基于Range-based的无线传感器网络定位算法研究与改进
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摘要
在无线传感器网络中,位置信息对传感器节点的监测活动至关重要,不包含位置信息的监测报告通常作用有限。另外,无线传感器网络的一些协议比如基于地理信息的路由也需要定位信息作为支撑,因此节点定位问题是无线传感器网络的重要研究内容。
通常按照是否需要预先通过测量来获得节点之间的距离(或角度)信息,把节点定位算法分为基于测距的定位算法和无需测距的定位算法。论文是围绕两种基于测距的定位算法：基于RSSI的定位算法和DV-Distance定位算法展开研究的。首先,论文对无线传感器网络节点定位技术进行了概述,介绍了与节点定位相关的概念、分类方式及测边定位的基本原理。
其次,对基于RSSI的定位算法进行了深入研究和仿真分析,该算法对节点的硬件要求低,实现简单,但是容易受锚节点稀疏、测距误差及通信功率有限的影响而导致定位覆盖率和定位精度不理想,为此,论文提出了一种分级迭代协作定位算法。该改进算法采用协作定位方式来提高定位覆盖率,通过加入锚节点位置优选策略和分级设置邻居节点数量阀值来减少定位误差,MATLAB仿真表明,分级迭代协作定位算法相比传统的基于RSSI定位算法,具有更高的定位覆盖率和定位精度。
再次,论文针对DV-Distance定位算法由于利用节点间多跳累积跳段距离表示欧式距离从而导致定位误差较大的问题,提出了一种进行循环迭代修正计算的改进算法。通过仿真,论文比较了改进的DV-Distance定位算法和传统的DV-Distance定位算法的性能,结果表明改进的DV-Distance算法提高了定位精度,且在继承了传统DV-Distance算法高定位覆盖率同时,还能更好地适应各向异性的网络结构,但是,改进算法的通信开销和计算量还有待改进。
最后,论文对相关研究工作进行了总结,并对未来的研究工作进行了展望。
In wireless sensor networks (WSN), localization information of sensor nodes are essential for WSN monitoring, sensed data is always meaningless without relating to its physical location. In addition, some middle ware services such as location aided routing need localization information. Therefore, it is very important to gain localization of sensor node automatically.
Generally positioning algorithm is divided into range-based algorithm and range-free algorithm according to whether it needs physical measurement to obtain the information about the distance between the nodes or not. The thesis focuses on the range-based algorithm of RSSI-based positioning algorithm and DV-Distance positioning algorithm. First, the thesis summarizes node positioning technology of the WSN, and then mainly introduces node positioning-related concepts and terminology, classification and the basic principles of measurement edge positioning.
Secondly, the RSSI algorithm is deeply discussed and simulation analyzed in this thesis. The algorithm requires low node hardware and its implement is simple. However, the algorithm is vulnerable to the impact of the sparse anchor nodes, ranging error and communication power, which resulted positioning coverage and positioning accuracy not ideal. So this thesis proposes a hierarchical iterative cooperative positioning algorithm. The improved algorithm uses cooperative method to improve positioning coverage and adopts position optimization strategy of the anchor nodes and grading sets the threshold of neighbor number to reduce positioning error. MATLAB simulation shows that the improved algorithm has a higher positioning coverage and positioning precision than the traditional RSSI algorithm.
Thirdly, the DV-Distance positioning algorithm is further studied and simulation analyzed. Due to the algorithm adopts multi-hop distance instead of inter-node Euclidean distance, it results biggish positioning error. In order to solve this problem, the thesis proposes an improved DV-Distance algorithm, which refines initial positioning results by iteration calculation. Compared with the traditional DV-Distance algorithm, positioning performance results show that the improved algorithm improves positioning accuracy, inherits the traditional DV-Distance algorithm excellent positioning coverage, and also better to adapt to the anisotropy of the network structure. However, communication overhead and computation of the improved algorithm should be improved.
Finally, the work of this thesis is concluded and future research work is prospected.
