高斯背景干扰下瞬态信号检测
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摘要
作为强背景干扰下工作的被动定位声纳系统，其第一要务是要高可靠地完成信号的检测。被动信号检测的最佳检测器是能量检测器，但是能量检测器往往因为背景干扰的起伏和信噪比的劣化导致检测性能的下降。
双谱检测由于具有很好的高斯干扰抑制能力，在瞬态信号检测方面具有能量检测不具有的优势，将双谱检测和能量检测结合构成的联合检测系统利用了水声信号中的二阶、三阶统计信息，增加了所利用的信息量，且能在更大程度上适应复杂水声环境变化，改善和提高水声信号的检测性能。
本文通过对高斯平稳随机过程和爆炸波瞬态信号的双谱特性分析，有效利用双谱特性差别进行瞬态信号检测。与能量检测器相比，双谱检测器具有更好的抗高斯噪声能力，试验仿真结果证明了这一点。
为了进一步提高瞬态信号检测性能，我们构建了双谱检测和能量检测相结合的联合检测系统，试验仿真结果表明，两者的结合具有更好的抗噪声能力和信号检测能力。
For passive sonar system operating in the background of strong interference, the most important task is to fulfill signal detection with high reliability. The optimum detector for passive detection is energy detector. Yet energy detector usually deteriorates due to fluctuation of background interference and a decrease in SNR.
Bispectrum detection features a good capability in depressing Gaussian interferences, so it outperforms energy detector in the case of instantaneous signal detection. By incorporating bispectrum detection and energy detection method, a coalition detection system can be developed, which can obtain more information by making use of the second and third order statistics of underwater acoustic signals, and can adapt to a broader extent to complicated underwater acoustic environments, thus greatly improving underwater acoustic signal detection performances.
In this paper stationary Gaussian random processes as well as bispectrums of instantaneous explosive wave signals are analyzed, and the differences between bispectrums are efficiently used for instantaneous signal detection. As compared with energy detector, bispectrum detector can depress Gaussian noise much better, which is proved via test simulation. In order to further increase instantaneous signal detection performances, we have constructed a coalition detection system upon bispectrum detection and energy detection. Test simulation results show that the incorporation of bispectrum detection and energy detection can bring out a much better capability in noise reduction and signal detection.
双谱检测由于具有很好的高斯干扰抑制能力，在瞬态信号检测方面具有能量检测不具有的优势，将双谱检测和能量检测结合构成的联合检测系统利用了水声信号中的二阶、三阶统计信息，增加了所利用的信息量，且能在更大程度上适应复杂水声环境变化，改善和提高水声信号的检测性能。
本文通过对高斯平稳随机过程和爆炸波瞬态信号的双谱特性分析，有效利用双谱特性差别进行瞬态信号检测。与能量检测器相比，双谱检测器具有更好的抗高斯噪声能力，试验仿真结果证明了这一点。
为了进一步提高瞬态信号检测性能，我们构建了双谱检测和能量检测相结合的联合检测系统，试验仿真结果表明，两者的结合具有更好的抗噪声能力和信号检测能力。
For passive sonar system operating in the background of strong interference, the most important task is to fulfill signal detection with high reliability. The optimum detector for passive detection is energy detector. Yet energy detector usually deteriorates due to fluctuation of background interference and a decrease in SNR.
Bispectrum detection features a good capability in depressing Gaussian interferences, so it outperforms energy detector in the case of instantaneous signal detection. By incorporating bispectrum detection and energy detection method, a coalition detection system can be developed, which can obtain more information by making use of the second and third order statistics of underwater acoustic signals, and can adapt to a broader extent to complicated underwater acoustic environments, thus greatly improving underwater acoustic signal detection performances.
In this paper stationary Gaussian random processes as well as bispectrums of instantaneous explosive wave signals are analyzed, and the differences between bispectrums are efficiently used for instantaneous signal detection. As compared with energy detector, bispectrum detector can depress Gaussian noise much better, which is proved via test simulation. In order to further increase instantaneous signal detection performances, we have constructed a coalition detection system upon bispectrum detection and energy detection. Test simulation results show that the incorporation of bispectrum detection and energy detection can bring out a much better capability in noise reduction and signal detection.
