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  • 标题:An IMM algorithm based on augmented kalman filter for maneuvering target tracking
  • 本地全文:下载
  • 作者:Ahmadreza Amirzadeh ; Ali Karimpour ; Ali Moeini
  • 期刊名称:Scientific Research and Essays
  • 印刷版ISSN:1992-2248
  • 出版年度:2011
  • 卷号:6
  • 期号:34
  • 页码:6787-6797
  • DOI:10.5897/SRE10.980
  • 语种:English
  • 出版社:Academic Journals
  • 摘要:In this paper, in order to increase the accuracy of interacting multiple model (IMM) algorithm in presence of low and medium maneuvers, a new IMM algorithm based on Augmented Kalman Filter (AUKF) has been proposed. The accuracy of the IMM algorithm depends upon having a set of filters with motion models which are similar at all times to the real target situations. One way to increase the accuracy of this estimator is to substitute more accurate filters instead of the Standard Kalman Filter (SKF) in it. In order to improve the performance of IMM algorithm, this paper proposes to replace each SKF in the IMM algorithm with the AUKF. Due to the better accuracy of the AUKF than SKF in presence of low and medium maneuvers, this substitution will improve the performance of IMM algorithm in these maneuvering levels. The Monte-Carlo simulation results show the accuracy of the proposed method.
  • 关键词:Maneuvering target tracking; interacting multiple model (IMM); standard kalman filter (SKF); augmented kalman filter (AUKF)
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