Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the Pocket.
Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the Pocket.
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使用口袋中的智能手机进行室内行人导航的航向估计
DOI：
10.3390/s150921518
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发表时间：
2015-08-28
期刊：
影响因子：
--
通讯作者：
Wu D
中科院分区：
文献类型：
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作者：
Deng ZA;Wang G;Hu Y;Wu D
航向估计是使用普遍可用的智能手机的室内行人导航的中心问题。对于放置在口袋中的智能手机，最流行的设备位置之一，航向估计的基本挑战是不断变化的设备坐标系和严重的室内磁扰动。为了解决这些问题，我们提出了一种新的航向估计方法的基础上旋转矩阵和主成分分析（PCA）。首先，通过一个相关的旋转矩阵，将加速度信号投影到一个参考坐标系（RCS）中，得到了加速度信号水平面的更精确估计。然后，我们利用PCA的加速度信号的水平面上的局部行走方向提取。最后，为了将局部行走方向转化为全局方向，我们开发了一个校准过程，而不需要嘈杂的指南针读数。此外，提出了一种转弯检测算法，以提高航向估计精度。实验结果表明，我们的方法优于传统的uDirect和PCA为基础的方法在准确性和可行性。
Heading estimation is a central problem for indoor pedestrian navigation using the pervasively available smartphone. For smartphones placed in a pocket, one of the most popular device positions, the essential challenges in heading estimation are the changing device coordinate system and the severe indoor magnetic perturbations. To address these challenges, we propose a novel heading estimation approach based on a rotation matrix and principal component analysis (PCA). Firstly, through a related rotation matrix, we project the acceleration signals into a reference coordinate system (RCS), where a more accurate estimation of the horizontal plane of the acceleration signal is obtained. Then, we utilize PCA over the horizontal plane of acceleration signals for local walking direction extraction. Finally, in order to translate the local walking direction into the global one, we develop a calibration process without requiring noisy compass readings. Besides, a turn detection algorithm is proposed to improve the heading estimation accuracy. Experimental results show that our approach outperforms the traditional uDirect and PCA-based approaches in terms of accuracy and feasibility.