Uncertainty Estimation for Atmospheric Acoustic Propagation Prediction Navy SBIR FY2008.1 Sol No.: Navy SBIR FY2008.1 Topic No.: N08-096 Topic Title: Uncertainty Estimation for Atmospheric Acoustic Propagation Prediction Proposal No.: N081-096-0544 Firm: Applied Physical Sciences Corp. 475 Bridge Street Suite 1 Groton, Connecticut 06340 Contact: Joshua Wilson Phone: (860) 448-3253 Web Site: www.aphysci.com Abstract: The propagation of acoustic signatures from vehicles, aircraft, boats and artillery can have a significant impact on military operations. Specifically combatants need to reliably detect enemy acoustic signatures while at the same time concealing their own. The physical propagation environment, including surface and atmospheric parameters, may drastically alter the range at which an emitting object may be detected. There are currently several models for predicting these acoustic propagation effects based on atmospheric profiles and/or ground topography. Unfortunately these models are sensitive to errors in environmental inputs. We propose a method for estimating the uncertainty (variance) of the acoustic propagation prediction given the uncertainty in the environmental inputs. Advantages to this new method are (1) it fits within current Parabolic Equation (PE) marching algorithms and does not require a second stand-alone code and (2) it is computationally efficient. This would allow our forces to simultaneously predict both the acoustic propagation and its uncertainty. The algorithm used to calculate the uncertainty may also be used to determine the sensitivity of the sound field to the various individual environmental parameters which could aid (1) in acoustic environmental parameter inversion and (2) in the intelligent allocation of meteorological measurement resources. Benefits: The proposed research would provide a significant improvement in the ability of Navy and Marine forces to reliably detect enemy combatants and to protect their own assets. This is particularly important in locations where the atmospheric parameters are complex and/or poorly known. This research could lead to field tests in Phase II, with validation against more computationally expensive Monte-Carlo methods, and development for deployment to the fleet in Phase III. In addition to its military uses, atmospheric propagation prediction is also important to other governmental and private groups for prediction noise from highways, airports and industrial sites. The proposed techniques may also be applied to undersea/submarine warfare where sound is the primary mode of target detection, navigation and communication. Return