Ultrasound Ranging for Pedestrian Dead Reckoning Systems

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题名:	Ultrasound Ranging for Pedestrian Dead Reckoning Systems
作者:	黃以寧;Huang,Yie-ning
贡献者:	資訊工程學系
关键词:	室內定位;超音波測距;卡爾漫濾波器;indoor localization;ultrasound ranging;kalman filter;dead reckoning
日期:	2014-08-20
上传时间:	2014-10-15 17:10:02 (UTC+8)
出版者:	國立中央大學
摘要:	近年來，室內定位已成為一個熱門話題。大部分的室內定位的方法需要另外架設基礎設施或額外的訓練來實踐。雖然傳統的行人航位推算系統（PDR）不需要額外的花費及訓練就可以實作在行動裝置上，但它會在短時間內迅速積累誤差，使得結果不被接受。為了解決這個問題，我們提出了基於超音波的合作式行人航位推算系統（UCPDR）。UCPDR的主要思想是結合超音波測距和附近的行人的位置信息，並使用機會式卡爾曼濾波器來改善PDR的準確性。為了評估UCPDR的可行性，我們在iOS平台上實作UCPDR系統，而實驗結果表明，UCPDR能夠透過鄰居的位置信息將誤差限制在4公尺內，也證明UCPDR系統的定位精准度優於PDR系統;Indoor localization has become a popular issue in recent years. Most of the indoor localization approaches either require the availability of an infrastructure or the additional training efforts. While traditional pedestrian dead reckoning (PDR) system can be implemented on mobile devices without additional cost and training, it accumulates errors quickly and leads to unacceptable results after a short period of time. To address this issue, we propose the ultrasound-based collaborative pedestrian dead reckoning system (UCPDR). The main idea of UCPDR is to exploit nearby pedestrians′ location information by ultrasound ranging and apply the opportunistic Kalman filter to improve the accuracy of PDR. To evaluate feasibility of UCPDR, a prototype is built on the iOS platform. The conducted experiment results shows that UCPDR is able to limit the localization error within 4m after a long period of time through the help of neighbors′ location information. Our UCPDR prototype always achieves a better localization accuracy than the traditional PDR system.
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