locations of objects of interest to users over time. A user may see a few images at a time, with no context as to its surroundings.

 

Satellite imagery can provide broad area maps over the ocean, but that imagery is not responsive enough and may be outdated for many time-critical missions. The Navy desires to use imagery captured by EO/IR sensors on aircraft to generate a broad area ortho-mosaic map of the water surface in order to aid in real-time situational awareness. The desired result is the generation of “satellite-like” maps of the ocean surface from the least time-late possible imagery data, and continual building and updating that map as sensors provide new data.

 

No such system currently exists. Basic tiling of imagery generally produces poor results that render the larger map virtually worthless. Software tools exist that can generate large ortho-mosaics, but they rely on fixed feature points, and therefore only work over land - not over water. Furthermore, these tools require intensive post-processing, so that a data set is many hours old by the time it is processed and available in a useful format.

 

The desired system should produce ortho-mosaic maps from EO/IR imagery of the water surface generated at 1-30 Hz from altitudes of 10-2000 meters, processed in real time, capable of covering hundreds of square nautical miles, while minimizing glare and other artifacts that would make the results difficult to use. The result would be a wide- view snapshot of the water’s surface that can be continually updated and output as keyhole markup language (kml) files, shapefiles, or any other geo-spatial data format. The real-time processing must be suitable to run on a small UAS deployed from a vessel at sea with limited or no connection to high-performance cloud computing.

 

PHASE I: Design and develop a concept for a technology that enables real-time, geo-referenced, ortho-mosaics of the water surface from EO/IR imagery of the ocean surface captured from small UAS. Provide a detailed description of the proposed solution along with supporting mathematical justification of the proposed approach. Identify sensor and processing requirements, as well as any other components necessary for the system. Identify limitations, such as lighting conditions, surface turbidity, sea state, or any other factor that may affect the performance of the system.

Build a prototype system and demonstrate it operating with representative data. The Phase I effort will include prototype plans to be developed under Phase II.

 

PHASE II: Test and validate the ortho-mosaic system onboard an UAS in a relevant environment, preferably over the ocean operating from a vessel offshore. The Navy may assist with a UAS/boat should the need arise.

Demonstrate real-time ortho-mosaic generation using both optical and IR imagery with a constantly expanding area of operation. Verify cross functionality with other geo-spatial data systems. Test the system in a wide range of conditions, starting in a benign environment. Demonstrate the portability of the system to other unmanned (such as, but not limited to, Scan Eagle, Fire Scout, Triton and Puma) or manned aircraft systems equipped with EO/IR sensors operating over water. Produce and deliver a final technical data package and a functional prototype system.

 

PHASE III DUAL USE APPLICATIONS: Complete final testing and perform necessary integration and transition for use in anti-submarine and countermine warfare, counter surveillance, and monitoring operations with appropriate current platforms and agencies, and future combat systems under development.

 

Commercially this product could be used to enable remote environmental monitoring of geophysical survey, facilities, and vital infrastructure assets. Industries such as geology, archaeology, mineral and energy exploration and oceanography would benefit from successful technology development.

 

REFERENCES:

1.   Bouin, M.-N., Ballu, V., & Calmant, S. “A Kinematic GPS Methodology for Sea Surface Mapping, Vanuatu.” Journal of Geodesy, Volume 83, Issue 12, December 2009, pp. 1203-1217. https://www.researchgate.net/publication/226790060_A_kinematic_GPS_methodology_for_sea_surface_mapping_ Vanuatu

 

2.   Deng, Z., Ji, M., & Zhang, Z. “Mapping Bathymetry from Multi-Source Remote Sensing Images: A Case Study in the Beilun Estuary, Guangxi, China.” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVII, Part B8, Beijing, 2008.