返回
Robust multiple model adaptive estimation for spacecraft autonomous navigation
DOI:10.1016/j.ast.2015.01.021.png)
摘要
En 中文
This paper focuses on the development of a robust multiple model adaptive estimation (RMMAE) algorithm and its performance analysis. The main goal of this work is to enhance the robustness of the estimator against the model parameter identification error. A proof is provided that shows the convergence property of the proposed algorithm. Further analysis shows that the RMMAE algorithm guarantees a bounded energy gain from the model parameter identification error to the estimation error. The performance of the RMMAE is evaluated via simulations for spacecraft autonomous navigation. Simulation results demonstrate the effectiveness of the new algorithm compared With the extended Kalman filter (EKF), the unscented Kalman filter (UKF), the robust Kalman filter (RKF) and the multiple model adaptive estimation (MMAE). (C) 2015 Elsevier Masson SAS. All rights reserved.
Keyword:
Multiple model adaptive estimation
Robust Kalman filter
Spacecraft autonomous navigation
X-ray pulsar
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.8
论文数:
1.0W
被引数:
3.0W
机构
暂无机构信息

