TDoA定位盲区分析与节点部署策略研究

doi:10.11959/j.issn.1000-436x.2023021

通信学报 ›› 2023, Vol. 44 ›› Issue (1): 1-13.doi: 10.11959/j.issn.1000-436x.2023021

• 学术论文 • 下一篇

TDoA定位盲区分析与节点部署策略研究

赵越¹, 李赞¹, 李冰², 郝本建¹

¹ 西安电子科技大学通信工程学院，陕西西安 710071
² 中国人民解放军31007部队，北京 100000

修回日期:2022-10-20 出版日期:2023-01-25 发布日期:2023-01-01
作者简介:赵越（1994- ），男，山西临汾人，博士，西安电子科技大学讲师，主要研究方向为无线网络定位、隐蔽通信等
李赞（1975- ），女，陕西西安人，博士，西安电子科技大学教授、博士生导师，主要研究方向为电磁频谱认知与管控、通信信号处理等
李冰（1978- ），男，江苏扬州人，博士，31007部队正高级工程师，主要研究方向为信号处理、无线通信等
郝本建（1982- ），男，山东泰安人，博士，西安电子科技大学教授，主要研究方向为信号识别、被动定位等
基金资助:
国家自然科学基金资助项目(62101403);国家杰出青年科学基金资助项目(61825104);陕西省科学技术协会青年人才托举计划项目基金资助项目(XXJS202229)

TDoA localization-refused area analysis and node placement strategy research

Yue ZHAO¹, Zan LI¹, Bing LI², Benjian HAO¹

¹ School of Telecommunications Engineering, Xidian University, Xi’an 710071, China
² Unit 31007 of PLA, Beijing 100000, China

Revised:2022-10-20 Online:2023-01-25 Published:2023-01-01
Supported by:
The National Natural Science Foundation of China(62101403);The National Natural Science Foundation for Distinguished Young Scholar(61825104);Young Talent Fund of Association for Science and Technology in Shaanxi(XXJS202229)

摘要/Abstract

摘要：

以克拉美罗下界（CRLB）作为定位精度衡量指标进行分析，探讨到达时间差（TDoA）定位场景中定位盲区的产生条件，分析不同因素对定位盲区的影响。此外，以无线传感器网络（WSN）所覆盖区域的平均CRLB为目标函数，构建了传感器节点优化部署问题，并提出基于定位盲区预判断的遗传算法进行求解。仿真验证了单信号源定位时CRLB的性质以及定位盲区的产生条件和出现区域。仿真结果表明，采用所提基于定位盲区预判断的遗传算法获得的节点部署方案时，定位精度比均匀角度部署提高 33.92%，比区域顶点部署提升 13.74%，比直接遗传算法提升9.65%。

关键词: 到达时间差, 定位盲区, 克拉美罗下界, 节点部署, 无线传感器网络

Abstract:

Regarding the Cramer-Rao lower bound (CRLB) as a localization accuracy metric, the sufficient conditions of the LRA in the time difference of arrival (TDoA)-based localization scenario were discussed and the influence of different factors on the LRA were analyzed.Furthermore, the node placement problem for wireless sensor network (WSN) was investigated by formulating an optimization problem with the objective as average CRLB, which was solved by a genetic algorithm based on LRA pre-judgment.Simulation validates the properties of the CRLB in a single-source scenario and verifies the sufficient condition and the spatial range of the LRA.The simulation also shows that the localization accuracy determined by the proposed algorithm is improved by 33.92% higher than the uniform angle array placement scheme, 13.74% compared to the regional vertex placement scheme, and 9.65% compared to the direct genetic algorithm.

Key words: time difference of arrival, localization-refused area, CRLB, node placement, wireless sensor network

中图分类号:

TN92

赵越, 李赞, 李冰, 郝本建. TDoA定位盲区分析与节点部署策略研究[J]. 通信学报, 2023, 44(1): 1-13.

Yue ZHAO, Zan LI, Bing LI, Benjian HAO. TDoA localization-refused area analysis and node placement strategy research[J]. Journal on Communications, 2023, 44(1): 1-13.

