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Computational Science Engineering Applications ResearchDetection of Moving Targets in Heterogeneous Radar Clutter ScenariosPrincipal Investigator: Juan Carlos Chaves, Ph.D., Ohio Supercomputer Center
Of all the sensing technologies available, ground moving-target indication (GMTI) radar has important advantages because of features such as day/night/all-weather operation and foliage, obscurants, smoke, and dust penetration. But GMTI radar data from targets also includes echoes from ground clutter, and the radar motion strongly degrades the performance of target detection for a conventional moving target. Space-time adaptive processing (STAP) is a signal- and image-processing technique that compensates for the radar’s platform motion. Engineers must carefully develop and efficiently implement the robust STAP algorithms, as the technique’s high-dimensional vectors and matrices render it computationally intensive. To improve efficiency, Ohio Supercomputer Center experts developed technology for DoD researchers that simplifies developing complicated algorithms such as STAP and significantly reduces the simulation times by connecting to and interacting with a supercomputer – while still using MATLAB software or related applications designed for basic desktop computers. “On my PC, it took almost 246 hours to complete a STAP simulation with 128 thresholds. On the ARL MSRC (Army Research Laboratory MSRC) system, it took 7 hours, which is 35 times faster. This is a tremendous improvement!” said Freeman Lin, Ph.D., Air Force Research Laboratory Sensors Directorate’s Electromagnetic Scattering Branch, based at Hanscomb AFB, Massachusetts. |
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Surveillance of the ground by air- and space-borne sensors has proven to be essential to military and intelligence organizations. Specifically, the U.S. Department of Defense’s 2006 Quadrennial Defense Review highlights the need for “a highly persistent capability to identify and track moving ground targets in denied areas.”