无线传感器网络中基于RSSI的三维定位改进算法研究
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摘要
无线传感器网络(Wireless Sensor Network,WSN)的出现引起了全世界的广泛关注。作为当今信息领域的研究热点,涉及多个学科、多种技术,主要包括：网络通信协议、核心支撑技术、自组织管理、开发与应用。丰富的核心支撑技术使得无线传感器网络构成了一个具体的面向特定应用的网络系统。作为核心支撑技术之一的无线传感器网络节点定位技术是所有应用的基础,因为在不知道相应的位置信息的情况下,传感数据往往是没有任何意义的。
在WSN的节点定位算法中,根据不同的分类标准有不同的分类结果,根据定位算法是否需要通过物理测量来获得节点之间的距离(或角度)信息,可以把定位算法分为两类：基于距离的定位算法和距离无关的定位算法。经过研究可知,前者总体上能取得较好的定位精度,因此,本文重点研究了基于距离的节点定位算法。
本文的主要工作归纳如下：
(1)简单介绍无线传感器网络的研究现状和发展动态,深入研究了现有的无线传感器网络节点定位算法的相关知识及基本原理,对这些算法进行介绍、分析、分类和比较,总结各自的优缺点。
(2)分析对比了现在常用的测距方式：红外线、超声波、GPS和RSSI等,重点研究了基于RSSI测距的定位算法,它无须额外硬件支持,仅仅利用对接收端无线信号的强度来计算发送节点和接收节点间的距离,基于RSSI的定位算法提供了最廉价的定位方法,所以基于RSSI的定位算法是无线传感器网络定位过程中较常采用的方法,然而,实际应用中,由于多径和非视线传播等造成的信号传播模型的复杂性,往往会导致RSSI测距具有很大的不稳定性,从而造成较大范围的定位误差。针对以上问题,本文提出了利用局部性原理来削减测距的不稳定性,即通过锚节点之间通信来获得其所在位置的的衰减系数。
(3)目前,大部分定位算法都是基于二维平面的算法。在实际应用中,节点的分布往往在地形比较复杂的三维空间环境中,二维平面中的算法在应用中会有很多问题。因此,三维空间中节点定位算法十分必要,针对应用范围的问题,本文提出了将RSSI测距扩展到三维的实际应用环境中。(4)由于主客观原因估测得到的多个节点位置可能存在明显错误,本文提出对这些估计位置进行过滤,当多数估计位置比较集中,而少数估计位置离集中位置比较远,我们可认为这几个少数位置是不可靠估计位置,可以除掉,其他位置认为是可靠的,以此来提高定位精度。(5)最后,用实验验证改进后算法的定位性能。采用MATLAB7.1仿真工具对基于RSSI的定位算法在二维空间中(RSSI-2D),基于RSSI的定位算法在三维空间中(RSSI-3D),基于RSSI的改进定位算法在三维空间中(IRSSI-3D)进行仿真实验。仿真结果表明,本文提出的基于RSSI的改进三维定位算法很好地提高了节点定位精度,应用范围广泛。
The appearance of Wireless Sensor Network (WSN) caused widespread concern around the world. As the research focus of current information field,it involves many disciplines and mutiple technologies,including network communication protocol, core support technology, self-organization and management, development and application. With the rich core support technology, the WSN constitutes a specific application-oriented network system. The localization technology, as one of the core support technologies,is the basis of all applications. Because, the sensor data is no sense, without the location information.
According to different classification criteria, the localization algorithms in WSN have different classification results. Based on the need to get the distance or angle among the nodes information by the physical measurement, location algorithms can be divided into two categories:range-based localization algorithm and range-free localization algorithm.The research shows that the former can achieve high location precision.Therefore, in this thesis, range-based localization algorithm is focused on.
Major tasks of the thesis are as follows:
(1) The research status and development trends of wireless sensor networks are introdued briefly. In-depth research on the knowledge and basic technique of nodes localization of WSN is given, and also a detailed description, classification, analysis and comparison of the staple algorithms at present are made to sum up their advantages and disadvantages.
