基于TDOA的自适应扩展卡尔曼滤波跟踪算法研究
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  • 英文篇名:Adaptive Interation Extended Kalman Filter Tracing Algorithm Based on TDOA
  • 作者:周恭谦 ; 杨露菁 ; 刘忠
  • 英文作者:ZHOU Gongqian;YANG Lujing;LIU Zhong;College of Electronic Engineering,Naval University of Engineering;
  • 关键词:自适应扩展卡尔曼滤波 ; 时差定位 ; 目标跟踪
  • 英文关键词:AEKF(adaptive iteration extended kalman filter);;TDOA(time difference of arrival);;location tracing
  • 中文刊名:JCGC
  • 英文刊名:Ship Electronic Engineering
  • 机构:海军工程大学电子工程学院;
  • 出版日期:2018-07-20
  • 出版单位:舰船电子工程
  • 年:2018
  • 期:v.38;No.289
  • 基金:国家自然科学基金(编号:61401493)资助
  • 语种:中文;
  • 页:JCGC201807008
  • 页数:4
  • CN:07
  • ISSN:42-1427/U
  • 分类号:35-38
摘要
论文对UWB中基于扩展卡尔曼滤波的TDOA跟踪定位算法研究。针对EKF算法会随着测量误差增大定位精度降低这一缺点,提出了一种自适应迭代扩展卡尔曼滤波算法(AIEKF),通过仿真对比表明该算法在测距误差增大时,该算法能保持良好的定位精度和收敛速度
        This paper studies the TDOA location tracing algorithm based on extended kalman filter in UWB. A kind of AEKF(adaptive iteration extended kalman filter)is proposed based on the disadvantage that the EKF algorithm's positioning accuracy re-duces with the increase of measurement error and the simulation results show that this algorithm can maintain good positioning accu-racy and convergence speed during the increase of the distance-measuring error.
引文
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