{"title":"What do filter coefficient relationships mean?","authors":"J. Gray, A. S. Smith-Carroll, W. Murray","doi":"10.1109/SSST.2004.1295615","DOIUrl":null,"url":null,"abstract":"There are three commonly used relationships between alpha and beta that are reported in the literature: Kalata, Benedict-Bordner, and continuous white noise. The Kalata relation is obtained from steady state Kalman filter theory assuming zero mean white noise in the position and velocity state equations. The Benedict-Bordner relation is derived based on good noise reduction and good tracking through maneuvers. Both the Kalata and Benedict-Bordner relationships can be derived without any reference to a Kalman filter. The question, given the variety of filter coefficient relationships, is which relationship should be chosen as part of a filter design and why? What does it mean to choose a particular filter coefficient relationship? What is the difference between filter coefficient relationship and a criteria to maximize performance? In this paper, the author tries to give the answer to these questions.","PeriodicalId":309617,"journal":{"name":"Thirty-Sixth Southeastern Symposium on System Theory, 2004. Proceedings of the","volume":"346 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Thirty-Sixth Southeastern Symposium on System Theory, 2004. Proceedings of the","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSST.2004.1295615","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
There are three commonly used relationships between alpha and beta that are reported in the literature: Kalata, Benedict-Bordner, and continuous white noise. The Kalata relation is obtained from steady state Kalman filter theory assuming zero mean white noise in the position and velocity state equations. The Benedict-Bordner relation is derived based on good noise reduction and good tracking through maneuvers. Both the Kalata and Benedict-Bordner relationships can be derived without any reference to a Kalman filter. The question, given the variety of filter coefficient relationships, is which relationship should be chosen as part of a filter design and why? What does it mean to choose a particular filter coefficient relationship? What is the difference between filter coefficient relationship and a criteria to maximize performance? In this paper, the author tries to give the answer to these questions.