无线传感器网络三维DV-Hop定位算法研究

发布时间：2018-01-18 07:26

本文关键词：无线传感器网络三维DV-Hop定位算法研究　出处：《江西理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：现如今无线传感器网络(Wireless Sensor Network,WSN)已成为IT行业中研究的热门方向,而它的一项核心性和支撑性技术就是节点定位技术。这一技术也是无线传感器网络在进行结构监测、环境监测、战场监视和动物跟踪等许多领域被广泛应用的前提。因此,实现节点高精度定位,明确事情发生的具体所在地对于传感器节点来说是最根本的功能之一。但现在大多算法都限制在二维平面的定位,对于三维复杂环境网络的定位算法相对较少,而三维网络定位比二维平面定位对于位置信息的要求更加充分,其空间的复杂度和对网络的连通度、密度也相应的增加,因此二维平面情况下的定位算法不能直接应用在三维环境中。本文主要把不需要测距的DV-Hop算法中心思想延伸至三维环境网络中,经过分析探讨3D-DV-Hop算法于定位过程当中所具有的缺陷和导致其出现误差原因,再经过理论性学习和研究,提出了针对性的改进方法。本文主要内容和所做工作如下:(1)对WSN定位技术的基本理论、算法分类、研究状况及应用进行了系统论述。重点通过对3D-DV-Hop算法基本思想、性能实现等进入深入探讨及研究,以此来奠定实现本文算法的理论基础。(2)为了降低三维空间网络中算法对未知节点所造成的定位误差,提高3D-DV-Hop算法定位精度,提出基于节点误差加权和三维双曲线定位的3D-DV-Hop改进方法。该算法首先采用对误差进行加权的办法处理待定位节点的平均跳距,然后分类选取待定位节点与锚节点间的跳段距离,最后将二维双曲线法拓展到三维环境网络中求解定位节点的坐标。仿真实验结果表明,改进算法在三维WSN环境中可以对待定位节点进行有效的定位,相较于对比文献有更高的定位精度。(3)由于WSN中节点一般都是杂乱且无规律的,网络中边缘地区的节点往往由于得不到锚节点确切坐标或者得不到充分能够完成定位的锚节点确切坐标而使得节点定位精度降低。针对这一情况,本文主要思想是在网络周边特定区域人工安置相应锚节点,以达到提高周边节点完成定位的数量,进而提高网络的整体定位精度,然后再使用改进的误差加权的方法获取待定位节点的有效平均跳距。实验数据表明,在不增加硬件设施和计算量的情况下,本文方法相较于3D-DV-Hop算法有很大的提高。
[Abstract]:Nowadays, Wireless Sensor Network (WSNs) has become a hot research direction in IT industry. One of its core and supporting technologies is node location technology, which is also the structure monitoring and environmental monitoring of wireless sensor networks. Battlefield surveillance and animal tracking are widely used in many fields. It is one of the most fundamental functions for sensor nodes to specify the location of what happened. However, most of the algorithms are limited to the location of two-dimensional plane, and there are relatively few localization algorithms for three-dimensional complex environment network. Three-dimensional network location requires more information than two-dimensional plane positioning, and its space complexity, connectivity and density also increase accordingly. Therefore, the localization algorithm in two-dimensional plane can not be directly applied in three-dimensional environment. In this paper, the central idea of DV-Hop algorithm which does not need ranging is mainly extended to three-dimensional environment network. Through the analysis of the 3D-DV-Hop algorithm in the localization process of defects and causes of errors, and then through theoretical learning and research. The main contents and work of this paper are as follows: 1) the basic theory and algorithm classification of WSN positioning technology. The research status and application are discussed systematically, especially through the basic idea of 3D-DV-Hop algorithm, performance realization and so on into the in-depth discussion and research. In order to reduce the location error caused by the algorithm to unknown nodes in three-dimensional space network, improve the positioning accuracy of 3D-DV-Hop algorithm. An improved 3D-DV-Hop method based on node error weighting and 3D hyperbolic positioning is proposed. Then the hopping distance between the node to be located and the anchor node is classified and the two-dimensional hyperbolic method is extended to solve the coordinates of the location node in the three-dimensional environmental network. The simulation results show that. The improved algorithm can effectively locate the location nodes in 3D WSN environment. Compared with the literature, the improved algorithm has a higher positioning accuracy. (3) because the nodes in WSN are generally chaotic and irregular. Nodes in the edge of the network often have low accuracy due to the lack of the exact coordinates of the anchor nodes or the exact coordinates of the anchor nodes that can be fully positioned. The main idea of this paper is to manually place anchor nodes in specific areas around the network in order to increase the number of peripheral nodes to complete the positioning and then improve the overall positioning accuracy of the network. Then the improved error weighting method is used to obtain the effective average hopping distance of the node to be located. The experimental data show that the hardware facilities and computation are not increased. Compared with the 3D-DV-Hop algorithm, the proposed method is much better than the 3D-DV-Hop algorithm.
【学位授予单位】：江西理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP212.9;TN929.5

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