一种基于Euclidean的无线传感器网络三维定位算法

 针对传感器网络在三维空间的应用,基于Euclidean定位算法,提出了对无线传感器节点进行三维定位的算法.将计算未知节点与锚节点间距离问题抽象为求解六面体顶点间的距离.根据问题的抽象,本文使用所提出的坐标法进行求解,并采用循环迭代的方式来提高节点的定位比例.仿真结果表明,三维空间的Euclidean定位算法各项指标均为良好,能有效地实现三维环境中的传感器节点定位.     

大规模WSNs多层定位模型与误差分析

 针对大规模无线传感器网络的定位问题,提出了一种多层定位模型.首先根据网络中节点的不同应用与软硬件特性将节点划分为多个定位层次,并按照各层次的特性设计相应的定位算法,然后融合各定位层次为整个无线传感器网络的定位.分析研究了各层的定位误差以及层与层之间的误差传播和积累,并给出了降低这些误差的方法.仿真结果表明,分层定位模型能较好地处理误差积累问题,对节点定位误差和测距误差具有一定的容错性,在通信级节点点位误差为0.05、RSSI测距误差为0.3的情况下,相比DV-Hop算法平均点位误差减小16%.     

改进的DV-Hop无线传感网络节点定位算法

针对传感器部署密度大、分布不均匀,DV-Hop定位算法误差大等问题,提出了一种改进DV-Hop的无线传感器节点定位算法.首先采用DV-Hop算法对未知传感器节点位置进行计算,然后在采用遗传算法对DV-Hop定位的误差进行修正.仿真结果表明,改进DV-Hop算法提高了节点的定位精度,降低定位的误差,更能真实地反映传感器网络节点的实际分布情况.     

一种降低定位误差的无线传感器网络节点定位改进算法

本文针对无线传感器网络节点的定位精度问题,提出了一种采用误差修正的方法来降低累积距离误差和定位误差的传感器网络节点定位改进算法,给出了该算法的基本原理与实现方法.该算法在不增加原算法通信量及计算复杂度的基础上提高了定位精度.仿真结果显示,在同等条件下,本文提出的算法定位精度提高了5～10%.     

基于接收信号强度的WSN概率定位算法

定位对无线传感器网络的应用、操作和管理发挥着至关重要的作用.针对传感器节点的定位,提出了一种基于接收信号强度的概率定位算法.介绍了算法原理及实现过程,讨论了信标节点分布对该算法性能的影响,最后比较了本概率定位算法和最小二乘定位算法在传感器节点定位性能上的优劣.仿真结果表明,信标节点分布对未知节点的定位误差具有较大的影响,本定位算法的性能要优于最小二乘定位算法.     

三维无线传感器网络节点的序列垂心定位

针对无线传感器网络的节点自定位技术提出了一种三维序列垂心算法,该算法利用锚节点两两之间的垂直平分面将定位空间分为边、面和体三类区域,缩小了未知节点可能存在的范围,并在所在范围内再次求出离未知节点最近三点组成的三角形的垂心作为未知点位置的估计。该算法改善了二维序列算法误差较大的问题,且不需要增加硬件设施来实现特殊的功能。仿真结果表明,该算法可以达到较高的定位精度,能够满足三维空间中未知节点定位的应用需要。     

基于改进DV-Hop的无线传感器网络节点定位算法

针对DV-Hop距算法定位误差大的难题,提出一种改进离估计误差,并利用DV-Hop的传感器节点定位算法。首先修正知节点与信标节DV-Hop算法对节点进行定位;然后对进V-Hop算法定位误差行校正,最后在Matlab 2012平台上对算法性能进行仿真分析。仿真结果表明,本文算法可以较好地克服DV-Hop算法存在的不足,提高了传感器节点的定位精度。     

基于萤火虫群的无线传感器网络节点定位方法

针对无线传感器网络中节点定位精度不高的问题,基于萤火虫群算法提出了一种新的定位方法(Node Localization based on Glowworm Swarm,NLGS).该方法首先结合锚点信息,给出了三维空间下未知节点位置的计算方法和误差优化模型,并利用萤火虫群算法对目标函数进行求解,以达到快速收敛的目的.通过利用OPNET进行仿真实验,研究了影响该方法的关键因素.实验结果表明,相比于其他算法,NLGS具有较好的适应性.     

