INS/GPS integrated navigation uncertain system state estimation based on minimal variance robust filtering

被引：0

作者：

Wu, Zhou ^{[1
]}

Shi, Hang ^{[2
]}

Liu, Baosheng ^{[3
]}

机构：

[1] Natl Univ Def Technol, Sch Mech Engn & Automat, Changsha 410073, Hunan, Peoples R China

[2] Tsinghua Univ, Dept Comp Sci & Technol, State Key Lab Intelligent Technol & Syst, Beijing 100084, Peoples R China

[3] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China

来源：

2006 IMACS: MULTICONFERENCE ON COMPUTATIONAL ENGINEERING IN SYSTEMS APPLICATIONS, VOLS 1 AND 2 | 2006年

关键词：

integrated navigation; uncertainty; Kalman filter; minimal variance robust filtering[SHI; 01;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

INS/GPS Integrated Navigation Systems are used for positioning and attitude determination in a wide range of applications. Combining INS and GPS organically, we can get an integrated navigating system which can overcome the respective defects of the two. systems and develop their advantages to form a complementary structure at the same time. GPS measurements can. be used correct the INS and sensor errors to provide high accuracy real-time navigation[FAR,98]. The integration of GPS and INS measurements is usually achieved using a Kalman Filter. But, usually uncertainties exist in INS/GPS Integrated real systems, which may cause filtering to divergence for classical Kalman filter. In order to solve this problem, a robust filter with minimal variance is addressed by this paper.

引用

页码：631 / +

页数：2