A fuzzy approach to low level sensor fusion with limited system knowledge

Abstract

When facing the need to perform low-level sensor fusion with only very limited knowledge available one has to come up with an alternative to the well known and proven Kalman filter. A very interesting candidate for such applications is the so called fuzzy (or soft) voter. This algorithm makes use of fuzzy logic principles to fuse signals in an efficient way and provides a figure of merit as well as sensor monitoring capabilities with very moderate demand for computation performance and memory. In this paper a computational efficient alternative implementation of soft voting for embedded applications is described. Furthermore, its performance is examined using scenarios typical to harsh operations environments using simulation.