无线传感器网络中声震信号的特征提取算法
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摘要
面向无线传感器网络在地面目标声震信号识别方面的应用需求,提出基于局域判别基(Local Discriminant Bases,LDB)算法的特征提取方法.并且,针对现有的基于时频能量图的可分性测度的缺点,提出新的基于概率密度估计的相对微分熵的可分性测度.基于实地采集到的信号的仿真实验表明,该方法在一定程度上提高了目标的正确识别率,降低了特征维数,具有实际的应用价值.
Feature extraction algorithm based on local discriminant bases (LDB) is proposed to satisfy the requirement of application on classification of acoustic-seismic signals of ground targets in wireless sensor networks. And a new discriminant measure using relative differential entropy which is based on probability density estimation is proposed to solve the problem of time-frequency energy map. Experiments based on real signals indicate that this method can improve the performance of classification at a certain extent and decrease the dimension of features,so it is practically valuable for application.
Feature extraction algorithm based on local discriminant bases (LDB) is proposed to satisfy the requirement of application on classification of acoustic-seismic signals of ground targets in wireless sensor networks. And a new discriminant measure using relative differential entropy which is based on probability density estimation is proposed to solve the problem of time-frequency energy map. Experiments based on real signals indicate that this method can improve the performance of classification at a certain extent and decrease the dimension of features,so it is practically valuable for application.
引文
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[1]崔莉,鞠海玲,苗勇,等.无线传感器网络研究进展[J].计算机研究与发展,2005,42(1):163-174.
[7]聂伟荣,朱继南.运动目标地震动信号的时频特征分析[J].南京理工大学学报,2002,26(5):478-482.
[8]聂伟荣,朱继南,郭亚军,等.地震动信号的分析与目标识别[J].电子科技大学学报,2003,32(1):26-30.
[12]柳革命,孙超,刘兵,等.局域判别基空间能量的水声目标特征提取[J].声学技术,2007,26(6):1089-1093.
[13]柳征,姜文利,周一宇.基于小波包变换的辐射源信号识别[J].信号处理,2005,21(5):460-464.
[2]Estrin D,Girod L,Pottie G,et al.Instrumenting the world with wireless sensor network[C].ICASSP′2001.Salt Lake City,UT,2001,2675-2678.
[3]Choe H,Karlsen R,Gerhart G,et al.Wavelet based ground vehi-cle recognition using acoustic signals[C].Proc.SPIE2762,1996,434-445.
[4]Liu Li.Ground vehicle acoustic signal processing based on biologi-cal hearing models[D].University of Maryland,College Park,1999.
[5]Wu H,Siegel M,Khosla P.Vehicle sound signature recognition by frequency vector principal component analysis[J].IEEE Trans-actions on Instrumentation and Measurement,1999,48(5):1005-1009.
[6]Lan Jin-hui,Nahavandi S,Lan Tian,et al.Recognition of moving ground targets by measuring and processing seismic signal[J].Measurement,2005,37:189-199.
[7]Nie Wei-rong,Zhu Ji-nan.Eigenvector analysis in time and fre-quency of seismic signals of moving target[J].Journal of Nanjing University of Science and Tecchnology,2002,26(5):478-482.
[8]Nie Wei-rong,Zhu Ji-nan,Guo Ya-jun,et al.Seismic signals a-nalysis and identification[J].Journal of UEST of China,2003,32(1):26-30.
[9]Mallat S.A wavelet tour of signal processing[M].San Diego:Academic Press,1998.
[10]Saito N,Coifman R R.Local discriminant bases[A].Wavelet ap-plication in signal and image processing II[C].Proc.SPIE Con-ference,San Diego,SA,1994,2303:2-14.
[11]Saito N,Coifman R R.Local discriminant bases and their applica-tions[J].Journal of Mathematical Imaging Vision,1995,5(4):337-358.
[12]Liu Ge-ming,Sun Chao,Liu Bing,et al.Feature extraction based on subspace energy of local discriminant basis[J].Technical A-coustics,2007,26(6):1089-1093.
[13]Liu Zheng,Jiang Wen-li,Zhou Yi-yu.Emitter signals recognition based on wavelet packet transform[J].Signal Processing,2005,21(5):460-464.
[14]Seekings P,Potter J.Classification of marine acoustic signals u-sing wavelets and neural networks[C].WESPAC8,Singapore,2003.
[15]Wu H W,Mendel J M.Classification of battlefield ground vehi-cles using acoustic features and fuzzy logic rule-based classifiers[J].IEEE Transactions on Fuzzy Systems,2007,15(1):56-72.
[16]Munich M E.Bayesian subspace methods for acoustic signature recognition of vehicles[C].EUSIPCO2004,Vienna,Austria,2004,6-10.
[17]Duarte M,Hu Y H.Vehicle classification in distributed sensor net-works[J].Journal of Parallel and Distributed Computing,2004,64(7):826-838.
[1]崔莉,鞠海玲,苗勇,等.无线传感器网络研究进展[J].计算机研究与发展,2005,42(1):163-174.
[7]聂伟荣,朱继南.运动目标地震动信号的时频特征分析[J].南京理工大学学报,2002,26(5):478-482.
[8]聂伟荣,朱继南,郭亚军,等.地震动信号的分析与目标识别[J].电子科技大学学报,2003,32(1):26-30.
[12]柳革命,孙超,刘兵,等.局域判别基空间能量的水声目标特征提取[J].声学技术,2007,26(6):1089-1093.
[13]柳征,姜文利,周一宇.基于小波包变换的辐射源信号识别[J].信号处理,2005,21(5):460-464.
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