Filtering-based indoor positioning using ultra wideband (UWB) requires known velocity to predict prior position in the prediction stage. Velocity can be obtained from an inertial measurement unit (IMU) sensor or the posterior state vector at the previous time stamp. Both methods have limitations when using them in practice. This paper proposes two novel velocity determination approaches, which use measurements to approximate velocity in a self-contained way. They are integrated into particle filtering algorithms for prior position determination. The test result shows that the particle filter with the proposed approaches performs similarly to the Rao-Blackwellized particle filter and slightly better than the particle filter with IMU. Compared with the standard particle filter, the particle filters with our proposed approaches achieve similar positioning accuracies with less computation time. Moreover, it is found that the integration of Angle-of-Arrival measurements in particle-filter-based positioning improves the 3-D positioning accuracy by about 37.3% on average.

中文翻译：

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用于基于超宽带 (UWB) 的室内定位的粒子滤波器中新颖的先验位置确定方法

使用超宽带 (UWB) 的基于滤波的室内定位需要已知速度来预测预测阶段的先前位置。速度可以从惯性测量单元 (IMU) 传感器或前一个时间戳的后验状态向量获得。这两种方法在实际使用时都有局限性。本文提出了两种新颖的速度确定方法，它们使用测量值以独立的方式近似速度。它们被集成到粒子滤波算法中，用于先验位置确定。测试结果表明，采用所提出方法的粒子滤波器的性能与 Rao-Blackwellized 粒子滤波器相似，略优于采用 IMU 的粒子滤波器。与标准粒子过滤器相比，使用我们提出的方法的粒子滤波器以更少的计算时间实现了类似的定位精度。此外，还发现在基于粒子滤波器的定位中集成到达角测量可将 3-D 定位精度平均提高约 37.3%。