On-board spacecraft relative pose estimation with high-order extended Kalman filter

作     者：Cavenago, Francesco Di Lizia, Pierluigi Massari, Mauro Wittig, Alexander 

作者机构：Politecn Milan Dept Aerosp Sci & Technol Via La Masa 34 I-20156 Milan Italy Univ Southampton Astronaut Grp Southampton SO17 1BJ Hants England 

出 版 物：《ACTA ASTRONAUTICA》 (宇航学报)

年 卷 期：2019年第158卷

页      面：55-67页

核心收录：

学科分类：08[工学] 0825[工学-航空宇航科学与技术] 

基　　金：Advanced Concepts Team under the Ariadna study "Assessment of onboard DA state estimation for spacecraft relative navigation" [IPL-PTE/LF/as/517.2016] 

主　　题：State estimation Kalman filter Differential algebra Space debris Nonlinear filter Pose estimation Processor in the loop 

摘      要：This paper analyzes the real-time relative pose estimation and attitude prediction of a tumbling target spacecraft through a high-order numerical extended Kalman filter based on differential algebra. Indeed, in the differential algebra framework, the Taylor expansion of the phase flow is automatically available once the spacecraft dynamics is integrated and thus the need to write and integrate high-order variational equations is completely avoided making the presented solution easier to implement. To validate the technique, the ESA s *** mission, involving the Envisat satellite, is used as reference test case. The developed algorithms are implemented on a BeagleBone Black platform, as representative of the limited computational capability available on onboard processors. The performance is assessed by varying the measurement acquisition frequency and processor clock frequency, and considering various levels of uncertainties. A comparison among the different orders of the filter is carried out.