On-Line Smoothing for an Integrated Navigation System with Low-Cost MEMS Inertial Sensors
AbstractThe 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.
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Chiang, K.-W.; Duong, T.T.; Liao, J.-K.; Lai, Y.-C.; Chang, C.-C.; Cai, J.-M.; Huang, S.-C. On-Line Smoothing for an Integrated Navigation System with Low-Cost MEMS Inertial Sensors. Sensors 2012, 12, 17372-17389.
Chiang K-W, Duong TT, Liao J-K, Lai Y-C, Chang C-C, Cai J-M, Huang S-C. On-Line Smoothing for an Integrated Navigation System with Low-Cost MEMS Inertial Sensors. Sensors. 2012; 12(12):17372-17389.Chicago/Turabian Style
Chiang, Kai-Wei; Duong, Thanh T.; Liao, Jhen-Kai; Lai, Ying-Chih; Chang, Chin-Chia; Cai, Jia-Ming; Huang, Shih-Ching. 2012. "On-Line Smoothing for an Integrated Navigation System with Low-Cost MEMS Inertial Sensors." Sensors 12, no. 12: 17372-17389.