多移动信标辅助的分布式节点定位方法

为提高移动信标辅助定位算法的定位精度,避免重复扫描待定位节点,提出了一种使用多个移动信标的定位方法。这些信标在遍历网络时保持一定相对位置关系,使用TDoA技术测距并为未知节点提供距离信息辅助其定位。提出了基于最优覆盖策略的2种移动信标路径规划方法。仿真结果表明,所提出的算法具有较高的定位精度,且所使用的移动路径性能较高。     

基于三边测量法的移动锚节点定位方案

确定节点的位置是无线传感器网络对监测区域相关信息进行感知、采集和处理所面临的首要问题,直接影响它在实际中的应用。文中介绍了无线传感器网络的基本概念、节点位置的计算方法以及典型的移动锚节点路径规划,提出一种基于三边测量法的移动锚节点定位方案。在保证遍历所有未知节点的前提下,该方案的路径规划较为简单,定位精度较高。     

一种基于移动锚节点的静态无线传感器网络定位算法构建和分析

随着网络技术在深入的发展,静态无线传感器网络主要是通过引入网络技术中具有数据采集能力、信息处理能力以及无线通信的能力的传感器节点进行相互交换信息,并且协调控制有机相结合。该技术的已经被广泛的应用于生活中的各个领域中,在移动锚节点的使用中,改变了静态无线传感器网络在发展中遇到了环境恶劣、不可到达区域最终实现了监测和跟踪的任务,有效的控制了节点位置的具体信息。     

无线传感器网络的节点定位方法

提出了一种MCBN (Monte Carlo localization boxed using non-anchor)定位算法.该算法建立在蒙特卡罗定位算法基础之上,利用两跳范围内可信任度权值最小且坐标确定的静态非锚节点,辅助网络中两跳范围内的锚节点构建最小锚盒,同时利用待定位节点上一时刻的位置信息和临时锚节点的特性增强样本过滤条件,进行快速抽样和样本过滤.仿真结果表明:MCBN同MCL和MCB算法相比,提高了节点定位精度,降低了节点能量损耗.     

基于UKF的移动信标辅助节点定位算法

常用的节点定位方法通常要求较多的信标节点,因此容易造成资源浪费.提出一种基于目标跟踪的移动信标辅助节点定位算法,信标节点在移动过程中周期性地发布自身位置信息,未知节点首先获取自身位置的近似估计,然后再利用无迹卡尔曼滤波(UKF)方法对移动信标进行跟踪,并完成进一步位置求精.在该算法中,未知节点之间无需相互通信,降低了能...     

基于移动锚节点的无线传感网络节点定位算法

在无线传感网络定位算法中,锚节点位置决定了节点定位精度。为此,提出基于高斯-Markov模型的移动锚节点的节点定位(GM-MAL)算法。GM-MAL算法基于高斯-Markov移动模型,提出自适应锚节点的移动路径规划,通过速度调整策略、垂直平分线策略、虚斥力策略以及虚引力策略规划路径。在定位阶段,将非凸优化问题转化为双凸形式,再利用交替最小算法(AMA)求解,进而获取更短的锚节点移动路径。实验数据表明,引入虚引力策略提高了路径规划精度,覆盖了更多的监测区域。此外,相比于线性算法,GM-MAL的定位精度得到提高。     

基于混合多锚节点的WSN传感器定位方案

针对传统DV-hop或DV-distance算法在随机大型WSN网络中定位精确度较低的问题,提出一种混合多锚节点的WSN定位方案。第一阶段,为OLSR协议(最优链路状态路由协议)引入补充的锚节点选取准则,并采用改进的OLSR完成第一阶段的定位;第二阶段,分别采用DV-hop与DV-distance搜索中继节点,同时将已定位的节点加入锚节点集合。实验结果表明,该算法获得了较好的定位精确度与稳定性。     

基于局部分布式优化的无线传感器网络定位算法

针对在不规则的无线传感器网络中锚节点分布稀疏,对某些节点定位造成较大误差的情况,在Anchor Selection算法的基础上提出一种局部分布式优化定位算法,采用先局部后整体的定位思想,通过几何关系优化对节点之间跳距的处理,并在定位过程中将合理估计出来的节点晋升为锚节点,为后续未知节点的定位带来更多的信息参考。实验结果表明,该算法在处理不规则网络时有较强的容错性,能得到较好的定位效果。     

无线传感器网络中基于刚性的移动锚节点路径规划

在移动锚节点辅助定位中,锚节点通常沿着预设轨迹扫描或采用随机方式移动,当节点分布不均匀、待定位区域形状复杂时,存在锚节点冗余移动、位置冗余广播及定位性能难以确保等问题。该文提出了利用网络拓扑信息进行移动路径规划的新思路,首先利用刚性理论将网络划分为多个唯一可定位的单元,之后寻找一条遍历各单元的最短路径作为锚节点的移动轨迹,锚节点沿着该轨迹移动、依次定位各单元。大规模仿真结果表明,该策略可以有效避免锚节点的冗余移动和位置广播,灵巧适应各种布设情形,与经典的扫描式路径相比,大大降低了路径长度和位置数目。     

信号强度和运动向量结合的无线传感器网络移动节点定位

无线传感器网络的定位是近年来无线传感器网络研究的重要课题.本文首先介绍了无线传感器网络的来源、重要性以及无线传感器网络定位的分类.然后提出了一种全新定位算法,信号强度和运动向量结合的无线传感器网络移动节点定位,简称SSMV算法,在外围布置四个锚节点,得用信号强度和未知节点在运动中向量的变化,对锚节点在内的未知节点进行定位,并对该算法进行了仿真和总结.通过与凸规划法进行比较,仿真结果表明,该算法有更高的定位精度.     

