摘要
针对行人室内定位精度不高的问题,提出的算法包括步频估计、步长估计和航向估计。改进的航向估计算法基于四元数姿态解算并利用扩展卡尔曼滤波(EKF)修正航向角的偏差。基于提出的定位算法,构建了以惯性测量单元为核心的实验平台,结果表明:算法具有可行性,定位的置信度达到98.28%,满足实际需求。
Aiming at problem of low indoor positioning precision of pedestrian,propose a new algorithm for pedestrian heading-estimation based on improved heading estimation. The algorithm includes the stride frequency estimation,the step length and heading estimation. The improved heading estimation algorithm is based on the quaternion attitude calculation and uses the extended Kalman filtering（EKF） to correct deviation of the heading angle. Based on the proposed algorithm,the experimental platform using inertial measurement unit as core is built.The results show that the proposed algorithm is feasible,and the confidence of positioning is 98. 28 %,which meets actual demand.
出处
《传感器与微系统》
CSCD
2018年第1期29-31,34,共4页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(51405198)
中央高校专项自主科研项目(JUSRP11464)
江苏省2016年度普通高校研究生实践创新计划项目(SJZZ16_0219)
关键词
行人航迹推算
航向估计
惯性测量单元
扩展卡尔曼滤波
pedestrian dead reckoning
heading estimation
inertial measurement unit （IMU）
extended Kalmanfiltering（EKF）
