Multistatic, Concurrent Detection, Classification and Localization Concepts for Autonomous, Shallow Water Mine Counter Measures
Abstract
The objective of SWAMSI is the development and demonstration of robust multi-static detection and classification of proud- and buried seabed objects using cooperative networks of autonomous vehicles with acoustic sources and receiving arrays. The emphasis of the MIT SWAMSI effort has focused on utilizing high fidelity acoustic modeling of both scatterers and shallow-water environments to better understand and bound the limits of detectability for mine-like objects via autonomous networks of sensors, and the assess the performance of time-reversal processing for concurrent detection, classification, localization and Tracking (DCLT) of seabed objects. The analysis s supported by series of experiments using multiple sonar-equipped AUVs in shallow water and then cross-validate the results obtained with high precision modeling and visualization. Another, related objective is to better understand the problems of cooperative autonomous vehicle interaction to define the base-line infrastructure requirements for cooperative detection, classification and navigation, an understanding which may lead to guidelines for optimal collaborative configuration control of the underwater sonar platforms.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 2012
- Accession Number
- ADA575092
Entities
People
- Arjuna Balasuriya
- Henrik Schmidt
Organizations
- Massachusetts Institute of Technology