The Performance Evaluation of Low Cost MEMS IMU/GPS Integrated Positioning and Orientation Systems Using Novel DBPNNs Embedded Fusion Algorithms

Kuan-Yun Chen and Cheng-Yueh Liu

Abstract:	Mobile mapping systems (MMSs) have been widely applied for acquiring spatial information in applications such as spatial information systems and 3D city models. Nowadays the most common technologies used for positioning and orientation of a mobile mapping system include using Global Positioning System (GPS) as a major positioning sensor and Inertial Navigation System (INS) as the major orientation sensor. In the classical approach, the limitation of Kalman Filter (KF) and the price of overall multi-sensor systems have limited the popularization of most land-based mobile mapping applications. Although intelligent sensor positioning and orientation schemes have been proposed consisting of Multi-layer Feed-forward Neural Networks (MFNNs), one of the most famous Artificial Neural Networks (ANNs), and smoother, in order to enhance the performance of a low cost Micro Electro Mechanical Systems (MEMS) Inertial Measurement Unit (IMU) and GPS integrated system, the automation of the MFNN applied is not as easy as initially expected. Therefore, this study not only addresses the problems of insufficient automation in the conventional methodology that has been applied in MFNN-smoother algorithms for MEMS IMU/GPS integrated systems proposed in previous studies, but exploits and analyzes the idea of developing alternative intelligent sensor positioning and orientation schemes that integrate various sensors in more automatic ways. The proposed schemes are implemented using one of the most famous constructive neural networks; Dynamic Back Propagation Neural Networks (DBPNNs), to overcome the limitations of conventional techniques based on the smoother algorithms as well as previously developed MFNN-smoother schemes. The DBPNNs applied also have the advantage of a more flexible topology compared to the MFNNs. The preliminary results presented in this article illustrate the effectiveness of the proposed schemes over smoother algorithms as well as the MFNN-smoother schemes based on the experimental data utilized in this study.
Published in:	Proceedings of the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2011) September 20 - 23, 2011 Oregon Convention Center, Portland, Oregon Portland, OR
Pages:	979 - 993
Cite this article:	Chen, Kuan-Yun, Liu, Cheng-Yueh, "The Performance Evaluation of Low Cost MEMS IMU/GPS Integrated Positioning and Orientation Systems Using Novel DBPNNs Embedded Fusion Algorithms," Proceedings of the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2011), Portland, OR, September 2011, pp. 979-993.
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