期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2010
卷号：XXXVIII - Part 1
出版社：Copernicus Publications
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 MFNN- KF/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
关键词：GPS/INS; Integration; Mobile Mapping Systems; Constructive Neural Networks; SGN
