Noise modeling concepts in nonlinear state estimation

• Published in: Journal of process control Vol. 19; no. 7; pp. 1111 - 1125
• Main Authors: Kolås, S., Foss, B.A., Schei, T.S.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2009
• Subjects: Constrained nonlinear systems; Joint UKF; Noise modeling; Nonlinear state estimation; Noise modeling; Constrained nonlinear systems; Nonlinear state estimation; Joint UKF
• ISSN: 0959-1524; 1873-2771
• DOI: 10.1016/j.jprocont.2009.03.002

It is quite common to assume that uncertainty enters through additive white noise sources when using recursive state estimation algorithms. Also unknown and time-varying parameters are often modeled similarly by augmenting the states with a parameter vector. Further, it is common to reflect initial model uncertainty through the choice of the initial covariance matrices for the states and parameters. In this paper we study noise modeling based on a hypothesis that it is important to model noise correctly. In practice this implies a critical view on the dominating ‘additive noise paradigm’ as a means to model uncertainty. Alternative concepts of modeling the noise are investigated, and it is shown that modeling noise by introducing it in the system auxiliary variables and control inputs may have a positive impact on estimation performance.