Buried Underwater Munitions and Clutter Discrimination
Abstract
Background - Low-frequency Synthetic Aperture Sonar LF-SAS) in tandem with magnetic sensing techniques have successfully demonstrated the ability to detect buried underwater munitions; however, these sensors also detect an inordinate amount of buried clutter. Processing techniques are needed to discriminate buried munitions from clutter. SERDP SON Number MMSON-10-02 stated that "clutter represent potentially significant sources of false alarms making detection and remediation of underwater munitions difficult and costly." Objective - The long-term objective of this joint research effort between the U.S. Army Engineering Research and Development Center (ERDC) and the Naval Research Laboratory (NRL) is to develop automated methods to discriminate buried underwater munitions from buried clutter by extending NRL's patented 2-D clutter classification techniques to the 3-D sub-bottom environment. These new techniques include the first phase of a clutter classification model that uses characteristics of buried munitions and clutter derived from modeled acoustic and magnetic signatures. Validation of the discrimination methods will be performed in a controlled environment at an environmentally representative field site in follow-on research. Technical Approach - The prior art of 2-D seafloor clutter discrimination detects mine-like objects in acoustic imagery and classifies them as mines or clutter based upon object dimensions, acoustic shadows, brightness and shape. To achieve the objectives, distinguishable characteristics between munitions and clutter were discovered through modeling and controlled experiments. The proposed 3-D Munitions and Clutter Classifier (MACC), which will be finalized in a follow-on study, will rely on NRL's automated techniques, including derived bottom clutter, roughness, 2-D side scan detection, 3-D sub-bottom detection, and magnetic detection. Bayesian inference will be used to fuse the various detection sensors.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2010
- Accession Number
- ADA600465
Entities
People
- Jesse Mcninch
- John Dubberley
- William Sanders
Organizations
- United States Army Corps of Engineers