The extended Kalman filter (EKF) is a popular state estimation method for nonlinear dynamical models. The model error covariance matrix is often seen as a tuning parameter in EKF, which is often simply postulated by the user. In this paper, we study the filter likelihood technique for estimating the parameters of the model error covariance matrix. The approach is based on computing the likeliho...

space-time adaptive processing is used for clutter mitigation in airborne radars. in this paper, deterministic clutter subspace and direct data domain methods are introduced due to the fact that space-time adaptive processing algorithm requires estimating covariance matrix, limited training data and high complexity in processing. in first proposed method, filter coefficients are calculated by e...

This paper proposes a class of H∞ filter design for Markovian jump systems with time-varying delays. Firstly, by exploiting a new Lyapunov function and using the convexity property of the matrix inequality, new criteria is derived for the H∞ performance analysis of the filtering-error systems, which can lead to much less conservative analysis results. Secondly, based on the obtained conditions,...

This brief presents the derivation of an arbitrary order delta operator-based direct-form IIR filter with minimum roundoff noise gain and sensitivity. It utilizes the concept of different coupling coefficients at different branch nodes for better noise gain suppression. Two possible structures for realizing the inverse delta operator are considered and procedures for calculating the optimal fil...

This paper considers the problem of discrete passive filter design method for singular systems with interval time-varying delay. A bounded real lemma (BRL) for discrete passivity with a dissipation of discretetime delayed singular systems by a Lyapunov function is derived. A delay-dependent discrete passive filter design method is proposed by linear matrix inequality (LMI) approach on the basis...