Full metadata record
DC FieldValueLanguage
dc.contributor.author林宗慶en_US
dc.contributor.authorLin, Tsung-Chingen_US
dc.contributor.author曾煜棋en_US
dc.contributor.authorTseng, Yu Cheeen_US
dc.date.accessioned2014-12-12T01:52:32Z-
dc.date.available2014-12-12T01:52:32Z-
dc.date.issued2010en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT079856510en_US
dc.identifier.urihttp://hdl.handle.net/11536/48387-
dc.description.abstract近年來位置感知服務已在手持裝置的軟體市場上越來越流行。然而,觀察現存的定位研究(例如: AoA, ToA, TDoA, GPS, RF相關定位方法),我們發現大部分的研究方法都需要仰賴環境中的無線訊號作為手持裝置的定位依據。 這樣的限制使得手持裝置在無法取得無線訊號的環境中難以使用位置感知服務。舉例來說,我們都知道GPS在室內極容易產生較大的定位誤差,甚至在衛星訊號被建築物完全阻隔時更無法取得定位結果。因此,在這篇論文中我們提出一個"自我感知(self-contented)"的定位方法。這種方法不需要仰賴環境中的無線訊號作為定位的參考或依據,取而代之的是使用智慧手機上的慣性元件(Inertial measurement unit)來取得 環境中標的物和使用者之間的視差角並用以定位。我們提出一個名為"inertial sensor-assisted localization(ISAL)"的概念,此概念是利用擴增實境的人機介面將環境中的標的物攝入其中,並透過影像處理的方法自動辨識或請使用者協助辨識環境中的標的物。在辨識標的物的同時我們利用手機上的磁力計來取得標的物和使用者之間的方位關係以及視差角資訊。接著,我們設計一個角度的定位演算法利用至少三個以上經過"辨識"的標的物資訊來計算出使用者的位置。最後,我們實作出這樣的一個系統概念並設計數種測試案例,包含在室內環境的測試以及室外環境測試,用以量測這個定位方法的效果。zh_TW
dc.description.abstractLocation tracking has become a popular application for mobile computing.While surveying existing localization approaches (e.g., AoA, ToA, TDoA,GPS, RF-based solutions), we observed that most of them rely on different auxiliary signals at certain distances to assist a device in self localization. This constrains the availability of location-based services (LBSs) when mobile devices can not receivethese auxiliary signals. For example, a well-known limitation of GPS is its function in an indoor environment. A``self-contented'' device can determine its own location without relying on an auxiliary signal. In this paper, we show this to be feasible by using IMU and visual sensors in a smart phone. A concept called {\em inertial sensor-assisted localization}(ISAL) is proposed. As an example, through augmented reality techniques, objects captured by the camera of a smart phone can be ``taged'' either manually or automatically by image process technique.At the same time, angles of these tagged objects are measured by the e-compassof the smart phone. We then proposed an angulation algorithm, which can measure the location of the phone given at least three tagging objects. We demonstrate several use cases of this technique and present several indoor and outdoor testing results to verify the proposed technique.en_US
dc.language.isozh_TWen_US
dc.subject實境擴增zh_TW
dc.subject移動計算zh_TW
dc.subject定位zh_TW
dc.subject位置感知服務zh_TW
dc.subject感知網路zh_TW
dc.subjectaugmented realityen_US
dc.subjectpervasive computingen_US
dc.subjectlocalizationen_US
dc.subjectlocation-based serviceen_US
dc.subjectsensor networken_US
dc.title一個不依靠外界無線訊號的定位方法zh_TW
dc.titleSelf-Contented Localization without Using Auxiliary Signalsen_US
dc.typeThesisen_US
dc.contributor.department網路工程研究所zh_TW
Appears in Collections:Thesis