(2) Ranging methods used commonly are analyzed and compared, including: infrared, ultrasonic, GPS, and RSSI, etc. The localization algorithm based on RSSI distance is focused on, without any additional hardware to support, the distance between sending node and receiving node is computed by using the strength of the wireless receiver signal.The localization algorithm based on RSSI provides the most inexpensive method.So the localization algorithm based on RSSI is used more often.However,in the practical applications, the complexity of the signal model caused by multipath and non line of sight, makes the RSSI ranging great instability,causing a wide range of positioning errors. To solve the above problem, locality principle is proposed to reduce the instability in this thesis.It is that the attenuation coefficient of anchor's location is obtained by communicatbing between anchors.
(3) At present, most of the location algorithms are based on two-dimensional. In practice, the distribution of nodes is often in the three-dimensional space complexity environment. So the algorithm in two-dimensional plane will have many problems. Therefore, the localization algorithm in three-dimensional space is very necessary. In this thesis,the RSSI ranging is proposed to extend the practical application of three-dimensional environment for the problem of application scope.
(4) For the estimated location, there maybe an obvious error due to objective and subjective reasons.It is proposed in this paper to filter the error location.When many estimated locations are more concentrated, the few are relatively far away from the central location.The few ones can be considered as unreliable and divided,others are considered as reliable to improve the location accuracy.
(5) Finally, the localization performance of improved algorithm is shown by simulation experiments.Using Simulation tool MATLAB 7.1,RSSI-based localization algorithm in two dimensions (RSSI-2D), RSSI-based localization algorithm in three dimensions (RSSI-3D), improved RSSI-based location algorithm in three-dimensional space (IRSSI-3D) were simulated. It is shown by the experiments that the IRSSI-3D algorithm proposed in this thesis has high localization precision and wide applications.
在WSN的节点定位算法中,根据不同的分类标准有不同的分类结果,根据定位算法是否需要通过物理测量来获得节点之间的距离(或角度)信息,可以把定位算法分为两类：基于距离的定位算法和距离无关的定位算法。经过研究可知,前者总体上能取得较好的定位精度,因此,本文重点研究了基于距离的节点定位算法。
本文的主要工作归纳如下：
(1)简单介绍无线传感器网络的研究现状和发展动态,深入研究了现有的无线传感器网络节点定位算法的相关知识及基本原理,对这些算法进行介绍、分析、分类和比较,总结各自的优缺点。
(2)分析对比了现在常用的测距方式：红外线、超声波、GPS和RSSI等,重点研究了基于RSSI测距的定位算法,它无须额外硬件支持,仅仅利用对接收端无线信号的强度来计算发送节点和接收节点间的距离,基于RSSI的定位算法提供了最廉价的定位方法,所以基于RSSI的定位算法是无线传感器网络定位过程中较常采用的方法,然而,实际应用中,由于多径和非视线传播等造成的信号传播模型的复杂性,往往会导致RSSI测距具有很大的不稳定性,从而造成较大范围的定位误差。针对以上问题,本文提出了利用局部性原理来削减测距的不稳定性,即通过锚节点之间通信来获得其所在位置的的衰减系数。
(3)目前,大部分定位算法都是基于二维平面的算法。在实际应用中,节点的分布往往在地形比较复杂的三维空间环境中,二维平面中的算法在应用中会有很多问题。因此,三维空间中节点定位算法十分必要,针对应用范围的问题,本文提出了将RSSI测距扩展到三维的实际应用环境中。(4)由于主客观原因估测得到的多个节点位置可能存在明显错误,本文提出对这些估计位置进行过滤,当多数估计位置比较集中,而少数估计位置离集中位置比较远,我们可认为这几个少数位置是不可靠估计位置,可以除掉,其他位置认为是可靠的,以此来提高定位精度。(5)最后,用实验验证改进后算法的定位性能。采用MATLAB7.1仿真工具对基于RSSI的定位算法在二维空间中(RSSI-2D),基于RSSI的定位算法在三维空间中(RSSI-3D),基于RSSI的改进定位算法在三维空间中(IRSSI-3D)进行仿真实验。仿真结果表明,本文提出的基于RSSI的改进三维定位算法很好地提高了节点定位精度,应用范围广泛。
The appearance of Wireless Sensor Network (WSN) caused widespread concern around the world. As the research focus of current information field,it involves many disciplines and mutiple technologies,including network communication protocol, core support technology, self-organization and management, development and application. With the rich core support technology, the WSN constitutes a specific application-oriented network system. The localization technology, as one of the core support technologies,is the basis of all applications. Because, the sensor data is no sense, without the location information.