通常按照是否需要预先通过测量来获得节点之间的距离(或角度)信息,把节点定位算法分为基于测距的定位算法和无需测距的定位算法。论文是围绕两种基于测距的定位算法：基于RSSI的定位算法和DV-Distance定位算法展开研究的。首先,论文对无线传感器网络节点定位技术进行了概述,介绍了与节点定位相关的概念、分类方式及测边定位的基本原理。
其次,对基于RSSI的定位算法进行了深入研究和仿真分析,该算法对节点的硬件要求低,实现简单,但是容易受锚节点稀疏、测距误差及通信功率有限的影响而导致定位覆盖率和定位精度不理想,为此,论文提出了一种分级迭代协作定位算法。该改进算法采用协作定位方式来提高定位覆盖率,通过加入锚节点位置优选策略和分级设置邻居节点数量阀值来减少定位误差,MATLAB仿真表明,分级迭代协作定位算法相比传统的基于RSSI定位算法,具有更高的定位覆盖率和定位精度。
再次,论文针对DV-Distance定位算法由于利用节点间多跳累积跳段距离表示欧式距离从而导致定位误差较大的问题,提出了一种进行循环迭代修正计算的改进算法。通过仿真,论文比较了改进的DV-Distance定位算法和传统的DV-Distance定位算法的性能,结果表明改进的DV-Distance算法提高了定位精度,且在继承了传统DV-Distance算法高定位覆盖率同时,还能更好地适应各向异性的网络结构,但是,改进算法的通信开销和计算量还有待改进。
最后,论文对相关研究工作进行了总结,并对未来的研究工作进行了展望。
In wireless sensor networks (WSN), localization information of sensor nodes are essential for WSN monitoring, sensed data is always meaningless without relating to its physical location. In addition, some middle ware services such as location aided routing need localization information. Therefore, it is very important to gain localization of sensor node automatically.
Generally positioning algorithm is divided into range-based algorithm and range-free algorithm according to whether it needs physical measurement to obtain the information about the distance between the nodes or not. The thesis focuses on the range-based algorithm of RSSI-based positioning algorithm and DV-Distance positioning algorithm. First, the thesis summarizes node positioning technology of the WSN, and then mainly introduces node positioning-related concepts and terminology, classification and the basic principles of measurement edge positioning.
Secondly, the RSSI algorithm is deeply discussed and simulation analyzed in this thesis. The algorithm requires low node hardware and its implement is simple. However, the algorithm is vulnerable to the impact of the sparse anchor nodes, ranging error and communication power, which resulted positioning coverage and positioning accuracy not ideal. So this thesis proposes a hierarchical iterative cooperative positioning algorithm. The improved algorithm uses cooperative method to improve positioning coverage and adopts position optimization strategy of the anchor nodes and grading sets the threshold of neighbor number to reduce positioning error. MATLAB simulation shows that the improved algorithm has a higher positioning coverage and positioning precision than the traditional RSSI algorithm.
Thirdly, the DV-Distance positioning algorithm is further studied and simulation analyzed. Due to the algorithm adopts multi-hop distance instead of inter-node Euclidean distance, it results biggish positioning error. In order to solve this problem, the thesis proposes an improved DV-Distance algorithm, which refines initial positioning results by iteration calculation. Compared with the traditional DV-Distance algorithm, positioning performance results show that the improved algorithm improves positioning accuracy, inherits the traditional DV-Distance algorithm excellent positioning coverage, and also better to adapt to the anisotropy of the network structure. However, communication overhead and computation of the improved algorithm should be improved.
Finally, the work of this thesis is concluded and future research work is prospected.
引文
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[18]杜亚江,高立兵.基于最小二乘法的RSSI测距环境参数修正方案.计算机系统应用,2012.21(2)：221-224.
[19]熊少英,于翔,刘乃安等.传感器网络中改进的DV-distance定位算法.数字技术与应用,2011.10：111-112.
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[21]王殊,阎毓杰,胡富平等.无线传感器网络的理论及应用.北京：北京航空航天大学出版社,2007.
[22]许力.无线传感器网络的安全和优化.北京：电子工业出版社,2009.
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[27]M. Youssef, M. Mah and A. Agrawala. Challenges:device-free passive localization for wireless environments. In:Proc of the 13th annual ACM international conference on Mobile computing and networking (MobiCom), Montreal, Quebec, Canada, 2007:222-229.
[28]M. Maroti, B. Kusy, G Balogh, et al. Radio interferometric geolocation. Proc of the 3rd international conference on Embedded networked sensor systems (SenSys), San Diego, USA, 2005:1-12.
[29]L. X. Hu and D. Evans. Localization for mobile sensor networks. Proceedings of the 10th ACM annual international conference on Mobile computing and networking (MobiCom), Philadelphia, Pennsylvania, USA, 2004:45-57.
[30]P. Bahl, N. Padmanabhan. Enhancements to the RADAR user location and tracking system. Technical Report MSR-TR-2000-12, Microsoft Research, Redmond, WA, USA, 2000.
[31]Spec:Smartdust chip with integrated RF communications.2001.
[32]K. Lorincz, M. Welsh. MoteTrack: A Robust, Decentralized Approach to RF-Based Location Tracking. In: Proc of International Workshop on Location and Contex-Awareness, Berlin, Germany: Springer-Verlag Press, 2005. pp. 63-82.
