Algorithm for classifying multiple targets using acoustic signatures
Thyagaraju Damarla, Tien Pham, Douglas E. Lake · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
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.