Pedestrian step detection method based on mobile phone built-in MEMS sensor
Mobile phone built-in MEMS sensor has the disadvantages of instable zero-bias and fast error divergence. In order to improve the accuracy of pedestrian step detection,three error processing model:Zero-bias correction,low-pass filtering and Kalman filtering are established based on graphical user interface(GUI). Double-features detection method using peak domain and time domain to constrain peak value is adopted. Then,two dynamic experimental scenes of steady and swing-arm progresses are designd to detect pedestrian's steps. The experimental results show that detection accuracy of pedestrian 's steps detected by double-features detection method is above 95％ in different dynamic scenes and the accuracy and robustness of the proposed algorithm are verified,satisfy the requirements of pedestrian's step detection.
MEMSgraphical user interface(GUI)zero-bias correctionlow-pass filteringKalman filtering
万方数据
维普
