Outer space is increasingly filled with satellites, no-longer working satellites, launch rockets, debris from launching satellites and some materials of space like meteorites. Many are too small for the network of radar stations, telescopes and even other satellites to spot. That can lead to debris or micro-meteorites damaging satellites or even threatening the International Space Station.
Space domain awareness (SDA) describes the knowledge and real-time understanding of these objects. The United States must overcome many technological challenges to achieve SDA dominance in the geostationary (GEO) region. The space beyond Earth's orbit - known as XGEO or cislunar space - is even more difficult to navigate. Fortunately, University at Buffalo researchers are up for the challenge.
A research team led by Moises Sudit and John Crassidis has received a $5 million grant to improve our ability to track and monitor this growing collection of space debris.
The Space Object Understanding and Reconnaissance of Complex Events (SOURCE) project is part of a newly established Space University Research Initiative (SURI) program that was created to spur university research into new technologies for the Air Force and U.S. Space Force (USSF).
The grant will focus on developing cutting-edge techniques for sensors and measurement strategies, data fusion and autonomy, as well as improving algorithms to better predict the movements of objects in space.
Funding Source: A U.S. Air Force Research Laboratory (AFRL) Space University Research Initiative (SURI)
Award Amount: $5 Million
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The project’s multidisciplinary team of investigators includes renowned researchers from the University at Buffalo, the Massachusetts Institute of Technology, Penn State University, Georgia Tech, and Purdue University. The team combines experts in cislunar astrodynamics, multi-modal sensing architectures, advanced data association algorithms, position and orientation estimation techniques, uncertainty quantification, RSO attribute estimation through characterization, dynamic sensing, catalog design, and autonomous decision-making element.
Last Modified December 12, 2022