无线传感器网络分布式节点定位算法研究
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摘要
集成了传感器、嵌入式计算、网络和无线通讯技术而成的无线传感器网络是一种全新的信息获取和处理技术,无线传感器网络可以自组织网络拓扑结构,节点间通过协同工作能够实时监测,感知和采集各种环境或监测对象的信息,并对其进行处理。无线传感器网络在国防、环境监测、空间探索、医疗卫生、精细农业、交通管理、制造业、反恐抗灾等领域具有广阔的应用前景。
     无线传感器网络节点定位问题,是无线传感器网络重要的共性支撑技术之一,对其研究具有非常重要的意义。本文对已有的无线传感器网络分布式节点定位算法进行了深入的研究,跟踪了国内外在该领域的研究进展,对已有的几种典型的分布式节点定位算法做出了深入分析,定量地比较了算法的性能。并在此基础上提出了一种新的分布式节点定位算法。该算法主要在两个方面改进了定位性能:一是从提高定位精度方面,结合了相关数学原理,引入了加权最小二乘估计的方法,建立了加权定位算法的方案,以抑制迭代定位过程中累积误差的影响;二是从提高定位覆盖率方面,建立了利用两个锚节点和一个连通限制条件定位的算法模型,与三边测量定位(trilateration)、多边测量定位(multilateration)以及Euclidean算法相结合,确立了一种高覆盖率的分布式节点定位算法。通过在NS-2仿真平台上对算法的仿真实验,统计分析了各种因素对算法定位性能的影响,仿真结果表明,该算法具有良好的性能。
     在实用化的定位系统研究方面,在实际的原型实验平台上实现了DV-hop定位算法,做出了实现定位系统的初步探索,奠定了进一步研究的良好基础。文章的最后对全文做了总结并对将来的研究方向做出了展望。
WSN(Wireless Sensor Network), which is made by the convergence of sensor, embedded computation, networks and wireless communication technologies, is a novel technology about acquiring and processing information. WSN have the ability to collaboratively monitoring, sensing, collecting and processing information of the physical world through ad-hoc deployment of numerous tiny, intelligent, wirelessly networked sensor nodes. Potential applications of such sensor networks span many domains: military surveillance;environmental monitoring (air, water, soil, chemistry);smart spaces;physiological monitoring;precision agriculture;transportation;factory instrumentation.Node localization provided the foundation for many application of WSN. In this paper, we first discussed several have been proposed distributed localization algorithms and quantitatively analyzed the performance. Secondly, a new distributed localization algorithms being proposed. Our approach improved the localization performance from two aspect: first, to restrain error accumulation during iterated localization process, we applying WLSE (Weighted Least Square Estimates) to node localization algorithm and choose proper weight coefficient to reduce location error;second, to improve localization coverage rate, we established a coordinate compute model based on two anchor and a connection constrain condition and integrated it with trilateration /multilateration and Euclidean algorithm.After that, we implemented DV-hop localization algorithm on our test-beds and evaluate and demonstrate the effectiveness of the localization system. Finally, we sum up this paper and the directions of research in this area are introduced.
引文
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