Analysis on Strong Tracking Filtering for Linear Dynamic Systems
Joint Authors
Ge, Quanbo
Shao, Teng
Sun, Ruoyu
Wen, Chenglin
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-09-10
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Strong tracking filtering (STF) is a popular adaptiveestimation method to effectively deal with state estimationfor linear and nonlinear dynamic systems with inaccuratemodels or sudden change of state.
The key of the STF is to usea time-variant fading factor, which can be evaluated based onthe current measurement innovation in real time, to forcefullycorrect one step state prediction error covariance.
The strongtracking filtering technology has been extensively applied inmany practical systems, but the theoretical analysis is highlylacking.
In an effort to better understand STF, a novel analysisframework is developed for the strong tracking filtering andsome new problems are discussed for the first time.
For this, wepropose a new perspective that correcting the state predictionerror covariance by using the fading factor can be thought ofdirectly modifying the state model by correcting the covarianceof the process noise.
Based on this proposed point of view,the conditions for the STF function to be effective are deeplyanalyzed in a certain linear dynamic system.
Meanwhile, issuesof false alarm and alarm failure are also briefly discussed for thestrong tracking filtering function.
Some numerical simulationexamples are demonstrated to validate the results.
American Psychological Association (APA)
Ge, Quanbo& Shao, Teng& Wen, Chenglin& Sun, Ruoyu. 2015. Analysis on Strong Tracking Filtering for Linear Dynamic Systems. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1074387
Modern Language Association (MLA)
Ge, Quanbo…[et al.]. Analysis on Strong Tracking Filtering for Linear Dynamic Systems. Mathematical Problems in Engineering No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1074387
American Medical Association (AMA)
Ge, Quanbo& Shao, Teng& Wen, Chenglin& Sun, Ruoyu. Analysis on Strong Tracking Filtering for Linear Dynamic Systems. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1074387
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074387