Pubblicazione scientifica

Passive acoustic detection of diver based on SVM

FILONE TECNOLOGICO	TEMA
sicurezza e qualità sui luoghi di lavoro

RIASSUNTO

In terms of divers equipped with open-circuit respirator, this paper studies the radiated mechanism of the divers' breathing signals. A SVM(Support Vector Machine) based approach to identify their radiated signal is proposed. In this method, the received signal is firstly processed using STFT(short-time Fourier transform). Then, the energy characteristics for sub-bands associated with the remarkable frequency is extracted to reduce the effect of random noise. Lastly, SVM-based method is applied to train many samples to obtain classifier related to classifying the diver. Based on the pool experiment, the comparison in accurate rate of recognition between the proposed SVM method and NMF (Normalized multi-band matched filter) based on setting threshold value in frequency domain is conducted. In addition, the problem of low efficiency of discriminating threshold value in detection in the case of irregular breath of diver is discussed. It is noted that passive diver recognition mainly depends on the divers' breathing signals and the SVM method has higher accuracy than the NMF according to the same set of data.

DATA

Data di pubblicazione: 01/08/2016

AUTORI

WU ZHAO
HONG CHEN
LONGFENG XIANG
XIAOMEI XIE
MIN CHEN
ZULI ZHAO
QI LI

ENTE DI AFFERENZA

SCIENCE & TECH ON ELTNC INFO CTRL LAB CHENGDU SICHUAN PROVINCE CHINA
SCHOOL OF ASTRONAUTICS & AERONAUTIC UNIV ELTNC SCIENCE & TECH OF CHINA CHENGDU SICHUAN PROVINCE CHINA

RIVISTA

2016 IEEE International Conference on Mechatronics and Automation (Page(s): 623-628)

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