TECHNOLOGY AREA(S): Battlespace, Electronics, Sensors

ACQUISITION PROGRAM: Undersea Technology (NAVSEA 073)

OBJECTIVE: Develop an electromagnetic (EM) beam propagation prediction toolset that combines the metrological Marine Wave Boundary Layer (MWBL) atmospheric model, the short pulse multi-band metrological toolset, and visualization software/hardware and uses compact single-aperture Light i detection and ranging (LIDAR) technology for estimating beam performance in the MWBL.

DESCRIPTION: Atmospheric metrological data are used to augment EM beam performance prediction models for estimating effects of atmospheric turbulence on EM beam propagation for a given set of environmental conditions. Estimating atmospheric parameters and their impact on EM beam propagation performance in proximity of the ocean surface is particularly challenging. Close to the surface, complex fluid mechanics and particle motion drive mass transport and turbulence in a region of the atmosphere from 0 to approximately 60 ft (18.2 m) above the sea-air interface defining a MWBL. Height dependent factors contributing to mass transport and turbulence in the MWBL include: gradients of temperature and pressure; wind speed and wave slap; aerosol content and dispersion; and evaporation and condensation of water vapor including humidity, rain, fog, and mist. Moreover, unlike higher altitudes in the atmosphere above the MWBL (at distances on the order of kilometers) where simplified approximations of isotropy and homogeneity hold up and are conventionally used for modeling effects of turbulence on beam propagation at these higher altitudes, near the marine surface where mass transport is prevalent, the assumptions of homogeneity and isotropy no longer apply.

Current atmospheric modeling algorithms, such as the Coupled Ocean-Atmosphere Response Experiment (COARE), Navy Atmospheric Vertical Surface Layer Model (NAVSLaM), Navy Surface Layer Optical Turbulence (NSLOT), and Laser Environmental Effects Definition and Reference (LEEDR), either do not predict the atmosphere accurately at the sea-air marine wave boundary layer or were not developed to predict an atmospheric profile given local meteorological measurements at the sea-air interface.

To date, sufficient 24/7 data measurement procedures and modeling techniques are lacking for making valid estimates of EM beam propagation performance predictions in the MWBL. Hence, the objective requirements of this topic are to: (a) gain an improved understanding of the underlying physics and mathematics of mass transport and turbulent effects on EM propagation in the MWBL; (b) develop new analytical techniques, modeling, data collection and visualization tools, and procedures for maximizing EM systems signal exploitation in the MWBL for submarine offensive, defensive, and stealth operational performance; and (c) develop a submarine-based single aperture measurement and performance modeling apparatus in which to estimate a priori EM beam propagation performance� in the MWBL. Toward this end, a multi-wavelength short pulsed (pico-second) Lidar-based laser system is required. Estimating �in situ� system electromagnetic beam propagation performance from a submarine is not practical for a submarine today. However, with rapid advances in laser and high-performance computing technology, the feasibility of employing a laser-based data collection apparatus on a submarine coupled with a high-performance computer data processing and modeling capability makes the prospect for fielding a prototype in the near-future quite possible.

Accurate marine wave boundary atmospheric models and data collection� at and below 60 feet are needed for performing high fidelity range estimation, ranging accuracy, target detection, identification and classification at range and power distribution along a horizontal or angular path between source and target-of-interest within the confines of the MWBL. Models and data extractions are useful not only as a tactical decision aid, but also for mission planning of EM system performance for hypothesized scenarios pertaining to offensive, defensive and stealth capabilities. Extrapolation of forecasted data in conjunction with �in situ� measurement profiles also may be used to increase predicted performance accuracy.� Forecasted and/or in situ measurement data may include, as examples: air temperature, pressure, and humidity; sea temperature; wind speed, evaporation layer, mist condition, sea particulate size, and wind direction. Visualization tools are required for providing temporally- and spatially-formatted data displays and performance information in a user-friendly format that augments visual interpretation of data and performance results as a tactical decision aid and performance.

PHASE I: Develop a concept to solve the Navy�s problem as described in the Description, and demonstrate the feasibility of that concept through simulation, modeling, and verification via data collection and development of short pulse multiband Lidar metrological system development over marine wave boundary layer. Model key elements of the concept to provide a high degree of confidence and data collection. Model the compact short pulse multi-band Lidar-based metrological tools that will be used for data collection over MWBL and determine their feasibility. Document the MWBL model and provide modeling, data supporting the approach and metrological system architecture based on multiband short pulse Lidar to monitor marine wave boundary layer particle size distribution, temperature, and pressure. Propose to the Government the expected level of accuracy. Develop a Phase II plan. The Phase I Option, if exercised, will lay out the model and characteristics for development into a prototype in Phase II.

PHASE II: Develop and deliver a prototype metrological system based on short-pulse multiband Lidar (single-aperture transmitter/receiver) for testing and evaluation based on the results of Phase I and the Phase II Statement of Work (SOW). Describe how the prototype will be evaluated to determine if the technology has the potential to meet Navy performance goals described in the Phase II SOW. Use the data collected using the prototype metrological system at marine atmospheric for the validation of the MWBL model and visualization software.� Deliver the toolset to the Navy to determine its capability in meeting Phase II performance goals through additional testing and refinement with atmospheric data captured using existing commercial meteorological tools and developed under a LIDAR tool set.

PHASE III DUAL USE APPLICATIONS: Support the Navy in transitioning the technology, including the marine visualization data, to Navy use. Transition of algorithms to the submarine combat system occurs through the PMS 435 Advanced Processor Build/Technical Insertion (TI-APB) process. Test data collected by the awardee during Phase II and data provided by the Government during Phase III. Provide technical support to the Navy over the course of transition.

This technology will have applications in atmospheric modeling for any worldwide scenarios where access to weather information is limited.

REFERENCES:

1. Fairall, C. W., et al. "Bulk Parameterization of Air-Sea Fluxes: Updates and Verification for the COARE Algorithm." Journal of Climate 16.4 (2003): 571-591. https://www.researchgate.net/publication/215721706_Bulk_Parameterization_of_Air--Sea_Fluxes_Updates_and_Verification_for_the_COARE_Algorithm

2. Frederickson, P. A., Davidson, K. L., Zeisse, C. R., and Bendall, C. S. �Estimating the Refractive Index Structure parameter (Cn2) over the Ocean Using Bulk Methods.� Journal of Applied Meteorology 39, 1770-1783 (2000). https://www.researchgate.net/publication/249607025_Estimating_the_Refractive_Index_Structure_Parameter_over_the_Ocean_Using_Bulk_Methods

3. Kemp, E., Felton, B., and Alliss, R. �Estimating the Refractive Index Structure-Function and Related Optical Seeing Parameters with the WRF�ARW.� Northrop Grumman Information Technology/TASC, Chantilly, Virginia. National Center for Atmospheric Research WRF User Workshop, P9.30 (2008). http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.525.3762&rep=rep1&type=pdf

4. Cagigal, M. and Canales, V. �Generalized Fried parameter after adaptive optics partial wave-front compensation.� J. Opt. Soc. Am. A 17, 903-910 (2000). https://www.researchgate.net/publication/12521033_Generalized_Fried_parameter_after_adaptive_optics_partial_wave-front_compensation

KEYWORDS: Light detection and Ranging; Lida r; Navy Atmospheric Vertical Surface Layer Model; NAVSLaM; High Energy Laser; HEL; Electronic Warfare; EW; Coupled Ocean Atmosphere Response Experiment; CORE