Particle Filtering Algorithm for Ultra-tight GNSS/INS Integration

David Bernal, Pau Closas, Juan A. Fernandez-Rubio

Abstract:	In this paper, we present an exhaustive derivation of the mathematical model considered in the Ultra-Tightly Coupled (UTC) approach. Since I and Q measurements involved in the integration are nonlinear, conventional approaches consider the use of an Extended Kalman Filter (EKF) by linearization of the system model. In contrast, Particle Filters (PF) are a set of Sequential Monte-Carlo (SMC) based algorithms used to compute the Bayesian recursion in general state-space models, i.e. nonlinear/nonGaussian. Taking advantage of this tool, we formulate a Particle Filter algorithm for the UTC GNSS/INS integration. The simple Bootstrap Filter algorithm has been programmed to validate the formulation presented. The great performance of the Bootstrap Filter invite us to study in depth the use of PF for the UTC GNSS/INS integration.
Published in:	Proceedings of the 21st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2008) September 16 - 19, 2008 Savannah International Convention Center Savannah, GA
Pages:	2137 - 2144
Cite this article:	Bernal, David, Closas, Pau, Fernandez-Rubio, Juan A., "Particle Filtering Algorithm for Ultra-tight GNSS/INS Integration," Proceedings of the 21st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2008), Savannah, GA, September 2008, pp. 2137-2144.
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