According to different classification criteria, the localization algorithms in WSN have different classification results. Based on the need to get the distance or angle among the nodes information by the physical measurement, location algorithms can be divided into two categories:range-based localization algorithm and range-free localization algorithm.The research shows that the former can achieve high location precision.Therefore, in this thesis, range-based localization algorithm is focused on.
Major tasks of the thesis are as follows:
(1) The research status and development trends of wireless sensor networks are introdued briefly. In-depth research on the knowledge and basic technique of nodes localization of WSN is given, and also a detailed description, classification, analysis and comparison of the staple algorithms at present are made to sum up their advantages and disadvantages.
(2) Ranging methods used commonly are analyzed and compared, including: infrared, ultrasonic, GPS, and RSSI, etc. The localization algorithm based on RSSI distance is focused on, without any additional hardware to support, the distance between sending node and receiving node is computed by using the strength of the wireless receiver signal.The localization algorithm based on RSSI provides the most inexpensive method.So the localization algorithm based on RSSI is used more often.However,in the practical applications, the complexity of the signal model caused by multipath and non line of sight, makes the RSSI ranging great instability,causing a wide range of positioning errors. To solve the above problem, locality principle is proposed to reduce the instability in this thesis.It is that the attenuation coefficient of anchor's location is obtained by communicatbing between anchors.
(3) At present, most of the location algorithms are based on two-dimensional. In practice, the distribution of nodes is often in the three-dimensional space complexity environment. So the algorithm in two-dimensional plane will have many problems. Therefore, the localization algorithm in three-dimensional space is very necessary. In this thesis,the RSSI ranging is proposed to extend the practical application of three-dimensional environment for the problem of application scope.
(4) For the estimated location, there maybe an obvious error due to objective and subjective reasons.It is proposed in this paper to filter the error location.When many estimated locations are more concentrated, the few are relatively far away from the central location.The few ones can be considered as unreliable and divided,others are considered as reliable to improve the location accuracy.
(5) Finally, the localization performance of improved algorithm is shown by simulation experiments.Using Simulation tool MATLAB 7.1,RSSI-based localization algorithm in two dimensions (RSSI-2D), RSSI-based localization algorithm in three dimensions (RSSI-3D), improved RSSI-based location algorithm in three-dimensional space (IRSSI-3D) were simulated. It is shown by the experiments that the IRSSI-3D algorithm proposed in this thesis has high localization precision and wide applications.
引文
[1]王殊,阎毓杰,胡富平等.无线传感器网络的理论及应用[M].北京：北京航空航天大学出版社,2007:142-164.
[2]孙利民,李建中,陈瑜等.无线传感器网络[M].北京：清华大学出版社,2005:11-156.
[3]张荣磊,刘琳岚,舒坚等.基于多维定标的无线传感器网络三维定位算法[J]. 计算机应用研究,2009,26(8)：3100-3105.
[4]He Tian, Huang Chengdu, Blum B M, etc. Range-free localization schemes in largescale sensor networks [C]//Proceedings of the 9 th Annual International Conference on Mobile computing and networking (MobiCom), SanDiego, California, USA:ACM Press, 2003:81-95.
[5]John A Stankovic. Wireless Sensor Networks[R]. Department of Computer Science University of Virginia,2006.
[6]朱红松,孙利民.无线传感器网络技术发展现状[J].中兴通讯技术学报,2009,15(5)：01-05.
[7]http://www.atosenet.com/shownews.php?nid=2010031702274553.
[8]吕鹏元.无线传感器网络定位算法研究[D].西安：西安电子科技大学,2009.
[9]http://www.atosenet. com/shownews.php?nid=2010031702044128.
[10]关媛媛,安世全,刘光明.提供精确室内定位信息的Cricket系统[J].重庆工业高等专科学校学报,2004,19(2)：39-41.
[11]顾一中.基于“北斗”导航系统的无线传感器网络定位算法研究[J].山东交通学院学报,2006,14(3)：58-61.
[12]Savvides A, Han C C, Srivastava M B. Dynamic finge-grained localization in ad-hoc networks of sensors[C].//Proc 7th Annual Int'l Conf on Mobile Computing and Networking (MobiCom). Rome, Italy. July 2001.166-179.
