The objective of the Office of Naval Research (ONR) Rapid Overt Reconnaissance (ROR) program and the Airborne Littoral Reconnaissance Technologies (ALRT) project's Littoral Assessment of Mine Burial Signatures (LAMBS) contract is to determine if electro-optical spectral discriminants exist that are useful for the detection of land mines located in littoral regions. Statistically significant buried mine overburden and background signature data were collected over a wide spectral range (0.35 to 14 µm) to identify robust spectral features that might serve as discriminants for new airborne sensor concepts. The LAMBS program further expands the hyperspectral database previously collected and analyzed on the U.S. Army's Hyperspectral Mine Detection Phenomenology program 1,2 to littoral areas where tidal, surf, and wind conditions can additionally modify spectral signatures.This work summarizes the LAMBS buried mine collections conducted at three beach sites -an inland bay beach site (Eglin AFB, FL, Site A-22), an Atlantic beach site (Duck, NC), and a Gulf beach site (Eglin AFB, FL, Site A-15). Characteristics of the spectral signatures of the various dry and damp beach sands are presented. These are then compared to buried land mine signatures observed for the tested background types, burial ages, and environmental conditions experienced.
The objective of the Office of Naval Research (ONR) Rapid Overt Reconnaissance (ROR) program and the Airborne Littoral Reconnaissance Technologies (ALRT) project's LAMBS effort is to determine if electro-optical spectral discriminants exist that are useful for the detection of land mines in littoral regions. Statistically significant buried mine overburden and background signature data were collected over a wide spectral range (0.35 to 14 µm) to identify robust spectral features that might serve as discriminants for new airborne sensor concepts. LAMBS has expanded previously collected databases to littoral areas -primarily dry and wet sandy soils -where tidal, surf, and wind conditions can severely modify spectral signatures.At AeroSense 2003, we reported completion of three buried mine collections at an inland bay, Atlantic and Gulf of Mexico beach sites. 1 We now report LAMBS spectral database analyses results using metrics which characterize the detection performance of general types of spectral detection algorithms. These metrics include mean contrast, spectral signal-to-clutter, covariance, information content, and spectral matched filter analyses. Detection performance of the buried land mines was analyzed with regard to burial age, background type, and environmental conditions. These analyses considered features observed due to particle size differences, surface roughness, surface moisture, and compositional differences.
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