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UC Irvine Receives NASA Contract To Pinpoint Mars Landings Within 100 Meters

The guidance algorithm "Evolved Acceleration Guidance Logic for Entry (EAGLE)," developed and tested extensively for Earth entry, is being adapted to Mars entry. The Mars EAGLE is being developed, tested, and validated to support pinpoint landing within 100 meters. Image credit: UC Irvine.

Irvine CA (SPX) Nov 02, 2004
UC Irvine Monday announced that a researcher within The Henry Samueli School of Engineering has been awarded a contract with NASA, through the Jet Propulsion Laboratory, to develop guidance algorithms aimed at pinpointing future Mars landers within 100 meters of the desired site.

Kenneth Mease, a professor of mechanical and aerospace engineering, is the principal investigator for the three year project, a collaborative effort involving his research group and researchers at JPL.

"Pinpointing a Mars landing to within 100 meters enables science instruments to be delivered close to gullies, rock outcrops or canyon walls. Without pinpoint accuracy, landing near such scientifically interesting objects would be too risky," said Mease.

"Mars missions to date have at best been capable of landing within 20-30 kilometers of a target site. Achieving pinpoint accuracy requires automated on-board guidance during the atmospheric flight and the terminal powered descent."

Mease's team will be developing an algorithm to control a Mars lander's flight during the "hypersonic entry phase" to compensate for variations in atmospheric conditions and vehicle performance, and deliver the vehicle with pinpoint accuracy to the parachute deployment point.

He is also developing a guidance algorithm that will steer the lander during the "powered descent phase" to compensate for wind drift during the parachute phase.

Comprehensive real-time simulation testing of the algorithms in flight-like processors will be conducted at JPL. The first demonstration of pinpoint landing is under consideration for a Mars mission in 2011.

The total contract value is $679,000.

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