计算机科学 ›› 2008, Vol. 35 ›› Issue (10): 49-52.

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面向无线传感器网络节点定位的自适应卡尔曼滤波算法收敛条件分析

李迅 王建文 李洪峻 马宏绪   

  1. 国防科技大学机电工程与自动化学院自动控制系,长沙410073
  • 出版日期:2018-11-16 发布日期:2018-11-16

LI Xun WANG Jian-wen LI Hong-jun MA Hong-xu (Department of Automatic Control, National University of Defense Technology, Changsha 410073, China)   

  • Online:2018-11-16 Published:2018-11-16

摘要: 分析了新息序列是有色噪声时自适应卡尔曼滤波算法(Adaptive Kal man Filter,AKF)的滤波效果,在范数意义下,证明了k时刻AKF算法中估计误差协方差矩阵和k时刻最优KF算法中估计误差协方差矩阵间距离与新息序列相关性成正比。利用上述结论,证明了所有AKF算法中估计误差协方差矩阵必逐渐远离1时刻最优KF算法中估计误差协方差矩阵。总结上述结论,发现AKF算法收敛条件可描述成以下几个等价命题:1)AKF算法中估计误差协方差矩阵与1时刻最优KF算法中估计误差协方差矩阵差有极限;2)k时刻AKF算

关键词: 无线传感器网络 节点定位 自适应卡尔曼滤波算法 滤波性能分析 滤波收敛性

Abstract: The filtering effects are analyzed when the innovations' series in an adaptive Kalman filter(AKF) is colored noise. Taken the matrix norm as a tool, it is proved that at time k, the distance between the covariance matrix in the AKF and the covariance matr

Key words: Wireless sensor network, Localization, Adaptive kalman filter, Filtering effect, Filtering convergence

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