NDLI: A hybrid prediction method and its application in the distributed low-cost INS/GPS integrated navigation system

Content Provider	IEEE Xplore Digital Library
Author	Xuemei Wang Chen, J.X. Wenbo Ni
Copyright Year	2015
Description	Author affiliation: Electromech. Meas. & Controlling Dept., Southwest Jiaotong Univ., Chengdu, China (Xuemei Wang) \|\| Comput. Sci. Dept., George Mason Univ., Fairfax, VA, USA (Chen, J.X.) \|\| Vehicle Eng. Dept., Southwest Jiaotong Univ., Chengdu, China (Wenbo Ni)
Abstract	In order to improve the accuracy of INS/GPS integrated navigation system during GPS signals blockage, an effective and low-cost method is to design the corresponding linear or non-linear predictor to predict the position and velocity errors between INS and GPS during GPS blockage and then to correct the results of INS. Based on the distributed data fusion system, a novel hybrid prediction method that combines the radial basis function network (RBFN) and Kalman filter (KF) together was proposed. The predicted value is divided into two parts. One part is the innovation component of KF and the other is the state prediction component of KF. The former is predicted with the designed 6 RBFNs; the latter is predicted with two distributed KFs. Through practical experiments and data processes, it is shown that the proposed hybrid predictor possibly improve the accuracy of INS during GPS blockage.
Starting Page	1205
Ending Page	1212
File Size	912900
Page Count	8
File Format	PDF
e-ISBN	9780982443866
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	ISIF
Subject Keyword	Global Positioning System Sensors Accuracy Training Noise Neurons radial basis function networks distributed information systems error correction GPS outages inertial navigation Kalman filter
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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