UXO Detection, Classification and Localization I

Recent advances in sensors and platforms used to detect, classify and localize UXO in the underwater environment have advanced to the point that full systems are ready for demonstrations. In this session, presentations on a variety of sensor and platform types ready for demonstration were given. This session also included discussion of machine learning technologies used to classify UXO and scoring methods to evaluate systems during demonstrations. 

Session Chair: Dr. Timothy Marston, University of Washington Applied Physics Laboratory (UW-APL)
Session Introduction Dr. Timothy Marston, University of Washington Applied Physics Laboratory (UW-APL)
Results from the First Two Demonstrations of a Buried-UXO Detection, Classification, Geo-location (D/C/G) System Dr. Kevin Williams, Applied Physics Laboratory, University of Washington
AUV-Based Structural Acoustic Sonars for Underwater Buried UXO Detection & Classification Dr. Brian H. Houston and Dr. Joseph A. Bucaro, Naval Research Laboratory (NRL)
Sediment Volume Search Sonar Dr. Daniel C. Brown, Applied Research Laboratory, Pennsylvania State University
TNO’s Testbed for Buried Object Detection and Classification Dr. Robbert van Vossen, The Netherlands Organisation (TNO)
Demonstrating Calibrated Phase-measuring Sidescan Sonar for Rapid Wide-area and Detailed Mapping of UXO Shallower than 5 m Dr. Kenneth G. Foote, Woods Hole Oceanographic Institution
Feature-Driven Navigation Enhancement Using Low frequency Acoustics Dr. Timothy Marston, University of Washington Applied Physics Laboratory (UW-APL)

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