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dc.contributor.author許雅倫en_US
dc.contributor.authorHsu, Ya-Lunen_US
dc.contributor.author羅濟群en_US
dc.contributor.author黃興進en_US
dc.contributor.authorLo, Chi-Chunen_US
dc.contributor.authorHwang, Hsin-Ginnen_US
dc.date.accessioned2015-11-26T00:55:49Z-
dc.date.available2015-11-26T00:55:49Z-
dc.date.issued2015en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT070253417en_US
dc.identifier.urihttp://hdl.handle.net/11536/126036-
dc.description.abstract由於建築物的阻礙,微弱的訊號使得全球定位系統(GPS, Global Positioning System)運用在室內定位中並不常見,第三代行動通訊標準所使用的高頻率訊號(>1GHz)會造成室內收訊較差,也不適合用在室內定位。因此,基於 IEEE 802.11 無線區域網路的指紋辨識演算法(Wi-Fi Fingerprinting)的室內定位方法為目前準確度高且較為普及的方式。傳統指紋辨識方法必須事前訓練模型並建立資料庫以供樣式比對,資料庫龐大時比對的時間也就越長,且一旦室內環境改變就必須再花時間重新訓練調整模型。隨著第四代行動通訊標準的出現,採用低頻率訊號的業者將可大幅改善室內死角的問題。本論文結合粒子濾波器(Particle Filter)與3GPP LTE Release 9中提出的兩個方法:觀察到達時間差(OTDOA)及增強型基地臺中心(ECID),提出一個室內定位方法。本文所提出的方法共有三個優點:不需要額外的硬體設備可以節省成本;不需要事先訓練模型可以節省時間;定位誤差相對於現有的定位方式相比提升了23%。zh_TW
dc.description.abstractNowadays, most indoor positioning methods are based on the IEEE 802.11 (Wireless Local Area Network) fingerprinting algorithm. The fingerprinting algorithm has to create a radio map in advance. However, the larger the coverage, the more the training time. Also, retraining is required along with the changing environment. Therefore, this paper proposes a non-training indoor positioning method, which combined particle filter with the OTDOA and ECID recommended in the 3GPP-LTE standard Release 9. The proposed method has the following three merits: no extra cost (hardware) is needed; training is not required; and the accuracy of positioning is up by 23% comparing to existing methods.en_US
dc.language.isoen_USen_US
dc.subject室內定位zh_TW
dc.subject長期技術演進zh_TW
dc.subject觀察到達時間差zh_TW
dc.subject增強型基地臺中心zh_TW
dc.subject粒子濾波器zh_TW
dc.subjectIndoor Positioningen_US
dc.subjectLong-Term Evolutionen_US
dc.subjectObserved Time Difference of Arrivalen_US
dc.subjectEnhanced Cell IDen_US
dc.subjectParticle Filteren_US
dc.title一個不需要事先訓練的4G LTE室內定位方法zh_TW
dc.titleA 4G-LTE-Based Non-training Indoor Positioning Methoden_US
dc.typeThesisen_US
dc.contributor.department資訊管理研究所zh_TW
Appears in Collections:Thesis