Assessing Realism and Uncertainties in Navy Decision Aids
Abstract
The proposed effort will use a team with expertise in observational physicaloceanography, numerical modeling, ocean acoustics and sonar signal processing to identify thestructures and variability of the ocean which have significant impact on naval operations andexamine the ability of current Navy models and reanalyses to capture those features. The teamwill exercise Navy training and onboard decision aids and examine if current decision aidsdemonstrate recognition of ocean features that impact operations and enable operators to makeuse of their presence. In this examination, the team will examine sources of uncertainty in theguidance from the decision aids. Specifically, they will examine how well they capture featuresof the ocean environment that impact acoustic propagation and/or how well they represent noisefields and thus their skill at the so-called DCLT (detection, classification, localization andtracking) processing for monitoring the ambient environment. We consider the ~ocean~ toinclude the status of the present environment and the predicted changes of the meteorology,physical oceanography and geoacoustics within the range and time scales relevant for themission assigned to the submarine. If this is so, the team will consider how improvedcommunication of more timely and accurate data from these models or from local in-situobservations could identify the significant ocean features which would reduce the uncertainty inthe decision aids. This reduction in uncertainty might come from concise alerting of the operatorto the presence of ocean features with known impacts, by better data compression for thecommunications, or by reducing the volume of the communications by using onboardoceanographic and acoustic codes and anticipating significant advances for future processingcapabilities onboard the submarine.The description of this effort can be located in R2 Sub-Activity Ocean Sciences in PE 0601153N.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 26, 2019
- Source ID
- N000141912716
Entities
People
- Henrik Schmidt
Organizations
- Massachusetts Institute of Technology
- Office of Naval Research
- United States Navy