Enhancing positioning accuracy of GPS/INS system during GPS outages utilizing artificial neural network

Date

2007-06-01

Author

Kaygisiz, Burak H.
Erkmen, Aydan Müşerref
Erkmen, İsmet

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Integrated global positioning system and inertial navigation system (GPS/INS) have been extensively employed for navigation purposes. However, low-grade GPS/INS systems generate erroneous navigation solutions in the absence of GPS signals and drift very fast. We propose in this paper a novel method to integrate a low-grade GPS/INS with an artificial neural network (ANN) structure. Our method is based on updating the INS in a Kalman filter structure using ANN during GPS outages. This study focuses on the design, implementation and integration of such an ANN employing an optimum multilayer perceptron (MLP) structure with relevant number of layers/perceptrons and an appropriate learning. As a result, a land test is conducted with the proposed ANN + GPS/INS system and we here provide the system performance with the land trials.

Subject Keywords

Computer Networks and Communications, Software, General Neuroscience, Artificial Intelligence

URI

https://hdl.handle.net/11511/39556

Collections

Department of Electrical and Electronics Engineering, Article