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

Authors:
Burak H. Kaygısız;Aydan M. Erkmen;İsmet Erkmen
Affiliations:
Defence Industries Research and Development Institute, The Scientific and Technical Research Council of Turkey, Balgat/Ankara, Turkey 06531;Electrical and Electronics Engineering Department, Middle East Technical University, Ankara, Turkey;Electrical and Electronics Engineering Department, Middle East Technical University, Ankara, Turkey
Venue:
Neural Processing Letters
Year:
2007

Citing 2
Cited 1

Modeling and sensitivity analysis of neural networks

Mathematics and Computers in Simulation - Special issue on neural networks/neural computing
Neural Networks for Optimization and Signal Processing

Neural Networks for Optimization and Signal Processing

In-car positioning and navigation technologies: a survey

IEEE Transactions on Intelligent Transportation Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.