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摘要:
在室内环境中,无线信道中的非视距和多径传输等效应严重影响了到达时间(TOA)定位系统的测距值精度,从而导致较大的测量误差和定位误差。将测距值优化抽象为非线性规划问题,在实现视距/非视距(LOS/NLOS)场景识别的基础上,利用TOA测距误差模型和“目标-基站”间的几何约束为序列二阶非线性规划方法设置合理的初始值,建立了目标函数和约束条件,对定位测距值进行了有效校正。利用典型的TOA测距误差模型进行了仿真验证,利用具有TOA测距功能的无线定位节点在办公环境中进行了实测验证。结果表明,该方法优化后的测距值精度明显优于原始测距值和传统的测距值修正方法,从而验证了该方法的有效性。
Abstract:The ranging accuracy of time of arrival (TOA) based indoor positioning system is significantly affected by multipath and non-line-of-sight (NLOS) of wireless channel in indoor environment. And these effects result in large measurement error and positioning error. In this paper, the optimization of distance is defined as a nonlinear programming problem. Based on the detection of line of sight (LOS) and NLOS, TOA ranging error model and geometric constraints between target and base stations are used to define the initial values, objective functions and constraint conditions for sequential quadratic nonlinear programming method effectively calibrates the positioning distance value. The typical TOA range error model is used for simulation. Field validation uses wireless positioning nodes with TOA ranging functions in the office environment. The results show that the ranging accuracy of the proposed algorithm is much higher than original range value and the other traditional distance mitigation algorithms, which verifies the effectiveness of the proposed algorithm.
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表 1 仿真实验测距误差均值和方差对比
Table 1. Comparison of mean and variance of range error in simulation experiment
测距方法 误差均值/m 误差方差/m2 原始方法 0.75 0.87 算法1 0.25 0.72 算法2 0.02 0.54 算法3 -0.03 0.76 本文方法 0.01 0.40 表 2 实测实验测距误差均值和方差对比
Table 2. Comparison of mean and variance of range error in actually measured experiment
测距方法 误差均值/m 误差方差/m2 原始方法 1.13 0.67 算法1 0.86 0.37 算法2 -0.21 0.50 算法3 0.45 0.58 本文方法 0.04 0.35 -
[1] AMUNDSON I, KOUTSOUKOS X D. A survey on localization for mobile wireless sensor networks[C]//Proceedings Mobile Entity Localization and Tracking in GPS-less Environnments. Berlin: Springer, 2009, 1: 235-254. https://www.mendeley.com/research-papers/survey-localization-mobile-wireless-sensor-networks-3/ [2] 王佳伟, 王敬东, 赵强, 等.基于CSS的室内测距优化技术[J].指挥控制与仿真, 2016, 38(3):131-135. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=QBZH201603026&dbname=CJFD&dbcode=CJFQWANG J W, WANG J D, ZHAO Q, et al.Optimization techniques for indoor ranging based on CSS[J].Command Control and Simulation, 2016, 38(3):131-135(in Chinese). http://kns.cnki.net/KCMS/detail/detail.aspx?filename=QBZH201603026&dbname=CJFD&dbcode=CJFQ [3] 李伟杰, 张霆廷, 张钦宇.基于机器学习的超宽带NLOS鉴别方法[J].计算机工程与设计, 2014, 35(3):750-754. doi: 10.3969/j.issn.1000-7024.2014.03.003LI W J, ZHANG T T, ZHANG Q Y.Identification of ultra wideband NLOS based on machine learning[J].Computer Engineering and Design, 2014, 35(3):750-754(in Chinese). doi: 10.3969/j.issn.1000-7024.2014.03.003 [4] WANG Z, ZEKAVAT S A.Omnidirectional mobile NLOS identification and localization via multiple cooperative nodes[J].IEEE Transactions on Mobile Computing, 2012, 11(12):47-59. http://d.old.wanfangdata.com.cn/NSTLQK/NSTL_QKJJ0227622277/ [5] 徐彤阳.基于减法聚类的TOA/AOA定位方法研究[J].