[33]D. Estrin, L. Girod. Robust Range Estimation using Acoustic and Multimodal Sensing. In: Proc of IEEE Int. Conf. on Intelligent Robots and Systems, USA:IEEE Computer Society, 2001.10, Vol.3(No.6):1312-1320.
[34]A. Savvidcs, C. C. Han. Dynamic Fine-Grained Localization in Ad-Hoc Networks of Sensors In: Proc of Mobile Computing and Networking, Italy. ACM Press, 2001.7, 166-179.
[35]罗娟.浅析基于TOA/TDOA的无线传感器网络节点定位算法.武汉工程职业技术学院学报,2009,21(2)：41-43.
[36]L. Xiao, R. F. Li. A Sensor Localization Algorithm in Wireless Sensor Networks Based on Nonmetric Multidimensional Scaling. Journal of Computer Research and Development, 2007, Vol.44(No.34):399-405.
[37]F. B. Wang, L. Shi. Self-Location Systems and Algorithms for Wireless Sensor Networks. Journal of Software, 2005, Vol.16(No.5):857-868.
[38]N. Bulusu, D. Estrub, J Heidemann.Tradeoffs in location support systems:The case for quality-expressive location models for applications. In:Proc of the Ubicomp 2001 Workshop on location Modeling for Applications, Atlanta, 2001.
[39]任智,李晴阳,陈前斌.无线网络衰落和损耗的建模与仿真研究.系统工程与电子技术,2009,31(12)：2813-2819.
[40]H. Lim, J. Hou. Localization for anisotropic sensor networks. Proc of the 24th Annual Joint Conference of the IEEE Computer and Communications (InfoCom), Miami, USA, 2005.
[41]黄河.各向异性无线传感网络节点定位问题研究：[博士学位论文],合肥：中国科学技术大学,2011.
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[53]D. H. Wang, H. D. Jia, F. X. Chen. An Improved DV-Distance Localization Algorithm for Wireless Sensor Networks. Advanced Computer ControI(ICACC), 2010,2nd, International Conference,2010,27-29(5):472-476.
[54]张东红,李科杰,吴德琼.一种改进型DV-Distance自定位算法.弹箭与制导学报,2008,28(3)：275-277.
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[2]张西红,周顺,陈立云等.无线传感网技术及其军事应用.北京：国防工业出版社,2010：142-164.
[3]M. Tubaishat, S. Madria. Sensor networks:an overview. Potentials, IEEE.2003,22(2): 20-23.
[4]R. Shorey, A. L. Ananda, Chan M. C, Ooi W. T. Mobile, Wireless, and Sensor Networks: Technology, Applications, and Future Directions. John Wiley & Sons, Inc.,2006.
[5]H. Frey. Scalable geographic routing algorithms for wireless ad-hoc networks. Network, IEEE.2004,18(4):18-22.
[6]J. Z. Li, J. B. Li, S. F. Shi. Concepts, issues and advance of sensor networks and data management of sensor works. Journal of Software, 2003,14(10):1717-1727.
[7]孙利民,李建中,陈渝等.无线传感器网络.北京：清华大学出版社,2005.
[8]R. Bajaj, S. L. Ranaweera, D. P. Agrawal. GPS:location-tracking technology. Computer. 2002,35(4):92-94.
[9]N. B. Priyantha, A. Chakraborty, H. Balakrishnan. The cricket location-support system. In: Proc of MOBICOM 2000, Boston, MA, ACM, ACM Press,2000,32-43.
[10]J. Krumm, S. Harris, B. Meyers, et al. Multi-camera Multi-person Tracking for EasyLiving. In:Proc of the Third IEEE International Workshop on Visual Surveillance (VS'2000) Dublin Ireland:2000,3-10.
[11]R. J. Orr, G. D. Abowd. The Smart Floor: a Mechanism for Natural User Identification and Tracking. In: Proc of the Conference on Human Factors in Computing Systems, Hague Netherlands:2000,275-276.
[12]K. Yedavalli, B. Krishnamachari. Sequence-based localization in wireless sensor networks. IEEE Transactions on Mobile Computing, 2008, 7(1):81-94.
[13]D. Nicolescu, B. Nath. Ad-hoc positioning systems(APS). IEEE GLOBECOM'01,2001, San Antonio, Texas,2001,5:2926-2931
[14]D. Nicolescu, B. Nath. DV based positioning in Ad-hoc networks. Journal of Telecommunication System, 2003,22(1-4):267-280
[15]C. Savarese, J. M Rabaey, J. Beutel. Locationing in Distributed Ad-Hoc Wireless Sensor Network. In:Proc of the 2001 IEEE International Conference on Acoustics, Speech and Signal, Salt Lake, USA, 2001.2037-2040.
