| 摘要: | 伴隨著無線通訊科技的迅速發展，內建無線區域網路(Wireless LAN, WLAN) 功能的終端裝置以及無線接取點(Access Point, AP)裝置架設的普及化，Wireless LAN的技術已廣泛的應用在商務區、學校、機場及其它公共區域，使得以定位為基礎的服務(Location-Based Service, LBS) 在商業、公眾安全的應用也博得青睞。室內定位技術之相關應用如：醫療照顧、工廠人員追蹤、緊急救難系統助以及商場動線導引等，被廣泛的提出並於以討論。目前一般所使用的定位技術包含兩種：一種是幾何三角定位法(Geometrical Triangulation)，另一種則為區域特徵指紋辨識法(Location Fingerprinting)；在室內的環境中，區域特徵指紋辨識法有較優於幾何三角定位法，原因在於室內的環境太過於複雜導致無法收集到足夠的資訊量來描述目標物所傳送過來的訊號強度。不論是戶外或室內的定位技術，其最大爭議便是定位的精確度，目前已經有許多文獻報告提供可利用或已應用之定位演算法。然而此類系統應用於室內環境定位會受限於AP的佈建數量不足，或因定位環境的遮蔽造成電磁波訊號的多重反射與折射現象產生不精確的定位結果。所以，為了提供相關之定位與追蹤應用服務，必須設計適當且有效的演算法精確預估行動裝置的室內位置。然而，在一個空間內佈建多個AP，以達到精準的定位結果，這樣的佈建是不合理的，而使用多個AP的原因是為了增加足夠的資訊量來描述目標物所傳送過來的訊號強度。本論文以一個新穎的室內定位解決方式，提供高精準度的位置評估。本論文提出智慧天線系統定位技術，藉由一個擁有智慧型天線系統的AP產生出多筆足夠描述目標物所傳送過來的訊號強度資訊量，以達到僅使用一個AP擁有高精準度的位置評估。實驗結果顯示出，藉由智慧天線系統收集訊號強度資訊量的定位技術確實產生高精準度的表現。此技術不僅實現高精度定位，並且提供了一個低成本的室內定位AP建置。計算結果說明，本論文提出的智慧天線系統定位技術讓精準度由1.34％提升到92.4％，而與傳統的區域特徵指紋辨識法相比本論文提出的系統將標準差減少96％。During the last few years, Wireless LAN (WLAN) has been rapidly growing and becoming more and more popular. In particular, the techniques of indoor location estimation are receiving a lot of attentions due to wide variety of service such as building the medical health care, tracking people for security issue, sustaining emergency supplement system, providing directional guidance, and so on. With the matured indoor location technology, the new demand on wireless applications is location-based service (LBS). It is toward the usage for the business, public securities and safety requirements. Therefore, increasing the accuracy of positioning is a significant issue for indoor location technologies.In indoor environments, the shadowing of positioning environment, the multi-path and reflection phenomenon make the position estimation inaccurate. In traditional location fingerprint method shows that more Access Point (AP) deployments can obtain enough Receive Signal Strength (RSS) information to describe signal characteristics of the target space. However, it does not make sense and increase waste costs. On the other hand, insufficient AP deployments would significantly downgrade the accuracy of position estimation, because RSS information which is measured for the target object could be not enough.This thesis provides a novel indoor positioning solution to increase the accuracy of location estimation by gathering abundant RSS from the AP which has multi-antennas architecture. Since the AP equipped multi-antennas, the AP gathers RSS from all of antenna sets periodically. This system obtains enough RSS to compute the user position.Experimental results show that the proposed indoor location estimation demonstrates a high accuracy of positioning and outstanding performance while RSS is collected by smart antenna technique. Our proposed method not only achieves the high-precision positioning but also provides a rational deployments of cost in indoor location environments. The numerical results show that the accuracy is increased from 1.34% to 92.4% and the error variance is reduced by 96% as compared to the traditional location fingerprint method. |
