Intelligent sensor positioning and orientation using a sgn embedded fusion algorithm for a mems IMU/GPS integrated system

Hsiu-Wen Chang, Kuan Yun Chen, Kai-Wei Chiang, Naser El-Sheimy

研究成果: Conference article同行評審

摘要

MMSs have been applied widely for acquiring spatial information in applications such as GIS and 3D city models. Nowadays the most common technologies used for MMS positioning and orientation include using GPS as a major positioning sensor and INS as the major orientation sensor. In the classical approach, the limitation of KF and the price of overall multi-sensor systems have limited the popularization of most land-based MMS applications. Although intelligent sensor positioning and orientation schemes have been proposed consisting of MFNN, one of the most famous ANNs, and KF/RTS, in order to enhance the performance of a low cost MEMS INS/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 MFNNKF/ RTS algorithms for INS/GPS integrated system proposed in previous studies, but also exploits and analyzes the idea of developing alternative intelligent sensor positioning and orientation schemes that integrate various sensors in a more automatic way. The proposed schemes are implemented using SGN to overcome the limitations of conventional techniques based on the KF/RTS algorithms as well as previously developed MFNN-KF/RTS schemes. The SGN(CCN)also has the advantage of a more flexible topology compared to the MFNN for INS/GPS integration. The results presented in this article illustrate the effectiveness of the proposed schemes over both KF/RTS algorithms as well as the MFNN-KF/RTS schemes.

All Science Journal Classification (ASJC) codes

  • 資訊系統
  • 地理、規劃與發展

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