Award Data

The amount of data collected from the suite of current and future sensors far surpasses the bandwidth of analysts to processes the data streams into actionable intelligence. This pixel to pupil ratio problem is a forcing function for developing robust algorithms which accurately find non-cooperative objects while minimizing the false alarm rate.  As exploitation algorithms are tasked with perform ...

TP Engineering personnel have extensive experience with electro-optic systems and high Pulse Repetition Frequency (PRF) Laser systems. We have detailed knowledge of Pockels cell systems enabling active gated imaging through foliage at PRF 100 kHz PRF. Such systems can dramatically improve and protect Geiger-mode LIDAR by both controlling the transmitter output and gating out unwanted return lig ...

Modern Artificial Intelligence (AI) solutions generally employ carefully-crafted Neural Networks (NNs) that require extensive human effort to perform detection, identification, and annotation on each image to create training datasets. AI tools are desired that are optimized for object identification and annotation across diverse families of image data, are reliable and robust, not dependent on e ...

The ubiquity of image sensors for data collection creates a glut of data, which leads to bottlenecks in the processing capabilities of modern systems. In order to process this data, meticulously labeled datasets are required and that must be reviewed by humans in order to guarantee state-of-the-art performance. In this effort we endeavor to create a system that can automatically exploit salient in ...

In the pattern of life problem space, data is often represented via mathematical graphs, in which a variety of algorithms may be employed to conduct semi-autonomous analysis. While successful empirical application of graph-domain algorithms on ABI problems has been achieved, most of these algorithms require a tuning parameter, which is often set heuristically in real-world scenarios. Arete has dev ...

The team of Signature Research, Inc. and Michigan Technological University will develop and demonstrate methods and metrics to evaluate the performance of machine learning-based computer vision algorithms with low numbers of samples of labeled EO imagery. We will use the existing xView panchromatic dataset to demonstrate a proof-of-concept set of tools. If successful, in Phase II, we will extend t ...

Arete will integrate the Mover Intelligence Extraction Engine with the Social Structured Framework (SSF) to produce a capability to generate narratives of MOVINT track data with context derived from associated Geographic Information Systems (GIS) and other foundation data. The Extraction Engine will be derived from the Arete Cognitive Behavior Classifier (CBC) to characterize MOVINT tracks into co ...

In recent years, it has become increasingly important to conduct Geospatial Intelligence (GEOINT) operation via commercial and government persistent sensor systems, which have produced a copious amount of data relevant to the National Geospatial-Intelligence Agency (NGA). As the supply of data expands, it is necessary to employ automated analytics to exploit the data efficiently. We cannot rely on ...

ATA Engineering, Inc., (ATA) proposes to develop and demonstrate a multiphysics framework for the radar cross-section (RCS) analysis of an ablating hypersonic vehicle in an ionized plasma flow field. ATA has developed a software toolset, known as the Multiphysics Engine, capable of modeling many of these hypersonic phenomena. It couples state-of-the-art solvers for CFD (Loci/CHEM), ablation (CHAR) ...

Low-shot objection recognition has become an area of active research in recent years, with advances dramatically improving performance when only a few samples are available, nominally fewer than 20. These technologies are a focus of the intelligence community (IC) because this challenge pertains to many intelligence problems, e.g., objects of interest are rare due to their use, sensitive nature, ...