UWB positioning optimization method based on redundant distance screening
ZHANG Shaohui1,3, QI Yuhao2, ZHAI Fangwen1, L�Hongbo4, SONG Yixu1
1. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China; 2. Equipment Management Center, Yanzhou Coal Mining Company Limited, Jining 273500, China; 3. School of Information Engineering, China University of Geosciences, Beijing 100083, China; 4. School of Mechanical and Material Engineering, North China University of Technology, Beijing 100144, China
Abstract:Ultra wide band (UWB) positioning technology establishes a mathematical model of the target location based on distance parameters. The problem of accurately solving the tag point positioning is transformed into an optimization problem of nonlinear equations due to ranging errors. Existing optimization methods may fail when certain distance errors are large. Therefore, this paper proposes an optimization method based on redundant distance screening by considering the distances between multiple positioning tags as constraints, filtering the redundant distances by weighting, and using a gradient descent method to optimize the initial value calculated by the Caffery method. In simulation experiments, the positioning error of this method is only 70% of the Caffery-Taylor (CT) method. In real data experiments, this method outperforms the CT method in terms of the optimization effect.
[1] HASHEM O, HARRAS K A, YOUSSEF M. Accurate indoor positioning using IEEE 802.11mc round trip time[J]. Pervasive and Mobile Computing, 2021, 75:101416. [2] SADHUKHAN P, GAIN S, DAHAL K, et al. An efficient clustering with robust outlier mitigation for Wi-Fi fingerprint based indoor positioning[J]. Applied Soft Computing, 2021, 109:107549. [3] 陈国良, 张言哲, 汪云甲, 等. WiFi-PDR室内组合定位的无迹卡尔曼滤波算法[J]. 测绘学报, 2015, 44(12):1314-1321. CHEN G L, ZHANG Y Z, WANG Y J, et al. Unscented Kalman filter algorithm for WiFi-PDR integrated indoor positioning[J]. Acta Geodaetica et Cartographica Sinica,Journal of Geodesy and Geoinformation Science, 2015, 44(12); 1314-1321. (in Chinese) [4] 席瑞, 李玉军, 侯孟书. 室内定位方法综述[J]. 计算机科学, 2016, 43(4):1-6, 32. XI R, LI Y J, HOU M S. Survey on indoor localization[J]. Computer Science, 2016, 43(4):1-6, 32. (in Chinese) [5] 闫大禹, 宋伟, 王旭丹, 等. 国内室内定位技术发展现状综述[J]. 导航定位学报, 2019, 7(4):5-12. YAN D Y, SONG W, WANG X D, et al. Review of development status of indoor location technology in China[J]. Journal of Navigation and Positioning, 2019, 7(4):5-12. (in Chinese) [6] 卢靖宇, 余文涛, 赵新, 等. 基于超宽带的移动机器人室内定位系统设计[J]. 电子技术应用, 2017, 43(5):25-28. LU J Y, YU W T, ZHAO X, et al. Design of indoor positioning system for mobile robot based on ultra-wideband[J]. Application of Electronic Technique, 2017, 43(5):25-28. (in Chinese) [7] 黄梦雨, 秦建军, 高磊, 等. 基于UWB的零转径跟随机器人控制系统设计[J]. 重庆理工大学学报(自然科学), 2019, 33(9):142-150. HUANG M Y, QIN J J, GAO L, et al. Design of zero turning radius following robot control system based on UWB[J]. Journal of Chongqing University of Technology(Natural Science), 2019, 33(9):142-150.(in Chinese) [8] 李浩博, 王坚, 王川阳. 超宽带室内动态定位精度影响探究[J]. 导航定位学报, 2018, 6(1):45-48. LI H B, WANG J, WANG C Y. Discussion on affection factors of UWB indoor kinematic positioning[J]. Journal of Navigation and Positioning, 2018, 6(1):45-48. (in Chinese) [9] 吴绍华, 张乃通. 基于UWB的无线传感器网络中的两步TOA估计法[J]. 软件学报, 2007, 18(5):1164-1172. WU S H, ZHANG N T. A two-step TOA estimation method for UWB based wireless sensor networks[J], Journal of Software, 2007, 18(5):1164-1172. (in Chinese) [10] BABA A I, WU F, AHMED T. A naive time of flight ranging scheme for wireless sensor networks[J]. International Journal of Communication Networks and Distributed Systems, 2020, 25(4):347-365. [11] ZHANG R, HÖFLINGER F, REINDL L. TDOA-Based localization using interacting multiple model estimator and ultrasonic transmitter/receiver[J]. IEEE Transactions on Instrumentation and Measurement, 2013, 62(8):2205-2214. [12] 王川阳, 王坚, 宁一鹏, 等. 超宽带定位的降噪方法研究[J]. 测绘科学, 2019, 44(4):175-181. WANG C Y, WANG J, NING Y P, et al. Study of noise reduction method for ultra wideband positioning[J]. Science of Surveying and Mapping, 2019, 44(4):175-181. (in Chinese) [13] YIN H H, XIA W W, ZHANG Y Y, et al. UWB-based Indoor high precision localization system with robust unscented Kalman filter[C]//2016 IEEE International Conference on Communication Systems (iccs). Shenzhen, China:IEEE Press, 2016:1-6. [14] 刘公绪, 史凌峰. 室内导航与定位技术发展综述[J]. 导航定位学报, 2018, 6(2):7-14. LIU G X, SHI L F. An overview about development of indoor navigation and positioning technology[J]. Journal of Navigation and Positioning, 2018, 6(2):7-14. (in Chinese) [15] 赵连军. 基于目标特征的单目视觉位置姿态测量技术研究[D]. 成都:中国科学院大学(中国科学院光电技术研究所), 2014. ZHAO L J. Research on mono-vision pose measurement based on features of target[D]. Chengdu:University of Chinese Academy of Sciences (Institute of Optics and Electronics, Chinese Academy of Sciences), 2014. (in Chinese) [16] EGGERT D W, LORUSSO A, FISHER R B. Estimating 3-D rigid body transformations:A comparison of four major algorithms[J]. Machine Vision and Applications, 1997, 9(5-6):272-290. [17] CAFFERY J J. A new approach to the geometry of TOA location[C]//IEEE Vehicular Technology Conference Fall 2000. Boston, MA, USA:IEEE Press, 2000:1943-1949. [18] 符世琛. 基于UWB测距的悬臂式掘进机位姿检测方法研究[D]. 北京:中国矿业大学(北京), 2018. FU S S. Research on pose detection method of boom-type roadheader based on UWB distance measurement[D]. Beijing:China University of Mining and Technology (Beijing), 2018. (in Chinese) [19] 符世琛, 李一鸣, 杨健健, 等. 基于超宽带技术的掘进机自主定位定向方法研究[J]. 煤炭学报, 2015, 40(11):2603-2610. FU S S, LI Y M, YANG J J, et al. Research on autonomous positioning and orientation method of roadheader based on Ultra Wide-Band technology[J]. Journal of China Coal Society, 2015, 40(11):2603-2610. (in Chinese)