船用无线传感器网络节点三维定位技术研究
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摘要
作为一种新兴的分布式测控技术,无线传感器网络(WSN:Wireless Sensor Network)被认为是二十一世纪改变世界的十大新技术之一,具有非常广阔的应用前景。一般而言,应用在不同领域的WSN具有不同的特点。本文针对船舶结构特点和WSN节点工作环境特点对船用无线传感器网络进行研究,提出船用无线传感器网络节点三维定位方法,并设计相关算法。
本文提出的定位方法由两部分组成,即舱室定位方法和舱内定位方法。舱室定位是指根据WSN的网络拓扑结构,确定未知节点(指待定位节点)的大体位置。具体而言,舱室定位是根据未知节点向基站发送数据包时所选用的中继节点的不同,来推断未知节点在船上的位置,得出的位置可能是一个具体的舱室,也可能是其所在的甲板层。舱室定位的精度与船舶的结构、节点的布置以及WSN的路由算法密切相关。舱内定位是指在获得未知节点所在舱室之后,根据未知节点与其舱室内的锚节点(指位置已知的节点)进行通信的RSSI(Received Signal Strength Indicator:接收信号强度指示)来计算它们之间的距离,并根据这些距离关系解算出未知节点的位置。
本文利用美国Crossbow公司生产的WSN节点,对舱室定位方法和舱内定位方法进行了验证,结果表明利用船用无线传感器网络拓扑结构与RSSI值进行定位是可行的。本文还通过编写基于TinyOS操作系统的节点应用程序和基于Matlab-GUI的定位应用程序实现了舱内定位的算法。
总之,本文对船用无线传感器网络的特点进行了研究,给出了舱室定位和舱内定位方法,实现了舱内定位算法,并在教学实习船“育鲲”轮进行了实船实验验证。本文工作是对WSN在船上应用的有益探索和尝试。
As an emerging distributed measuring and controlling technology, Wireless Sensor Network (WSN) has very broad application prospect considered as one of the top ten new technologies that would change the world of the 21 century. In general WSN in different fields has different characteristics. This paper researches the structure of the ship and the work environment of WSN nodes, put forward the method of 3D location on shipboard, and designs the related algorithm.
The location method raised by this paper consists of two parts:location method among compartments and location method in a compartment. Location method among compartments refers to confirm the unknown nodes (refer to the nodes to be located) according to the topology of WSN on shipboard. To be specific, the position result is achieved by analyzing the different repeater nodes which are chosen by the unknown nodes when they send message packets to base station, and the result may be a cabin, a compartment or a deck. The precision of this location method is tightly related to the structure of the ship, distribution of nodes and routing algorithm of WSN. Location method in a compartment refers to the method in which we can calculate the position result by the distance relationship achieved by the RSSI (Received Strength Signal Indicator) between the unknown nodes and the anchor nodes (refer to the nodes located) in the compartment after obtaining the compartment of the unknown nodes.
Using the nodes produced by American Crossbow this paper has verified the location method among compartments and location method in a compartment, and come to the conclusion that it is feasible to get the position result by the two methods. In addition, this paper has realized the location method in a compartment by writing TinyOS and Matlab programs.
In a word, this paper has researched the characteristics of WSN on board, raised the location method among compartments and the location method in a compartment, realized the location algorithm among compartments, and verified them by doing experiments on YuKun, a teaching practice ship. This paper has explored and tried the WSN location on shipboard.
本文提出的定位方法由两部分组成,即舱室定位方法和舱内定位方法。舱室定位是指根据WSN的网络拓扑结构,确定未知节点(指待定位节点)的大体位置。具体而言,舱室定位是根据未知节点向基站发送数据包时所选用的中继节点的不同,来推断未知节点在船上的位置,得出的位置可能是一个具体的舱室,也可能是其所在的甲板层。舱室定位的精度与船舶的结构、节点的布置以及WSN的路由算法密切相关。舱内定位是指在获得未知节点所在舱室之后,根据未知节点与其舱室内的锚节点(指位置已知的节点)进行通信的RSSI(Received Signal Strength Indicator:接收信号强度指示)来计算它们之间的距离,并根据这些距离关系解算出未知节点的位置。
本文利用美国Crossbow公司生产的WSN节点,对舱室定位方法和舱内定位方法进行了验证,结果表明利用船用无线传感器网络拓扑结构与RSSI值进行定位是可行的。本文还通过编写基于TinyOS操作系统的节点应用程序和基于Matlab-GUI的定位应用程序实现了舱内定位的算法。
总之,本文对船用无线传感器网络的特点进行了研究,给出了舱室定位和舱内定位方法,实现了舱内定位算法,并在教学实习船“育鲲”轮进行了实船实验验证。本文工作是对WSN在船上应用的有益探索和尝试。
As an emerging distributed measuring and controlling technology, Wireless Sensor Network (WSN) has very broad application prospect considered as one of the top ten new technologies that would change the world of the 21 century. In general WSN in different fields has different characteristics. This paper researches the structure of the ship and the work environment of WSN nodes, put forward the method of 3D location on shipboard, and designs the related algorithm.
The location method raised by this paper consists of two parts:location method among compartments and location method in a compartment. Location method among compartments refers to confirm the unknown nodes (refer to the nodes to be located) according to the topology of WSN on shipboard. To be specific, the position result is achieved by analyzing the different repeater nodes which are chosen by the unknown nodes when they send message packets to base station, and the result may be a cabin, a compartment or a deck. The precision of this location method is tightly related to the structure of the ship, distribution of nodes and routing algorithm of WSN. Location method in a compartment refers to the method in which we can calculate the position result by the distance relationship achieved by the RSSI (Received Strength Signal Indicator) between the unknown nodes and the anchor nodes (refer to the nodes located) in the compartment after obtaining the compartment of the unknown nodes.
