Award Data

Reducing the False Alarm Rate (FAR) of Automated Target Recognition (ATR) algorithms for Synthetic Aperture Radar (SAR) imagery is crucial for Intelligence, Surveillance, Reconnaissance (ISR) and precision target engagement missions. While modern Deep Learning (DL) ATR networks have demonstrated advanced predictive capabilities and generalization for SAR imagery, they lack spatial awareness, resul ...

This research aims to develop decision support tools for better maintenance and planning of renewable energy generation and storage assets using atmospheric, local weather, and on-ground environmental data blended with site-, regional- and national-generation data. The study will use a combination of these data to understand the relationship between non-cloud cover based atmospheric conditions and ...

Reducing the false alarm rate (FAR) of Automated Target Recognition (ATR) algorithms is crucial for intelligence, surveillance, reconnaissance (ISR) and precision target engagement missions. There are many contributing factors that result in higher FAR for deep learning (DL) ATR networks operating on Synthetic Aperture Radar (SAR) imagery, including: image distortions, unrepresentative target sign ...

We propose to use Aerosol Optical Depth (AOD) measurements as an early warning system, to cue on-site validation of the soiling station and any available meteorological (MET) station data to validate if a work order to clean deposited particulate matter is necessary. This would move from reactive maintenance – often weeks delayed, to proactive maintenance – getting ahead of the weather impact ...

Correctly labeled data is essential for training AI/ML-based automatic target recognition (ATR). The training process is all the more complicated in synthetic aperture radar (SAR) images because of their unique phenomenology, such as orientation-sensitive target signatures, layover, cross-range smearing, and radio frequency interference. New automated technology must reduce the cost and acc ...

Exum Instruments’ Massbox is a single analytical instrument that offers rapid, high-sensitivity measurements of additive manufacturing (AM) feedstock powders and printed parts. Determining chemical composition for any manufactured material is critical to understanding and predicting a part’s performance. Current methods of chemical characterization are difficult and time-consuming, requiring m ...

Filtering airborne infectious particles from indoor air is a critical element in controlling the spread of disease during COVID and future pandemics that are transmitted through the air. The aim of this proposed research from Ratiocinative Engineering Services, LLC is to develop a testbed that will lead to more accessible and robust quality control testing of air filtration and ventilation systems ...

The Ocean Color and Cloud Monitor (OCCaM) is a hyperspectral based instrument suite with ocean color and cloud observational capabilities. Following the successful Phase I SBIR design period, the Phase II effort will focus on the integration of the Phase I design into a benchtop unit for testing and validation of the design concept. The payload was designed to meet the SWaP requirements of a comme ...

The National Geospatial Intelligence Agency (NGA) requires a state-of-the-art model to quickly find and define new target sets within ever increasing datasets. Grey Matters’ CREATIVE PERCEPTION will provide the NGA with an advanced detection algorithm suite that can be easily upgraded to new target sets with a minimum amount of labeled training data. CREATIVE PERCEPTION, based on a complex sel ...

US military and intelligence agencies, including the NGA, have invested significant resources in data collection and effective search and analytics tools. However, due to increasing amounts of data, finding relevant information has become more difficult. NGA analysts are often overwhelmed with data and spend too much time solving data problems rather than solving intelligence problems. Thus, there ...