多运动模式下的累积误差修正行人航位推算算法  

Pedestrian Dead Reckoning Algorithm with Cumulative Error Correction in Multi-Motion Mode

作　　者：施元昊 张健铭 徐正蓺[2] 滕国伟[1] SHI Yuanhao;ZHANG Jianming;XU Zhengyi;TENG Guowei(School of Communication and Information Engineering,Shanghai University,Shanghai 200444,China;Shanghai Advanced Research Institute,Chinese Academy of Sciences,Shanghai 201210,China;School of Electronics Electrical and Communication Engineering,University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]上海大学通信与信息工程学院,上海200444 [2]中国科学院上海高等研究院,上海201210 [3]中国科学院大学电子电器与通信工程学院,北京100049

出　　处：《计算机工程》2020年第12期305-312,共8页Computer Engineering

基　　金：上海市科技创新行动计划(19DZ1202200);上海市青年科技英才扬帆计划(18YF1425600)。

摘　　要：多运动模式行人航位推算算法采用零速校正消除累计误差,但零速校正错判会导致误差。针对该问题,提出一种基于长短时记忆网络的自适应零速检测算法。构建长短时记忆网络提取不同运动模式下零速区间的三轴加速度、三轴角速度和时序特征,通过优化零速检测算法实现多运动模式下的自适应零速检测,在此基础上采用差分进化算法融合蓝牙等定位方式对累积误差进行数据修正。实验结果表明,与传统卡尔曼滤波算法相比,本文算法定位绝对误差由6.43 m减少到0.94 m,相对误差由1.246%降至0.182%。Zero velocity correction is used to eliminate the cumulative error inthe multi-mode Pedestrian Dead Reckoning(PDR)algorithm.To solve the problem,this paper proposes an adaptive zero velocity detection algorithm based on Long Short-Term Memory(LSTM)network.An LSTM network is constructed to extract the triaxial acceleration,triaxial angular velocity and time sequence characteristics of zero velocity interval under different motion modes.The adaptive zero velocity detection is realized by optimizing the zero velocity detection algorithm.On this basis,the Differential Evolution(DE)Algorithm is used to fuse positioning methods such as Bluetooth to correct the accumulated errors.Experimental results show that compared with the traditional Kalman filter algorithm,the proposed algorithm reduces the absolute positioning error from 6.43 m to 0.94 m,and the relative error from 1.246%to 0.182%.

关 键 词：行人航位推算 长短时记忆网络 零速检测 自适应算法 差分进化算法 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置]