Monte Carlo localization of wireless sensor networks with a single mobile beacon

One of the most important tasks in sensor networks is to determine the physical location of sensory nodes as they may not all be equipped with GPS receivers. In this paper we propose a localization method for wireless sensor networks (WSNs) using a single mobile beacon. The sensor locations are maintained as probability distributions that are sequentially updated using Monte Carlo sampling as the mobile beacon moves over the deployment area. Our method relieves much of the localization tasks from the less powerful sensor nodes themselves and relies on the more powerful beacon to perform the calculation. We discuss the Monte Carlo sampling steps in the context of the localization using a single beacon for various types of observations such as ranging, Angle of Arrival (AoA), connectivity and combinations of those. We also discuss the communication protocol that relays the observation data to the beacon and the localization result back to the sensors. We consider security issues in the localization process and the necessary steps to guard against the scenario in which a small number of sensors are compromised. Our simulation shows that our method is able to achieve less than 50% localization error and over 80% coverage with a very sparse network of degree less than 4 while achieving significantly better results if network connectivity increases.     

相关性匹配蓝牙信标位置指纹库的室内定位

针对K近邻算法(KNN)在对偏向于某个样本点的未知点进行三角质心定位时定位精度变差的情况,提出了应用相关系数去匹配蓝牙信标iBeacon位置指纹库的室内定位算法.通过比较待定位点和位置指纹库中参考样点的相似程度,并进行数据差异显著性检验,来检验采集的待定位点数据与指纹库数据是否显著相关,然后取相关性较高的样本点进行加权平均匹配定位.实验结果显示,相关系数匹配位置指纹库算法可将2 m以内的定位精度从65%提高到92%,相较于传统的KNN匹配定位算法有着定位精度高、计算量小、定位时间短等优势.     

Optimising mobile phone self-location estimates by introducing beacon characteristics to the algorithm

Positioning technologies that use global system for mobile communication (GSM) networks for location estimation (such as the privacy observant location system (POLS) and the place lab framework) lack the accuracy that other positioning technologies like the global positioning system (GPS) have. GPS receivers are most of the time capable of placing a person within 10 m of a known location. Place Lab is an open platform framework implemented in Java for client-side location sensing that can calculate a position estimate from various beacon sources, such as GSM beacons. The POLS framework is a counterpart of Place Lab for Windows Smartphone devices which provide the tools to develop location-based services quickly. There is a lack of accuracy, however, when the location estimation algorithm uses only GSM readings. Measurements that have been made with Place Lab show a median accuracy of 232 m in downtown areas. Place Lab and POLS do not need additional hardware, apart from the mobile phone itself, however, their lack of accuracy compared to GPS is significant. Due to this rather poor accuracy, the use of those frameworks is limited to applications where the accuracy is not crucial. This article presents the results of improving the accuracy of location estimation in urban areas by extending the algorithm used in the POLS and Place Lab frameworks to take into account the beacon properties, effective radiated power (ERP) and beacon height when estimating a position. The extended algorithm based on beacon properties outperforms the centroid algorithm by over 30%.     

An efficient algorithm for mobile objects localization

A new efficient algorithm based on time of arrival to determine the position of a mobile object (MO) in a wireless environment is proposed. Since all operations in our algorithm are simple add and shift operations, it can be easily implemented in the MO's firmware or hardware to reduce the number of instructions and computational cost involved in the localization task. Simulation results show that the proposed algorithm outperforms other algorithms in terms of computational cost and implementation simplicity. Copyright © 2007 John Wiley & Sons, Ltd.     

A distributed routing algorithm for mobile wireless networks

We present a loop-free, distributed routing protocol for mobile packet radio networks. The protocol is intended for use in networks where the rate of topological change is not so fast as to make flooding the only possible routing method, but not so slow as to make one of the existing protocols for a nearly-static topology applicable. The routing algorithm adapts asynchronously in a distributed fashion to arbitrary changes in topology in the absence of global topological knowledge. The protocol's uniqueness stems from its ability to maintain source-initiated, loop-free multipath routing only to desired destinations with minimal overhead in a randomly varying topology. The protocol's performance, measured in terms of end-to-end packet delay and throughput, is compared with that of pure flooding and an alternative algorithm which is well-suited to the high-rate topological change environment envisioned here. For each protocol, emphasis is placed on examining how these performance measures vary as a function of the rate of topological changes, network topology, and message traffic level. The results indicate the new protocol generally outperforms the alternative protocol at all rates of change for heavy traffic conditions, whereas the opposite is true for light traffic. Both protocols significantly outperform flooding for all rates of change except at ultra-high rates where all algorithms collapse. The network topology, whether dense or sparsely connected, is not seen to be a major factor in the relative performance of the algorithms.The work of A. Ephremides was supported in part by the National Science Foundation under grants D-CDR-8803012 and EEC94-02384.     

WSNs中基于数据匹配的分布式故障节点检测算法

针对无线传感网络的节点故障问题,提出一种新的分布式故障节点检测算法(DFDA).DFDA算法利用节点度信息估计节点对网络的重要性,并尽可能将节点度高的节点保存到网络中.通过比较节点间感测的数据,检测故障节点.为了增强检测的准确性,采用双重测定策略.仿真结果表明,相比于同类算法,DFDA算法提高了检测故障节点的精确度,并...     

基于RSSI的节点定位算法的研究

在无线传感器网络的节点定位中,原RSSI定位算法利用接收信号强度的对数正态模型,其存在计算量大、功耗大等问题。由于物体运动不会突变,可以利用以前的轨迹与速度,预测当前时刻的位置信息,采用改进的神经网络算法,对当前时刻的位置做了很好的预测。实验结果表明,该算法与传统的RSSI算法相比,减小了采样范围,提高了定位精度,降低了无线传感系统的功耗。