Award Data

Nanohmics and Professor Gennady Shvets at the University of Texas at Austin propose to develop a Multi-Spectral RectennaTM (MSR) composed of a large area flexible sheet of plasmonic absorber structures coupled to an advanced scintered nanoparticle diode junction material. The resulting film would generate rectified current vertically, from the plasmonic strips to the underlying mirror layer, enabl ...

Explosion of military vehicle fuel tanks upon encountering an Improvised Explosive Device (IED) causes significant damage to both military personnel and equipment. The fuel tank explosion is caused by explosive buildup and combustion of fuel vapor within the tank headspace. Further damage is also caused by projectile penetration of the fuel tank, resulting in spraying of the superheated fuel onto ...

The objective of this Phase I STTR program is to develop and qualify innovative lightweight, high temperature composite materials that provide ballistic, blast and flame protection to MTVR fuel tanks and engine compartment structures. NanoSonic will work closely with Virginia Tech to simulate the conditions encountered during an IED blast and implement this information for Phase I material develop ...

The objective of this Phase I STTR is to design and qualify affordable, flame resistant HybridSil copolymers that may be integrated within carbon fiber reinforced composites in place of brominated vinyl esters for improved fire resistance, negligible smoke toxicity, and enhanced mechanical properties. Equally important, down-selected copolymer matrices will provide tailorable room and low temperat ...

The team of 3 Phoenix, Inc and George Mason Univserity propose to develop and evaluate innovative algorithms for a multi-modal adaptive data fusion system applicable for intelligence, surveillance, reconnaissance, and tracking (ISRT) in general environments. In particular the algorithm will be designed for automatic target recognition in high density littoral environments. The approach presented i ...

Bottom mounted undersea surveillance systems are required by the Navy to Detect, Classify and Localize (DCL) underwater threats during operations and intelligence gathering. To meet the needs of future naval operations they must be easily deployable from a number of platforms and autonomously perform the DCL mission and autonomously report. The primary risks to these bottom mounted surveillance sy ...

The Anti Submarine Warfare Commander (ASWC) needs an accurate operational picture and timely answers to critical questions in order to take effective action. They operate under severe time pressure, performing complex multi-component decision tasks, and in rapidly evolving and changing information and situational states. Our overarching technical objective for the proposed work is to provide an ef ...

Previous efforts to improve Anti-Submarine Warfare situational understanding have focused on developing fusion techniques for improving the tactical picture. These fusion processes primarily operate on"hard"sensor data that is amenable to software implementation. The Navy now seeks to develop tools to improve the ASW operator's understanding of higher level tactical situations, thereby improv ...

Sensor fusion allows a robot to overcome many of the drawbacks of individual sensors, but such techniques require precise calibration of all sensors. In support of the Navy's requirements to develop low-cost and robust sensors, TRACLabs and SwRI propose to design and demonstrate a combined EO/LIDAR perception system that facilitates improved autonomy for UGVs. We call this system LEOPARD (for ...

With the rise in global terrorism over the last decade, the nature of hostile threats has broadened, requiring increased visibility into critical systems and infrastructure. Despite the vital role that technology has played in enhancing the military"s ability to obtain intelligence to identify, track, and neutralize threats, the promise of automated collection and analysis of situational awareness ...