Reduction of Sensory Inaccuracy in Nonlinear Systems using Particle Filters

Abstract

In signal processing and control applications, on-line state estimation plays important role in stability of the system. In cases where state and/or measurement functions are highly nonlinear and/or the noise is not Gaussian, conventional filters such as extended Kalman filters do not provide satisfactory results. In this paper, particle filters and its application to a nonlinear problem are examined