无线传感器网络中序列定位新算法的研究

 在无线传感器网络中传统的序列定位算法将空间划分为点、边和面等不同的区域,但以面重心为未知点定位时误差较大. 针对此节点自定位算法的误差问题,提出了一种序列定位与三点垂心法相结合的节点定位改进算法,给出了该算法的基本原理与实现方法. 通过进一步判断排列顺序相关系数的三个最大值,求出离未知节点“最近”的三个区域的重心构成的三角形的垂心,进一步滤掉节点不可能存在的区域,减少定位误差. 该算法增加了计算未知节点精确位置的计算量,但不需要增加节点的硬件条件和计算复杂度. 仿真结果表明,与传统序列定位算法和三点垂心法相比,新算法可以明显的提高定位精度,随着锚节点数的增多,定位误差呈大幅度的减少.     

基于几何特性的非直达波定位算法

现有的无线传感器网络定位算法未考虑非直达波误差,由于无线传感器网络中任意两节点之间都可能存在通信,因此其定位问题比无线蜂窝通信系统更为复杂.为了解决现有节点定位算法未考虑非直达波误差的问题,依据分布式节点定位体系结构,提出非直达波环境下的基于几何特性的节点定位算法.该算法将不等式约束、非直达波统计特征和稳健代价函数等非直达波抑制准则,与无线传感器节点定位手段如距离测量矩阵相结合,仿真结果表明,它在无线传感器网络定位应用中要优于其他的定位算法.     

一种基于射线模型的图像定位系统

图像定位技术在现实中有广泛的应用,如导航、路径规划、虚拟现实等.对于用户而言,只需拍摄一张图像即可实现定位.本文提出了一种基于射线摄像机模型的图像定位系统,包含基于射线模型的三维重构算法和基于位姿图优化的图像定位方法.提出的三维重构算法利用射线模型的内在几何性质,能够处理全景和鱼眼等广角摄像机模型,降低采集和重构的代价,提升重构的效果.基于位姿图的定位方法融合了图像与点云匹配的信息和图像间相对位姿信息实施定位,得到更高的定位精度.实验证明本文方法的有效性.     

MANCL: a multi‐anchor nodes collaborative localization algorithm for underwater acoustic sensor networks

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.     

CT-based software for 3-D localization and reconstruction instepping source brachytherapy

Describes innovative software for catheter localization and 3D reconstruction in stepping-source brachytherapy applications. The patient information is a set of computed tomography (CT) slices, scanned during the implantation of brachytherapy catheters. Catheter geometry and patient anatomy are exported for use with dose calculation software modules. The errors produced by the system are also encouragingly low. Time savings were achieved compared with other traditional reconstruction techniques. Various automated procedures, 3D graphics and a user-friendly GUI have contributed to providing a powerful, comprehensive software tool that is directly useable in clinical practice     

Multiple-sensor integration for rapid and high-precision coordinatemetrology

The development of a multiple-sensor coordinate measuring system (CMM) is introduced and its applications to automated part localization and rapid surface digitization are experimentally demonstrated. The developed multiple-sensor CMM is characterized by an integrated use of a high-precision CMM equipped with a motorized touch probe, and a 3D active vision system, advanced computational software, and the associated electronics. The 3D active vision system is capable of digitizing surface coordinates of objects having multiple features; thus intelligent feature recognition algorithms can be applied to extract the global surface information of the object. The obtained information can be subsequently used to automatically guide the touch probe for rapid coordinate data acquisition and to strategically control the coordinate measuring machine for high precision sampling of critical surface area. In this paper, the information automation for the multiple-sensor integrated system is demonstrated in part localization     

Localization in terrestrial and underwater sensor‐based m2m communication networks: architecture,classification and challenges

Localizing machine‐type communication (MTC) devices or sensors is becoming important because of the increasing popularity of machine‐to‐machine (M2M) communication networks for location‐based applications. These include such as health monitoring, rescue operations, vehicle tracking, and wildfire monitoring. Moreover, efficient localization approaches for sensor‐based MTC devices reduce the localization error and energy consumption of MTC devices. Because sensors are used as an integral part of M2M communication networks and have achieved popularity in underwater applications, research is being conducted on sensor localization in both underwater and terrestrial M2M networks. Major challenges in designing underwater localization techniques are the lack of good radio signal propagation in underwater, sensor mobility management, and ensuring network coverage in 3D underwater M2M networks. Similarly, predicting the mobility pattern of MTC devices, trading‐off energy consumption and location accuracy pose great design challenges for terrestrial localization techniques. This article presents a comprehensive survey on the current state‐of‐the‐art research on both terrestrial and underwater localization approaches for sensor‐based MTC devices. It also classifies localization approaches based on several factors, identifies their limitations with potential solutions, and compares them. Copyright © 2015 John Wiley & Sons, Ltd.     

