基于手机内置MEMS传感器的行人步数检测方法  

Pedestrian step detection method based on mobile phone built-in MEMS sensor

作　　者：赵桂玲[1] 王续 梁伟东 ZHAO Guiling;WANG Xu;LIANG Weidong(School of Geomatics,Liaoning Technical University,Fuxin 123000,China)

机构地区：[1]辽宁工程技术大学测绘与地理科学学院,辽宁阜新123000

出　　处：《传感器与微系统》2024年第7期128-131,共4页Transducer and Microsystem Technologies

基　　金：辽宁省自然科学基金资助项目(2020—MS—303);辽宁省教育厅一般项目(LJ2020JCL015);地理信息工程国家重点实验室、自然资源部测绘科学与地球空间信息技术重点实验室联合基金资助项目(2022—01—11)。

摘　　要：手机内置微机电系统(MEMS)传感器具有零偏不稳定性和误差发散快等缺点。为了提高行人步数检测的准确性,基于图形用户界面(GUI),建立零偏校正、低通滤波和卡尔曼(Kalman)滤波3种误差处理模型。采用峰值域和时间域共同约束峰值的双特征检测方法,设计平稳前进和摆臂前进两种动态实验场景,检测行人步数。实验结果表明:在不同动态场景下,双特征检测行人步数的准确率均在95%以上,验证了所提算法的准确性和鲁棒性,满足行人步数检测的要求。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.

关 键 词：微机电系统 图形用户界面 零偏校正 低通滤波 卡尔曼滤波 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]