Peformance comparison of Autonomous neural network based GPS/INS integration

Author

Malleswaran, M. ; Vaidehi, V. ; Jebarsi, M.

Author_Institution

Dept. of Electron. & Commun. Eng., Anna Univ. of Technol., Tirunelveli, India

fYear

2011

fDate

14-16 Dec. 2011

Firstpage

401

Lastpage

406

Abstract

In positioning and navigation applications, Inertial navigation system (INS) and Global positioning system (GPS) technologies have been widely utilized. Each system has its own unique characteristics and limitations. Therefore, the integration of the two systems offers a number of advantages and overcomes each system inadequacies. The proposed schemes are implemented using the Autonomous neural networks (AUNN) - the cascade correlation network (CCN) and the Feedback cascade correlation network (FBCCN) that was able to construct the topology by itself autonomously on the fly and achieve prediction performance with less hidden neurons.

Keywords

Global Positioning System; feedback; inertial navigation; neural nets; FBCCN; GPS/INS integration; Global Positioning System; autonomous neural network; feedback cascade correlation network; inertial navigation system; performance comparison; Biological neural networks; Correlation; Global Positioning System; Network topology; Neurons; Topology; Training; AUNN; CCN; FBCCN; GPS; INS;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Computing (ICoAC), 2011 Third International Conference on

Conference_Location

Chennai

Print_ISBN

978-1-4673-0670-6

Type

conf

DOI

10.1109/ICoAC.2011.6165209

Filename

6165209