引用本文:臧荣春, 崔平远, 崔祜涛, 金艺.基于IMM-UKF的组合导航算法[J].控制理论与应用,2007,24(4):634~638.[点击复制]
ZANG Rong-chun, CUI Ping-yuan, CUI Hu-tao, JIN Yi.Integrated navigation algorithm based on IMM-UKF[J].Control Theory and Technology,2007,24(4):634~638.[点击复制]
基于IMM-UKF的组合导航算法
Integrated navigation algorithm based on IMM-UKF
摘要点击 3636  全文点击 3205  投稿时间：2005-10-09  修订日期：2006-09-11
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DOI编号  10.7641/j.issn.1000-8152.2007.4.023
  2007,24(4):634-638
中文关键词  Unscented卡尔曼滤波  交互多模型  组合导航
英文关键词  Unscented Kalman filter  interacting multiple model  integrated navigation
基金项目  国防科工委基础科研项目(J1600B001); 国家高技术研究发展计划(863 计划)项目“组合导航系统自主重构技术与智能导航算法研究”(2006AA12Z305)”.
作者单位
臧荣春, 崔平远, 崔祜涛, 金艺 哈尔滨工业大学深空探测基础研究中心, 黑龙江哈尔滨150080
大庆油田电力集团宏伟热电厂, 黑龙江大庆163411 
中文摘要
      为解决非线性动态系统滤波的非线性和噪声不确定等问题, 设计了一种基于交互多模型(IMM)的Unscented 卡尔曼滤波器(UKF), 针对噪声变化情况建立一组非线性模型, 与每个模型对应的UKF可以达到二阶以上的滤波精度. IMM-UKF 滤波器的输出为各滤波器的概率加权融合, 因此, 根据噪声变化而调整的模型概率使系统输出对噪声变化具有自适应能力. 利用该算法对组合导航系统进行了仿真试验, 该算法精度高,模型切换速度快, 能适用于动态系统.
英文摘要
      A new unscented Kalman filter (UKF) based on interacting multiple model (IMM) is presented to solve the problem of nonlinear filtering and noise modeling. The uncertainty of the noise can be described by a set of switching models. In every model a UKF is running, and the UKF for nonlinear filtering can achieve accuracy at least to the second order. The output of the IMM-UKF is the weighted sum of a bank of parallel unscented Kalman filters. The self-adaptive filtering for different noises can be performed by the adjustment of all models weights.The application of the algorithm on integrated navigation system shows a high precision and switching speed, so it is applicable to dynamic systems.