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(HealthNewsDigest.com) – Tracking stars in space and orienting satellites that handle everything from telecommunications to health data and weather monitoring will become more accurate, quicker and cheaper thanks to the development of a new algorithm by two prize-winning graduate students from MIT and Johns Hopkins University. Julian Brown, a doctoral student and researcher at MIT’s Space Systems Laboratory, and Keaton Stubis, an MIT graduate and Johns Hopkins University doctoral student in mathematics, were awarded the top prize at the AIAA/USU Conference on Small Satellites for their presentation of a star-tracking algorithm that provides significantly faster, more accurate star identification at a tiny fraction of the current cost, enabling the development of the next generation of spacecraft navigation technology.
Brown and Stubis shared the honor and the accompanying $10,000 prize by securing first place in the Frank J. Redd Student Competition, named after the founder of the AIAA/USU Conference on Small Satellites. The competition provides undergraduate and graduate students pursuing a degree in an engineering or scientific discipline with the opportunity to share their work on small satellite concepts and missions. Each year, college students from across the globe compete for awards made possible through generous donations from organizations and individuals within the small satellite community. Awards are given to competition finalists presenting to a prestigious panel of scientists at the Small Satellite Conference, including those with high-level positions at leading universities, major commercial space programs, the Department of Defense, and NASA.
The new Tetra Star Identification Algorithm is a significant advance over the system that had been the gold standard in star tracking since 2001, the renowned “Lost in Space Pyramid Algorithm” developed by Texas A&M Professor of Aerospace Engineering Daniele Mortari. The new Tetra Star Tracking Algorithm not only increases identification speed by more than 6,000 percent and decreases inaccuracy by between 300 to 100,000 percent for uncalibrated cameras, correcting for centroiding error, rotation, and field of view error, but does so at a tiny fraction of the current estimated equipment costs of hundreds of thousands of dollars, using materials costing only fifty dollars.
“Tetra opens the door for a new generation of star trackers,” write Brown and Stubis in their paper, TETRA: Star Identification with Hash Tables. “Acquisition time, which is the time it takes a star tracker to produce its first attitude solution after startup, is no longer limited by solving the lost-in-space problem. Using Tetra, spacecraft cameras are now capable of rapid self-calibration on-orbit, improving pointing precision without careful alignment on the ground. Tetra also enables star trackers to be built more compactly, as they no longer need RAM to operate. The possibilities are staggering.”
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