Propagating Integrity Bounds in Nonlinear State Estimation

K. O'Brien, J. Rife

Abstract:	Future safety-critical GNSS applications will require state-estimation techniques that ensure integrity. Currently existing state estimators are not suitable for many high-integrity applications because of the way they propagate random variables through nonlinear system dynamics. The major difficulty in nonlinear stateestimation problems dealing with integrity lies in accounting for the nonlinear distortions to the error distribution. This paper proposes a state-estimation method that employs a Gaussian overbound with integrity ensured by an additional unsigned bias. More specifically, the paper focuses on only the prediction step of Bayesian estimation. The resulting predictor resembles a Kalman filter that propagates mean, covariance, and one additional term: the unsigned bias. This solution has the benefit of being relatively computationally efficient while still retaining rigorous integrity.
Published in:	Proceedings of the 22nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2009) September 22 - 25, 2009 Savannah International Convention Center Savannah, GA
Pages:	1807 - 1818
Cite this article:	O'Brien, K., Rife, J., "Propagating Integrity Bounds in Nonlinear State Estimation," Proceedings of the 22nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2009), Savannah, GA, September 2009, pp. 1807-1818.
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