篇名 |
Pedestrian Inertial Navigation with Building Floor Plans for Indoor Environments via Particle Filter
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並列篇名 | Pedestrian Inertial Navigation with Building Floor Plans for Indoor Environments via Particle Filter |
作者 | Yushuai Zhang、Jianxin Guo、Rui Zhu、Zhengyang Zhao、Feng Wang、Liping Wang |
英文摘要 | With the rapid development of smart city, the indoor positioning services became more and more important. During the existing solutions, inertial measurement unit (IMU) with pedestrian dead reckoning (PDR) was a promising scheme since they did not require external equipment in the environment. However, the orientation drift of low-cost IMU limited their application in practical. To address this problem, a zero-velocity update (ZUPT) framework included Kalman filter and particle filter is designed based on the foot-based low-cost IMU and digital floor plan to provide the service of personal navigation. In the designed Smoothing for ZUPT-aided INSs framework, the Kalman filter is used to estimate the position and attitude by zero velocity correction technique. Then, the particle filter is used to improve the localization and heading accuracy by map matching. The position estimation presented in this study achieves an average position error of 1.16 m. The experimental results show that the designed framework can solve the personal navigation problem in the case of building plan information assistance and help improve the accuracy and reliability of continuous position determination of personal navigation systems effectively.
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起訖頁 | 017-033 |
關鍵詞 | pedestrian dead reckoning、zero-velocity update、particle filter、map matching |
刊名 | 電腦學刊 |
期數 | 202206 (33:3期) |
DOI |
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