title: On-line smoothing for an integrated navigation system with low-cost MEMS inertial sensors.
abstract: The integration of the Inertial Navigation System (INS) and the Global Positioning System (GPS) is widely applied to seamlessly determine the time-variable position and orientation parameters of a system for navigation and mobile mapping applications. For optimal data fusion, the Kalman filter (KF) is often used for real-time applications. Backward smoothing is considered an optimal post-processing procedure. However, in current INS/GPS integration schemes, the KF and smoothing techniques still have some limitations. This article reviews the principles and analyzes the limitations of these estimators. In addition, an on-line smoothing method that overcomes the limitations of previous algorithms is proposed. For verification, an INS/GPS integrated architecture is implemented using a low-cost micro-electro-mechanical systems inertial measurement unit and a single-frequency GPS receiver. GPS signal outages are included in the testing trajectories to evaluate the effectiveness of the proposed method in comparison to conventional schemes.
authors: Department of Geomatics, National Cheng-Kung University, 1 University Road, Tainan 701, Taiwan.
authors: Kai-Wei
authors: KW
authors: Chiang
authors: Thanh Trung
authors: TT
authors: Duong
authors: Jhen-Kai
authors: JK
authors: Liao
authors: Ying-Chih
authors: YC
authors: Lai
authors: Chin-Chia
authors: CC
authors: Chang
authors: Jia-Ming
authors: JM
authors: Cai
authors: Shih-Ching
authors: SC
authors: Huang
mesh_terms: D000465:Algorithms; D040362:Geographic Information Systems; D006801:Humans; D055617:Micro-Electrical-Mechanical Systems; D018511:Systems Integration