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.
| Original language | English |
|---|---|
| Pages (from-to) | 17372-17389 |
| Number of pages | 18 |
| Journal | Sensors (Switzerland) |
| Volume | 12 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 2012 Dec 1 |
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All Science Journal Classification (ASJC) codes
- Analytical Chemistry
- Atomic and Molecular Physics, and Optics
- Biochemistry
- Instrumentation
- Electrical and Electronic Engineering
Cite this
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On-line smoothing for an Integrated Navigation System with low-cost MEMS inertial sensors. / Chiang, Kai-Wei; Duong, Thanh Trung; Liao, Jhen Kai; Lai, Ying-Chih; Chang, Chin Chia; Cai, Jia Ming; Huang, Shih Ching.
In: Sensors (Switzerland), Vol. 12, No. 12, 01.12.2012, p. 17372-17389.Research output: Contribution to journal › Article
TY - JOUR
T1 - On-line smoothing for an Integrated Navigation System with low-cost MEMS inertial sensors
AU - Chiang, Kai-Wei
AU - Duong, Thanh Trung
AU - Liao, Jhen Kai
AU - Lai, Ying-Chih
AU - Chang, Chin Chia
AU - Cai, Jia Ming
AU - Huang, Shih Ching
PY - 2012/12/1
Y1 - 2012/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84871679532&partnerID=8YFLogxK
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U2 - 10.3390/s121217372
DO - 10.3390/s121217372
M3 - Article
VL - 12
SP - 17372
EP - 17389
JO - Sensors
JF - Sensors
SN - 1424-3210
IS - 12
ER -