[16]C. Savarese, J. M. Rabaey, K. Langendoen. Robust Positioning Algorithms for Distributed Ad-Hoc Wireless Sensor Networks. In:Proc of the USENIX Technical Annual Conference. Monterey, USA, 2002.317-327.
[17]任维政,徐连明,邓中亮等.基于RSSI的测距差分修正定位算法.传感技术学报,2008.21(7)：1247-1250.
[18]杜亚江,高立兵.基于最小二乘法的RSSI测距环境参数修正方案.计算机系统应用,2012.21(2)：221-224.
[19]熊少英,于翔,刘乃安等.传感器网络中改进的DV-distance定位算法.数字技术与应用,2011.10：111-112.
[20]付华,孙蕾.无线传感器网络DV-Distance定位算法.计算机系统应用,2010.19(3)：56-58.
[21]王殊,阎毓杰,胡富平等.无线传感器网络的理论及应用.北京：北京航空航天大学出版社,2007.
[22]许力.无线传感器网络的安全和优化.北京：电子工业出版社,2009.
[23]李晓维.无线传感器网络技术.北京：北京航空航天大学出版社,2007.
[24]T. He, C. Huang, B. M. Blum, J. A. Stankovic, T Abdelzaher. Range-free localization schemes for large scale sensor networks.In:Proc 9th Annual Int'l Conf on Mobile Computing and Networking(MobiCom), San Diego, CA.2003:81-85.
[25]N. B. Priyantha, H. Balakrishnam, E. Demaine, S. Teller. Anchor-free distributed localization in sensor networks. Technical Report MIT-LCS-TR-892, MIT Lab for Computer Science, April 2003.
[26]于宏毅,李鸥,张效义等.无线传感器网络理论、技术与实现.北京：国防工业出版社,2008.
[27]M. Youssef, M. Mah and A. Agrawala. Challenges:device-free passive localization for wireless environments. In:Proc of the 13th annual ACM international conference on Mobile computing and networking (MobiCom), Montreal, Quebec, Canada, 2007:222-229.
[28]M. Maroti, B. Kusy, G Balogh, et al. Radio interferometric geolocation. Proc of the 3rd international conference on Embedded networked sensor systems (SenSys), San Diego, USA, 2005:1-12.
[29]L. X. Hu and D. Evans. Localization for mobile sensor networks. Proceedings of the 10th ACM annual international conference on Mobile computing and networking (MobiCom), Philadelphia, Pennsylvania, USA, 2004:45-57.
[30]P. Bahl, N. Padmanabhan. Enhancements to the RADAR user location and tracking system. Technical Report MSR-TR-2000-12, Microsoft Research, Redmond, WA, USA, 2000.
[31]Spec:Smartdust chip with integrated RF communications.2001.
[32]K. Lorincz, M. Welsh. MoteTrack: A Robust, Decentralized Approach to RF-Based Location Tracking. In: Proc of International Workshop on Location and Contex-Awareness, Berlin, Germany: Springer-Verlag Press, 2005. pp. 63-82.
[33]D. Estrin, L. Girod. Robust Range Estimation using Acoustic and Multimodal Sensing. In: Proc of IEEE Int. Conf. on Intelligent Robots and Systems, USA:IEEE Computer Society, 2001.10, Vol.3(No.6):1312-1320.
[34]A. Savvidcs, C. C. Han. Dynamic Fine-Grained Localization in Ad-Hoc Networks of Sensors In: Proc of Mobile Computing and Networking, Italy. ACM Press, 2001.7, 166-179.
[35]罗娟.浅析基于TOA/TDOA的无线传感器网络节点定位算法.武汉工程职业技术学院学报,2009,21(2)：41-43.
[36]L. Xiao, R. F. Li. A Sensor Localization Algorithm in Wireless Sensor Networks Based on Nonmetric Multidimensional Scaling. Journal of Computer Research and Development, 2007, Vol.44(No.34):399-405.
[37]F. B. Wang, L. Shi. Self-Location Systems and Algorithms for Wireless Sensor Networks. Journal of Software, 2005, Vol.16(No.5):857-868.
[38]N. Bulusu, D. Estrub, J Heidemann.Tradeoffs in location support systems:The case for quality-expressive location models for applications. In:Proc of the Ubicomp 2001 Workshop on location Modeling for Applications, Atlanta, 2001.
[39]任智,李晴阳,陈前斌.无线网络衰落和损耗的建模与仿真研究.系统工程与电子技术,2009,31(12)：2813-2819.
[40]H. Lim, J. Hou. Localization for anisotropic sensor networks. Proc of the 24th Annual Joint Conference of the IEEE Computer and Communications (InfoCom), Miami, USA, 2005.
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