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无线传感器网络节点定位算法的研究
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摘要
基于非测距的定位算法是无线传感器网络节点定位算法的研究热点之一,目前关于非测距的DV-Hop算法的理论和现实研究主要存在两个问题:国内外虽有很多学者对该算法进行了相关改进,但从整体上考虑效率都不太理想;人们对DV-Hop算法的改进基本集中在二维空间,而现实应用都在三维空间中。因此,为了使DV-Hop算法及其改进算法的应用更为广泛,在不断提高算法性能外,还需要将这些二维算法扩展到三维空间,再将其应用于实际生活中。
     本文在阅读大量参考文献的基础上,利用多种定位优化方法和参与定位的信标节点有效性的判别方法,围绕怎样提高节点定位算法的定位精度和覆盖率,主要做了如下的研究工作:
     (1)从无线传感器网络的定位技术入手,对节点间的测距技术和定位计算方法的优缺点和适应情况进行分析,总结出节点定位算法的性能评价标准,为定位算法的精度改进和性能评价作了准备工作。
     (2)对DV-Hop算法的定位过程、网络生存力、定位精度、以及各向异性稀疏网络中的各项性能指标进行仔细研究。通过分析各种DV-Hop改进算法的优缺点,引入限定跳数、共线性判断、归一化加权、总体最小二乘等方法对定位的各个阶段进行改进和优化,提出了一种二维DV-Hop改进算法,并通过实验仿真验证该算法的正确性和高效性。
     (3)将DV-Hop算法扩展到三维空间,提出一种新型的基于移动信标的三维DV-Hop算法。通过引入移动代理技术计算信标节点的最小跳数,减少网络的数据流量;按信标节点的数量分情况利用平移坐标法、画圆法或总体最小二乘法来定位未知节点坐标,提高定位的覆盖率,并通过仿真实验来验证该算法的有效性和实用性。
The based on the range-free positioning algorithm is one of the research focuses in the node localization algorithm of the wireless sensor network. There mainly have two problems in the theory and practical research of the range-free DV-Hop algorithm at present. Many scholars at home and abroad have been proposed some related improved algorithms, but from the whole consideration those algorithms are not very satisfactory. The improvements of the DV-Hop algorithms are in two-dimensional space basically, but the real applications are concentrated in three-dimensional space. So in order to make the applications of the DV-Hop algorithm and its improvement algorithms is more extensive, not only improve these algorithms performance constantly, but also need extend these two-dimensional algorithms to three-dimensional space, and then apply it to real life.
     On the basis of reading a lot of reference, this paper using a variety of positioning optimization methods and the judgmental methods of the beacon nodes’validity, focus on how to improve the positioning accuracy and coverage of the node localization algorithm, the main studies of this paper are as follows.
     Firstly, start from the positioning technology of the wireless sensor network, analyzing the advantages, disadvantages and adaptation of the technology for the distance between nodes and the position calculation methods, and summed up the performance evaluation criteria of the node positioning algorithm, made a preparation in the positioning algorithm’s accuracy improving and performance evaluating.
     Secondly, studying the positioning process, the network survival, the positioning accuracy of the DV-Hop algorithm, and the performance indicators in the anisotropic sparse network, analyzing the degree of the DV-Hop improved algorithms' pros and cons in theoretical, introducing the limited number of the hops, collinearity judgments, normalized weighting, total least squares and other methods to improving and optimizing the various stages of positioning, proposed an improving DV-Hop algorithm in two-dimensional, and through the simulation experiments to verify the correctness and efficiency of this algorithm.
     Lastly,extending the DV-Hop algorithm to three-dimensional space, proposed a new three-dimensional DV-Hop algorithm based mobile beacon. In order to reduce the network traffic, introducing the mobile agent technology to calculate the minimum hops of the beacon node. Using the translation coordinate method, draw circle method, and total least squares to locate the unknown nodes' coordinates according to the number of the beacon nodes, to improve the coverage. And verified the effectiveness and practicality of this algorithm by the simulation experiments.
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