共查询到18条相似文献,搜索用时 156 毫秒
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针对Distance Vector-Hop (DV-Hop) 定位算法存在较大定位误差的问题,该文提出了一种基于误差距离加权与跳段算法选择的遗传优化DV-Hop定位算法,即WSGDV-Hop定位算法。改进算法用基于误差与距离的权值处理锚节点的平均每跳距离;根据判断的位置关系选择适合的跳段距离计算方法;用改进的遗传算法优化未知节点坐标。仿真结果表明,WSGDV-Hop定位算法的性能明显优于Distance Vector-Hop (DV-Hop) 定位算法,减小了节点定位误差、提高了算法定位精度。 相似文献
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为了减小DV-Hop算法在无线传感器网络节点定位中的误差,提出了一种基于混合人工蜂群算法的改进算法。该算法结合了粒子群算法收敛速度快和蜂群算法搜索能力强的特性,首先通过DV-Hop算法估计锚节点与未知节点之间的距离,然后采用粒子群算法计算未知节点的初始位置,最后利用蜂群算法进行迭代求精,从而实现基于不同距离测量方法的总体优化。仿真结果表明,改进算法的定位精度较DV-Hop算法和基于粒子群的定位算法有明显改善。 相似文献
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针对距离矢量跳距(Distance Vector Hop, DV-Hop)定位算法通信半径选择不合理导致平均跳距和定位误差较大的问题,提出一种基于混沌粒子群改进的DV-Hop定位算法,利用混沌映射的遍历性和随机性实现粒子的局部深度搜索,避免粒子群算法陷入局部最优。通过混沌粒子群优化(Particle Swarm Optimization, PSO)算法迭代求解所有信标节点的通信半径,引入混沌理论调整非线性惯性权重优化搜索过程,通过混沌搜索和混沌扰动迭代求解信标节点的最佳通信半径;通过极大似然估计(Maximum Likelihood Estimate, MLE)法计算的平均定位误差作为混沌粒子群算法的适应值函数;使用费希尔矩阵求解的误差下限作为约束条件求解适应值函数,同时把平均通信半径作为节点能耗模型的阈值来降低节点能量消耗。仿真实验表明,提出的算法在不增加算法复杂度的前提下能够在定位精度方面提升近58%,节点能量消耗方面降低近24%。 相似文献
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DV-Hop算法是一种低成本、低定位精度的无需测距定位算法,在粗精度定位中应用广泛。为提高DV-Hop算法定位精度,从减小锚节点的平均每一跳距离误差和减小未知节点平均每一跳校正值误差两方面考虑。首先,用最佳指数值下的公式计算锚节点平均每一跳距离。然后,将未知节点的校正值加权处理,使所有的锚节点根据与未知节点距离的远近影响校正值的大小。MATLAB实验证明,改进的基于最佳指数值下的加权DV-Hop算法比DV-Hop算法、加权DV-Hop、最佳指数值下DV-Hop算法定位精度分别提高2%左右、1.65%左右、1.15%左右,同时不会增加网络硬件成本。 相似文献
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节点定位是无线传感器网络(Wireless Sensor Networks,WSNs)的关键技术之一。针对传统距离向量跳段(Distance Vector Hop,DV-Hop)算法定位误差偏大的问题,提出了一种改进蜜獾算法(Honey Badger Algorithm,HBA)与DV-Hop相结合的算法。首先,针对网络平均跳距估计不准的问题,依据锚节点比例对未知节点平均跳距进行分段修正。其次,采用改进型的HBA替换最小二乘法估算未知节点的位置,进一步降低计算误差。初始化蜜獾个体时引入Sobol序列,增加初始种群的多样性;为了加强HBA的局部搜索能力,引入了螺旋更新策略。最后,采用镜像策略规避估算位置越界的情况。结果表明,所提算法相较于传统DV-Hop算法、平均跳距修正的DV-Hop算法和基于粒子群优化(Particle Swarm Optimization,POS)的DV-Hop算法具有更高的定位精度和稳健性。 相似文献
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一种基于加权处理的无线传感器网络平均跳距离估计算法 总被引:6,自引:0,他引:6
定位技术是无线传感器网络的关键技术之一,传统DV-Hop定位算法只考虑了最近一个锚节点估计的平均跳距离值,而单个锚节点估计的平均跳距离值无法准确地反映网络的实际平均跳距离。本文提出了一种基于加权处理的平均跳距离估计算法,考虑多个锚节点估计的平均跳距离值,根据距离未知节点的跳数进行加权,使网络平均跳距离的估计更加准确,从而提高定位精度。仿真结果表明,与DV-Hop算法的平均跳距离估计算法相比,本文算法更准确地估计平均跳距离,降低了均方根误差,并提高了定位精度。 相似文献
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本文在基于三维DV-Hop定位算法的基础上,提出了一种基于平均跳距修正的三维DV-Hop定位算法.该算法除了将DV-Hop定位算法从二维空间扩展到三维空间以外,还对未知节点到锚节点的平均每跳距离作了相应的修正,仿真结果表明:与原始算法相比改进后的算法定位精度有了一定提高. 相似文献
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An improved DV-HOP localization algorithm is proposed based on the traditional DV-HOP localization algorithm in the paper. There will be a big error that using the nearest anchor node’s average hop distance instead of the average hop distance of all the anchor nodes that involved in the localizing in the traditional DV-HOP localization algorithm. Therefore, the improved algorithm introduces threshold M, it uses the weighted average hop distances of anchor nodes within M hops to calculate the average hop distance of unknown nodes. In addition, the positioning results are corrected in the improved algorithm. The simulation results show that the new localization algorithm effectively improves the positioning accuracy compared with the traditional DV-HOP localization algorithm, it is an effective localization algorithm in the wireless sensor networks. 相似文献
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Node localization is one of the most critical issues for wireless sensor networks, as many applications depend on the precise location of the sensor nodes. To attain precise location of nodes, an improved distance vector hop (IDV-Hop) algorithm using teaching learning based optimization (TLBO) has been proposed in this paper. In the proposed algorithm, hop sizes of the anchor nodes are modified by adding correction factor. The concept of collinearity is introduced to reduce location errors caused by anchor nodes which are collinear. For better positioning coverage, up-gradation of target nodes to assistant anchor nodes has been used in such a way that those target nodes are upgraded to assistant anchor nodes which have been localized in the first round of localization. For further improvement in localization accuracy, location of target nodes has been formulated as optimization problem and an efficient parameter free optimization technique viz. TLBO has been used. Simulation results show that the proposed algorithm is overall 47, 30 and 22% more accurate than DV-Hop, DV-Hop based on genetic algorithm (GADV-Hop) and IDV-Hop using particle swarm optimization algorithms respectively and achieves high positioning coverage with fast convergence. 相似文献
