Award Data

This proposal is submitted in response to the DoD’s need for a low-power, US-sourced, ultra-wideband VCO designed to work over -55ºC to 125ºC, with high level of programmability and reconfigurability for different applications. This proposal describes a novel design that meet these requirements, building on more than 10 years of prior R&D in this area.

One advanced material found to survive high G-forces and also is defect and grain-size free is thermos-plastic formed (TPF) Bulk Metallic Glasses (BMG). Unlike MEMS-based silicon components which often do not survive high-G, high shock environments, Tanner Research and Yale University have successfully demonstrated thermos-plastic formed (TPF) Bulk Metallic Glass (BMG) use as an alternative materi ...

Implementation of multiple parallel current-sharing filaments in high-voltage photoconductive semiconductor switches (PCSS) has been shown to be very effective in scaling the current handling capability of the devices. This approach increases the active current-switching area on the surface of the device to handle higher total current. In this effort, we will develop a vertical geometry PCSS that ...

Passive components, such as resistors, capacitors and inductors, present a unique complication when reverse engineering is attempted.  Automated measurements of device values on populated printed circuit boards  - resistance, capacitance and inductance - is complicated by the network effect of neighboring components connected to the component being measured.  Some solutions are applicable to s ...

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 ...

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 ...

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 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 ...

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 ...