[13]崔平远,郑黎方,裴福俊等.车载GPS_DR组合导航系统自适应信息融合算法研究[J].计算机测量与控制,2007,12(15)：1807-1809.
[14]汪泉弟,魏欣,杜松旺等.一种高精度无线传感器网络节点三维定位算法[J].传感技术学报,2008,21(12)：2050-2053.
[15]郭昀,罗志祥,贾亚黎.三维空间中无线传感器网络节点定位算法[J].船舶电子工程,2007,27(4)：70-75.
[16]刘玉恒,蒲菊华,赫阳等.无线传感器网络三维自身定位方法[J].北京航空航天大学学报,2008,34(6)：647-651.
[17]http://baike. baidu.com/view/215367.htm.
[18]Hui Qu, Stephen B. Wicker. Co-designed anchor-free localization and location-based routing algorithm for rapidly-deployed wireless sensor networks[J]. Information Fusion, 2007:1-12.
[19]郑相全.无线自组网技术使用教程[M].北京：清华大学出版社,2001.36-45.
[20]王继春.无线传感器网络节点定位若干问题研究[D].合肥：中国科学技术大学,2009.
[21]马祖长,孙怡宁,梅涛.无线传感器网络综述[J].通信学报,2004,25(4):114-124.
[22]孙雨耕,张静,孙永进等.无线自组传感器网络[J].传感技术学报,2004,17(2):331-348
[23]代宏阳,唐宏,胡锡鹏.无线传感器网络在军事中的应用研究[J].电脑知识与技术,2010,06(16)：4408-4415.
[24]齐楠,韩波,李平.智能交通系统中无线传感器网络的应用[J].机电工程,2007,24(10).85-87.
[25]黄布毅,何超前,李冬富等.基于无线传感器网络的家庭安防报警系统设计[J].测控技术与仪器仪表,2007,01,74-76.
[26]蒋承延,吴思远.基于无线传感器网络的智能家居系统[J].传感器与仪器仪表.2007,24(5):199-202.
[27]刘宝.ZigBee网络及其在医疗监护系统中的应用研究[D].兰州：兰州理工大学,2009.
[28]Ju Hailing, Miao Yong, Li Tianpu etc. Overview of wireless sensor networks[J]. Computer Research and Development, January,2005,42(1):163-174.
[29]聂文惠,鞠时光,薛安荣.一种基于无线传感器网络的三维定位模型[J].计算机科 学,2009,36(12)：55-58.
[30]Tinos R, Navarro-Serment L, Paredis C. Fault Tolerant Localization for Teams of Distributed Robots[C].//In Proceeding of IEEE International Conference on Intelligent Robots and Systems, Oct.2001,1061-1066.
[31]聂宽胜,刘军.WSN定位算法实际应用性能评价指标及其影响因素的分析[J].安防科技研究与探索,2009,06,3-5.
[32]Gustav J. Jordt, Rusty O. Baldwin, John F. Raquet etc. Energy cost and error performance of range-aware, anchor-free localization algorithms [J]. Ad Hoc Networks, 2008,6:539-559.
[33]Lee Johnson C, Leung Victor C.M, Cao Jiannong etc. Key management issues in wireless sensor networks:Current proposals and future developments[C].//IEEE Wireless Communications.2007,14(5):76-84.
[34]Rao A, Papadimitriou C etc. Geographic routing without location information[C].//: Proc. of the 9th Annual Int'l Conf. on Mobile computing and Networking. San Diego:ACM Press,2003.96-108.
[35]祁会波.无线传感器网络中基于移动锚节点的定位算法研究[D].太原：太原理工大学,2010.
[36]王雪.无线传感器网络测量系统[M].北京：机械工业出版社,2007.307-320.
[37]Aline Baggio, Koen Langendoen. Monte Carlo localization for mobile wireless sensor networks[J]. Ad Hoc Networks,2007:1-5.
[38]Jeongkeun Lee, Kideok Cho, Seungjae Lee etc. Distributed and energy-efficient target localization and tracking in wireless sensor networks[J]. Computer Communications,2006, 29:2494-2505.
