Award Data

This effort will develop and demonstrate methods for remotely assessing the status of electrical grids based on the illumination from lights powered by those grids. It will lead to the development of low-cost sensors which can be passively assess grid health over a large scale. This effort will assess grid health by exploiting recent advances in high-spatial, high-temporal resolution imaging and t ...

To address NGA’s requirements, Sonalysts’ team of world-class experts in underwater optical communication proposes development and implementation of the Precision Optical Navigation Transceiver for Undersea Systems (PONTUS). PONTUS will transfer navigation information from an Underwater Navigation Beacon (UNB) to an Unmanned Undersea Vehicle (UUV) in an electromagnetic-spectrum-denied (e.g., G ...

Machine learning models are susceptible to adversarial attacks that make modifications to the input data in order to cause misclassifications. The root cause is the linearity of the decision boundaries of machine learning models in relation to their inputs. One promising direction is to represent the input data as a distribution. Quantum information science entails techniques for working with wave ...

In this SBIR project, EMAG Technologies Inc. proposes to develop a compact, low-cost, scalable, transmit-only X-band active phased array antenna with phase-only nulling capability based on our proven VISAT architecture. The proposed AESA will use commercial PCB manufacturing platform and will utilize commercial off-the-shelf (COTS) parts and components for the entire multilayer stack-up. The propo ...

The U.S. military is increasingly focused on long-range warfare by delivering time-critical guided hypersonic projectiles to troops on the ground. Additionally, in recent years long range precision fires have become a priority for ranges on the order of 250 nm. On the development path to reaching these extended ranges, the U.S. DoD, Strategic Capabilities Office, Office of Navy Research, Navy and ...

State of the art object detection in satellite imagery currently requires large quantities of hand-labeled satellite images. But what if there exists only very limited satellite imagery of the object, perhaps a single pass? Current deep learning solutions can not learn effective models with this extremely limited data. If, however, there exists model of the object that can be used to synthesize mo ...