Compact satellite swarms enable future space mission concepts including cellular architecture, disaggregation, orbital construction, and cooperative inspection. Such swarms can cooperatively determine position and orientation (known as pose) of their constituent satellites by collecting and sharing relative pose measurements. This paper presents sensor selection strategies which reduce the number of computationally expensive vision-based pose measurements which must be collected while still maintaining accurate localization. The first method accounts for the impact of relative viewing geometry and solar angle on relative pose measurements. The second method uses uniformly sampled random spanning trees. The third method randomly selects pose measurements. Selected relative pose measurements are then fused in a Multiplicative Extended Kalman Filter for decentralized cooperative localization. Localization results using simulated measurement data and rendered stereo images are presented.

Date Published: 13 May 2019
PDF: 8 pages
Proc. SPIE 11017, Sensors and Systems for Space Applications XII, 1101705 (13 May 2019); doi: 10.1117/12.2518809

Published in SPIE Proceedings Vol. 11017:
Sensors and Systems for Space Applications XII
Genshe Chen; Khanh D. Pham, Editor(s)