引文
1．P．G．柏格曼等著，邵维文等译．水声学物理基础．科学出版社，1958
2. Robert J.Urick. Principles of Underwater Sound. 3d edition, McGraw-Hill Book Company, 1983
3．那健等．鱼雷初始信号特征研究．大连：水中目标特性研究学术交流会论文集，1998
4．吕俊军等．鱼雷噪声时频谱特征及其在鱼雷报警中的应用．大连：水中目标特性研究学术交流会论文集，1998
5．马骏等．螺旋桨涡激诱发振动响应试验研究．大连：水中目标特性研究学术交流会论文集，1998
6．马徐琨等．某型鱼雷水下辐射噪声线谱机理初析．宜昌：1993年全国水声学术交流会论文集，1993
7．梁国龙等．水声信道中窄CW脉冲的低虚警检测．宜昌：1993年全国水声学学术交流会论文集，1993
8．张贤达．《现代信号处理》．清华大学出版社，1995。
9. Doron Kletter and Hagit Messer. Suboptimal Detection of Non-Gaussian Signals by Third-Order Spectral Analysis. IEEE Trans on ASSP, Vol.38, No.6, June 1990, P901-909。
10．王燕麟．瞬态信号双谱能量检测．太原：水中探测技术交流会论文集，1996
11．张贤达．时间序列分析—高阶统计量方法．清华大学出版社，1996。
12．郭龙祥等．双谱在组合传感器信号线谱检测中的应用研究．声学技术2001增刊，2001年全国水声学学术会议论文集，2001。
13．杨晨阳等．利用高阶统计量进行信号检测．武汉：第五届全国信号处理学术会议论文集，1994
14. Lakshmi.A, Subroto Ghosh, Unnikrishnan.A. Bispectrum Approach. for Differentiating Underwater Acoustic Sources Using Self-Ognizing Feature Maps. Singapo: UDT, 200315．郑兆宁等著．水声信号被动检测与参数估计理论．科学出版社，1983
16．张兰秀等译．水下信号和数据处理．中国船舶工业总公司第七一六研究所情报室出版发行，1993
17. Kai M H. Narrowband weak signal detection by higher order spectrum [J]. IEEE Tran Signal Processing. 1996, 44(4): 874-879
18. Hinich M J, Wilson G R. Detection of non-gaussian signal in non-gaussian noise using the bispectrum [J]. IEEE Trans on ASSP, 1990, 38(7): 1126-1131
19. MELVIN J Hinich. Detecting a transient signals by bispectral analysis[J]. IEEE Transactions on ASSP, 1990, 38(7): 1277-1283
20. David O Walsh, Pamela A Delaney. Detection of transient signals in multipath environments [J]. IEEE Journal of Oceanic Engineering, 1995, 20(2): 687-695
21．周越，杨杰．基于高阶累积量的水声噪声检测与识别[J]．兵工学报，2002，23(1)：72-78
22．王燕麟．基于匹配滤波的LFM信号高阶谱检测[J]．声学与电子工程，1997，(4)：1-9
23. C.L. Nikias and M.R. Raghuveer, Bispectrum Estimation. A Digital Signal Processing Framework. Proceedings of the IEEE, Vol. 75, No. 7, July 1987
24. J.M. Mendel. Tuturial on Higher-order Statistics (Spectra) in Signal Processing and System Theory: Theoretical Results and Some Applications. Proceedings of the IEEE, Vol. 79, March 1991
25. C.L. Nikias and J.M. Mendel. Signal Processing with Higher-order Spectra. IEEE Signal Processing Magazine, July 1993
26. M.J. Hinich, D. Marandino and E.J. Sullivan. Bispectrum of Ship-Radiated Noise. Acoustical Society of America, Vol. 85, No. 4, April 1989
27. Fan Yangye, Shang Jiuhao. Feature extraction of ship radiated noise using higher order spectrum. Chinese Journal Of Acoustics 2000, Vol 19, No 2
28. A.D. Spaulding. Local optimum and suboptimum detector performance of non-Gaussian interference environment. IEEE Trans,??Commun. Vol. COM-33, no. 6, pp. 509-517, 1985
29. Sundaramoorthy G, Raghuveer M R, Dianat S A. Bispectral reconstruction of signals in noise: Amplitude reconstruction issues[J]. IEEE Trans, Acoustics Speech, Signal Processing, 1990, 38: 1297～1306
30．沈民奋，孙丽莎．现代随机信号与系统分析[M]．北京：科学出版社，1998
31．樊养余，孙进才，李平安等．基于高阶谱的船舶目标识别．模式识别与人工智能．1999，12(2)：229-233
32．飞思科技产品研发中心编著．MATLAB7辅助信号处理技术与应用．电子工业出版社，2005
