Abstract: To meet the requirements of realizing three-dimensional indoor positioning without global positioning system and other wireless networks, an inertial indoor positioning algorithm is proposed. In this algorithm, the three-dimensional acceleration is obtained by combining the accelerometer with the gyroscope. The three-dimensional velocity and position are then calculated by integral. A zero velocity update method is used to improve the positioning accuracy and rate of success. The detection of motionless status between moving steps is judged by combining the magnitude of angular velocity with the magnitude and variance of acceleration. An extended Kalman filter is designed for this method to correct the velocity and the position. The proposed inertial indoor positioning system is realized based on the iOS platform, and its effectiveness is verified.

Key words: iOS platform, inertial, indoor positioning, extended Kalman filter, zero velocity update

摘要： 针对缺少GPS及其他无线定位网络环境下的三维室内定位需求，提出了一种基于惯性测量的室内定位算法。该算法通过加速度计与陀螺仪的配合，获取设备运动的三维加速度，通过积分得到三维速度与位移。为提高定位成功率与准确性，引入了零速度修正方法，结合角速度模值、加速度模值及其方差进行静止状态检测，利用设计的扩展型卡尔曼滤波器对速度和位移进行修正。对使用该算法的惯性室内定位系统在iOS平台上进行了实现及有效性验证。

关键词: iOS平台, 惯性, 室内定位, 扩展型卡尔曼滤波器, 零速度修正