Estimation of maneuvering aircraft states and time-varying wind with turbulence

Abstract

This paper presents an application of the Square Root-Unscented Kalman Filter (SR-UKF) to the estimation of aircraft system states and to the estimation of the total wind vector made up of a time-varying prevailing wind plus turbulence. The estimates are computed using conventional auto-pilot sensors with exponentially correlated measurement errors. The objective of this work is to investigate the convergence limitations of the estimates considering the covariance and correlation time constants of the measurement error models as well as the level of intensity of the turbulence.