The discrete-time compensated Kalman filter †

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...

Discrete Kalman Filter Tutorial

be the set of k observations. Finding xak, the estimate or analysis of the state space xk, given Zk and the initial conditions is called the filtering problem. When the dynamic model for the process, f(·), and for the measurements, h(·), are linear, and the random components x0, wk, vk are uncorrelated Gaussian random vectors, then the solution is given by the classical Kalman filter equations ...

Space–time Kalman filter

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.

A Kalman Filter-based Stable Dynamic Inversion for Discrete-time, Linear, Time-varying Systems

In this paper the problem of estimating an unknown input for discretetime, non-minimum phase, multivariable, linear time-varying systems (LTV) is considered. The initial condition of the plant may be unknown and stochastic process and measurement noise are included. The input signal is modelled as a random walk with drifts. Then it is estimated using a Kalman filter for a uniformly detectable a...