Vehicle state and parameter estimation based on adaptive robust unscented particle filter

Robust Adaptive Unscented Particle Filter

Unscented Kalman Filter for Vehicle State Estimation

Vehicle Dynamics Control (VDC) systems require the information about system variables, which cannot be directly measured, e.g., the wheel slip or the vehicle side-slip angle. This paper presents a new concept for the vehicle state estimation under assumption that the vehicle is equipped with the standard VDC sensors. It is proposed to utilize an Unscented Kalman Filter (UKF) for estimation purp...

Aerodynamic parameter estimation using adaptive unscented Kalman filter

Purpose – The purpose of this paper is to estimate aerodynamic parameters accurately from flight data in the presence of unknown noise characteristics. Design/methodology/approach – The introduced adaptive filter scheme is composed of two parallel UKFs. At every time-step, the master UKF estimates the states and parameters using the noise covariance obtained by the slave UKF, while the slave UK...

The Unscented Rao-Blackwellized Marginal Particle Filter applied to the joint state and parameter estimation problem

1 Problem mathematical formulation Let us consider a time-varying system described by k, θ, Sk, Zk, where k is the time index, θ is a vector of parameters, Sk is a random vector corresponding to the time-varying state at time k (with the corresponding realization denoted by sk), and Zk is a random vector corresponding to the observation process at time k (with the corresponding realization deno...

adaptive setting of scaling parameter in unscented kalman filter based on interactive multiple modes

this paper studies the use of unscented kalman filters (ukf) to estimate nonlinear dynamics and, specifically, adaptive determination of scaling parameters in these filters. due to lack of analytic solution and use of numerical methods instead, the computational load of these filters increases drastically. in this paper, a new method is proposed based on interactive multiple models (imm) which ...