2. Robert J.Urick. Principles of Underwater Sound. 3d edition, McGraw-Hill Book Company, 1983
3．那健等．鱼雷初始信号特征研究．大连：水中目标特性研究学术交流会论文集，1998
4．吕俊军等．鱼雷噪声时频谱特征及其在鱼雷报警中的应用．大连：水中目标特性研究学术交流会论文集，1998
5．马骏等．螺旋桨涡激诱发振动响应试验研究．大连：水中目标特性研究学术交流会论文集，1998
6．马徐琨等．某型鱼雷水下辐射噪声线谱机理初析．宜昌：1993年全国水声学术交流会论文集，1993
7．梁国龙等．水声信道中窄CW脉冲的低虚警检测．宜昌：1993年全国水声学学术交流会论文集，1993
8．张贤达．《现代信号处理》．清华大学出版社，1995。
9. Doron Kletter and Hagit Messer. Suboptimal Detection of Non-Gaussian Signals by Third-Order Spectral Analysis. IEEE Trans on ASSP, Vol.38, No.6, June 1990, P901-909。
10．王燕麟．瞬态信号双谱能量检测．太原：水中探测技术交流会论文集，1996
11．张贤达．时间序列分析—高阶统计量方法．清华大学出版社，1996。
12．郭龙祥等．双谱在组合传感器信号线谱检测中的应用研究．声学技术2001增刊，2001年全国水声学学术会议论文集，2001。
13．杨晨阳等．利用高阶统计量进行信号检测．武汉：第五届全国信号处理学术会议论文集，1994
14. Lakshmi.A, Subroto Ghosh, Unnikrishnan.A. Bispectrum Approach. for Differentiating Underwater Acoustic Sources Using Self-Ognizing Feature Maps. Singapo: UDT, 200315．郑兆宁等著．水声信号被动检测与参数估计理论．科学出版社，1983
16．张兰秀等译．水下信号和数据处理．中国船舶工业总公司第七一六研究所情报室出版发行，1993
17. Kai M H. Narrowband weak signal detection by higher order spectrum [J]. IEEE Tran Signal Processing. 1996, 44(4): 874-879
18. Hinich M J, Wilson G R. Detection of non-gaussian signal in non-gaussian noise using the bispectrum [J]. IEEE Trans on ASSP, 1990, 38(7): 1126-1131
19. MELVIN J Hinich. Detecting a transient signals by bispectral analysis[J]. IEEE Transactions on ASSP, 1990, 38(7): 1277-1283
20. David O Walsh, Pamela A Delaney. Detection of transient signals in multipath environments [J]. IEEE Journal of Oceanic Engineering, 1995, 20(2): 687-695
21．周越，杨杰．基于高阶累积量的水声噪声检测与识别[J]．兵工学报，2002，23(1)：72-78
22．王燕麟．基于匹配滤波的LFM信号高阶谱检测[J]．声学与电子工程，1997，(4)：1-9
23. C.L. Nikias and M.R. Raghuveer, Bispectrum Estimation. A Digital Signal Processing Framework. Proceedings of the IEEE, Vol. 75, No. 7, July 1987
24. J.M. Mendel. Tuturial on Higher-order Statistics (Spectra) in Signal Processing and System Theory: Theoretical Results and Some Applications. Proceedings of the IEEE, Vol. 79, March 1991
25. C.L. Nikias and J.M. Mendel. Signal Processing with Higher-order Spectra. IEEE Signal Processing Magazine, July 1993
26. M.J. Hinich, D. Marandino and E.J. Sullivan. Bispectrum of Ship-Radiated Noise. Acoustical Society of America, Vol. 85, No. 4, April 1989
27. Fan Yangye, Shang Jiuhao. Feature extraction of ship radiated noise using higher order spectrum. Chinese Journal Of Acoustics 2000, Vol 19, No 2
28. A.D. Spaulding. Local optimum and suboptimum detector performance of non-Gaussian interference environment. IEEE Trans,??Commun. Vol. COM-33, no. 6, pp. 509-517, 1985
29. Sundaramoorthy G, Raghuveer M R, Dianat S A. Bispectral reconstruction of signals in noise: Amplitude reconstruction issues[J]. IEEE Trans, Acoustics Speech, Signal Processing, 1990, 38: 1297～1306
30．沈民奋，孙丽莎．现代随机信号与系统分析[M]．北京：科学出版社，1998
31．樊养余，孙进才，李平安等．基于高阶谱的船舶目标识别．模式识别与人工智能．1999，12(2)：229-233
32．飞思科技产品研发中心编著．MATLAB7辅助信号处理技术与应用．电子工业出版社，2005