Ball, John E.
Anderson, Derek T.
Younan, Nicolas H.
Date of Degree
Graduate Thesis - Open Access
Electrical and Computer Engineering
Master of Science
James Worth Bagley College of Engineering
Department of Electrical and Computer Engineering
Different signal processing techniques for synthetic aperture acoustic (SAA) and highresolution voxel radar (HRVR) sensing modalities for side-attack explosive ballistic (SAEB) detection are proposed in this thesis. The sensing modalities were vehicle mounted and the data used was collected at an army test site. More specifically, the use of a frequency azimuthal (fraz) feature for SAA and the fusion of a matched filter (MF) and size contrast filter (SCF) for HRVR was explored. For SAA, the focus was to find a signature in the target’s response that would vary as the vehicle’s view on the target changed. For the HRVR, the focus was put on finding objects that were both anomalous (SCF) and target-like (MF). The results in both cases are obtained using receiver operating characteristic (ROC) curves and both are very encouraging.
Dowdy, Joshua L, "Signal Processing and Machine Learning for Explosive Hazard Detection using Synthetic Aperture Acoustic and High Resolution Voxel Radar" (2018). Theses and Dissertations MSU. 3943.