NASA's Artemis 1 mission is poised to take a key step toward returning humans to the moon after a half-century hiatus. The launch was scheduled for the morning of Aug. 29, 2022, but was postponed due to an issue with one of the rocket's engines. The next opportunity to launch the rocket is Sept. 2, 2022. The mission is a shakedown cruise—sans crew—for NASA's Space Launch System and Orion Crew Capsule.

The spacecraft is scheduled to travel to the moon, deploy some small satellites and then settle into orbit. NASA aims to practice operating the spacecraft, test the conditions crews will experience on and around the moon, and assure everyone that the spacecraft and any occupants can safely return to Earth.

The Conversation asked Jack Burns, a professor and space scientist at the University of Colorado Boulder and former member of the Presidential Transition Team for NASA, to describe the mission, explain what the Artemis program promises to do for space exploration, and reflect on how the space program has changed in the half-century since humans last set foot on the lunar surface.

Lunar regolith is a layer of loosely-packed rocky grains deposited on the lunar surface, whose physical and chemical properties are important for deciphering the geologic history and formulating lunar spacecraft design. Probing the thermal conductivity of the lunar regolith has drawn a lot of attention since the Apollo era. Early measurements focused on the Apollo regolith samples, but the experimental data were available only at a few landing sites at the nearside.

The CE-4 spacecraft landed at 45.4446°S, 177.5991°E, on the floor of Von Kármán crater, on January 3rd, 2019. After landing, the Yutu-2 rover was released via the deployed two rails.

A spacecraft attitude kinematics model, attitude measurement model, and filter algorithm are three important parts in spacecraft attitude determination, and a high-precision filtering algorithm is the key to attitude determination. The classical sigma-point Kalman filter (SPKF) is widely used in a spacecraft state estimation area with the Gaussian white noise hypothesis.

Although the SPKF algorithm performs well in ideal Gaussian white noise, the actual operating conditions of the spacecraft in orbit are complicated. Space environmental interference, solar panel jitter, and flicker noise will make the noise no longer meet the Gaussian distribution and present a heavy-tailed non-Gaussian situation, where the classical SPKF filtering method is no longer applicable, and there will be obvious accuracy degradation or even filtering divergence.

In a research paper recently published in Space: Science & Technology, a joint team from the Army Engineering University of PLA and Chinese Academy of Military Science, proposed a robust Centered Error Entropy Unscented Kalman Filter (CEEUKF) algorithm by combining the deterministic sampling criterion with the centered error entropy criterion.