Convergence of discrete-time Kalman filter estimate to continuous time estimate

Using data-driven discrete-time models and the unscented Kalman filter to estimate unobserved variables of nonlinear systems.

This paper addresses the problem of state estimation for nonlinear systems by means of the unscented Kalman filter (UKF). Compared to the traditional extended Kalman filter, the UKF does not require the local linearization of the system equations used in the propagation stage. Important results using the UKF have been reported recently but in every case the system equations used by the filter w...

Extended-Kalman-Filter-like observers for continuous time systems with discrete time measurements

In this short note is studied the observer introduced in [1] and [5]. The relationship between the Lipschitz constant and the measurement stepsize is exhibited. For second order system, we evaluate the authorized measurement stepsize.

Discrete - time Kalman Filter and the Particle Filter

A discrete-time system is a process that transforms input discrete-time signals into output discretetime signals. Simply stated, it takes an input sequence and produces an output sequence. Such a system usually takes the form of xk = Fk−1xk−1 +Gk−1uk−1 +wk−1, (1) where the n-vectors xk and xk−1 are the states at the current and previous time steps, the l-vector uk is a known input, and the n-ve...

Square Root Cubature Kalman Filter-Kalman Filter Algorithm for Intelligent Vehicle Position Estimate ¬リニ

A new filtering algorithm, adaptive square root cubature Kalman filter-Kalman filter (SRCKF-KF) is proposed to reduce the problems of amount of calculation, complex formula-transform, low accuracy, poor convergence or even divergence. The method uses cubature Kalman filter (CKF) to estimate the nonlinear states of model while its linear states are estimated by the Kalman filter (KF). The simula...

Space–time Kalman filter