全球定位系統(Global Positioning System, GPS)及慣性導航系統(Inertial Navigation System, INS)為常用之室外定位技術，其應用已十分普遍。而亦有相當多地研究致力於發展室內定位系統，然而，由於衛星訊號於室內環境會有遮蔽之現象而無法提供正確之室內定位解。另外，低成本之微機電系統慣性導航元件之定位誤差易隨運作時間而累積。低功耗藍牙(Bluetooth Low Energy, BLE) 為新規格之藍牙技術，其主要特點有: 耗電量極低、運作時間長、低成本且現今之智慧型手機大多搭載其規格之藍牙晶片。因此，本研究採用其技術來發展室內定位系統。此外，指紋比對法(fingerprinting)為常用於室內定位且為精度較高之定位演算法。指紋比對法之運作方式分為兩個階段，第一為建立空間之訊號強度分布圖(radio map)；第二為將使用者收到之訊號強度與訊號強度分布圖進行比對而獲取使用者之座標資訊。該演算法之最大缺點為製作強度分布圖十分耗時，且需定期維護方能維持其定位精度。
本研究欲採用即時動態定位系統(e-GPS)之主站概念來補足其缺點，主站於本研究中為可在定點連續接收低功耗藍牙訊號之接收儀，其可用來自動且週期性地產生訊號強度分布圖。此外，此系統使用卡曼濾波器產生全域之訊號強度改正量，用以縮小訊號強度分布圖與使用者所處環境之差異。本研究額外亦考量低功耗藍牙發射器與手機天線之相對方位對訊號強度造成之影響，其影響即納入該定位系統之計算。本研究之定位系統誤差量於0.9至1.6公尺之間，相較於原始訊號強度之定位成果，該系統至多可降低63%之定位誤差。因此，本研究所提出之定位系統使用低成本之低功耗藍牙裝置即可提供穩定且良好之室內定位成果，且不須耗時地維護及建立訊號強度分布圖。

In recent years, Global Positioning System (GPS) and Inertial Navigation System (INS) are the common positioning techniques for outdoor applications. Therefore, many　researches are committed themselves to the development of indoor positioning applications. However, GPS signals are blocked easily and fail to provide the correct position within indoor environments. On the other hand, the errors of low-cost Micro Electro Mechanical Systems (MEMS) IMU are accumulated over time. Bluetooth Low Energy (BLE) is the latest technology of Bluetooth. Its advantages contain ultra-low-power consumption, working for a long time, low cost and implementing in the smartphones with Bluetooth 4.0 chip. Hence, this research aims at constructing an indoor positioning system with BLE. The fingerprinting is the general positioning methodology used in wireless communication technologies. It consists of two main phases: offline phase and online phase. Offline phase is to construct radio maps representing the distribution of received signal strength indication (RSSI) in a certain space in advance. Then, the position of a smartphone user is estimated by matching the RSSI in radio maps in offline phase. Although the accuracy by this method is better than other positioning algorithms such as trilateration, its main shortcoming is extremely time-consuming. Moreover, the radio maps are not able to meet the situation during experiment because the signal power is attenuated by many environmental factors.
Thus, this research aims at developing an indoor positioning system, which combining the concept of main stations in e-GPS. The radio maps are automatically established and updated in period by main stations fixed in the indoor space. Additionally, the global RSSI correction model is constructed by Kalman filter (KF) using the RSSI from main stations for complementing the environmental difference between radio maps and the circumstance where users are tending to do positioning. In another hand, the errors caused by the relative orientation between a beacon and the antenna on the smartphone are considered in the proposed system. The RMSE of the proposed system is within 0.9 to 1.6 meters. The positioning errors can be reduced up to 63%. Consequently, the proposed system is able to provide stable and good positioning accuracy with low-cost beacons and receivers. Especially, it does not consume many efforts to construct and maintain radio maps.

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