基于序列检测的行人导航航向误差修正算法研究
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摘要
针对行人自主定位MEMS惯性器件存在随时间累积的漂移误差导致航向发散的问题,提出一种有步态约束(转弯0°,90°或180°)的序列检测方法。通过训练行人不同的步行行为数据得到步态序列模板,根据所匹配模板下的航向约束实时地修正航向漂移误差。为了验证算法的有效性,在室内结构规则化的走廊进行多次行走实验,行走路程为500 m,实验结果表明,所提方法可以有效地抑制行人导航航向发散的现象,定位误差约为总路程的0.7%。
Since the MEMS inertial device for pedestrian autonomous positioning has drift error caused by the accumulation of time,which would lead to heading divergence,a sequence detection method with gait constraints(turning angle is 0°,90° or180°) is proposed. The gait sequence template is obtained by training the different walking behavior data of pedestrians.According to the heading constraints of matched templates,the heading drift error is corrected in real time. The 500 m walking experiments are carried out in the corridor with indoor structure regularization to verify the effectiveness of the algorithm. The experimental results show that the proposed method can effectively suppress the heading divergence of pedestrian navigation,and the positioning error is about 0.7% of the total distance.
Since the MEMS inertial device for pedestrian autonomous positioning has drift error caused by the accumulation of time,which would lead to heading divergence,a sequence detection method with gait constraints(turning angle is 0°,90° or180°) is proposed. The gait sequence template is obtained by training the different walking behavior data of pedestrians.According to the heading constraints of matched templates,the heading drift error is corrected in real time. The 500 m walking experiments are carried out in the corridor with indoor structure regularization to verify the effectiveness of the algorithm. The experimental results show that the proposed method can effectively suppress the heading divergence of pedestrian navigation,and the positioning error is about 0.7% of the total distance.
引文
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[2] JIMéNEZ A R,SECO F,PRIETO J C,et al. Indoor pedestrian navigation using an INS/EKF framework for yaw drift reduction and a foot-mounted IMU[C]//2010 IEEE the 7th Workshop on Positioning Navigation and Communication. Dresden:IEEE,2010:135-143.
[3] BORENSTEIN J,OJEDA L,KWANMUANG S. Heuristic reduction of gyro drift in IMU-based personnel tracking systems[J]. Journal of navigation,2009,62(1):41-58.
[4]楼喜中,周乐宇,叶敏展,等.基于角度的HDE算法在室内行人航迹定位中的研究[J].传感技术学报,2015,15(4):598-602.LOU Xizhong,ZHOU Leyu,YE Minzhan,et al. Research on indoor pedestrian track location using angle-based HDE algorithm[J]. Chinese journal of sensors and actuators,2015,15(4):598-602.
[5] JIMENEZ A R,SECO F,ZAMPELLA F,et al. Improved heuristic drift elimination(iHDE)for pedestrian navigation in complex buildings[C]//2011 IEEE International Conference on Indoor Positioning and Indoor Navigation. Guimaraes,Portugal:IEEE,2011:1-8.
[6] JIMENEZ A R,SECO F,ZAMPELLA F,et al. Improved heuristic drift elimination with magnetically-aided dominant directions(MiHDE)for pedestrian navigation in complex buildings[J]. Journal of location based services,2012(6):186-210.
[7]李超,苏中,朱嘉林,等.可穿戴式自主定位技术的零速触发算法研究[J].传感技术学报,2014,27(5):627-632.LI Chao,SU Zhong,ZHU Jialin,et al. Zero-speed triggering algorithm for wearable autonomous positioning technology[J].Chinese journal of sensors and actuators,2014,27(5):627-632.
[8] JU H J,LEE M S,PARK C G,et al. Advanced heuristic drift elimination for indoor pedestrian navigation[C]//2014 IEEE International Conference on Indoor Positioning and Indoor Navigation. Busan:IEEE,2014:729-732.
[9] LI Y,SONG Q,MA M,et al. Near real time heading drift correction for indoor pedestrian tracking based on sequence detection[C]//2016 IEEE International Conference on Indoor Positioning and Indoor Navigation. Alcala de Henares:IEEE,2016:1-4.
[10] ZHANG X,RONG Z,GUO M F,et al. Yaw error self-observation algorithm for pedestrian navigation via foot-mounted inertial navigation system[J]. Journal of Chinese inertial technology,2015,23(4):457-466.