Paper
29 May 2014 Target detection and identification using synthetic aperture acoustics
Author Affiliations +
Abstract
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) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mary Knox, Stacy Tantum, and Leslie Collins "Target detection and identification using synthetic aperture acoustics", Proc. SPIE 9072, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX, 907206 (29 May 2014); https://doi.org/10.1117/12.2050390
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Cited by 1 scholarly publication.
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KEYWORDS
Current controlled current source

Target detection

Acoustics

Backscatter

Feature extraction

Image compression

Transceivers

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