图/表 10

图1

图2

表1

图3

图4

图5

图6

图7

图8

图9

参考文献 27

[1]	BOUKERCHE A , OLIVEIRA H A B F , NAKAMURA E F ,et al. Localization systems for wireless sensor networks[J]. IEEE Wireless Communications, 2007,14(6): 6-12.
[2]	MAO G Q . Wireless sensor network localization techniques[J]. Computer Networks, 2007,51(10): 2529-2553.
[3]	郝本建, 朱建峰, 李赞 ,等. 基于TDoAs与FDoAs的多信号源及感知节点联合定位算法[J]. 电子学报, 2015,43(10): 1888-1897.
	HAO B J , ZHU J F , LI Z ,et al. Joint multiple disjoint sources and sensors localization based on TDoAs and FDoAs[J]. Acta Electronica Sinica, 2015,43(10): 1888-1897.
[4]	HO K C , XU W W . An accurate algebraic solution for moving source location using TDoA and FDoA measurements[J]. IEEE Transactions on Signal Processing, 2004,52(9): 2453-2463.
[5]	WANG Y , HO K C . An asymptotically efficient estimator in closed-form for 3-D AoA localization using a sensor network[J]. IEEE Transactions on Wireless Communications, 2015,14(12): 6524-6535.
[6]	STEIN S . Algorithms for ambiguity function processing[J]. IEEE Transactions on Acoustics,Speech,and Signal Processing, 1981,29(3): 588-599.
[7]	SHARP I , YU K G , GUO Y J . GDOP analysis for positioning system design[J]. IEEE Transactions on Vehicular Technology, 2009,58(7): 3371-3382.
[8]	肖潇, 陶晓明, 陆建华 . 基于高能效无线接入网的绿色无线通信关键技术研究[J]. 电信科学, 2011,27(11): 75-83.
	XIAO X , TAO X M , LU J H . Study on key technologies of green wireless communications with energy efficient wireless access network[J]. Telecommunications Science, 2011,27(11): 75-83.
[9]	沈梦魁 . 无线通信中的室内中继技术及其关键器件研究[D]. 成都:电子科技大学, 2018.
	SHEN M K . Research on indoor relay and key components for wireless communication[D]. Chengdu:University of Electronic Science and Technology of China, 2018.
[10]	王太军 . 短波传播特性及盲区通信策略分析[J]. 通信与信息技术, 2019(6): 48-54.
	WANG T . Shortwave propagation characteristics and blind spot communication strategy analysis[J]. Communication ＆ Information Technology, 2019(6): 48-54.
[11]	郭福成, 李腾 . 基于时差和频差的固定多站定位方法及分析[J]. 系统工程与电子技术, 2011,33(9): 1954-1958.
	GUO F , LI T . Passive localization method and its precision analysis based on TDoA and FDoA of fixed sensors[J]. Systems Engineering and Electronics, 2011,33(9): 1954-1958.
[12]	常新亚, 谢斌, 张晓敏 ,等. 双星 TDoA/FDoA 定位系统的目标定位精度分析[J]. 航天器工程, 2013,22(4): 35-42.
	CHANG X Y , XIE B , ZHANG X M ,et al. Target location accuracy analysis of dual-satellites location system using TDoA and FDoA[J]. Spacecraft Engineering, 2013,22(4): 35-42.
[13]	陆安南, 缪善林, 邱焱 . 基于阵列信号处理的高性能双星定位[J]. 航天电子对抗, 2015,31(1): 18-20,33.
	LU A N , MIAO S L , QIU Y . High performance passive localization of dual-satellite system based on array signal processing[J]. Aerospace Electronic Warfare, 2015,31(1): 18-20,33.
[14]	陈俊 . 2 种锚点分布对定位的特殊影响分析[J]. 中国新通信, 2018,20(22): 166.
	CHEN J . Analysis of the special influence of the two anchor distributions on positioning[J]. China New Telecommunications, 2018,20(22): 166.
[15]	QIN Z T , WANG J , WEI S M . A study of 3D sensor array geometry for TDoA based localization[C]// Proceedings of CIE International Conference on Radar (RADAR). Piscataway:IEEE Press, 2016: 1-5.
[16]	王维超 . 基于稀疏恢复的班组无源定位方法研究[D]. 济南:山东大学, 2019.
	WANG W C . The research on team passive locating based on sparse recovery[D]. Jinan:Shandong University, 2019.
[17]	LUI K , SO H C . A study of two-dimensional sensor placement using time-difference-of-arrival measurements[J]. Digital Signal Processing, 2009,19(4): 650-659.
[18]	YANG B , SCHEUING J . Cramer-Rao bound and optimum sensor array for source localization from time differences of arrival[C]// Proceedings of IEEE International Conference on Acoustics,Speech,and Signal Processing. Piscataway:IEEE Press, 2005: 961-964.
[19]	YANG B , SCHEUING J . A theoretical analysis of 2D sensor arrays for TDoA based localization[C]// Proceedings of IEEE International Conference on Acoustics Speech and Signal Processing. Piscataway:IEEE Press, 2006: 901-904.
[20]	YANG B , . Different sensor placement strategies for TDoA based localization[C]// Proceedings of IEEE International Conference on Acoustics,Speech and Signal Processing. Piscataway:IEEE Press, 2007: 1093-1096.
[21]	贾兴江, 周一宇, 郭福成 . 三机无源定位二维布阵优化研究[J]. 现代雷达, 2010,32(2): 7-11.
	JIA X J , ZHOU Y Y , GUO F C . Two-dimensional optimal sensors placement for passive location system using three aircrafts[J]. Modern Radar, 2010,32(2): 7-11.
[22]	LIN T Y , HSIEH K C , HUANG H C . Applying genetic algorithms for multiradio wireless mesh network planning[J]. IEEE Transactions on Vehicular Technology, 2012,61(5): 2256-2270.
[23]	TAO X , SONG W . Location-dependent task allocation for mobile crowdsensing with clustering effect[J]. IEEE Internet of Things Journal, 2019,6(1): 1029-1045.
[24]	LORENZO B , GLISIC S . Optimal routing and traffic scheduling for multihop cellular networks using genetic algorithm[J]. IEEE Transactions on Mobile Computing, 2013,12(11): 2274-2288.
[25]	REID D J . Genetic algorithms in constrained optimization[J]. Mathematical and Computer Modelling, 1996,23(5): 87-111.
[26]	FOY W H . Position-location solutions by Taylor-series estimation[J]. IEEE Transactions on Aerospace and Electronic Systems, 1976,12(2): 187-194.
[27]	AMIRI R , BEHNIA F , NOROOZI A . An efficient estimator for TDoA-based source localization with minimum number of sensors[J]. IEEE Communications Letters, 2018,22(12): 2499-2502.

