近年來，行人導航系統逐漸發展，而大多的感測器多放置在腰部或腳上，以建立模型來測量運動的物理量，計算出行走的路徑距離。而本論文提出將感測器放在手腕上，進行分析與模型規畫。許多導航公司推出多款運動手錶，其使用GPS訊號告知跑者許多跑步相關資訊，但GPS訊號於城市或隧道應用中受限於衛星訊號品質，且無法保證訊號之連續完整性。為了有效達成精度與不受環境的影響，本論文將加速儀與GPS做整合在手錶上，包含位置鎖住、擴展式卡爾曼濾波器整合與適應性校正之參數更新等處理流程。適當的校正演算法與訊號處理可以有效降低模型與GPS估測誤差，且能在無GPS環境下進行模型估測，亦可保證推估的距離之有效性與可靠性。

Recently, the pedestrian navigation system(PNS) was developed gradually and most sensors of PNS were put around the waist or foot to establish a model to figure out the path and distance. In this study, the researcher put the sensor around the wrist to do the analysis. Many companies developed sport watches with global positioning system(GPS) to provide consumers with their running information. However, the GPS signals in urban or tunnel are often influenced by the environments. To overcome this limitation, this study installed the sensor in wrist watches and combined accelerator measurements with GPS in position calculations. The process includes position locking, extended Kalman Filter and adaptive parameter adjustment. The researcher found that the appropriate parameter adjustment and signal processing algorithms can effectively reduce the positioning, allowed the method to do the estimation without GPS signal, and prove the validity and reliability of data.

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