刘韬, 徐爱功, 隋心, 王长强. 新息向量的抗差Kalman滤波方法及其在UWB室内导航中的应用[J]. 武汉大学学报 ( 信息科学版), 2019, 44(2): 233-239. DOI: 10.13203/j.whugis20170067
引用本文: 刘韬, 徐爱功, 隋心, 王长强. 新息向量的抗差Kalman滤波方法及其在UWB室内导航中的应用[J]. 武汉大学学报 ( 信息科学版), 2019, 44(2): 233-239. DOI: 10.13203/j.whugis20170067
LIU Tao, XU Aigong, SUI Xin, WANG Changqiang. An Improved Robust Kalman Filtering Method Based on Innovation and Its Application in UWB Indoor Navigation[J]. Geomatics and Information Science of Wuhan University, 2019, 44(2): 233-239. DOI: 10.13203/j.whugis20170067
Citation: LIU Tao, XU Aigong, SUI Xin, WANG Changqiang. An Improved Robust Kalman Filtering Method Based on Innovation and Its Application in UWB Indoor Navigation[J]. Geomatics and Information Science of Wuhan University, 2019, 44(2): 233-239. DOI: 10.13203/j.whugis20170067

新息向量的抗差Kalman滤波方法及其在UWB室内导航中的应用

An Improved Robust Kalman Filtering Method Based on Innovation and Its Application in UWB Indoor Navigation

  • 摘要: 针对超宽带(ultra wideband,UWB)室内导航中非视距(non line of sight,NLOS)测距误差会大幅降低导航精度以及系统噪声的不确定性导致滤波精度不高的问题,提出了一种基于新息向量的抗差Kalman滤波方法。该方法在UWB室内导航线性化模型的基础上,利用单个新息值构造抗差因子矩阵,从而消除非视距测距误差的影响,同时对系统噪声协方差矩阵进行实时估计和修正。实验结果表明,该方法不但能有效地消除非视距测距误差对导航解算的影响,而且能进一步提高导航解算的精度和稳定性。

     

    Abstract: In UWB indoor navigation, the accuracy of navigation resolution is greatly affected by non line of sight(NLOS) ranging error, and low filtering precision is influenced by uncertain system noise. To solve these problems, an improved robust Kalman filtering based on innovation is proposed and applied in ultra wideband(UWB) indoor navigation. On the foundation of the linear UWB indoor navigation model, the new method uses single innovation values to construct the matrix with robust factors and eliminate the influence of NLOS ranging error. Meanwhile, the new method does real-time estimation and corrects the system noise covariance matrix. Experimental result verifies the effectiveness of the new method. It is shown that the new method can not only effectively eliminate the influence of NLOS ranging error on navigation resolution, but also can further improve the filter precision and reliability in indoor navigation.

     

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