Pei H. Leong, S. Arulampalam, T. Lamahewa, T. Abhayapala
{"title":"Gaussian-sum cubature Kalman smoothers for bearings-only tracking","authors":"Pei H. Leong, S. Arulampalam, T. Lamahewa, T. Abhayapala","doi":"10.1109/ISSNIP.2014.6827589","DOIUrl":null,"url":null,"abstract":"In this paper, a fixed-lag and a fixed-interval Gaussian-sum cubature Kalman smoother are proposed for the bearings-only tracking problem. The smoothers are of the forward-backward type and they utilise the Gaussian-sum cubature Kalman filter with improved robustness presented by the authors in [1]. Simulation results show that both the fixed-lag and fixed-interval smoothers exhibit improved accuracy over their filtering counterpart and outperform other existing smoothers of the same type for this problem, with the root-mean-square error overlapping the Cramér-Rao lower bound.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSNIP.2014.6827589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, a fixed-lag and a fixed-interval Gaussian-sum cubature Kalman smoother are proposed for the bearings-only tracking problem. The smoothers are of the forward-backward type and they utilise the Gaussian-sum cubature Kalman filter with improved robustness presented by the authors in [1]. Simulation results show that both the fixed-lag and fixed-interval smoothers exhibit improved accuracy over their filtering counterpart and outperform other existing smoothers of the same type for this problem, with the root-mean-square error overlapping the Cramér-Rao lower bound.