Author

Julie White

Advisor

Anderson, Derek

Committee Member

Ball, John

Committee Member

Younan, Nicolas

Date of Degree

8-1-2017

Document Type

Graduate Thesis - Open Access

Degree Name

Master of Science

College

James Worth Bagley College of Engineering

Abstract

Explosive hazards, above and below ground, are a serious threat to civilians and soldiers. In an attempt to mitigate these threats, different forms of explosive hazard detection (EHD) exist; e.g, multi-sensor hand-held platforms, downward looking and forward looking vehicle mounted platforms, etc. Robust detection of these threats resides in the processing and fusion of different data from multiple sensing modalities, e.g., radar, infrared, electromagnetic induction (EMI), etc. The focus of this thesis is on the implementation of two new algorithms to form a new energy-based prescreener in hand-held ground penetrating radar (GPR). First, B-scan signal data is curvelet filtered using either Reverse- Reconstruction followed by Enhancement (RRE) or selectivity with respect to wedge information in the Curvelet transform, Wedge Selection (WS). Next, the result of a bank of matched filter are aggregated and run a size contrast filter with Bhattacharyya distance. Alarms are then combined using weighted mean shift clustering. Results are demonstrated in the context of receiver operating characteristics (ROC) curve performance on data from a U.S. Army test site that contains multiple target and clutter types, burial depths, and times of the day.

URI

https://hdl.handle.net/11668/20981

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