基于惯性导航的室内定位误差修正算法

针对惯性导航系统(INS)在室内定位过程中,位移误差随时间不断积累而导致定位精度不高的问题,通过分析人行走的特征,以及行走过程中零速点的特性,提出了基于惯性导航的室内定位误差修正算法。使用最大似然估计法对加速度计和陀螺仪的输出参数进行判断,确定零速点,然后通过扩展卡尔曼滤波(EKF)算法,分别建立定位系统的状态方程和观测方程对误差进行修正。利用Matlab搭建仿真平台,对算法进行了仿真。仿真实验结果表明:改进后的零速检测算法,提高了零速点检测准确率,使位移误差得到了有效抑制,并将定位误差控制在了3%以内。改进算法对室内定位误差修正具有一定的实用价值。

Indoor positioning error correction algorithm based on inertial navigation

Aiming at the problem that the displacement error of the INS is accumulated over time, which leads to lower positioning accuracy in the process of indoor positioning, an indoor positioning error correction algorithm based on inertial navigation is introduced by analyzing the characteristics of people and zero speed during walking. The algorithm determines the zero velocity point by judging the output of the accelerometer and the gyroscope through the maximum likelihood estimation algorithm, and then performs the error correction by using the extended Kalman filter algorithm to establish the state equation and observation equation. Simulation platform is set up by using Matlab for the algorithm simulation. The results show that the improved zero speed detection algorithm improves the accuracy rate of zero speed detection, makes displacement error to be suppressed effectively, and controls the location error within 3%. The improved algorithm has some practical value for indoor positioning error correction.