DocumentCode :
49873
Title :
Design of an Acoustic Target Classification System Based on Small-Aperture Microphone Array
Author :
Jingchang Huang ; Xin Zhang ; Feng Guo ; Qianwei Zhou ; Huawei Liu ; Baoqing Li
Author_Institution :
Shanghai Inst. of Microsyst. & Inf. Technol., Shanghai, China
Volume :
64
Issue :
7
fYear :
2015
fDate :
Jul-15
Firstpage :
2035
Lastpage :
2043
Abstract :
The acoustic recognition module of the unattended ground sensor (UGS) system applied in wild environments is faced with the challenge of complicated noise interference. In this paper, a small-aperture microphone array (MA)-based acoustic target classification system, including the system hardware architecture and classification algorithm scheme, is designed as a node-level sensor for the application of UGS in noisy situation. Starting from the analysis of signature of the acoustic signal in wild environments and the merits of small-aperture array in noise reduction, a closely arranged microelectromechanical systems MA is designed to improve the signal quality. Considering the similarities between speaker discrimination and acoustic target recognition, a classification algorithm scheme, consisting of a simplified Mel-frequency cepstrum coefficients and the Gaussian mixture model, is developed to distinguish acoustic targets´ patterns. The proposed classification algorithm has been implemented on embedded system after being tested on training datasets. By combining the small-aperture array and low-complexity classification algorithm, the presented acoustic classification prototype system is portable and efficient. To demonstrate the efficiency of the design, the prototype system is verified in a practical situation with the employment of wheeled and tracked vehicles. Evaluation of the system performances in comparison with other state-of-the-art methods indicates that the proposed design is practical for the acoustic target classification and may be widely adopted by UGS.
Keywords :
acoustic devices; acoustic noise; acoustic signal processing; microphone arrays; Gaussian mixture model; UGS application; acoustic classification prototype system; acoustic recognition module; acoustic signal; acoustic target classification; acoustic target classification system design; acoustic target pattern; acoustic target recognition; classification algorithm scheme; closely arranged microelectromechanical system; complicated noise interference; low-complexity classification algorithm; node-level sensor; noisy situation; signal quality; simplified Mel-frequency cepstrum coefficient; small-aperture microphone array-based acoustic target classification system; speaker discrimination; state-of-the-art method; system hardware architecture; tracked vehicle employment; training datasets; unattended ground sensor system; wheeled vehicle employment; wild environments; Acoustics; Arrays; Harmonic analysis; Micromechanical devices; Microphones; Noise; Signal processing algorithms; Acoustic classification system; Gaussian mixture model; Mel-frequency cepstrum coefficients; microelectromechanical systems; noise; small-aperture array; small-aperture array.;
fLanguage :
English
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9456
Type :
jour
DOI :
10.1109/TIM.2014.2366979
Filename :
6963365
Link To Document :
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