Multi scale feature based matched filter processing  

作　　者：LIJun HOUChaohuan 

机构地区：[1]InstituteofAcoustics,TheChineseAcademyofSciencesBeijing100080

出　　处：《Chinese Journal of Acoustics》2004年第4期331-339,共9页声学学报（英文版）

基　　金：This work was supported by the National Natural Science Foundation of China (60272087).

摘　　要：Using the extreme difference of self-similarity and kurtosis at large level scale of wavelet transform approximation between the PTFM (Pulse Trains of Frequency Modulated) signals and its reverberation, a feature-based matched filter method using the classify-before-detect paragriam is proposed to improve the detection performance in reverberation and mul-tipath environments. Processing the data of lake-trails showed that the processing gain of the proposed method is bigger than that of matched filter about 10 dB. In multipath environments, detection performance of matched filter become badly poorer, while that of the proposed method is improved better. It shows that the method is much more robust with the effect of multipath.Using the extreme difference of self-similarity and kurtosis at large level scale of wavelet transform approximation between the PTFM (Pulse Trains of Frequency Modulated) signals and its reverberation, a feature-based matched filter method using the classify-before-detect paragriam is proposed to improve the detection performance in reverberation and mul-tipath environments. Processing the data of lake-trails showed that the processing gain of the proposed method is bigger than that of matched filter about 10 dB. In multipath environments, detection performance of matched filter become badly poorer, while that of the proposed method is improved better. It shows that the method is much more robust with the effect of multipath.

分 类 号：TN713.6[电子电信—电路与系统]