Observability Analysis in Parameters Estimation of an Uncooperative Space Target

作     者：Xianghao Hou Gang Qiao 

作者机构：Acoustic Science and Technology Laboratory and College of Underwater Acoustic EngineeringHarbin Engineering UniversityHarbin150001China 

出 版 物：《Computer Modeling in Engineering & Sciences》 (工程与科学中的计算机建模（英文）)

年 卷 期：2020年第122卷第1期

页      面：175-205页

核心收录：

学科分类：08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 081102[工学-检测技术与自动化装置] 

基　　金：The authors wish to express their appreciation to the reviewers for their helpful suggestions which greatly improved the presentation of this paper 

主　　题：Parameter estimations observability analysis dual quaternions extended Kalman filter 

摘      要：To study the parameter estimating effects of a free-floating tumbling space target,the extended Kalman filter(EKF)scheme is utilized with different high-nonlinear translational and rotational coupled kinematic&dynamic models on the LIDAR *** the aforementioned models and measurements results in the situation where one single state can be estimated differently with varying accuracies since the EKFs based on different models have different *** the proposed EKFs,the traditional quaternions based kinematics and dynamics and the dual vector quaternions(DVQ)based kinematics and dynamics are used for the modeling of the relative motions between a chaser satellite and an uncooperative *** the non-contact estimating scenarios,only highly nonlinear relative attitude and range measurements:the grapple fixture on the target measured from the chaser satellite via vision-based sensors,can be *** evaluating the results of the EKFs,the observability properties of each EKF are studied analytically and numerically with the the Observability Gramian matrices(OG)and the standard deviations for every estimated *** analysis of observability perform intensive studies and reveal the intrinsic factors that affect the accuracy and stability of the parameters estimation of an uncooperative space ***,the analytical and numerical results show the optimal composition of the kinematic&dynamic models and measurements.