基于角度的HDE算法在室内行人航迹定位中的研究

发布时间：2018-01-14 14:14

本文关键词：基于角度的HDE算法在室内行人航迹定位中的研究　出处：《传感技术学报》2015年04期 　论文类型：期刊论文

【摘要】：针对现有启发式偏移消除算法HDE(Heuristic Drift Elimination)中航向角推算不准确、反馈系数鲁棒性较差的问题,提出了对经过扩展卡尔曼滤波的航向角进行启发式漂移消除的算法AHDE(Angle Heuristic Drift Elimination)。首先利用扩展卡尔曼滤波EKF(Extended Kalman Filter)融合陀螺仪、加速度信息,通过四元数的更新来估计航向角,再用启发式漂移消除算法对航向角进行修正,最后结合步数及步长信息推算出行人的行走轨迹。实验结果显示,在行走方向较为固定的典型室内环境中,行走距离在250 m时,该算法平均误差不超过2 m,而HDE算法误差会达到4 m左右。并且该系统具有比对陀螺仪数据进行启发式漂移消除系统更强的鲁棒性。当以100 Hz频率读取数据时,AHDE算法反馈系数的选择范围由HDE算法的[0.001,0.028]扩展为[0.005,0.23],几乎扩大了一个数量级。
[Abstract]:To eliminate the existing heuristic migration algorithm (Heuristic Drift Elimination) HDE aircraft to angle calculation is not accurate, the feedback coefficient of poor robustness problems, put forward by the extended Calman filter to eliminate the drift angle heuristic algorithm AHDE (Angle Heuristic Drift Elimination). First, using the extended Calman filter EKF (Extended Kalman Filter) fusion gyroscope the acceleration information, by four yuan, the number of updates to estimate the heading angle, using heuristic algorithm to eliminate drift of heading angle was corrected according to the number of steps and step information calculate the pedestrian walking trajectory. Experimental results show that the typical indoor environment in the direction of travel is fixed, the walking distance in 250 m, the algorithm the average error is less than 2 m, and the error HDE algorithm will reach about 4 m. And the system has data alignment gyro drift heuristic The robustness of the system is eliminated. When the data is read at 100 Hz frequency, the selection range of the AHDE algorithm's feedback coefficient is expanded from the [0.001,0.028] of the HDE algorithm to [0.005,0.23], which has expanded by an order of magnitude.

【作者单位】：中国计量学院信息工程学院;中国电信股份有限公司浙江分公司;
【分类号】：TN966
【正文快照】： 在现代生活中,人们对定位与导航的信息需求日益膨胀,在GPS等卫星定位技术不能使用的室内环境中,基于惯性测试单元IMU(Inertial Measure U-nit)的室内导航技术应用越来越广泛。Levi和Judd在1996年首次提出了行人航迹推算PDR(Pedestrian Dead Reckoning)的概念[1],主要是根据陀

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