Linearization errors inherent in the specification of an extended Kalman filter (EKF) can
severely degrade its performance. This correspondence presents a new approach to the …

We study the problem of finite-horizon Kalman filtering for systems involving a norm-
bounded uncertain block. A new technique is presented for robust Kalman filter design. This …

A significant shortcoming of the state space control theory that emerged in the 1960s was its
lack of concern for the issue of robustness. However, in the design of feedback control …

We present a robust recursive Kalman filtering algorithm that addresses estimation problems
that arise in linear time-varying systems with stochastic parametric uncertainties. The filter …

This paper is concerned with the design of robust filters that ensure minimum filtering error
variance bounds for discrete-time systems with parametric uncertainty residing in a polytope …

A theoretical analysis is made of the error propagation due to numerical roundoff for four
different Kalman filter implementations: the conventional Kalman filter, the square root …

The Kalman Filter (KF) is one of the most widely used methods for tracking and estimation
due to its simplicity, optimality, tractability and robustness. However, the application of the KF …

This article provides a simple and intuitive derivation of the Kalman filter, with the aim of
teaching this useful tool to students from disciplines that do not require a strong …

The well‐known conventional Kalman filter gives the optimal solution but requires an
accurate system model and exact stochastic information. In a number of practical situations …

This paper addresses several challenging problems of robust filtering. We derive new linear
matrix inequality (LMI) characterizations of minimum variance or H/sub 2/performance and …