2025/02/23 by Yijun Tang, Jiang Yunxiao, Tang, Yijun +7
Engineering · Environmental Science · Physics and Astronomy · #Astro and Planetary Science #Earth and Planetary Astrophysics (astro-ph.EP) #FOS: Physical sciences #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Isotope Analysis in Ecology #Space Exploration and Technology
paper · pdf · doi:10.48550/arxiv.2502.16458
openalex publication_date 2025/02/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
China plans to launch a probe (Tianwen-2) around 2025, mainly for exploring the near-Earth asteroid 2016 HO3 . The mission involves close-range exploration, landing, and mining operations that require three-dimensional modeling of the asteroid, which requires prior knowledge of its material composition and uniformity. This information is crucial in progressive or ground exploration processes. Our research focuses on high-precision intelligent inversion of complex physical properties of asteroids based on spectral data, providing support for further analysis of aster oid materials, density, and structure. We have developed a platform for asteroid spectral classification, albedo estimation, and composition analysis, which includes three types of neural networks based on Transformer attention mechanism: One for spectral classification, achieving a four-class classification accuracy of 97.28% and an eleven-class classification accuracy of 95.69%; second one for albedo estimation, with an average absolute error of 0.0308 in S-type asteroid albedo estimation, and the third one for composition analysis, with a predicted spectral angular distance of only 0.0340 and a root mean square error of 0.1759 for the abundance of end members. These results indicate that our network can provide high-precision asteroid spectral classification, albedo estimation, and composition analysis results. In addition, we utilized the platform to analyze and provide results for six asteroids.