Oceanic Eng., vol.28. NO. 3, Jul. 2003
[11] Douglas A. Abraham, Peter K. WilieR. Active Sonar Detection in Shallow Water Using the Page Test. IEEE J. Oceanic Eng., vol. 27. NO. 1, Jan. 2002
[12] Douglas A. Abraham, Anthony P. Lyons, Exponential Scattering and K-Distributed Reverberation. Proc. OCEANS'01 conf., Nov. 2001, pp. 1622-1628
[13] Douglas A. Abraham, Anthony P. Lyons, Novel Physical Interpretations of K-distribution Reverberation. IEEE J. Oceanic Eng., vol. 27. NO. 4, Oct. 2002
[14] Douglas A. Abraham, Anthony P. Lyons, Simulation of Non-Rayleigh Reverberation and Clutter. IEEE J. Oceanic Eng., vol. 29. NO. 2, Apr. 2004
[15] Douglas A. Abraham, Anthony P. Lyons, Reverberation Envelope Statistics and Their Dependence on Sonar Bandwidth and Scattering Patch Size. IEEE J. Oceanic Eng., vol. 29. NO. 1, Jan. 2004
[16] Dale D. Ellis, Shallow Water Reverberation: Normal-Mode Model Predictions Compared with Bistatic Towed-Array Measurements. IEEE J. Oceanic Eng.,??vol. 18. NO. 4, Oct. 1993
[17] Dale D. Ellis, A Shallow-Water Normal-Mode Reverberation Model. J. Acoust. Soc. Am. 97(5), May, 1995
[18] 丁玉美、高西全，数字信号处理。西安电子科技大学出版社，2001
[19] E. Jakeman, P. N. Pusey, A Model for Non-Rayleigh Sea Echo. IEEE Transactions on Antennas and Propagation, vol. 24. NO. 6, pp. 806-814. 1976
[20] 方士良，海洋混响信号的序贯仿真。声学技术，vol．15．NO．3，1996
[21] 方士良、毛卫宁、陆佶人，海洋混响自相关函数的估计。东南大学学报，vol．25．NO．4A．Jul．1995
[22] Finn B. Jensen, William A. Kuperman, Michael B. Porter, Henrik Schmidt, Computational Ocean Acoustics. New York, 2000
[23] 葛凤翔、蔡平、惠俊英、彭应宁，混响背景中目标回波检测和参数估计的一种新方法。电子学报，vol．29．NO．3，Mar．2001
[24] Gareth R. Elston, Judith M. Bell, Pseudospectral Time-Domain Modeling of Non-Rayleigh Reverberation: Synthesis and Statistical Analysis of a Sidescan Sonar Image of Sand Ripples. IEEE J. Oceanic Eng., vol.29. NO. 2, Apr. 2004
[25] Henry Cox, Hung Lai, Geometric Comb Waveforms for Reverberation Suppression. IEEE Digital Object Identifier, vol. 2. NO. 2, Oct. 1994
[26] 候自强，声呐信号处理。海洋出版社，1986
[27] 胡广书，数字信号处理—理论、算法与实现。清华大学出版社，1999
[28] 惠俊英，水下声信道。国防工业出版社，1992
[29] 金受琪，多普勒声呐导航。人民交通出版社，1982
[30] Joseph M. Fialkowski, Roger C. Gauss, David M. Drumheller, Measurements and Modeling of Low-FrequencyNear-Surface Scattering Statistics. IEEE J. Oceanic Eng., vol. 29. NO. 2, Apr. 2004
[31] Kevin D. Lepage, Statistics of Broad-Band Bottom Reverberation Predictions in Shallow-Water Waveguides. IEEE J. Oceanic Eng., vol. 29. NO. 2, Apr. 2004
[32] 李启虎，声呐信号处理引论．海洋出版社，1985
[33] 李启虎，数字式声纳设计原理．安徽教育出版社，2002
[34] 刘伯胜、雷家煜，水声学原理。哈尔滨工程大学出版社，1997
[35] Marc Gensane, A Statistical Study of Acoustic Signals Backscattered from the Sea Bottom. IEEE J. Oceanic Eng., vol.14. NO. 1, Jan. 1989
[36] Ming Gu, Douglas A. Abraham, Using McDaniel's Model to Represent Non-Rayleigh Reverberation. IEEE J. Oceanic Eng., vol.26. NO. 3, Jul. 2001[37] M. Wazenski, D. Alexandrou, D. Defatta, ROC Evaluation of Adaptive Beamforming in a Simulation Shallow Water Environment. IEEE J. Oceanic Eng., vol. 21. NO. 1, Jan. 1996
