Spacecraft autonomous navigation using multiple model adaptive estimator

Abstract

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.

Citation

Xiong, K., Wei, C. and Liu, L. (2015), "Spacecraft autonomous navigation using multiple model adaptive estimator", Aircraft Engineering and Aerospace Technology, Vol. 87 No. 5, pp. 465-475. https://doi.org/10.1108/AEAT-08-2013-0151