Award Data

Combining information from disparate sensors can lead to better situational awareness and improved inference performance; unfortunately, traditional multi-sensor fusion cannot capture complex dependencies among different objects in a scene, nor can it exploit context to further boost performance. Integrating context information within a fusion architecture to reason cohesively about scenes of inte ...

Missile defense faces the challenges of rapidly maturing and evolving complex threats, possessing capabilities which require the use of all available resources to successfully detect, track and identify the lethal objects. Future performance will rely on multiple sensors such as ground and sea based radars and electro-optical and infrared sensors for target recognition. It is crucial to develop a ...

Thermally induced fatigue and residual stress introduced during fabrication are sources of failure in microelectronics, which raises reliability concerns for MDA and its system integrators. CFDRC has teamed with experts in the reliability of microelectronics packaging to develop a physics based modeling and testing protocol to correlate material properties and thermal loading conditions to stress ...

We propose a novel computational framework for discrimination that incorporates sensor data from observations of the engagement and from kill assessment (KA) that such sensors can provide. The KA information is combined with data from other sensors to improve the discrimination decision and to reduce the probability of correlated shots. Approved for Public Release 16-MDA-8620 (1 April 16)

Miniaturized base metal electrodes (BME) multilayer ceramic capacitors (MLCC) are of great interest for future missile applications as designers are striving to achieve smaller, lighter, cheaper, faster and better electronic assemblies without sacrificing long-term performance. Unfortunately, screening, reliability and qualifications criteria are either not available or not standardized. In the ...

Physical Sciences Inc. (PSI) proposes to design, develop, and demonstrate a portable, non-invasive, real-time sensor to assess the chemical and physical health of solid rocket motors (SRMs) as a function of age without affecting the motors integrity. In Phase I, a sensor to monitor specific gas species that are markers of the chemical and mechanical aging processes of composite and double base pr ...

Space Micro will develop the core of the decision support system, assemble the models and material properties and demonstrate the utility of the program in materials selection on a subset of failures related to a specific test-bed, which will be the attachment of quad-flat no-leads (QFN) and ball grid array (BGA) devices to printed wiring boards using different solders, underfills, QFN or BGA geom ...

In our Adaptive Management and Mitigation of Uncertainty in Fusion (AMMUF) project, we will model the entire multi-sensor fusion process as a probabilistic model and reason about the different design and algorithmic decisions that can be made by system engineers. This fusion model will use standard fusion system representations and ideas from statistical relational learning field to create flexibl ...

Leveraging the results of our Phase I work, the Torch Team proposes to execute laboratory-based experiments to elucidate fundamental micro-debris formation mechanisms to improve optical modeling of impacts. Optical signatures from impacts collected over the last decade have identified definitive micro-debris parameter trends. However, current theories have difficulty reproducing these optical ob ...

Boston Fusion, together with our teammate Syracuse University, propose a program of research and development, Uncertainty Characterization Using Copulas (UC)2, that will result in a parametric framework based on the statistical theory of copulas for modeling uncertainties for the problem of object classification. (UC)2 will produce a mathematical framework, founded on rigorous theoretical analysis ...