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Indoor 3D pedestrian tracking algorithm based on PDR using smarthphone

机译:智能手机基于PDF的室内3D行人跟踪算法

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In this paper, we develop the indoor navigation system based on PDR (Pedestrian Dead Reckoning) using various sensors in smartphone. Usually PDR is consisted of step detection, step length estimation and heading estimation. The issue of PDR is step length estimation and to enhance the accuracy of step length, we apply the walking status recognition algorithm using ANN (Artificial Neuron Network). The features used in ANN are extracted through sensor signals of accelerometer and gyroscope. After recognizing the walking status, it is applied to estimate the step length. And when the status is recognized as stop, even if sensor signal is generated by redundant motion or movement of pedestrian, the moved distance is not calculated additionally and distance error is not increased. We use the barometric pressure sensor to extend the positioning area to whole building. To verify the proposed indoor navigation system, we implemented the application for android and conducted the experiment. Through the results, we demonstrated the accuracy of our system.
机译:本文中,我们使用智能手机中的各种传感器开发了基于PDR(行人航位推算)的室内导航系统。通常,PDR由步长检测,步长估计和航向估计组成。 PDR的问题是步长估计,并且为了提高步长的准确性,我们应用了使用ANN(人工神经元网络)的步行状态识别算法。 ANN中使用的特征是通过加速度计和陀螺仪的传感器信号提取的。识别出步行状态后,将其用于估算步长。并且,当状态被识别为停止时,即使由于多余的运动或行人的移动而产生传感器信号,也不会另外计算移动距离,并且不会增加距离误差。我们使用大气压力传感器将定位区域扩展到整个建筑物。为了验证提议的室内导航系统,我们实现了适用于Android的应用程序并进行了实验。通过结果,我们证明了系统的准确性。

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