Award Data

This Phase 2 Enhancement seeks to improve the quality of synthetic data to be representative of real data (using whatever criteria the algorithm deems important for detect, classify, and track of an object of interest at rest and/or in motion) and to maximize algorithm performance such that when the algorithm is introduced to real data with a real object of interest in its real environment, the al ...

Advances in location acquisition and remote sensing have resulted in explosive growth of spatial trajectory data, which capture the mobility of diverse entities. Intelligence analysts need technologies that can provide automated assistance regarding the detection, understanding, and sharing of salient, culturally-informed activities from this mover intelligence (MOVINT) data. Aptima and PatchPlus ...

CoVar’s DOCTRINAIRE is a new approach to computer aided object annotation that is modeled after the way expert end-users leverage generic, robust background information (e.g., what wheels look like) and known doctrine (the size and shape of components on a pickup truck) to perform reliable, explainable object detection and annotation. Our approach solves the robustness problem by training a reli ...

Photonwares proposes to develop a novel large aperture and fast EO shutter capable of meeting the NGA requirements for laser-based remote sensing applications. The clear aperture can be up to 25mmx25mm while the transition time is shorter than 10ns and the repetition rate can reach over 1MHz with a high on/off contrast ratio. The design is based on our over 20 years of commercial expertise on Pock ...

The primary goal of this proposed project is to develop a general-purpose technique for the problem of algorithm parameter selection (APS) that achieves the best performance of the algorithm and demonstrates its effectiveness within graph analysis, for the problem of community detection, or clustering.  Cell Matrix Corporation (CMC) will develop a means to greatly simplify the tweaking typically ...

LUCID (Land Use Classification Intelligence Discovery) is a novel artificial intelligence (AI) system that achieves on-demand classification of fine-grained Land Use and Land Cover (LULC) categories to create detailed LULC-annotated geospatial grid maps by orchestrating seamless fusion of satellite imagery, remote sensing, and non-imagery geospatial data layers. LUCID fuses multiple data sources/m ...

Commercial imaging satellites capture the majority of the planet’s surface every day, generating millions of images. Searching such data for specific objects of interest is extremely difficult to do manually without automated computer image analytics. NGA is seeking a novel scientific formalism and tools for training overhead image detectors on rare and new objects of interest, for which large, ...

Physical Sciences Inc. (PSI) will develop a Recycling Fast-Response Atom Interferometer for Navigation (ReFRAIN) as an atom interferometer (AI) accelerometer specially designed to improve inertial navigation systems (INS) on moving platforms.  The ReFRAIN provides sensitivity, dynamic range, bandwidth, and bias stability that matches or exceeds state of the art mechanical accelerometers.  PSI in ...

The conditions encountered by hypersonic vehicles are complex due to the non-linear, strong interaction between the flow field environment and vehicle.  Successful modeling requires multi-physics capabilities that can properly take into account high-temperature gas dynamics, which includes excitation of internal energy modes, finite-rate gas chemistry, turbulent flow, and complex plasma physics, ...

To attack the challenge of object identification and annotation across diverse families of image data, Prometheus and Raytheon will implement a software toolkit based on our new mathematically–based AI tool. The AI input will be matrix coefficients resulting from the unique Prometheus-developed energy-spreading transform, PONS, the Prometheus Orthonormal Set. PONS is currently in use by both the ...