[38] Paul C Etter, Underwater Acoustic Modeling Principles, Techniques and Applications. Elsevier Applied Science, Lodon and New York, 1991
[39] Richard O. Nielsen, Sonar Signal Processing. Artech House, 1991
[40] Stanley G. Chamberlain, John C. Galli, A Model for Numerical Simulation of Nonstationary Sonar Reverberation Using Linear Spectral Prediction. IEEE J. Oceanic Eng., vol. 8. NO. 1, Jan. 1983
[41] Steven Kay, John Salisbury, Improved Active Detection Using Autoregressive Prewhiteners. J. Acoust. Soc. Am. 87(5), Apr, 1990
[42] 孙文俊、杨益新，基于蒙特卡洛方法的主动声纳信号检测性能分析。计算机仿真，已录用
[43] 孙文俊、杨益新、邹士新、马远良，非瑞利分布混响背景下信号的检测。2005年全国水声学学术会议论文集
[44] 苏金明、张莲花、刘波，MATLAB工具箱应用。电子工业出版社，2004
[45] 田坦、刘国枝、孙大军，声呐技术。哈尔滨工程大学出版社，2002
[46] 王新晓、黄建国、张群飞，海洋混响仿真技术研究。声学与电子工程，2000
[47] William S. Hodgkiss, An Oceanic Reverberation Model. IEEE J. Oceanic Eng., vol. oe-9. NO. 2, Apr. 1984
[48] 徐新盛、张燕、李海森、杨士莪，海底混响仿真研究。声学学报，vol．23．NO．2，Mar．1998
[49] 杨崇林，姚蓝，探测高速小目标的声呐信号波形设计。声学技术，vol．18．NO．3，Mar．1999
[50] 赵树杰，信号检测与估计理论。西安电子科技大学，1998
[51] 朱华、黄辉宁、李永庆等，随机信号分析。北京理工大学出版社，2003
[52] 朱埜，主动声呐检测信息原理。海洋出版社，1990
[53] 朱维庆、魏振华、耿学义、潘峰、李炘，非平稳水声混响过程的自适应谱估计。声学学报，vol．20．NO．2，Mar．1995
[54] 朱燕堂、赵选民、徐伟，应用概率统计方法。西北工业大学出版社，2001
[55] 赵航芳、祝献、宫先仪，混响背景下的信号检测。哈尔滨工程大学学报，vol．25．NO．1．Feb．2004
[2] 奥里雪夫斯基，海洋混响的统计特性。科学出版社，1977
[3] 奥里雪夫斯基，声呐统计方法。国防工业出版社，1984
[4] 陈亚勇，MATLAB信号处理详解。人民邮电出版社，2001
[5] 蔡平、梁国龙、葛凤翔、惠俊英，界面混响信号的仿真研究。哈尔滨工程大学学报，vol．21．NO．4，Aug．2000
[6] 蔡平、梁国龙、葛凤翔、惠俊英，WVD-HT用于混响背景中检测多普勒目标回波的仿真研究。哈尔滨工程大学学报。vol．21．NO．3，Jun．2000
[7] Douglas A. Abraham. Statistical Normalization of Non-rayleigh Reverberation. Proc. OCEANS'97 conf., Halifax, NS, Canada, Oct. 1997, pp. 500-505
[8] D. A. Abraham, Modeling Non-Rayleigh Reverberation. SR-266, SACLANT Und. Res. Cen. May. 1997
[9] D. A. Abraham, Choosing a Non-Rayleigh Reverberation Model. Proc. OCEANS'99 conf., Nov. 1999, pp. 284-288
[10] Douglas A. Abraham. Signal Excess in K-Distributed Reverberation. IEEE J. Oceanic Eng., vol.28. NO. 3, Jul. 2003
[11] Douglas A. Abraham, Peter K. WilieR. Active Sonar Detection in Shallow Water Using the Page Test. IEEE J. Oceanic Eng., vol. 27. NO. 1, Jan. 2002
[12] Douglas A. Abraham, Anthony P. Lyons, Exponential Scattering and K-Distributed Reverberation. Proc. OCEANS'01 conf., Nov. 2001, pp. 1622-1628
[13] Douglas A. Abraham, Anthony P. Lyons, Novel Physical Interpretations of K-distribution Reverberation. IEEE J. Oceanic Eng., vol. 27. NO. 4, Oct. 2002
[14] Douglas A. Abraham, Anthony P. Lyons, Simulation of Non-Rayleigh Reverberation and Clutter. IEEE J. Oceanic Eng., vol. 29. NO. 2, Apr. 2004
[15] Douglas A. Abraham, Anthony P. Lyons, Reverberation Envelope Statistics and Their Dependence on Sonar Bandwidth and Scattering Patch Size. IEEE J. Oceanic Eng., vol. 29. NO. 1, Jan. 2004
[16] Dale D. Ellis, Shallow Water Reverberation: Normal-Mode Model Predictions Compared with Bistatic Towed-Array Measurements. IEEE J. Oceanic Eng.,??vol. 18. NO. 4, Oct. 1993
[17] Dale D. Ellis, A Shallow-Water Normal-Mode Reverberation Model. J. Acoust. Soc. Am. 97(5), May, 1995
[18] 丁玉美、高西全，数字信号处理。西安电子科技大学出版社，2001