[39]Koen Langendoen, Niels Reijers. Distributed localization in wireless sensor networks:a quantitative comparison[J]. Computer Networks,2003,43:499-518.
[40]Dimitrios Koutsonikolas, Saumitra M. Das, Y. Charlie Hu. Path planning of mobile landmarks for localization in wireless sensor networks[J]. Computer Communications,2007, 30:2577-2592.
[41]Bulusu B, Heidemann J, Estrin D. Density adaptive algorithms for beacon placement in wireless sensor networks. In:IEEE ICDCS'01, Phoenix, AZ.2001.04
[42]Doherty L, Pister K S J, Ghaoui L E. Convex Position Estimation in Wireless sensor networks [C]. In Proceeding of Joint Conference of the IEEE Computer and Communications Societies, April 2001,3:1655-1663.
[43]Shang Y, Ruml W, Zhang Y etc. Localization from mere connectivity [J]. Ad Hoc Networking & Computing. Annapolis:ACM Press,2003:201-212.
[44]李娟,王珂.Bounding Cube:一种无线传感器网络节点三维定位算法fJ].中国海洋大学学报,2009,36(06)：1265-1268.
[45]于宁,万江文.无线传感器网络三维抽样定位[J].北京邮电大学学报,2008,36(03):13-18.
[46]戴桂兰,赵冲冲.一种基于球面坐标的无线传感器网络三维定位机制[J].电子学报,2008,36(7)：1297-1303.
[47]Horacio A.B.F. Azzedine Boukerche. Localization In time and space for wireless sensor networks, Performance Evaluation[R]. Paradise Research Laboratory, SITE University of Ottawa, Canada,2008.
[48]梁小满,姜晓奇,李英玲.无线传感器网络节点的三维质心定位算法[J].通信技术,2009,42(02)：121-124.
[49]姜志鹏,高随祥.无线传感器网络节点定位的同心圆改进算法[J].计算机科学,2009,36(10)：46-54.
[50]刘克中,喻钦.无线传感器网络中多能量级质心定位方法[J].华中科技大学学报,2009,37(08)：61-64.
[51]方震,赵湛,郭鹏等.基于RSSI测距分析[J].传感技术学报,2007,21(11)：2526-2530.
[52]段渭军,黄笑利,王福狗等.无线传感器网络测距技术的研究[J].计算机科学,2007,24(9)：55-56.
[53]Shi Chunhe, Han Xiaowei, Yuan Zhonghu, Yang Daquan. Research and Application in the Key Technology of Wireless Sensor Network Location System[C].//Proceeding of the 2009 International Workshop on Information Security and Application.2009.11.484-487.
[54]刘运杰,金明录,崔承毅.基于RSSI的无线传感器网络修正加权质心定位算法[J].传感技术学报,2010,23(05)：717-720.
[55]屈巍,汪晋宽,刘志刚.传感器网络中一种基于RSSI的圆环重叠定位机制[J].东北大学学报,2010,31(03)：354-357.
[56]周燕,李海成.基于RSSI无线传感器网络空间定位算法[J].通信学报,2009,30(06):75-79.
[57]VIANI F, LIZZI L, ROCCA P etc. Object tracking through RSSI measurements in wireless sensor networks[J]. Electronics Letters.2008,44(10):653-654.
[58]KAZUYA T, TETSUSHI I. Decision experiment of attenuation constant during location estimation in RSSI[A]. Proceedings of 9th International Conference on Parallel and Distributed Computing, Applicationsand Technologies[C]. Dunedin, New Zealand,2008. 431-436.
[2]孙利民,李建中,陈瑜等.无线传感器网络[M].北京：清华大学出版社,2005:11-156.
[3]张荣磊,刘琳岚,舒坚等.基于多维定标的无线传感器网络三维定位算法[J]. 计算机应用研究,2009,26(8)：3100-3105.
[4]He Tian, Huang Chengdu, Blum B M, etc. Range-free localization schemes in largescale sensor networks [C]//Proceedings of the 9 th Annual International Conference on Mobile computing and networking (MobiCom), SanDiego, California, USA:ACM Press, 2003:81-95.
[5]John A Stankovic. Wireless Sensor Networks[R]. Department of Computer Science University of Virginia,2006.
[6]朱红松,孙利民.无线传感器网络技术发展现状[J].中兴通讯技术学报,2009,15(5)：01-05.
