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A Framework for Navigation with LTE Time-Correlated Pseudorange Errors in Multipath Environments

机译:多路径环境中具有LTE时间相关伪距错误的导航框架

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A navigation framework based on a multi-state constraint Kalman filter (MSCKF) is proposed to reduce the effect of time-correlated pseudorange measurement noise of cellular long-term evolution (LTE) signals. The proposed MSCKF framework captures the position of the antenna over a window of measurements to impose constraints on the position estimate. Simulation results are presented showing a reduction of 57% and 51% in the two- dimensional (2D) and three-dimensional (3D) position root mean squared-error (RMSE), respectively, using the proposed framework compared to an extended Kalman filter (EKF). Experimental results on a ground vehicle navigating in an urban environment are presented showing a reduction of 29% and 64.7% in the 2D and 3D position RMSE, respectively, and a reduction of 19.6% and 86.7% in the 2D and 3D maximum error, respectively, using the proposed framework compared to an EKF.
机译:提出了一种基于多状态约束卡尔曼滤波器(MSCKF)的导航框架,以减少蜂窝长期演进(LTE)信号与时间相关的伪距测量噪声的影响。所提出的MSCKF框架在测量窗口上捕获天线的位置,以对位置估计施加约束。仿真结果表明,与扩展的卡尔曼滤波器相比,使用建议的框架,二维(2D)和三维(3D)位置均方根误差(RMSE)分别降低了57%和51% (EKF)。提出了在城市环境中导航的地面车辆的实验结果,显示2D和3D位置RMSE分别降低了29%和64.7%,2D和3D最大误差分别降低了19.6%和86.7%。 ,与EKF相比,使用建议的框架。

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