水下目标回波与混响的分数阶Fourier域盲分离
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摘要
海底混响是水下掩埋目标探测的主要干扰,而掩埋层对声波的吸收导致声散射回波信号微弱。针对强干扰下的弱信号分离的问题,研究了目标声散射回波与混响在最佳分数阶Fourier变换域中的能量聚集性差异,提出了目标回波与混响的分数阶Fourier域盲分离方法。推导了目标几何声散射成分与混响在最佳分数阶Fourier域的能量分布特性,通过在最佳分数阶Fourier域构建广义相关矩阵构建目标函数,分离出目标回波声散射信号。仿真与数据处理结果表明:分数阶Fourier域盲分离算法分离出了目标声散射信号,提高了目标回波信号的信混比;与时频域盲分离算法相比,避免了在时频面上对目标自项时频点的选取,低信混比下分离效果好。
Seafloor reverberation is the main interference for active sonar echoes,especially for targets buried in the bottom. The target scattering echoes are weak because the buried layer is characterized by strong absorption of sound waves. To solve the weak signal separation problem under strong disturbance,the energy aggregation differences in the optimal fractional Fourier transform domain was studied. On this basis,a blind separation algorithm for target echo and reverberation in fractional Fourier transform domain was presented,deducing the energy distribution characteristics of the target' s geometrical sound scattering components and reverberation in the best fractional Fourier domain. By constructing the generalized correlation matrix of the objective function in the best fractional Fourier domain,the target acoustic scattering signals were separated through approximate joint diagonalization. Simulation and data processing results show that the blind separation algorithm in the fractional Fourier domain separated the target acoustic scattering signal and improved the signal-to-reverberation ratio( SRR) of the target echoes. Compared with the blind separation algorithm in time frequency domain,the proposed algorithm avoids the selection of self-term time-frequency points and improves the separation performance in low SRR.
Seafloor reverberation is the main interference for active sonar echoes,especially for targets buried in the bottom. The target scattering echoes are weak because the buried layer is characterized by strong absorption of sound waves. To solve the weak signal separation problem under strong disturbance,the energy aggregation differences in the optimal fractional Fourier transform domain was studied. On this basis,a blind separation algorithm for target echo and reverberation in fractional Fourier transform domain was presented,deducing the energy distribution characteristics of the target' s geometrical sound scattering components and reverberation in the best fractional Fourier domain. By constructing the generalized correlation matrix of the objective function in the best fractional Fourier domain,the target acoustic scattering signals were separated through approximate joint diagonalization. Simulation and data processing results show that the blind separation algorithm in the fractional Fourier domain separated the target acoustic scattering signal and improved the signal-to-reverberation ratio( SRR) of the target echoes. Compared with the blind separation algorithm in time frequency domain,the proposed algorithm avoids the selection of self-term time-frequency points and improves the separation performance in low SRR.
引文
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[14]TANG Dajun,JACKSON D R.Application of smallroughness perturbation theory to reverberation in range-dependent waveguides[J].The journal of the acoustical society of America,2012,131(6):4428-4441.
[15]QI Lin,TAO Ran,ZHOU Siyong,et al.Detection and parameter estimation of multicomponent LFM signal based on the fractional Fourier transform[J].Science in China F:information sciences,2004,47(2):184-198.
[16]ZHAO Yanbo,YU Hua,WEI Gang,et al.Parameter estimation of wideband underwater acoustic multipath channels based on fractional fourier transform[J].IEEE transactions on signal processing,2016,64(20):5396-5408.
[2]DERBESSE L,PERNOD P,LATARD V,et al.Acoustic scattering from complex elastic shells:visualization of S0,A0and A waves[J].Ultrasonics,2000,38(1/2/3/4/5/6/7/8):860-863.
[3]GINOLHAC G,JOURDAIN G.“Principal component inverse”algorithm for detection in the presence of reverberation[J].IEEE journal of oceanic engineering,2002,27(2):310-321.
[4]GINOLHAC G,JOURDAIN G.“Principal component inverse”algorithm for detection in the presence of reverberation[J].IEEE journal of oceanic engineering,2002,27(2):310-321.
[5]杨阳,李秀坤.水下目标声散射信号的时频域盲抽取[J].物理学报,2016,65(16):164301.YANG Yang,LI Xiukun.Blind source extraction based on time-frequency characteristics for underwater object acoustic scattering[J].Acta physica sinica,2016,65(16):164301.
[6]ANDERSON S D,SABRA S G,ZAKHARIA M E,et al.Time-frequency analysis of the bistatic acoustic scattering from a spherical elastic shell[J].The journal of the acoustical society of America,2012,131(1):164-173.
[7]ANDERSON S D.Time-frequency methods for the analysis of multistaic acoustic scattering of elastic shells in shallow water[D].Atlanta,USA:Georgia Institute of Technology,2011:1-20.
[8]WANG Ruhang,HUANG Jianugo,ZHANG Yujie.An improved prewhitening method for LFM reverberation in shallow sea using frequency focusing transformation[C]//20102nd International Conference on Signal Processing Systems.Dalian,China,2010.
[9]JIA Hongjian,LI Xiukun,MENG Xiangxia.Rigid and elastic acoustic scattering signal separation for underwater target[J].The journal of the acoustical society of America,2017,142(2):653-665.
[10]王强,潘翔.水下沉底小目标回波的短时FrFT滤波分析[J].浙江大学学报:工学版,2008,42(6):918-922.WANG Qiang,PAN Xiang.Analysis of small underwater bottomed target echo time-frequency filter characteristics based on short-time FrFT[J].Journal of Zhejiang university:engineering science,2008,42(6):918-922.
[11]李秀坤,孟祥夏,夏峙.水下目标几何声散射回波在分数阶傅里叶变换域中的特性[J].物理学报,2015,64(6):064302.LI Xiukun,MENG Xiangxia,XIA Zhi.Characteristics of the geometrical scattering waves from underwater target in fractional Fourier transform domain[J].Acta physica sinica,2015,64(6):064302.
[12]汤渭霖.声呐目标回波的亮点模型[J].声学学报,1994,19(2):92-100.TANG Weilin.Highlight model of echoes from sonar targets[J].Acta acustica,1994,19(2):92-100.
[13]HARRISON C H.An approximate form of the Rayleigh reflection loss and its phase:application to reverberation calculation[J].The journal of the acoustical society of A-merica,2010,128(1):50-57.
[14]TANG Dajun,JACKSON D R.Application of smallroughness perturbation theory to reverberation in range-dependent waveguides[J].The journal of the acoustical society of America,2012,131(6):4428-4441.
[15]QI Lin,TAO Ran,ZHOU Siyong,et al.Detection and parameter estimation of multicomponent LFM signal based on the fractional Fourier transform[J].Science in China F:information sciences,2004,47(2):184-198.
[16]ZHAO Yanbo,YU Hua,WEI Gang,et al.Parameter estimation of wideband underwater acoustic multipath channels based on fractional fourier transform[J].IEEE transactions on signal processing,2016,64(20):5396-5408.
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