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Proceedings Paper

Algorithm for classifying multiple targets using acoustic signatures
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Paper Abstract

In this paper we discuss an algorithm for classification and identification of multiple targets using acoustic signatures. We use a Multi-Variate Gaussian (MVG) classifier for classifying individual targets based on the relative amplitudes of the extracted harmonic set of frequencies. The classifier is trained on high signal-to-noise ratio data for individual targets. In order to classify and further identify each target in a multi-target environment (e.g., a convoy), we first perform bearing tracking and data association. Once the bearings of the targets present are established, we next beamform in the direction of each individual target to spatially isolate it from the other targets (or interferers). Then, we further process and extract a harmonic feature set from each beamformed output. Finally, we apply the MVG classifier on each harmonic feature set for vehicle classification and identification. We present classification/identification results for convoys of three to five ground vehicles.

Paper Details

Date Published: 9 August 2004
PDF: 7 pages
Proc. SPIE 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII, (9 August 2004); doi: 10.1117/12.544523
Show Author Affiliations
Thyagaraju Damarla, Army Research Lab. (United States)
Tien Pham, Army Research Lab. (United States)
Douglas Lake, Univ. of Virginia (United States)

Published in SPIE Proceedings Vol. 5429:
Signal Processing, Sensor Fusion, and Target Recognition XIII
Ivan Kadar, Editor(s)

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