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 |
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Pages (from-to) | 17372-17389 |
Number of pages | 18 |
Journal | Sensors (Switzerland) |
Volume | 12 |
Issue number | 12 |
DOIs | |
Publication status | Published - 2012 Dec |
All Science Journal Classification (ASJC) codes
- Analytical Chemistry
- Biochemistry
- Atomic and Molecular Physics, and Optics
- Instrumentation
- Electrical and Electronic Engineering