Low-order discrete linear filters: Their optimal structure
type: Item
instance of: scholarly article
title: Low-order discrete linear filters: Their optimal structure
zbMATH Open document ID: 1073.93571
author: E. A. Rudenko
published in: Automation and Remote Control
publication date: 2004-10-13T00:00:00Z
review text: The right side of the difference equation describing a nonlinear filter of order equal to the number of estimated components of the Markov vector of the state of the observed object is determined. The presented modification of the nonlinear filter is based on the determination of an optimal filter in the class of filters of arbitrary structure -- this class being wider than the class used in the conditionally optimal nonlinear filtering method. The minimum of the mean-square estimation error as the optimality criterion is used. Relations for exactly determining the mean-square optimal structure of the filter, the joint probability distributions of the object and filter states, and the measurer output are derived. They are used in developing approximate methods of synthesizing suboptimal, low-order, nonlinear filters. An example is given.
reviewed by: Vyacheslav A. Vasiliev
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 62M05
Mathematics Subject Classification ID: 93C10
zbMATH DE Number: 2107783
zbMATH Keywords: nonlinear filtering
zbMATH Keywords: Markov sequences
zbMATH Keywords: Kalman filter
zbMATH Keywords: Pugachev filtering method
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 2107783