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Qilian Liang's signal processing system eliminates redundant data.
One UT Arlington electrical engineer is partnering with the U.S. Navy to do more with less.
Professor Qilian Liang was recently awarded a five-year, $797,500 grant by the Office of Naval Research (ONR) to simplify data collection through an algorithmic system he designed and is streamlining. The goal is to create a signal processing system that provides better information for radar while collecting less data.
“When the Navy’s radar looks at a specific area, it takes into account everything in that area,” Dr. Liang explains. “Much of that data isn’t needed for the system to come to a precise answer on what a radar system says is there. If you take in less data, it takes the system less time to make an informed decision.”
The amount of time and space saved depends on the sample size of whatever the Navy is asking the system to evaluate. The redundant data is eliminated with co-prime and nested samplings in time and spatial domains, which only keep a small subset of data. (Co-prime signal processing is a new waveform sampling strategy that offers simplified sensor array design, streamlined signal processing, and efficient image formation techniques.)
“This project will help to automate processes that provide small tactical units with more efficient data processing,” Liang says.
He believes the results from this research will potentially benefit different programs on Navy and Marine Corps ships and planes; for example, besides helping make their radars more efficient, it could improve the performance of sensor and surveillance systems.
Liang’s grant was funded by the ONR Basic Research Challenge program, which was established to competitively select and fund promising research projects in new areas not addressed by current programs. Its aim is to stimulate new, high-risk research that fosters leading-edge science.
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