参考节点	WSN₁		WSN₂
参考节点	Root CRLB/m	RMSE/m	Root CRLB/m	RMSE/m
s₁	5.951 0	6.437 6	5.951 0	6.449 6
s₂	5.951 0	6.166 6	5.951 0	6.220 7
s₃	5.951 0	6.095 7	5.951 0	6.107 3
s₄	5.951 0	6.034 9	5.951 0	6.091 8
s₅	5.951 0	7.116 9	5.951 0	7.547 9

TDoA定位盲区分析与节点部署策略研究

TDoA localization-refused area analysis and node placement strategy research

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 10

参考文献 27

相关文章 15

Metrics

推荐阅读 0

[1]	马帅, 李兵, 盛海鸿, 谷荣妍, 周辉, 王洪梅, 王悦, 李世银. 基于深度强化学习的可见光定位通信一体化功率分配研究[J]. 通信学报, 2022, 43(8): 121-130.
[2]	李翠然, 王雪洁, 谢健骊, 吕安琪. 基于改进PSO的铁路监测线性无线传感器网络路由算法[J]. 通信学报, 2022, 43(5): 155-165.
[3]	杜秀娟, 王丽娟, 刘静萍, 金龙. 基于归零神经动力学的水下无线传感器网络节点测距定位方法[J]. 通信学报, 2022, 43(10): 177-185.
[4]	孙爱晶, 李世昌, 张艺才. 基于PSO优化模糊C均值的WSN分簇路由算法[J]. 通信学报, 2021, 42(3): 91-99.
[5]	王天荆,李秀琴,白光伟,沈航. 无线传感器网络中基于自适应网格的多目标定位算法[J]. 通信学报, 2019, 40(7): 197-207.
[6]	马方立,徐扬,徐鹏. 基于大地经纬度的二维TDOA无源定位[J]. 通信学报, 2019, 40(5): 136-143.
[7]	郝晓辰,姚宁,解力霞,王姣姣,王立元. 联合功率与信道的WSN生命期优化博弈算法[J]. 通信学报, 2019, 40(4): 62-70.
[8]	刘琳岚,高声荣,舒坚. 基于随机森林的链路质量预测[J]. 通信学报, 2019, 40(4): 202-211.
[9]	武小年,张楚芸,张润莲,孙亚平. WSN中基于改进粒子群优化算法的分簇路由协议[J]. 通信学报, 2019, 40(12): 114-123.
[10]	刘浩然,赵赫瑶,邓玉静,王星淇,尹荣荣. 基于非合作博弈的无线传感器网络覆盖控制算法[J]. 通信学报, 2019, 40(1): 71-78.
[11]	乐燕芬,汤卓,盛存宝,施伟斌. 基于多分布密度位置指纹的高效室内定位算法研究[J]. 通信学报, 2019, 40(1): 172-179.
[12]	舒坚,刘满兰,尚亚青,陈宇斌,刘琳岚. 基于高斯过程回归的链路质量预测模型[J]. 通信学报, 2018, 39(7): 148-156.
[13]	郝晓辰,王立元,刘金硕,解力霞,张文焕. WSN中基于双群体差分进化的资源分配优化算法[J]. 通信学报, 2018, 39(4): 68-75.
[14]	蒋婵,李陶深,梁俊斌. 移动低占空比无线传感器网络中低时延的数据持续性提高算法[J]. 通信学报, 2018, 39(3): 53-62.
[15]	王继红,石文孝. 认知无线传感器网络分簇路由协议综述[J]. 通信学报, 2018, 39(11): 156-169.