电子测量技术, 2013, 36(10):91-93. doi: 10.3969/j.issn.1002-7300.2013.10.023XU T Y.Research on TOA/AOA location method based on subtractive clustering[J].Electronic Measurement Technology, 2013, 36(10):91-93(in Chinese). doi: 10.3969/j.issn.1002-7300.2013.10.023 [6] HEIDARI M, AKGUL F O, PAHLAVAN K. Neural network assisted identification of the absence of direct path in indoor localization[C]//IEEE Global Telecommunications Conference. Piscataway, NJ: IEEE Press, 2007: 387-392. https://ieeexplore.ieee.org/document/4410989/ [7] HEIDARI M, ALSINDI A N, PAHLAVAN K.UDP identification and error mitigation in TOA-based indoor localization systems using neural network architecture[J].IEEE Transactions on Wireless Communications, 2009, 8(7):3597-3607. doi: 10.1109/TWC.2009.080415 [8] RAO N S V, XU X, SAHNI S. A computational geometry method for TDOA triangulation[C]//IEEE International Conference on Information Fusion. Piscataway, NJ: IEEE Press, 2007: 1-7. http://ieeexplore.ieee.org/document/4408050/ [9] ARIAS-DE-REYNA E.A maximum likelihood UWB localization algorithm exploiting knowledge of the service area layout[J].Wireless Personal Communications, 2013, 69(4):1413-1426. doi: 10.1007/s11277-012-0642-2 [10] PARK C H, CHANG J H.TOA source localization based on weighted least squares estimator in LOS/NLOS mixture environments[J].International Journal of Distributed Sensor Networks, 2016, 12(12):44-53. [11] LIANG S C, LIAO L H, LEE Y C.Localization algorithm based on improved weighted centroid in wireless sensor networks[J].Journal of Networks, 2014, 9(1):183-189. http://connection.ebscohost.com/c/articles/97557309/localization-algorithm-based-improved-weighted-centroid-wireless-sensor-networks [12] WANG Y, ZHENG F, WIEMELER M, et al. Reference selection for hybrid TOA/RSS linear least squares localization[C]//2013 IEEE 78th Vehicular Technology Conference. Piscataway, NJ: IEEE Press, 2013: 1-5. http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=6692388 [13] HE J, GENG Y, PAHLAVAN K.Toward accurate human tracking:Modelling time-of-arrival for wireless wearable sensors in multipath environment[J].IEEE Sensors Journal, 2014, 14(11):122-145. https://ieeexplore.ieee.org/document/6895130/?arnumber=6895130 [14] GHASSEMZADEH S S.The ultra-wideband indoor path loss model[J].IEEE Communication Letters, 2002, 7(2):58-66. [15] HEIDARI M, AKGUL F O, PAHLAVAN K.Identification of the absence of direct path in ToA-based indoor localization systems[J].International Journal of Wireless Information Networks, 2008, 12(3-4):117-127. doi: 10.1007/s10776-008-0084-7 [16] CAO M, ANDERSON B, MORSE A S.Sensor network localization with imprecise distances[J].Systems & Control Letters, 2006, 55(11):887-893. http://www.sciencedirect.com/science/article/pii/S0167691106000879 [17] AKGUL F O.Modeling the behavior of multipath components pertinent to indoor geolocation[M].New York:Worcester Polytechnic Institute, 2010:89-93. [18] WANN C D, CHIN H C. Hybrid TOA/RSSI wireless location with unconstrained nonlinear optimization for indoor UWB channels[C]//2007 IEEE Wireless Communications and Networking Conference. Piscataway, NJ: IEEE Press, 2007: 3940-3945. http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=4224965 [19] BOGGS P, TOLLE J.Sequential quadratic programming[J].Acta Numerica, 1995, 4(4):1-51. doi: 10.1007%2F0-387-22742-3_18 [20] ALAVI B, PAHLAVAN K.Modeling of the TOA based distance measurement error using UWB indoor radio measurements[J].IEEE Communication Letters, 2006, 10(4):275-277. doi: 10.1109/LCOMM.2006.1613745 [21] MARANO S, GIFFORD W M, WYMEERSCH H, et al.NLOS identification and mitigation for localization based on UWB experimental data[J].IEEE Journal on Selected Areas in Communications, 2010, 28(7):1026-1035. doi: 10.1109/JSAC.2010.100907 [22] HATAMI A. Application of channel modeling for indoor localization using TOA and RSS[D]. New York: Worcester Polytechnic Insititute, 2006: 42-47. http://www.openthesis.org/documents/Application-channel-modeling-indoor-localization-33244.html