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Vehicle type recognition by acoustic signal based on waveletpacket decomposition and approximate entropy(PDF)


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Vehicle type recognition by acoustic signal based on waveletpacket decomposition and approximate entropy
Qi Xiaoxuan12Du Li1Zhang Guoshan2
1.School of Information Engineering,Shenyang University,Shenyang 110044,China; 2.School of Electrical Engineering & Automation School,Tianjin University,Tianjin 300072,China
vehicle type recognition acoustic signal approximate entropy wavelet packet decomposition support vector machine
In order to improve the accuracy of vehicle type recognition under the condition of strong noise interference,the approximate entropy theory is introduced in this paper to analyse radiated acoustic signals from moving vehicles. Approximate entropy exposes a strong anti-interference ability and can be utilized to extract the feature characteristics from acoustic signals with the interference of dynamic background noise. Firstly,a three-layer wavelet packet decomposition method is utilized to analyse acoustic signals to obtain eight sub-frequent band signals. Then,the irregularity of each sub-frequent band signal is quantified by approximate entropy. Finally,the obtained adjacent ratio of these approximate entropies are used as the feature vector of target vehicles,which is input to the support vector machine for automatic classification of vehicle types. Experiments are conducted under normal conditions as well as strong windy conditions,feature characteristics baed on the wavelet decomposition approximate entropy could get satisfactory classification accuracy. The results show that the proposed method can identify vehicle types by acousitc signals effectively and is robust especially for windy cases.


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Last Update: 2020-02-29