Improved EKF method of estimating locations with sudden high jumps in the measurement noise
type: Item
instance of: scholarly article
title: Improved EKF method of estimating locations with sudden high jumps in the measurement noise
zbMATH Open document ID: 1020.93024
DOI: 10.1023/A:1014295030080
author: Arie Berman
author: Joshua Dayan
author: Bernard Friedland
published in: Journal of Intelligent \& Robotic Systems
publication date: 2002-07-08T00:00:00Z
review text: Range and bearing navigation is commonly used in many systems. The obtained measurements are accompanied by noise and possible errors which may lead to wrong decisions of the control and guidance system. The authors suggest an improved method, over the Kalman filter with standard gates, of filtering unexpected high measurement noise. Optimal variable correlation gates around the predicted values of the signal states reduce the unexpected noise effect. Values of measurements out of these gates are not considered, and the integration of the prediction model for the tracked signal continues until a new measurement is received within the gate opening.
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 93C73
zbMATH DE Number: 1764779
zbMATH Keywords: validation gate
zbMATH Keywords: tracking
zbMATH Keywords: high-jump noise
zbMATH Keywords: bearing navigation
zbMATH Keywords: guidance system
zbMATH Keywords: Kalman filter
zbMATH Keywords: variable correlation gates
zbMATH Keywords: unexpected noise
zbMATH Keywords: prediction model
reviewed by: Grigori N. Milstein
MaRDI profile type: Publication
full work available at URL: a:1014295030080
OpenAlex ID: W1598197101
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description: scientific article; zbMATH DE number 1764779