引用本文:张鹏,邓自立.带未知有色观测噪声的自校正融合Kalman滤波器[J].控制理论与应用,2012,29(1):85~90.[点击复制]
ZHANG Peng,DENG Zi-li.Self-tuning fusion Kalman filter with unknown colored observation noises[J].Control Theory and Technology,2012,29(1):85~90.[点击复制]
带未知有色观测噪声的自校正融合Kalman滤波器
Self-tuning fusion Kalman filter with unknown colored observation noises
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DOI编号  10.7641/j.issn.1000-8152.2012.1.CCTA101287
  2012,29(1):85-90
中文关键词  多传感器信息融合  解耦融合  未知有色观测噪声  辨识  自校正Kalman滤波器  收敛性
英文关键词  multisensor information fusion  decoupled fusion  unknown colored measurement noises  identification  self-tuning Kalman filter  convergence
基金项目  国家自然科学基金资助项目(NSFC–60874063).
作者单位E-mail
张鹏 黑龙江大学 自动化系
哈尔滨德强商务学院 计算机与信息工程系 
zp52218@sina.com.cn 
邓自立* 黑龙江大学 自动化系 dzl@hlju.edu.cn 
中文摘要
      对于带未知有色观测噪声的多传感器线性离散定常随机系统, 未知模型参数和噪声方差的一致的融合估值器用递推增广最小二乘法(RELS)和求解相关函数方程得到. 将这些估值器代入到最优解耦融合Kalman滤波器中, 得出了自校正解耦融合Kalman滤波器, 并用动态方差误差系统分析(DVESA)和动态误差分析(DESA)方法证明了它收敛于最优解耦融合Kalman滤波器, 因而具有渐近最优性. 一个带3传感器跟踪系统的仿真例子说明了其有效 性.
英文摘要
      For the multisensor linear discrete time-invariant stochastic system with unknown colored observation noises, the consistent fused estimators of unknown model parameters and noise variances are obtained by using the recursive extended-least-squares (RELS) method and solving the correlation function equations. Substituting them into the optimal decoupled fused Kalman filter, we obtain a self-tuning decoupled fused Kalman filter. By means of the dynamic variance error system analysis (DVESA) method and the dynamic error system analysis (DESA) method, this filter is proved to be convergent to the optimal decoupled fusion Kalman filter with asymptotic optimality. A simulation example for a targettracking system with 3 sensors shows its effectiveness.