Object Recognition using Light Curve Inversion

Research Areas: Autonomous Systems

Principal Investigator: Carolin Frueh

Light Curves are an easy and cheap way of collecting information on very distant objects, for which no resolved imaging can be acquired. For autonomous object recognition, light curve inversion is used to extract shape information from non-resolved imagery. The mathematical foundation is explored to find robust formulations for reliable shape inversion for realistic human-made objects, which include sharp edges and concavities. We have successfully achieved reliable shape inversion on real data.

Personnel

Other Faculty: Vladimir Oliker, Emory University

Students: Alexander Burton Liam Robinson

Representative Publications

L. Robinson, C. Frueh, Light Curve Inversion for Reliable Shape-Reconstruction of Human-Made Space Objects, AAS/AIAA Astrodynamics Specialist Conference, Charlotte, North Carolina, August 7-11, 2022
S. Fan, C. Frueh, A Direct Light Curve Inversion Scheme and the Influence of Measurement Noise, Journal of Astronautical Science, submitted 2018
A. Buzzoni, D. Koschny, G. Drolshagen, E. Perozzi, O. Hainaut, S. Lemmens, G. Altavilla, I. Foppiani, J. Nomen, N. S?nchez-Ortiz, W. Marinello, G. Pizzetti, A. Soffiantini, S. Fan, C. Frueh, The observing campaign on the deep-space debris WT1190F as a test case for short-warning NEO impacts, Icarus, Vol. 304, pp. 4-8, doi:10.1016/j.icarus.2017.10.006, 2017

Keywords: light curve inversion, non-resolved imaging