Application of the sliding innovation filter to complex road

Abstract

The sliding innovation filter (SIF) is a newly developed filter that may be applied to both linear and non-linear systems. The SIF shares similar principles with sliding mode observers (SMO) and other variable structure filters such as the smooth variable structure filter (SVSF). The SIF utilizes the true trajectory as a hyperplane and forces the estimates to stay within a region of the hyperplane through the use of a discontinuous correction gain. In this paper, the SIF is applied to the well-known complex road estimation problem with nonlinear system function. The results of the application are compared with the SVSF, and future work is discussed.