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Guangjie Han Chenyu Zhang Tongqing Liu Lei Shu 《Wireless Communications and Mobile Computing》2016,16(6):682-702
Localization is an essential and major issue for underwater acoustic sensor networks (UASNs). Almost all the applications in UASNs are closely related to the locations of sensors. In this paper, we propose a multi‐anchor nodes collaborative localization (MANCL) algorithm, a three‐dimensional (3D) localization scheme using anchor nodes and upgrade anchor nodes within two hops for UASNs. The MANCL algorithm divides the whole localization process into four sub‐processes: unknown node localization process, iterative location estimation process, improved 3D Euclidean distance estimation process, and 3D DV‐hop distance estimation process based on two‐hop anchor nodes. In the third sub‐process, we propose a communication mechanism and a vote mechanism to determine the temporary coordinates of unknown nodes. In the fourth sub‐process, we use two‐hop anchor nodes to help localize unknown nodes. We also evaluate and compare the proposed algorithm with a large‐scale localization algorithm through simulations. Results show that the proposed MANCL algorithm can perform better with regard to localization ratio, average localization error, and energy consumption in UASNs. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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Anchor‐free distance estimation: A new approach to distance estimation for multihop ad hoc wireless networks 下载免费PDF全文
Stathis Mavridopoulos Petros Nicopolitidis Georgios Papadimitriou 《International Journal of Communication Systems》2018,31(13)
In ad hoc wireless networks, devices that normally cannot directly communicate route their messages through intermediate nodes. The number of those nodes is called hop count, a useful metric in estimating the distance between 2 nodes. Current methods usually depend on special nodes, called anchors, that need accurate localization information, in order to calculate an estimate for the average distance traversed per hop. The drawback of this approach is that anchor nodes increase the overall cost and complexity of the system. To address this problem, this letter proposes a novel, anchor node–free algorithm that can achieve a useful estimate for actual distance between 2 nodes, by analytically finding an estimate for the average maximum distance traveled per hop and multiplying with the hop count. The only requirement is the a priori knowledge of the networks' node density and the node range. The performance of our method is compared with a recent anchor node–based method and is shown to yield similar location estimation accuracy, despite the fact that it does not use anchor nodes. 相似文献
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Considering energy consumption, hardware requirements, and the need of high localization accuracy, we proposed a power efficient range-free localization algorithm for wireless sensor networks. In the proposed algorithm, anchor node communicates to unknown nodes only one time by which anchor nodes inform about their coordinates to unknown nodes. By calculating hop-size of anchor nodes at unknown nodes one complete communication between anchor node and unknown node is eliminated which drastically reduce the energy consumption of nodes. Further, unknown node refines estimated hop-size for better estimation of distance from the anchor nodes. Moreover, using average hop-size of anchor nodes, unknown node calculates distance from all anchor nodes. To reduce error propagation, involved in solving for location of unknown node, a new procedure is adopted. Further, unknown node upgrades its location by exploiting the obtained information in solving the system of equations. In mathematical analysis we prove that proposed algorithm has lesser propagation error than distance vector-hop (DV-Hop) and other considered improved DV-Hop algorithms. Simulation experiments show that our proposed algorithm has better localization performance, and is more computationally efficient than DV-Hop and other compared improved DV-Hop algorithms. 相似文献