1. Jamming Resistant Adaptive Radio System
Developing smart antennas for jam-resistant cognitive or software defined radio systems entails a number of challenging issues. Researchers at the University of Texas are investigating methods to locate jamming signals and then take evasive action to maintain a communication link. Their work involves the use of large arrays of miniaturized, tunable antennas and adaptive filters to protect the system. The goal is to design a resilient communication system resistant to jamming signals in a wide spectrum of frequencies.
2. All-Electric Ship Simulation
All-Electric Ships (AES) are designed to make more efficient use of on-board power, cut fuel use, and meet future requirements for high-power weapons such as the electromagnetic gun, high power microwave, and high energy lasers. The simulation models of the AES provide a platform for evaluating the power system and its different components under various operating loads and conditions. It includes the major system onboard the AES, incorporates intermittent and continuous duty loads, and simulates different types of energy storage systems.
3. Automated SIGINT/COMINT Platform
A group of researchers from Texas A&M University is interested in using Factor Graphs or Bayesian Belief Networks as a unifying framework that connects multiple antenna techniques, estimation and detection algorithms, and modular subsystems for collection, processing, and geospatial data fusion in a Signal Intelligence (SIGINT) and Communications Intelligence (COMINT) system.
4. Axisymmetric Tandem Mirror Machine Control
Modern plasma research is concentrated on plasma confinement using closed, toroidal magnetic fields systems (tokamak) which are typically more complex, expensive, and harder to control than other options. Researchers at the University of Texas are building an axisymetric tandem mirror machine to act as an intense neutron source for testing new materials to be used in future tokamak plasma fusion reactors.
5. Image-Guided Surgery
Researchers at UTSA are interested in developing a general-purpose, real-time, model-based predictive control system that involves adaptive feedback for real-time control of a laser probe and online computer simulations of the complex thermal environments that evolve during surgery. New approaches to data-driven simulation will be developed with the hope of delivering predictable thermal patterns in vivo for laser irradiation heating and integrating the point-wise temperature measured heating information, tissue response, and damage to enable complete tumor destruction with minimal damage to normal tissues.