NDLI: SOANFIS assisted GPS/MEMS-INS integrated positioning errors prediction

Content Provider	IEEE Xplore Digital Library
Author	Li Cong Honglei Qin Juhong Xing
Copyright Year	2010
Description	Author affiliation: School of Electronic and Information Engineering, Beihang University, Beijing, China (Li Cong; Honglei Qin; Juhong Xing)
Abstract	To solve the problem that GPS/MEMS-INS (micro-electro-mechanical system — inertial navigation system) integrated positioning errors accumulate rapidly with time during GPS outages, a kind of SOANFIS (self-organizing adaptive neuro-fuzzy inference system) is proposed to predict the positioning errors of GPS/MEMS-INS integrated navigation system. When GPS is available, not only the parameters of SOANFIS are tuned, but also its structure is evolved online at each epoch. This method can efficiently reflect the error characteristics changing with time of the integrated navigaiton systems, especially when the vehicle has a high dynamic. The simulated test results show that when compared to ANFIS with fixed structure, SOANFIS has better dynamic adaptability and further improves the positioning accuracy of GPS/MEMS-INS integrated navigation system when GPS signals are blocked.
Starting Page	3810
Ending Page	3814
File Size	336164
Page Count	5
File Format	PDF
ISBN	9781424465132
e-ISBN	9781424465163
DOI	10.1109/CISP.2010.5646761
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy neural netwo-rk Heuristic algorithms Artificial neural networks integrated navigation SOANFIS MEMS-INS Vehicle dynamics Global Positioning System Vehicles
Content Type	Text
Resource Type	Article

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