For the general nonlinear systems, a universal weighted measurement fusion (WMF) algorithm is presented via the Taylor series expansion method. Based on the proposed fusion algorithm and the well-known Unscented Kalman Filter (UKF), the WMF-UKF is presented. It is proven that the proposed WMF-UKF asymptotically approaches to the centralized measurement fusion UKF (CMF-UKF) with the increase of ...

To combat the impacts of uncertain noise on estimation vehicle state parameters and high cost sensors, a state-observer design with an adaptive unscented Kalman filter (AUKF) is developed. The equation observer derived by establishing vehicle’s three degrees-of-freedom (DOF) model. On this basis, Sage–Husa algorithm (UKF) are combined to form AUKF adaptively update statistical feature measureme...

Acoustic travel-time tomography of the atmosphere is a nonlinear inverse problem which attempts to reconstruct temperature and wind velocity fields in the atmospheric surface layer using the dependence of sound speed on temperature and wind velocity fields along the propagation path. This paper presents a statistical-based acoustic travel-time tomography algorithm based on dual state-parameter ...

Simultaneous state and parameter estimation based actuator fault detection and diagnosis (FDD) for single-rotor unmanned helicopters (UHs) is investigated in this paper. A literature review of actuator FDD for UHs is given firstly. Based on actuator healthy coefficients (AHCs), which are introduced to represent actuator faults, a combined dynamic model is established with the augmented state co...

Stability and control characteristics analysis has long been the important research area of aircraft flight dynamics, which is the critical factor of control system design, performance evaluation and integrated design of aircraft. The linear perturbation equations describing aircraft longitudinal and lateral motion, which are derived from nonlinear dynamic equations based on the small perturbat...

The premise of vehicle intelligent decision making is to obtain motion state parameters accurately and in real-time. Several cannot be measured directly by sensors, so estimation algorithms based on filtering are effective solutions. most representative algorithm the Kalman filter, especially standard unscented filter (UKF) that has been widely used because its superiority dealing with nonlinea...

The Extended Kalman Filter (EKF) is a well established technique for position and velocity estimation. However, the performance of the EKF degrades considerably in highly non-linear system applications as it requires local linearisation in its prediction stage. The Unscented Kalman Filter (UKF) was developed to address the non-linearity in the system by deterministic sampling. The UKF provides ...

Based on presentation of the principles of the EKF and UKF for state estimation, we discuss the differences of the two approaches. Four rather different simulation cases are considered to compare the performance. A simple procedure to include state constraints in the UKF is proposed and tested. The overall impression is that the performance of the UKF is better than the EKF in terms of robustne...