本論文旨在開發一以慣性感測器為基礎之可攜式行人導航系統與其軌跡估測演算法，其主要目的在於精準地獲得行人於室內行走之軌跡。使用者配戴此系統可以在室內環境以正常速度行走進行行人導航。首先，我們整合加速度計、陀螺儀、磁力計、微控制器與藍芽無線傳輸模組形成一可攜式行人導航系統。接著，我們開發了一即時行人軌跡估測演算法，其演算法是基於握持在手上之可攜式行人導航系統所開發用來即時估測行人行走軌跡之演算法。為了降低慣性感測器的誤差累積，我們開發了一融合加速度計、陀螺儀與磁力計感測訊號之擴展式卡爾曼濾波器演算法，來加以降低慣性感測器訊號本身內部所產生的誤差。最後，由實驗結果成功地驗證此可攜式行人導航系統與其行人導航演算法之有效性。

This thesis presents a wearable pedestrian navigation system and its associated pedestrian navigation algorithm to estimate pedestrian walking trajectories in indoor environment. Users can carry the system to walk in indoor environment at normal speed without any external positioning techniques. First, we integrate a triaxial accelerometer, a triaxial gyroscope, a triaxial magnetometer, a microcontroller, and a Bluetooth wireless transmission module into the wearable pedestrian navigation system. The real-time pedestrian trajectory estimation algorithm based on the hand-held wearable pedestrian navigation system is developed for estimating the pedestrian walking trajectory in real-time. In order to minimize the cumulative error of the inertial sensors, we have utilized a sensor fusion technique based on the extended Kalman filter (EKF) to fuse the accelerations, angular velocities, and magnetic signals. Finally, the experimental results have successfully validated the effectiveness of the proposed wearable pedestrian navigation system and its associated pedestrian navigation algorithm.

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