面向室内定位的改进行人航位推算方法

An Improved Pedestrian Dead Reckoning Algorithm for Indoor Positioning

摘要:

为提高室内定位精度,本文对行人航位推算的步数检测、步长估计及航向估计进行了改进研究;首先,将自相关分析法和自适应波峰检测法相结合提出了一种新检测算法；其次,基于Scarlett模型提出了融合前一步步长的改进步长估算模型；再次,基于方向传感器算法,通过设定主导航向并结合卡尔曼滤波,来减少直线行走航向估计误差;最后,通过实验验证改进方法提高了步数检测准确率和步长检测精度,减少了航向角误差,取得了较好的室内定位效果。

Abstract:

In order to improve the accuracy of indoor positioning, the step detection, stride length estimation and heading estimation of pedestrian dead reckoning are improved. Firstly, by combining the self-correlation analysis algorithm and the adaptive peak detection method, a new detection algorithm is proposed. Secondly, based on Scarlett model, a new stride length measurement model is proposed that takes the stride length of the previous step into consideration. Thirdly, based on the algorithm of the orientation, the main navigation direction is set, and the Kalman filter is used for reduce the heading estimation error of walking in a straight line. Finally, the experiments verified that the improved method improves the accuracy of step detection and stride length estimation and reduces the heading angle error and achieves the better result in the indoor positioning.