Indoor 3D positioning system requires precise information from all three dimensions in space, but measurements in the vertical direction are usually interfered by sensors properties, unexpected obstructions, and other factors. Thus, accuracy and robustness are not guaranteed. Aiming at this problem, we propose a novel sensor fusion algorithm to improve the height estimation for a UWB-barometer integrated positioning system by introducing a pseudo reference update mechanism and the extended Kalman filter (EKF). The proposed fusion approach effectively helps with sensing noise reduction and outlier restraint. The results from numerical experiment investigations demonstrate that the accuracy and robustness of the proposed method achieved better improvement in height determination.

中文翻译：

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在 UWB 气压计 3D 室内定位系统上使用扩展卡尔曼滤波器改进高度估计

室内 3D 定位系统需要空间中所有三个维度的精确信息，但垂直方向的测量通常会受到传感器特性、意外障碍物和其他因素的干扰。因此，不能保证准确性和鲁棒性。针对这个问题，我们提出了一种新的传感器融合算法，通过引入伪参考更新机制和扩展卡尔曼滤波器（EKF）来改进 UWB 气压计集成定位系统的高度估计。所提出的融合方法有效地帮助感知降噪和异常值抑制。数值实验研究的结果表明，所提出的方法的准确性和鲁棒性在高度确定方面取得了更好的改进。