{"title":"A semi-Markov multiple event filter for maneuvering targets","authors":"P. Abeles, M. Kovacich","doi":"10.1109/ICIF.2007.4407972","DOIUrl":null,"url":null,"abstract":"Tracking maneuvering targets is a difficult problem due to unpredictable maneuvers which change the target's state and/or dynamics. To ensure track accuracy a filter needs to model the target correctly and quickly respond to maneuvers. A new sequential filter is proposed which attempts to improve upon existing algorithms in several areas. A more flexible internal model is used to describe effects of maneuver events. Maneuver hypotheses have improved temporal accuracy. A semi-Markov process is used to describe the probability of an event occurring as a function of time. In simulated test scenarios the new algorithm performs as well as or significantly better than Interacting Multiple Model filter.","PeriodicalId":298941,"journal":{"name":"2007 10th International Conference on Information Fusion","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 10th International Conference on Information Fusion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIF.2007.4407972","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
Tracking maneuvering targets is a difficult problem due to unpredictable maneuvers which change the target's state and/or dynamics. To ensure track accuracy a filter needs to model the target correctly and quickly respond to maneuvers. A new sequential filter is proposed which attempts to improve upon existing algorithms in several areas. A more flexible internal model is used to describe effects of maneuver events. Maneuver hypotheses have improved temporal accuracy. A semi-Markov process is used to describe the probability of an event occurring as a function of time. In simulated test scenarios the new algorithm performs as well as or significantly better than Interacting Multiple Model filter.