Pedestrian Navigation Method Based on UWB and SINS

doi:10.16182/j.issn1004731x.joss.19-FZ0386

Abstract

Abstract: In view of the problem that the inertial navigation error is accumulating with time and UWB indoor is hard to continue tracking problems in complex environment, an extended Kalman filter (EKF) fusing UWB and sins pedestrian navigation is proposed.The zero speed correction algorithm is used to trigger EKF at zero speed. The sins is corrected by the velocity error measurement provided by sins and the position error measurement provided by UWB restraining error accumulation.When UWB signal is interrupted, the position of UWB output without interruption is taken as the starting position. The experiment results of SINS autonomous navigation show that UWB+SINS method complements the advantages and disadvantages of the two methods, restrains the accumulation of errors and ensures the continuity of navigation, improves the accuracy of pedestrian navigation, and the navigation error is 0.50%.

Key words: pedestrian navigation, strapdown inertial navigation, UWB, extended kalman filtering, data fusion

CLC Number:

TP391.9

Yang Yang, Li Qing. Pedestrian Navigation Method Based on UWB and SINS[J]. Journal of System Simulation, 2019, 31(12): 2636-2642.

References

[1] Foxlin E.Pedestrian Tracking with Shoe-Mounted Inertial Sensors[J]. IEEE Computer Graphics and Applications (S0272-1716), 2005, 25(6): 38-46.
[2] Benini A, Mancini A, Longhi S.An IMU/UWB/Vision-based Extended Kalman Filter for Mini-UAV Localization in Indoor Environment using 802.15.4a Wireless Sensor Network[J]. Journal of Intelligent & Robotic Systems (S0921-0296), 2013, 70(1/4): 461-476.
[3] 郁嘉宇, 赵忠, 李凡, 等. 基于MEMS/UWB组合的室内定位方法[J]. 导航定位与授时, 2018, 5(6): 77-85.
Yu Jiayu, Zhao Zhong, Li Fan, et al.Indoor positioning method based on MEMS/UWB combination[J]. Navigation Positioning and Timing, 2018, 5(6): 77-85.
[4] 曾庆化, 王敬贤, 孟骞, 等. 基于UWB优化配置的室内行人导航方法[J]. 中国惯性技术学报, 2017, 25(2): 186-191.
Zeng Qinghua, Wang Jingxian, Meng Qian, et al.Indoor pedestrian navigation method based on optimal allocation of UWB[J]. Chinese Journal of Inertial Technology, 2017, 25(2): 186-191.
[5] 孙璧文, 樊启高, 武亚恒, 等. 基于PDR/UWB紧耦合的足绑式行人导航技术[J]. 传感器与微系统, 2017, 36(3): 43-47, 50.
Sun Biwen, Fan Qigao, Wu Yaheng, et al.Foot-mounted pedestrian navigation technology based on tightly coupled PDR/UWB[J]. Sensors and Microsystems, 2017, 36(3): 43-47, 50.
[6] Chen Pengzhan, Kuang Ye, Chen Xiaoyue.UWB/ Improved PDR Integration Algorithm Applied to Dynamic Indoor Positioning for Pedestrians[J]. Sensors (S1424-8220), 2017, 17(9): 2065-2065.
[7] 苏中, 李擎, 李旷振, 等. 惯性技术[M]. 北京: 国防工业出版社, 2011.
Su Zhong, Li Qing, Li Kuangzhen, et al.Inertial Technology[M]. Beijing: National Defence Industry Press, 2011.
[8] 李超, 苏中, 朱嘉林. 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. A Research about Zero Velocity Trigger Algorithm Used in the Wearable Autonomous Positioning Technology[J]. Journal of Sensing Technology, 2014, 27(5): 627-632.
[9] 汪天生, 李擎. 改进的零速修正算法在行人自主导航中的应用[J]. 系统仿真学报, 2018, 30(11): 336-343.
Wang Tiansheng, Li Qing.Application of Improved ZUPT in Pedestrian Self-Navigation[J]. Journal of System Simulation, 2018, 30(11): 336-343.
[10] 谷志丹, 李擎, 赵辉. 行人自主导航定位的多级滤波方法[J]. 系统仿真学报, 2018, 30(12): 235-239, 245.
Gu zhidan, Li Qing, Zhao Hui. Multi-stage Filtering Method for Pedestrian Navigation and Location[J]. Journal of system simulation, 2018, 30(12): 235-239, 245.
[11] 秦永元, 张洪钺, 王叔华. 卡尔曼滤波与组合导航原理[M]. 西安: 西北工业大学出版社, 2012.
Qin Yongyuan, Zhang Hongyue, Wang Shuhua.Kalman filtering and combined navigation principle[M]. Xi'an: Northwest Polytechnical University Press, 2012.

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