3D Single‐Molecule Imaging of Transmembrane Signaling by Targeting Nanodiamonds

Fluorescent nanodiamonds (FNDs) have recently emerged as promising probes for imaging applications. A significant limitation of the applications is the use of FNDs as endogenous protein tags for long‐term 3D single molecule imaging to gain critical understanding of the underlying mechanism such as transmembrane signaling. Here, FNDs conjugated with transforming growth factor (TGF) are developed as an imaging probe for endogenous TGF‐beta (TGF‐β) receptor labeling and 3D single molecule imaging. FNDs display higher localization accuracy in 3D than organic dye making it an ideal candidate for nanoscopy applications. The real‐time dynamics of TGF‐β receptors after binding conjugated FNDs and in cells treated with therapeutic small molecule kinase inhibitors (SMI) are further monitored. The Bayesian treatment of hidden Markov models confirms and quantifies three different diffusive states and the transition rates between the three states. The kinetic reaction favors a faster diffusion population after therapeutic SMI treatment. The results show that immobilized TGF‐β is critical for active signaling. SMI treatment can release TGF‐β from the signaling complex. The results demonstrate the reported method that provides a powerful technique to study the mechanism of transmembrane signaling and valuable insights for developing better therapeutic for TGF‐β‐associated cancers.     

PSD – probabilistic algorithm for mobile robot 6D localization without natural and artificial landmarks based on 2.5D map and a new type of laser scanner in GPS-denied scenarios

This paper presents an approach to mobile robot 6D localization based on a 3D laser scanner in GPS-denied scenarios. Commonly, 6D localization using laser scanners is performed with the use of extraction and association of the features or by comparison of the whole scans (very often off-line) using the ICP algorithm or its modifications. However, in some unstructured non-urbanized rough terrain environments, feature extraction does not seem to be reliable enough. For such kind of environment, we present a new method to mobile robot localization in GPS-denied applications, called PSD (Point-to-Surfel Distance). Unlike state of the art localization methods using laser scanners, we consider every single laser scanner measurement as an observation and use Point-to-Surfel Distance for correction of position and orientation of the robot. Mobile robot localization is based on a specific representation of the terrain in the 2.5D surfel map (terrain height and inclination). The simulation tests compared our method using extended Kalman filter (EKF) and single laser scanner measurements with an up-to-date method using particle filter (PF) and comparing the scan lines with the reference map and with another method using Gaussian mixture maps. The tests confirmed that the proposed method provides satisfying results for GPS-denied scenarios in rough terrain without extractable landmarks and our method is thirty times faster than the PF method (serial implementation). KITTI benchmark tests and real terrain experiments confirmed its usefulness and advantages as well.     

无线传感器网络节点的三维质心定位算法研究

无线传感器网络可以在广泛的应用领域内实现复杂的大规模监测和追踪任务,而节点的自定位技术是传感器网络的关键技术。文章以二维质心定位算法为基础,提出了三维质心定位算法,用C＋＋仿真结果表明,二维质心定位算法升级为三维质心定位算法没有明显增加算法的复杂性,也不影响覆盖率、通信报丈量和二维定位误差,但却能提供三维定位坐标信息。     

3D Underwater Sensor Network Localization

We transform the 3D underwater sensor network (USN) localization problem into its 2D counterpart by employing sensor depth information and a simple projection technique. We first prove that a nondegenerative projection preserves network localizability. We then prove that given a network and a constant k, all of the geometric k-lateration localization methods are equivalent. Based on these results, we design a purely distributed bilateration localization scheme for 3D USNs termed as underwater sensor positioning (USP). Through extensive simulations, we show that USP has the following nice features: (1) improved localization capabilities over existing 3D methods, (2) low storage and computation requirements, (3) predictable and balanced communication overhead, and (4) robustness to errors from the underwater environment.     

An energy efficient joint localization and synchronization solution for wireless sensor networks using unmanned aerial vehicle

Localization and synchronization are fundamental services for many applications in wireless sensor networks (WSNs), since it is often required to know the sensor nodes’ position and global time to relate a given event detection to a specific location and time. However, the localization and synchronization tasks are often performed after the sensor nodes’ deployment on the sensor field. Since manual configuration of sensor nodes is usually an impractical activity, it is necessary to rely on specific algorithms to solve both localization and clock synchronization problems of sensor nodes. With this in mind, in this work we propose a joint solution for the problem of 3D localization and time synchronization in WSNs using an unmanned aerial vehicle (UAV). A UAV equipped with GPS flies over the sensor field broadcasting its geographical position. Therefore, sensor nodes are able to estimate their geographical position and global time without the need of equipping them with a GPS device. Through simulation experiments, we show that our proposed joint solution reduces time synchronization and localization errors as well as energy consumption when compared to solutions found in the literature.