正交小波多尺度阵列观测声信息融合预处理算法
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摘要
在声阵列信号处理中,为了提高窄带声信号的信噪比,降低信号的失真率,提出了基于q带正交小波多尺度分析的阵列观测声信息融合预处理算法。首先,该算法将多通道阵列声信号随机分组,基于正交小波多尺度分析得到阵列信号的细节信号矩阵函数及近似信号矩阵函数;其次,构建了各组细节信号的互相关函数,给出了细节信号互相关矩阵,以细节信号的均值互相关函数为细节阈值,得到了融合细节信号集合;再次,基于融合细节信号集合和近似信号矩阵函数重构了声信号。最后,通过静态半实物仿真试验及能量比、标准差、相关系数、信噪比四个方面的统计分析,表明融合预处理算法后的观测信号不仅保留了初始观测信号90%的声能,降低了初始观测信号的波动程度,而且还保持了初始观测信号90%的相似度,提高了信噪比,降低了信号的失真率。
In oder to improve the SNR and reduce the distortion of narrowband signal in acoustic array signal processing,the fusion preprocessing algorithm of array measurement signal based on orthogonal wavelet multi-scale analysis is proposed. Firstly,the multi-channel acoustic signals are grouped at random,then the details signal matrix function and approximation signal matrix function are obtained based on orthogonal wavelet multi-scale analysis.Secondly,the cross-correlation function of details signal is constructed,and the details signal cross-correlation matrix is also obtained,so the fusion details signal mathematical set is presented due to the threshold of details signal means cross-correlation function. Thirdly,the array acoustic signals are reconstructed based on the fusion details signal mathematical set and approximation signal matrix. Finally,based on the static simulation and statistical analysis as energy ratio,standard deviation,correlation coefficient and SNR,the observation signal not only saves acoustic energy 90% of original observation signals,reduces the volatility of initial observation signals,but also maintained 90% similarity,improves the signal to noise ratio and reduces the distortion.
In oder to improve the SNR and reduce the distortion of narrowband signal in acoustic array signal processing,the fusion preprocessing algorithm of array measurement signal based on orthogonal wavelet multi-scale analysis is proposed. Firstly,the multi-channel acoustic signals are grouped at random,then the details signal matrix function and approximation signal matrix function are obtained based on orthogonal wavelet multi-scale analysis.Secondly,the cross-correlation function of details signal is constructed,and the details signal cross-correlation matrix is also obtained,so the fusion details signal mathematical set is presented due to the threshold of details signal means cross-correlation function. Thirdly,the array acoustic signals are reconstructed based on the fusion details signal mathematical set and approximation signal matrix. Finally,based on the static simulation and statistical analysis as energy ratio,standard deviation,correlation coefficient and SNR,the observation signal not only saves acoustic energy 90% of original observation signals,reduces the volatility of initial observation signals,but also maintained 90% similarity,improves the signal to noise ratio and reduces the distortion.
引文
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11 吕艳新,顾晓辉.多传声器小波多尺度信息融合滤波算法,仪器仪表学报,2012;33(4):788—794LüYanxin,Gu Xiaohui.Filtering algorithm for multi-microphones based on wavelet multi-scale information fusion.Chinese Journal of scientific Instrument,2012;33(4):788—794
12 Zhong Xionghu,Hopgood J R.Particle filtering for TDOA based acoustic source tracking:nonconcurrent multiple talkers.Signal Processing,2014;96:382—394
13 Steen K A,Mc Clellan J H,Green O,et al.Acoustic source tracking in long baseline microphone arrays.Applied Acoustics,2015;87 :38—45
14 Tian Ye,Chen Zhe,Yin Fuliang.Distributed Kalman filter-based speaker tracking in microphone array networks.Applied Acoustics,2015;89:71—77
15 Zhong Xionghu,Premkumar A B.Multiple wideband source detection and tracking using a distributed acoustic vector sensor array:a random finite set approach.Signal Processing,2014;94:583—594
2 Sankaranayaan A C,Zheng Qinfen,Chellappa R.Vehicle tracking using acoustic and video sensors.ADA431619,2004:2—8
3 Fulghum T L.The jakes fading model for antenna arrays incorporating azimuth spread vehicular technology.IEEE,2002;51(5):967 —977
4 Bird J S,Mullins G K.Analysis of swath bathymetry sonar accuracy.IEEE Journal of Oceanic Engineering,2005;30(2):372—390
5 de Jesus J U,Calvo J J V,Pucnte A I.Surveillance system based on data fusion from image acoustic array sensors.IEEE AES Systems Magazine,2000:9—16
6 刘亚雷.三位运动声阵列对声目标跟踪理论研究.南京:南京理工大学,2013Liu Yalei.Study on the tracking theory of 3d dynamic acoustic array for acoustic.Nan Jing:Nan Jing University of Science and Theology,2013
7 Wang D,Wang L.Global motion parameters estimation using a fast and robust algorithm.IEEE Trans on Circuits and Systems for Vide Technology,1997;7(5):823—826
8 Porat B,Friedlander B.A frequency domain algorithm for multiframe detection and estimation of dim targets.IEEE Trans on Pattern Analysis and Machine Intelliqence,1990;12(4):398—401
9 Barnett J.Statistical analysis of median subtraction filtering with application to point target detection in inrfared background.Proc SPIE,1989;1050:10—18
10 宋玉来,卢奂采,金江明.单层传声器阵列信号空间重采样的声波分离方法.物理学报,2014;63(19):1—9Song Yulai,Lu Huancai,Jin Jiangming.Sound wave separation method based on spatial signals resampling with single layer microphone array.Acta Phys Sin,2014;63(19):1—9
11 吕艳新,顾晓辉.多传声器小波多尺度信息融合滤波算法,仪器仪表学报,2012;33(4):788—794LüYanxin,Gu Xiaohui.Filtering algorithm for multi-microphones based on wavelet multi-scale information fusion.Chinese Journal of scientific Instrument,2012;33(4):788—794
12 Zhong Xionghu,Hopgood J R.Particle filtering for TDOA based acoustic source tracking:nonconcurrent multiple talkers.Signal Processing,2014;96:382—394
13 Steen K A,Mc Clellan J H,Green O,et al.Acoustic source tracking in long baseline microphone arrays.Applied Acoustics,2015;87 :38—45
14 Tian Ye,Chen Zhe,Yin Fuliang.Distributed Kalman filter-based speaker tracking in microphone array networks.Applied Acoustics,2015;89:71—77
15 Zhong Xionghu,Premkumar A B.Multiple wideband source detection and tracking using a distributed acoustic vector sensor array:a random finite set approach.Signal Processing,2014;94:583—594