基于实时步长匹配的行人室内定位方法

摘要

针对室内定位研究中行人航位推算(PDR)算法的传统步长模型无法充分反映个体差异性的问题,提出一种以卫星测距为基础,建立个体步长特征数据库代替步长模型的方法.在室外将卫星测距应用到步长测算中,建立不同速度特征与步长的对应关系.在室内,改进了K-最近邻(KNN)算法,对跨步进行实时步长匹配,结合方向信息计算出行人的当前位置.实验结果表明,室内定位最大误差距离可以控制在4%以内,平均绝对误差距离可以控制在2%以内,定位精度较传统步长模型有较大提高.%Focus on the problem of the traditional step-size model used in pedestrian dead reckoning algorithm cannot fully reflect individual differences in the research of indoor positioning. We propose a method to establish database of individual feature of step-size based on satellite ranging and then replace the step-size model. Satellite ranging is applied to calculate the step-size in the outdoor, the corresponding relationship between different speed features and step-size is set up. Then we carry out real-time step-size matching indoors for the step, using improved K-nearest-neighbor(KNN) algorithm and calculate people's current position combined with direction information. The actual test results show that the maximum error distance can be controlled within 4%, and the mean absolute error distance can be controlled within 2%. The positional accuracy has a larger enhancement compared to the traditional step-size model.