The Naval Explosive Ordnance Disposal Technology Division (NAVEODTECHDIV) is conducting an exploratory development program for the development of small, inexpensive, robotic technologies that enable systems that will clear unexploded submunitions and mines from contaminated land areas. The concentration is on control methodologies to enable teams of small autonomous robots to work together to p...

PURPOSE: This note describes the development of a polarized illuminator system for providing continuous broad beam of very-near infrared (VNIR) radiation to be used in imaging polarimetry applications. This system was developed for field characterization of geo-environmental surfaces (e.g., soil and vegetation), and discrimination of these surfaces from objects of military interest (e.g., unexp...

We propose statistical processing methods and performance analysis techniques for discrimination and localization of Unexploded Ordnance (UXOs) using EMI sensors based on nonparametrically defined prior probability density functions for target-relevant features. In the first part of this thesis, new sets of UXO discrimination methods using these nonparametric prior models are introduced where w...

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Several approaches to the detection of Unexploded Ordnance (UXO) in the ground are discussed. Methods exploiting the coupling of sound into the earth are shown to have promise. These approaches can use both linear and non-linear phenomena as clues. Also discussed is the potential of a ground penetrating radar method that is based on a nonlinear phenomenon.

In this chapter, we outline the statistical procedures that can be employed for the detection of unexploded ordnance (UXO). Phenomenological modeling is first developed to relate the collected data to a sensor’s feature parameters, which in turn allow for physics-based signal processing. Starting with the Bayesian framework, we introduce minimax and robust detection that do not require prior pr...