Award Data

ABSTRACT: Current methods for inspecting the external surface of manned and unmanned low-observable (LO) aircraft are time consuming and error prone. Technology that can reduce inspection times and minimize human error will benefit the Air Force by significantly increasing aircraft reliability and availability while reducing lifecycle maintenance costs. To address this need, Intelligent Automat ...

ABSTRACT: This proposal presents an Air Force Satellite Control Network (AFSCN) upgrade scheme using smart antenna and cognitive satellite radio techniques. On the remote tracking station (RTS) side, switched beam smart antenna, distributed beam forming technique, multiple access technique based on FDMA and/or CDMA are applied to obtain multiple satellites reception objective. On the satellite si ...

ABSTRACT: In this proposal a Game-theoretic Universal Anti-RFI Defense (GUARD) framework for Satellite Communications is proposed. Key components of the GUARD framework include i) Radio Frequency Interferences (RFI) modeling and impact evaluation infrastructure, which allows the evaluation of the impact of RFI from various sources, and provides a comprehensive RFI knowledge base to SATCOM; ii) RF ...

EO/IR sensors can provide high spatial resolution images using multiple frequency bands ranging from the visible to mid-wave IR. EO/IR sensors have been very successful for terrain imaging from subsonic aircraft and from satellites. Imaging using these platforms has been studied extensively. EO/IR sensors can provide high spatial resolution images using multiple frequency bands ranging from the v ...

We propose to research the feasibility of rapidly reconstituting a ground based sensor system for space situational awareness with a large fraction of the capability of the GEODSS sensor system. This system can be deployed quickly to a GEODSS site where ...

There are many challenges in creating Air Force systems that are resilient against cyber threats. The cyber environment and its threats are highly dynamic, requiring practices and training to be dynamic as well. Cyber threats must be considered during th...

We aim to develop data-driven heterogeneous data fusion approaches for unanticipated event/target detection, which will be more robust and immune to model mismatch problems encountered by model-based approaches. Considering the low intrinsic dimensionality of the sensor data, we propose several data-level fusion approaches based on some state-of-the-art dimensionality reduction techniques. For lin ...

Improving feature extraction, event detection, and target classification in multi-sensor systems requires new mathematical methods and processing techniques. In addition, previous research and experience suggests that leveraging sensor data that has not experienced significant dimensionality reduction can preserve subtle features when processed jointly with other relevant data. However, traditiona ...

Current methods for inspecting the external surfaces of low-observable (LO) aircraft are time consuming and error prone. Technology that can reduce inspection times and minimize human error will benefit the Air Force by increasing assessment reliability and aircraft availability while reducing maintenance costs. To address this need, Intelligent Automation (IAI) and Carnegie Mellon University (CMU ...

Our Phase I work focused on improving modeling and simulations so that the impact of autonomous systems in the battlespace could be better understood. As we have trained our attention on Phase II, it has become increasingly clear that the work we are doing to improve the modeling and simulation of autonomous systems also provides significant leverage for the development of the intelligent behavior ...