Acoustic Detection for Vehicle Targets and Recognition by Data Fusion

Author

Lan, Jinhui ; Zhang, Zhaohui ; Xiong, Shenshu

Author_Institution

Inf. Eng. Sch., Beijing Univ. of Sci. & Technol.

Volume

1

fYear

2005

fDate

16-19 May 2005

Firstpage

551

Lastpage

553

Abstract

This paper researches acoustic signals of typical vehicle targets in order to extract features and to recognize vehicle targets. As a data fusion method, the technique of artificial neural networks combined with genetic algorithm (ANNCGA) is applied for recognition of acoustic signals that belong to different kinds of vehicle targets. The technique and its architecture have been presented. The algorithm had been used for classification and recognition of acoustic signals of vehicle targets in the outdoor environment. Through experiments, it can be proven that acoustic properties of target acquired are correct, ANNCGA data fusion method is effective to solve the problem of target recognition

Keywords

acoustic signal detection; genetic algorithms; neural nets; sensor fusion; vehicles; ANNCGA; acoustic detection; acoustic signal classification; acoustic signal recognition; acoustic signals; artificial neural networks; data fusion; feature extraction; genetic algorithm; target recognition; vehicle recognition; vehicle targets; Acoustic sensors; Acoustic signal detection; Acoustic testing; Diesel engines; Feature extraction; Frequency; Surveillance; Target recognition; Vehicle detection; Vehicles; Acoustic detection; Data fusion; Target recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference, 2005. IMTC 2005. Proceedings of the IEEE

Conference_Location

Ottawa, Ont.

Print_ISBN

0-7803-8879-8

Type

conf

DOI

10.1109/IMTC.2005.1604177

Filename

1604177