Spacecraft autonomous navigation using multiple model adaptive estimator

• Published in: Aircraft Engineering and Aerospace Technology Vol. 87; no. 5; pp. 465 - 475
• Main Authors: Xiong, Kai, Wei, Chunling, Liu, Liangdong
• Format: Journal Article
• Language: English
• Published: Bradford Emerald Group Publishing Limited 07.09.2015
• Subjects: Accuracy; Adaptive systems; Aerospace engineering; Aircraft; Aircraft components; Algorithms; Autonomous navigation; Computer simulation; Covariance matrix; Engineering; Error detection; Errors; Estimators; Extended Kalman filter; Navigation; Navigation systems; Rangefinding; Simulation; Spacecraft; Velocity; Autonomous navigation; Liaison navigation; Multiple model adaptive estimator; Spacecraft
• ISSN: 1748-8842; 0002-2667; 1758-4213
• DOI: 10.1108/AEAT-08-2013-0151

Purpose – The purpose of this paper is to present a variable structure multiple model adaptive estimator (VSMMAE) for liaison navigation system. Liaison navigation is an autonomous navigation method where inter-satellite range measurements are used to estimate the orbits of all participating spacecrafts simultaneously. Design/methodology/approach – To overcome the problem caused by an inaccurate initial state, a navigation algorithm is designed based on the multiple model adaptive estimation technique. The multiple models are constructed by different initial error covariance matrices. To reduce the computational cost, the likely-model set (LMS) algorithm is adopted to eliminate the unlikely models. Findings – It is specified that the performance of the liaison navigation based on the extended Kalman filter (EKF) is sensitive to the initial error. Simulation results show that the VSMMAE outperforms the EKF in the presence of a large initial error. Practical implications – The presented algorithm is applicable to spacecraft autonomous navigation. Originality/value – A novel navigation algorithm based on the VSMMAE is developed. It is an effective method for the liaison navigation system.