TECHNOLOGY AREAS: Information Systems, Battlespace

ACQUISITION PROGRAM: NITES ACAT IV

The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), which controls the export and import of defense-related material and services. Offerors must disclose any proposed use of foreign nationals, their country of origin, and what tasks each would accomplish in the statement of work in accordance with section 3.5.b.(7) of the solicitation.

OBJECTIVE: Develop a computationally efficient and accurate means to predict atmospheric acoustic propagation (AAP) characteristics for a wide range of sources to include ground and air vehicles and ordinance detonation.

DESCRIPTION: The variability of the physical environment has a significant impact on sensor systems and platform vulnerability of Navy/USMC ground vehicles, boats and aircraft. Of the various aspects of the physical environment, the local acoustic propagation conditions play a significant role in force protection and platform detection by changing the acoustic signature and range characteristics. Anomalous propagation conditions (sound focusing) can enhance or degrade operational detection ranges and ranges at which threats can be detected by friendly forces. Additionally, the same propagation conditions can have a very significant impact on the range at which a ground vehicle, boat or aircraft can be counter detected by an enemy asset. The accurate prediction of local propagation conditions is a prerequisite to effectively managing the impacts of varying atmospheric acoustic propagation and optimizing sensors and systems for tactical advantage.

Over the past few decades, a number of approaches have been recommended and employed to improve local estimates of propagation conditions. Although many provide accurate propagation algorithms that allow for estimation of atmospheric acoustic propagation conditions, they often have less than optimal characteristics such as estimating errors in the overall acoustic performance prediction when environmental forecast errors are present. This requires rigorous assimilation and analysis techniques coupled to a sensing strategy to more fully exploit knowledge about local propagation conditions, while leveraging existing and future sensing capabilities.

The AAP prediction system must couple the physics of the environment to the source�s acoustic signature to deliver accurate acoustic predictions for acoustic sensing systems to include the human ear. Innovative techniques to couple source, propagation environments and receiver within an architecture to permit modular upgrades on various source and receiver models as well as physical environmental forecast models. An ability to assimilate available acoustic observations to accurately estimate uncertainty in prediction performance should be a central capability of the AAP Prediction System. The prediction uncertainty should include an analysis of both errors in the source characteristics as well as the errors in the prediction model to include environmental forecast errors.

PHASE I: Develop the conceptual design of an AAP prediction system, based on a four dimension (time and space) atmospheric representation with uncertainty measures based on data assimilation/fusion scheme that is constrained by both the data and physics based models. This architecture must take into account the various confidence levels of collected data and provide for methodologies to develop advanced data quality control and assimilation algorithms. The design must address the uncertainty associated with any data fusion and business logic processes in terms of the parameters provided to operators. The design must be developed in sufficient detail to permit a reasonable evaluation of the approach, using either simulated data or available environmental data to demonstrate the feasibility of the selected technology or technique.

PHASE II: Develop a working prototype system and a conduct demonstration to quantify the accuracy of the system. Test the prototype data assimilation system and document the system characteristics to include system performance in a range dependent time varying environment. Human system interface (HSI) elements should be included in the design of the prototype planning system to facilitate data quality control. Demonstrate the value of the proposed system with the use of performance metrics � e.g. the assimilation and fusion process must be completed within time constraints dictated by the perish ability of the specific data types being fused. Available meteorological forecast data sets can be used in the demonstration as environmental inputs to the acoustic propagation algorithms.

PHASE III: The prototype capability will be transitioned to the Navy Integrated Tactical Environmental Sub-system (NITES) applications suite under the NITES Next Generation POR and provided to the Naval Oceanographic Office to support Reach-back Concept of Operations. The contractor shall work with the METOC Production Centers and NITES Program leads to develop an acceptable concept of operation (CONOPS) for the fusion capability.

PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: The technology successfully developed in this project will have multiple military and commercial applications. Military applications will include feedback to mission planners to optimize sensor performance with respect to operational range and to assess vulnerability to minimize counter detection risks.

Non-military applications will include the ability to apply this capability to provide improvements to numerous commercial flight operations in support of acoustic noise abatement efforts, assist a wide range of commercial users in predicting acoustic noise level variations and provide tools that permit industrial operators to adjust their activities in order to remain compliant with permitted noise levels under dynamic atmospheric conditions.

REFERENCES:

1. Le, P.A., Garces, M., Blanc, E., Barthelemy, M., Drob, D.P., "Acoustic propagation and atmospheric characteristics derived from infrasonic waves generated by the Concorde", J. Acoust. Soc. Am., Vol. 111, No. 1 Pt 2, January 2002, pp 629-41.

2. Lihoreau,B., Gauvreau, B., Bérengier, M., Blanc-Benon, P., Calmet, I., "Outdoor sound propagation modeling in realistic environments: Application of coupled parabolic and atmospheric models", J. Acoust. Soc. Am. 120 _1_, July 2006, pp 110-19.

3. Lingevitch, J.F.,Collins, M.D., Dacol, D.K., Drob, D.P., Rogers, J.C.W., and Siegmann, W.L., "A wide angle and high Mach number parabolic equation", J. Acoust. Soc. Am., Vol. 111, No. 2, February 2002, pp 729-34

4. Salomons, E.M., "Computational Atmospheric Acoustics", Kluwer Academic Publishers, 2001

KEYWORDS: Atmospheric Acoustic Prediction; Acoustic Propagation; Four Dimensional Atmospheric Forecast; Data Assimilation; Anomalous propagation; Prediction Uncertainty

TPOC: Ed Mozley
Phone: (858)537-0230
Fax: (619)524-3034
Email: [email protected]
2nd TPOC: Tom Piwowar
Phone: (619)524-7921
Fax: (619)524-3034
Email: [email protected]

** TOPIC AUTHOR (TPOC) **

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