隨著智慧型行動裝置及導航定位科技的快速發展，導航定位已成為目前日常生活上不可或缺的工具，室外的導航定位可以利用全球導航衛星系統(GlobalNavigation Satellite System, GNSS)導航訊號進行，但是室內定位部分由於訊號遮蔽，導致無法接收GNSS訊號進行導航定位，因此室內定位的各類方式應運而生，如藍芽、無線射頻技術(Radio Frequency IDentification，RFID)、iBeacon等。使用行動裝置之微機電系統(Micro Electro Mechanical Systems，MEMS)獲取陀螺儀與加速度儀資訊，不藉由其他額外之訊號進行室內導航為最經濟之方式，然步長估計與步伐偵測為影響此種導航方式精度好壞之重要因素。因此本研究使用濾波進行加速度數據前處理並透過改良式的Wolf method偵測步伐，步長估計則加入腿長因素進行推求。經由本研究成果顯示使用Savitzky-Golay Filter有助於提升步伐偵測的準確性，且引入腿長做為步長估計參數進行最小二乘複迴歸分析可以提升步長估計約3%。

The widespread adoption of mobile device has improved the accuracy of navigation and location. Since nowadays Global Navigation Satellite System (GNSS) is easier to be installed in the mobile device to locate and navigate in the outdoors. Signals of GNSS are obstructed indoors so navigation and positioning would be a hard task to be executed indoors. Hence, methods of indoor positioning appear as the instruments of Bluetooth, RFID, IBeacon etc. Every method of indoor positioning has its respective cost to affect the selection of indoor positioning technique. In this study, use data of gyroscope and accelerometer from Micro Electro Mechanical Systems (MEMS) and detect footsteps by using filter to smooth the signal, and then estimate the step length by the ordinary least square. Our results show that using the Savitzky-Golay Filter to detect footsteps can improve 3% in the accuracy rate of step detection and apply leg length as parameter in step length estimation can get the closer result with real step length.