[19] E. Jakeman, P. N. Pusey, A Model for Non-Rayleigh Sea Echo. IEEE Transactions on Antennas and Propagation, vol. 24. NO. 6, pp. 806-814. 1976
[20] 方士良，海洋混响信号的序贯仿真。声学技术，vol．15．NO．3，1996
[21] 方士良、毛卫宁、陆佶人，海洋混响自相关函数的估计。东南大学学报，vol．25．NO．4A．Jul．1995
[22] Finn B. Jensen, William A. Kuperman, Michael B. Porter, Henrik Schmidt, Computational Ocean Acoustics. New York, 2000
[23] 葛凤翔、蔡平、惠俊英、彭应宁，混响背景中目标回波检测和参数估计的一种新方法。电子学报，vol．29．NO．3，Mar．2001
[24] Gareth R. Elston, Judith M. Bell, Pseudospectral Time-Domain Modeling of Non-Rayleigh Reverberation: Synthesis and Statistical Analysis of a Sidescan Sonar Image of Sand Ripples. IEEE J. Oceanic Eng., vol.29. NO. 2, Apr. 2004
[25] Henry Cox, Hung Lai, Geometric Comb Waveforms for Reverberation Suppression. IEEE Digital Object Identifier, vol. 2. NO. 2, Oct. 1994
[26] 候自强，声呐信号处理。海洋出版社，1986
[27] 胡广书，数字信号处理—理论、算法与实现。清华大学出版社，1999
[28] 惠俊英，水下声信道。国防工业出版社，1992
[29] 金受琪，多普勒声呐导航。人民交通出版社，1982
[30] Joseph M. Fialkowski, Roger C. Gauss, David M. Drumheller, Measurements and Modeling of Low-FrequencyNear-Surface Scattering Statistics. IEEE J. Oceanic Eng., vol. 29. NO. 2, Apr. 2004
[31] Kevin D. Lepage, Statistics of Broad-Band Bottom Reverberation Predictions in Shallow-Water Waveguides. IEEE J. Oceanic Eng., vol. 29. NO. 2, Apr. 2004
[32] 李启虎，声呐信号处理引论．海洋出版社，1985
[33] 李启虎，数字式声纳设计原理．安徽教育出版社，2002
[34] 刘伯胜、雷家煜，水声学原理。哈尔滨工程大学出版社，1997
[35] Marc Gensane, A Statistical Study of Acoustic Signals Backscattered from the Sea Bottom. IEEE J. Oceanic Eng., vol.14. NO. 1, Jan. 1989
[36] Ming Gu, Douglas A. Abraham, Using McDaniel's Model to Represent Non-Rayleigh Reverberation. IEEE J. Oceanic Eng., vol.26. NO. 3, Jul. 2001[37] M. Wazenski, D. Alexandrou, D. Defatta, ROC Evaluation of Adaptive Beamforming in a Simulation Shallow Water Environment. IEEE J. Oceanic Eng., vol. 21. NO. 1, Jan. 1996
[38] Paul C Etter, Underwater Acoustic Modeling Principles, Techniques and Applications. Elsevier Applied Science, Lodon and New York, 1991
[39] Richard O. Nielsen, Sonar Signal Processing. Artech House, 1991
[40] Stanley G. Chamberlain, John C. Galli, A Model for Numerical Simulation of Nonstationary Sonar Reverberation Using Linear Spectral Prediction. IEEE J. Oceanic Eng., vol. 8. NO. 1, Jan. 1983
[41] Steven Kay, John Salisbury, Improved Active Detection Using Autoregressive Prewhiteners. J. Acoust. Soc. Am. 87(5), Apr, 1990
[42] 孙文俊、杨益新，基于蒙特卡洛方法的主动声纳信号检测性能分析。计算机仿真，已录用
[43] 孙文俊、杨益新、邹士新、马远良，非瑞利分布混响背景下信号的检测。2005年全国水声学学术会议论文集
[44] 苏金明、张莲花、刘波，MATLAB工具箱应用。电子工业出版社，2004
[45] 田坦、刘国枝、孙大军，声呐技术。哈尔滨工程大学出版社，2002
[46] 王新晓、黄建国、张群飞，海洋混响仿真技术研究。声学与电子工程，2000
[47] William S. Hodgkiss, An Oceanic Reverberation Model. IEEE J. Oceanic Eng., vol. oe-9. NO. 2, Apr. 1984
[48] 徐新盛、张燕、李海森、杨士莪，海底混响仿真研究。声学学报，vol．23．NO．2，Mar．1998
[49] 杨崇林，姚蓝，探测高速小目标的声呐信号波形设计。声学技术，vol．18．NO．3，Mar．1999
[50] 赵树杰，信号检测与估计理论。西安电子科技大学，1998
[51] 朱华、黄辉宁、李永庆等，随机信号分析。北京理工大学出版社，2003
[52] 朱埜，主动声呐检测信息原理。海洋出版社，1990
[53] 朱维庆、魏振华、耿学义、潘峰、李炘，非平稳水声混响过程的自适应谱估计。声学学报，vol．20．NO．2，Mar．1995
[54] 朱燕堂、赵选民、徐伟，应用概率统计方法。西北工业大学出版社，2001
[55] 赵航芳、祝献、宫先仪，混响背景下的信号检测。哈尔滨工程大学学报，vol．25．NO．1．Feb．2004