TECHNOLOGY AREA(S): Battlespace, Electronics, Sensors

ACQUISITION PROGRAM: Coastal Battlefield Reconnaissance and Analysis (COBRA), PMS 495, Mine Warfare Program Office

OBJECTIVE: Research and develop a comprehensive software Surf Zone scene generation, target insertion, and sensor performance model.

DESCRIPTION: The Navy is interested in technologies that facilitate automated target recognition capabilities for previously unseen Surf Zone (SZ) environments and target threats. Typically, algorithms are optimized based on available test data sets, of which most is Beach Zone (BZ) data. This may hinder the assessment and optimization of system performance in new environments and for new target threats. Such constraints may lead to outliers in the operational performance of the system when generalizations of past performance are extended to specific unseen locales and target types. To address these issues, in lieu of conducting numerous costly data collections, there is a need for a comprehensive system model to generate images simulating those acquired in SZ environments and/or with new target types. The technologies developed under this topic will decrease costs by lowering the number of flight tests necessary for algorithm development and enable performance estimations in areas of interest where imagery is lacking. With costs for a SZ test approximately $750k and improving modeling and simulation efforts, testing is the focus area for cost saving efforts. This program�s technological contributions are the following: a tool that inserts new target threats into existing multi-spectral images; a tool that generates Coastal Battlefield Reconnaissance and Analysis (COBRA) equivalent synthetic scenes from other airborne Intelligence, Surveillance, and Reconnaissance (ISR) sensors imagery; and a radiometric model of COBRA�s multi-spectral camera. Additionally, this capability will improve COBRA�s SZ Probability of Detection (PD) and Probability of False Alarm (PFA), which are COBRA Key Performance Parameters, against new target threats and environments.

Currently, no end-to-end simulation of the dynamic SZ environment exists. Previous SZ research efforts have only led to static SZ models that breakdown under the SZ�s true dynamic conditions. These models have several problems including non-rotational assumptions for internal wave velocities, inability to simulate complex free surfaces near the wave crest, and accuracy limitations. The comprehensive model to be developed will include sub-models for the SZ environment, targets, platform, and passive and active sensors. For potential techniques applicable to the comprehensive model, see references 2-5. SZ environment models can be cued from existing information sources, such as imagery collected by other airborne sensors. To represent the changing SZ conditions, SZ environment models will be dynamic and will include wave dynamics (including breaking and object motion), foam, turbidity, and flotsam. Target models will allow insertion of targets into the scene, including mines and obstacles. The platform model will include aspects of the sensor platform affecting image acquisition, including platform position, orientation, and sensor pointing. The passive sensor model will provide a parametric, multi-spectral radiometric response given the scene radiometry generated by the other models whereas the active sensor model will provide a response based on specified wavelength interrogation. The Navy will provide imagery, metadata, and a data description to the awardee(s).

PHASE I: Develop a concept for a comprehensive SZ modeling tool. Prepare conceptual designs for each model component, including target, SZ scene background, platform, and sensor. Demonstrate the feasibility to generate a limited set of dynamic SZ scenes with realistic radiometric properties. Develop a Phase II plan. The Phase I Option, if exercised, will expand the SZ scenes to a wider variety of SZ conditions, develop design specifications and capabilities description to build a comprehensive modeling tool prototype solution in Phase II, and work with the Navy to develop a list of potential test environments.

PHASE II: Based on the results of Phase I and the Phase II Statement of Work (SOW), develop and deliver a comprehensive modeling tool prototype, and evaluate the scene generation model and radiometric models against previously collected imagery to determine whether the models meet performance goals as defined. Ensure that the prototype parameter will be at the mine-like object (MLO) level, as opposed to the minefield level. Demonstrate model performance through prototype testing and detailed analysis. Prepare a Phase III development plan to transition the technology to Navy use.

PHASE III DUAL USE APPLICATIONS: Support the Navy in transitioning the technology for Navy use on the COBRA program by working closely with the current prime contractor to integrate the technology. Utilize the models and software tools to improve performance of the COBRA Block I System. Support updates to the COBRA Technical Data Package (TDP) to support the Navy in transitioning the design and technology into the COBRA Production baseline for future Navy use. Support the Navy for test and validation to certify and qualify the system for Navy use.

The technology developed here can be applied to commercial activities that require performance evaluation of multi-spectral remote sensing systems for applications such as forestry, agriculture, and Intelligence Preparation of the Operational Environment (IPOE). Models could support commercial applications such as airborne-based detection and tracking of distressed swimmers in high surf, detection of sharks for swimmer safety in populated waters, monitoring of mammals for boater safety, and erosion monitoring of shoreline, surf zone, and subsea reefs.

REFERENCES:

1. "AN/DVS-1 Coastal Battlefield Reconnaissance and Analysis (COBRA)." The US Navy � Fact File.� Last update 4 October 2017. http://www.navy.mil/navydata/fact_display.asp?cid=2100&tid=1237&ct=2

2. Shaw, G. and Burke, H. �Spectral Imaging for Remote Sensing." Lincoln Laboratory Journal, Volume 14, No.1, pp. 3 � 28, 2003. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.69.1178&rep=rep1&type=pdf

3. Fanning, J., Halford, C., Jacobs, E., and Richardson, P. �Multispectral Imager Modeling." SPIE Vol 5784, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing, 2005. https://doi.org/10.1117/12.604056

4. Keen, Wayne, Tanner, Michael, Coker, Charles, and Crow, Dennis. �GPU based synthetic scene generation for maritime environments." SPIE Vol 7663, Technologies for Synthetic Environments: Hardware-in-the-Loop Testing XV, 2010. https://doi.org/10.1117/12.851782

5. �The Digital Imaging and Remote Sensing Image Generation Model.� The Digital Imaging and Remote Sensing Laboratory at Rochester Institute of Technology. http://dirsig.org/

6. Song, C. and A. I. Sirvientea, 2004, �A numerical study of breaking waves�, Physics of Fluids 16, 2649.

7. Liu, Y., 2012 �Numerical study of strong free surface flow and breaking waves.� PhD thesis, The Johns Hopkins University.

8. Wang, Z., Yang, J. & Stern, F., 2016, �High-fidelity simulations of bubble, droplet and spray formation in breaking waves.� J. Fluid Mech. 792, 307�327.

9. Miyata, H., et al., 1996, �Numerical simulation of three-dimensional breaking waves, Journal of Marine Science and Technology.� Volume 1, Issue 4, pp 183�197.

10. Lubin, P. & Glockner, S. 2015 �Numerical simulations of three-dimensional plunging breaking waves: generation and evolution of aerated vortex filaments.� J. Fluid Mech. 767, 364�393.

11. Lubin, P., Glockner, S., Kimmoun, O. & Branger, H. 2011 �Numerical study of the hydrodynamics of regular waves breaking over a sloping beach.� Eur. J. Mech. (B/Fluids) 30 (6), 552�564. http://dx.doi.org/10.1016/j.euromechflu.2011.01.001

KEYWORDS: Target Insertion; Multispectral Scene Generation; Radiometric Sensor Model; Coastal Battlefield Reconnaissance and Analysis (COBRA); Surf Zone Model; Active Sensor Model Based on Specified Wavelength Interrogation