Target detection and identification using synthetic aperture acoustics

Published

Conference Paper

Recent research has shown that synthetic aperture acoustic (SAA) imaging may be useful for object identification. The goal of this work is to use SAA information to detect and identify four types of objects: jagged rocks, river rocks, small concave capped cylinders, and large concave capped cylinders. More specifically, we examine the use of frequency domain features extracted from the SAA images. We utilize Support Vector Machines (SVMs) for target detection, where an SVM is trained on target and non-target (background) examples for each target type. Assuming perfect target detection, we then compare multivariate Gaussian models for target identification. Experimental results show that SAA-based frequency domain features are able to detect and identify the four types of objects. © 2014 SPIE.6.

Full Text

Duke Authors

Cited Authors

  • Knox, M; Tantum, S; Collins, L

Published Date

  • January 1, 2014

Published In

Volume / Issue

  • 9072 /

Electronic International Standard Serial Number (EISSN)

  • 1996-756X

International Standard Serial Number (ISSN)

  • 0277-786X

International Standard Book Number 13 (ISBN-13)

  • 9781628410099

Digital Object Identifier (DOI)

  • 10.1117/12.2050390

Citation Source

  • Scopus