[7]http://www.atosenet.com/shownews.php?nid=2010031702274553.
[8]吕鹏元.无线传感器网络定位算法研究[D].西安：西安电子科技大学,2009.
[9]http://www.atosenet. com/shownews.php?nid=2010031702044128.
[10]关媛媛,安世全,刘光明.提供精确室内定位信息的Cricket系统[J].重庆工业高等专科学校学报,2004,19(2)：39-41.
[11]顾一中.基于“北斗”导航系统的无线传感器网络定位算法研究[J].山东交通学院学报,2006,14(3)：58-61.
[12]Savvides A, Han C C, Srivastava M B. Dynamic finge-grained localization in ad-hoc networks of sensors[C].//Proc 7th Annual Int'l Conf on Mobile Computing and Networking (MobiCom). Rome, Italy. July 2001.166-179.
[13]崔平远,郑黎方,裴福俊等.车载GPS_DR组合导航系统自适应信息融合算法研究[J].计算机测量与控制,2007,12(15)：1807-1809.
[14]汪泉弟,魏欣,杜松旺等.一种高精度无线传感器网络节点三维定位算法[J].传感技术学报,2008,21(12)：2050-2053.
[15]郭昀,罗志祥,贾亚黎.三维空间中无线传感器网络节点定位算法[J].船舶电子工程,2007,27(4)：70-75.
[16]刘玉恒,蒲菊华,赫阳等.无线传感器网络三维自身定位方法[J].北京航空航天大学学报,2008,34(6)：647-651.
[17]http://baike. baidu.com/view/215367.htm.
[18]Hui Qu, Stephen B. Wicker. Co-designed anchor-free localization and location-based routing algorithm for rapidly-deployed wireless sensor networks[J]. Information Fusion, 2007:1-12.
[19]郑相全.无线自组网技术使用教程[M].北京：清华大学出版社,2001.36-45.
[20]王继春.无线传感器网络节点定位若干问题研究[D].合肥：中国科学技术大学,2009.
[21]马祖长,孙怡宁,梅涛.无线传感器网络综述[J].通信学报,2004,25(4):114-124.
[22]孙雨耕,张静,孙永进等.无线自组传感器网络[J].传感技术学报,2004,17(2):331-348
[23]代宏阳,唐宏,胡锡鹏.无线传感器网络在军事中的应用研究[J].电脑知识与技术,2010,06(16)：4408-4415.
[24]齐楠,韩波,李平.智能交通系统中无线传感器网络的应用[J].机电工程,2007,24(10).85-87.
[25]黄布毅,何超前,李冬富等.基于无线传感器网络的家庭安防报警系统设计[J].测控技术与仪器仪表,2007,01,74-76.
[26]蒋承延,吴思远.基于无线传感器网络的智能家居系统[J].传感器与仪器仪表.2007,24(5):199-202.
[27]刘宝.ZigBee网络及其在医疗监护系统中的应用研究[D].兰州：兰州理工大学,2009.
[28]Ju Hailing, Miao Yong, Li Tianpu etc. Overview of wireless sensor networks[J]. Computer Research and Development, January,2005,42(1):163-174.
[29]聂文惠,鞠时光,薛安荣.一种基于无线传感器网络的三维定位模型[J].计算机科 学,2009,36(12)：55-58.
[30]Tinos R, Navarro-Serment L, Paredis C. Fault Tolerant Localization for Teams of Distributed Robots[C].//In Proceeding of IEEE International Conference on Intelligent Robots and Systems, Oct.2001,1061-1066.
[31]聂宽胜,刘军.WSN定位算法实际应用性能评价指标及其影响因素的分析[J].安防科技研究与探索,2009,06,3-5.
[32]Gustav J. Jordt, Rusty O. Baldwin, John F. Raquet etc. Energy cost and error performance of range-aware, anchor-free localization algorithms [J]. Ad Hoc Networks, 2008,6:539-559.
[33]Lee Johnson C, Leung Victor C.M, Cao Jiannong etc. Key management issues in wireless sensor networks:Current proposals and future developments[C].//IEEE Wireless Communications.2007,14(5):76-84.
