DGPS/INS Integration Using Linear Neurons

Faroog Ibrahim, Nizar Al-Holou, Tom Pilutti and Anya Tascillo

Abstract:	This paper presents a new method for integrating a speed-based Inertial Navigation System (INS) and a Differential Global Positioning System (DGPS) for land vehicle navigation. This method of integration relies on the use an artificial linear neuron. The neuron adaptively estimates the scale factor and the bias INS error source values during the availability of the DGPS, and then uses these estimated values to aid the INS during DGPS outages or unsuitable DGPS solutions. The linear neurons send these error source estimations with the corresponding statistics to correct the INS position solution. A statistical propagator propagates these statistics to the next DGPS epoch and reflects them onto the INS position solution. Then a statistical combiner optimally combines the DGPS and the INS position solution. The experimental results demonstrate the advantages of this work over a typical Kalman filter method in terms of performance and computation time. The system can fill a 30 second gap online with 0.3m accuracy.
Published in:	Proceedings of the 13th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 2000) September 19 - 22, 2000 Salt Palace Convention Center Salt Lake City, UT
Pages:	2455 - 2463
Cite this article:	Ibrahim, Faroog, Al-Holou, Nizar, Pilutti, Tom, Tascillo, Anya, "DGPS/INS Integration Using Linear Neurons," Proceedings of the 13th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 2000), Salt Lake City, UT, September 2000, pp. 2455-2463.
Full Paper:	ION Members/Non-Members: 1 Download Credit Sign In