Speed Sensor Error Sources Estimation Using a Linear Neuron

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

Abstract:	This paper presents a method of estimating the bias and scale factor in a speed sensor using a model-based linear neuron. The training of the linear neuron is performed online in a random manner during the availability of the desired target. This method is applied to the DGPS Aided INS system. The desired target in this case is chosen to be the derived DGPS travel distance. Using this approach, the linear neuron adaptively estimates the speed measurement error source values during the availability of DGPS, and then uses these estimated values to aid the INS during DGPS outages or unsuitable DGPS solutions. The experimental results demonstrate the advantages of this work over typical KF methods in terms of performance and computation time.
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:	2603 - 2608
Cite this article:	Ibrahim, Faroog, Al-Holou, Nizar, Pilutti, Tom, Tascillo, Anya, "Speed Sensor Error Sources Estimation Using a Linear Neuron," 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. 2603-2608.
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