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UPF算法在状态估计中的应用 被引量：3

Application of Unscented Particle Filtering Algorithm on State Estimation
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摘要 首先分析了基于贝叶斯理论的粒子滤波算法的原理;然后在分析采样-重要性-重采样算法基础上讨论了粒子滤波算法存在的主要问题,研究了一种使用UKF产生重点密度函数的粒子滤波算法(UPF);最后通过实例将该算法与粒子滤波算法进行比较,仿真结果表明UPF算法运算时间低于粒子滤波算法。 The Particle Filter （PF） algorithm based on Bayesian theory is analyzed. Then, based on the analysis of a standard algorithm of sampling-importance-resampling filter, the problems of PF are discussed and another PF algorithm which importance density is generated by UKF is researched. Finally, the comparison of two algorithms＂ performance is presented by an application example, the simulation results have shown that calculation time of the unscented particle filter （UPF） is less than PF.
作者 彭云辉 缪栋 刘冬 杨小冈
机构地区 第二炮兵工程学院
出处 《微电子学与计算机》 CSCD 北大核心 2006年第11期41-43,共3页 Microelectronics & Computer
关键词 粒子滤波 贝叶斯估计 非线性滤波 UPF Particle filter, Bayesian estimation, Nonlinear filter, Unscented particle filter
分类号 TN957.51 [电子电信—信号与信息处理]
  • 相关文献

参考文献5

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二级参考文献6

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共引文献14

同被引文献24

  • 1郝晶,李卫忠,白剑林.一种多速率的交互式多模型粒子滤波算法[J].微电子学与计算机,2009,26(2):163-166. 被引量：3
  • 2田力伟,黄建国.粒子滤波在机动目标纯方位跟踪中的应用[J].微电子学与计算机,2005,22(10):81-84. 被引量：6
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引证文献3

二级引证文献15

微电子学与计算机
2006年 第11期

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