[34]Rao A, Papadimitriou C etc. Geographic routing without location information[C].//: Proc. of the 9th Annual Int'l Conf. on Mobile computing and Networking. San Diego:ACM Press,2003.96-108.
[35]祁会波.无线传感器网络中基于移动锚节点的定位算法研究[D].太原：太原理工大学,2010.
[36]王雪.无线传感器网络测量系统[M].北京：机械工业出版社,2007.307-320.
[37]Aline Baggio, Koen Langendoen. Monte Carlo localization for mobile wireless sensor networks[J]. Ad Hoc Networks,2007:1-5.
[38]Jeongkeun Lee, Kideok Cho, Seungjae Lee etc. Distributed and energy-efficient target localization and tracking in wireless sensor networks[J]. Computer Communications,2006, 29:2494-2505.
[39]Koen Langendoen, Niels Reijers. Distributed localization in wireless sensor networks:a quantitative comparison[J]. Computer Networks,2003,43:499-518.
[40]Dimitrios Koutsonikolas, Saumitra M. Das, Y. Charlie Hu. Path planning of mobile landmarks for localization in wireless sensor networks[J]. Computer Communications,2007, 30:2577-2592.
[41]Bulusu B, Heidemann J, Estrin D. Density adaptive algorithms for beacon placement in wireless sensor networks. In:IEEE ICDCS'01, Phoenix, AZ.2001.04
[42]Doherty L, Pister K S J, Ghaoui L E. Convex Position Estimation in Wireless sensor networks [C]. In Proceeding of Joint Conference of the IEEE Computer and Communications Societies, April 2001,3:1655-1663.
[43]Shang Y, Ruml W, Zhang Y etc. Localization from mere connectivity [J]. Ad Hoc Networking & Computing. Annapolis:ACM Press,2003:201-212.
[44]李娟,王珂.Bounding Cube:一种无线传感器网络节点三维定位算法fJ].中国海洋大学学报,2009,36(06)：1265-1268.
[45]于宁,万江文.无线传感器网络三维抽样定位[J].北京邮电大学学报,2008,36(03):13-18.
[46]戴桂兰,赵冲冲.一种基于球面坐标的无线传感器网络三维定位机制[J].电子学报,2008,36(7)：1297-1303.
[47]Horacio A.B.F. Azzedine Boukerche. Localization In time and space for wireless sensor networks, Performance Evaluation[R]. Paradise Research Laboratory, SITE University of Ottawa, Canada,2008.
[48]梁小满,姜晓奇,李英玲.无线传感器网络节点的三维质心定位算法[J].通信技术,2009,42(02)：121-124.
[49]姜志鹏,高随祥.无线传感器网络节点定位的同心圆改进算法[J].计算机科学,2009,36(10)：46-54.
[50]刘克中,喻钦.无线传感器网络中多能量级质心定位方法[J].华中科技大学学报,2009,37(08)：61-64.
[51]方震,赵湛,郭鹏等.基于RSSI测距分析[J].传感技术学报,2007,21(11)：2526-2530.
[52]段渭军,黄笑利,王福狗等.无线传感器网络测距技术的研究[J].计算机科学,2007,24(9)：55-56.
[53]Shi Chunhe, Han Xiaowei, Yuan Zhonghu, Yang Daquan. Research and Application in the Key Technology of Wireless Sensor Network Location System[C].//Proceeding of the 2009 International Workshop on Information Security and Application.2009.11.484-487.
[54]刘运杰,金明录,崔承毅.基于RSSI的无线传感器网络修正加权质心定位算法[J].传感技术学报,2010,23(05)：717-720.
[55]屈巍,汪晋宽,刘志刚.传感器网络中一种基于RSSI的圆环重叠定位机制[J].东北大学学报,2010,31(03)：354-357.
[56]周燕,李海成.基于RSSI无线传感器网络空间定位算法[J].通信学报,2009,30(06):75-79.
[57]VIANI F, LIZZI L, ROCCA P etc. Object tracking through RSSI measurements in wireless sensor networks[J]. Electronics Letters.2008,44(10):653-654.
[58]KAZUYA T, TETSUSHI I. Decision experiment of attenuation constant during location estimation in RSSI[A]. Proceedings of 9th International Conference on Parallel and Distributed Computing, Applicationsand Technologies[C]. Dunedin, New Zealand,2008. 431-436.