State Estimation for the Homogeneous 1-D Euler Equation by Unscented Kalman Filtering

Abstract

In this article we present a dynamic state estimation method for a one dimensional flow field which is described by the homogeneous Euler equation. The estimated quantities include the pressure, velocity, density and temperature field, which are of interest, for instance, for some combustion concepts. The algorithm relies only on a small number of discrete pressure measurements from the flow field. The influence of the number of used pressure measurements on the convergence speed of the algorithm is investigated. For the state estimation, an Unscented Kalman Filter scheme is exploited. The proposed method is applied in numerical simulations to demonstrate its effectiveness.