Using the nodes produced by American Crossbow this paper has verified the location method among compartments and location method in a compartment, and come to the conclusion that it is feasible to get the position result by the two methods. In addition, this paper has realized the location method in a compartment by writing TinyOS and Matlab programs.
In a word, this paper has researched the characteristics of WSN on board, raised the location method among compartments and the location method in a compartment, realized the location algorithm among compartments, and verified them by doing experiments on YuKun, a teaching practice ship. This paper has explored and tried the WSN location on shipboard.
引文
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[3]徐为,郦苏丹,彭伟.无线传感器网络时间同步算法综述[J].计算机与信息技术,2008,(10)：1021-1023
[4]张付杰,彭争,齐亚峰.无线传感器网络研究进展[J].现代农业技术,2010,1(1)：16-20
[5]KDOUH H, BROUSSEAU C, ZAHARIA G, et al. Applying ubiquitous wireless technologies for shipboard monitoring systems[C]. proceedings of the Wireless Personal Multimedia Communications (WPMC),2011 14th International Symposium on, F 3-7 Oct.2011,1-5
[6]KDOUH H, ZAHARIA G, BROUSSEAU C, et al. ZigBee-based sensor network for shipboard environments[C]. proceedings of the Signals, Circuits and Systems (ISSCS),2011 10th International Symposium on, F June 302011-July 1 2011,1-4
[7]YOO Y, CHOI M, KWON K-D, et al. Optimal transmission power of wireless sensors for real-time systems in ship area networks[C]. proceedings of the Wireless Pervasive Computing (ISWPC),2010 5th IEEE International Symposium on, F 5-7 May 2010,74-79
[8]PAIK B-G, CHO S-R, PARK B-J, et al. Employment of Wireless Sensor Networks for Full-Scale Ship Application [J]. Embedded and Ubiquitous Computing,2007,4808(1)13-22
[9]马善伟,刘赟.无线传感网络系统在船舶机舱中的应用研究[J].上海造船,2008,(01)：34-36
[10]肖德宏.基于WSN的船舶机舱温度监测系统研究与设计[D],大连：大连海事学,2008
[11]王慧勇.船舶机舱WSN的MAC层协议优化与仿真[D],大连：大连海事大学,2010
[12]刘克中.无线传感器网络分布式节点定位方法研究[D],武汉：华中科技大学,2006
[13]李娟.无线传感器网络节点定位算法及能量高效路由协议的研究[D],长春：吉林大学,2009
[14]GIROD L, ESTRIN D. Robust range estimation using acoustic and multimodal sensing[C]. proceedings of the Intelligent Robots and Systems,2001 Proceedings 2001 IEEE/RSJ International Conference on, F 2001, (3)1312-1320
[15]NICULESCU D, BADRI N. Ad hoc positioning system (APS) using AOA[C]. proceedings of the INFOCOM 2003 Twenty-Second Annual Joint Conference of the IEEE Computer and Communications IEEE Societies, F 30 March-3 April 2003, (3)1734-1743
[16]XIUZHEN C, THAELER A, GUOLIANG X, et al. TPS:a time-based positioning scheme for outdoor wireless sensor networks[C]. proceedings of the INFOCOM 2004 Twenty-third AnnualJoint Conference of the IEEE Computer and Communications Societies, F 7-11 March 2004, (4)2685-2696
[17]BAHL P, PADMANABHAN V N. RADAR:an in-building RF-based user location and tracking system[C]. proceedings of the INFOCOM 2000 Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies Proceedings IEEE, F 2000, (2)775-784
[18]李新.无线传感器网络中节点定位算法的研究[D],合肥：中国科学技术大学,2008
[19]刘影.无线传感器网络节点定位算法研究[D],长春：吉林大学,2011
[20]牛延超.无线传感器网络非测距定位技术研究[D],北京：北京交通大学,2010
[21]AO J, LIU Y. Localization algorithm based on NMDS-MLE-RSSI[C]. proceedings of the Computational Problem-Solving (ICCP),2010 International Conference on, F 3-5 Dec.2010, 104-107
[22]XIUFANG F, ZHANQIANG G, MIAN Y, et al. Fuzzy distance measuring based on RSSI in Wireless Sensor Network[C]. proceedings of the Intelligent System and Knowledge Engineering, 2008 ISKE 2008 3rd International Conference on, F 17-19 Nov.2008,395-400
[23]DAIYA V, EBENEZER J, MURTY S A V S, et al. Experimental analysis of RSSI for distance and position estimation[C]. proceedings of the Recent Trends in Information Technology (ICRTIT), 2011 International Conference on, F 3-5 June 2011,1093-1098
[24]ARTHI R, MURUGAN K. Localization in Wireless Sensor Networks by Hidden Markov Model[C]. proceedings of the Advanced Computing (ICoAC),2010 Second International Conference on, F 14-16 Dec.2010,14-18
[25]PAUL A S, WAN E A. RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers [J]. Selected Topics in Signal Processing, IEEE Journal of,2009,3(5):860-73.
[26]王书锋,侯义斌,黄樟钦,等.无线感知网络最小二乘法定位算法的误差分析与优化[J].系统仿真学报,2009,(19)：6221-6220
[27]NICULESCU D, NATH B. DV Based Positioning in Ad Hoc Networks [J]. Telecommunication Systems,2003,22(1):267-80
[28]HE T, HUANG C, M.BLUM B, et al. Range-Free Localization Schemes for Large Scale Sensor Networks [J]. MobiCom,2003
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