Sensors 2012, 12(12), 17372-17389; doi:10.3390/s121217372
Article

On-Line Smoothing for an Integrated Navigation System with Low-Cost MEMS Inertial Sensors

1, 1,* email, 1, 2, 2, 2 and 2
Received: 17 October 2012; in revised form: 6 December 2012 / Accepted: 7 December 2012 / Published: 13 December 2012
(This article belongs to the Section Physical Sensors)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.
Keywords: on-line smoothing; INS/GPS integration; Kalman filter
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MDPI and ACS Style

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.

AMA Style

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.

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