Node positioning is a fundamental problem in applications of wireless sensor networks (WSNs). In this paper, a new range-free algorithm, called spring swarm localization algorithm (SSLA), is proposed for positioning W...Node positioning is a fundamental problem in applications of wireless sensor networks (WSNs). In this paper, a new range-free algorithm, called spring swarm localization algorithm (SSLA), is proposed for positioning WSNs. To determine the locations of sensor nodes, the proposed algorithm uses network topology information and a small fraction of sensor nodes which know their locations. Numerical simulations show that high positioning accuracy can be obtained by using the algorithm. Some examples are given to illustrate the effectiveness of the algorithm.展开更多
车联网(Internet of Vehicles,Io V)被认为是物联网中最有可能率先突破应用的一个重要分支,成为目前研究的重点和热点.其中,车辆节点的定位和位置感知技术是车联网的技术核心,不仅关系到车辆行驶过程中的安全,而且影响着车联网的发展前...车联网(Internet of Vehicles,Io V)被认为是物联网中最有可能率先突破应用的一个重要分支,成为目前研究的重点和热点.其中,车辆节点的定位和位置感知技术是车联网的技术核心,不仅关系到车辆行驶过程中的安全,而且影响着车联网的发展前景.首先,提出了车联网定位和位置感知的评价标准,介绍了无线定位测距技术的实现原理和方法.在此基础上,重点阐述了车联网的定位和位置感知技术,讨论了相关算法以及在车联网中的应用特点.最后,在综合分析了现有研究成果的同时,对未来的研究方向进行了展望.展开更多
Localization using a Wireless Sensor Network (WSN) has become a field of interest for researchers in the past years. This information is expected to aid in routing, systems maintenance and health monitoring. For examp...Localization using a Wireless Sensor Network (WSN) has become a field of interest for researchers in the past years. This information is expected to aid in routing, systems maintenance and health monitoring. For example, many projects aiming to monitor the elderly at home include a personal area network (PAN) which can provide current location of the patient to the medical staff. This article presents an overview of the current trends in this domain. We introduce the mathematical tools used to determine position then we introduce a selection of range-free and range-based proposals. Finally, we provide a comparison of these techniques and suggest possible areas of improvement.展开更多
Node localization is commonly employed in wireless networks. For example, it is used to improve routing and enhance security. Localization algorithms can be classified as range-free or range-based. Range-based algorit...Node localization is commonly employed in wireless networks. For example, it is used to improve routing and enhance security. Localization algorithms can be classified as range-free or range-based. Range-based algorithms use location metrics such as ToA, TDoA, RSS, and AoA to estimate the distance between two nodes. Proximity sensing between nodes is typically the basis for range-free algorithms. A tradeoff exists since range-based algorithms are more accurate but also more complex. However, in applications such as target tracking, localization accuracy is very important. In this paper, we propose a new range-based algorithm which is based on the density-based outlier detection algorithm (DBOD) from data mining. It requires selection of the K-nearest neighbours (KNN). DBOD assigns density values to each point used in the location estimation. The mean of these densities is calculated and those points having a density larger than the mean are kept as candidate points. Different performance measures are used to compare our approach with the linear least squares (LLS) and weighted linear least squares based on singular value decomposition (WLS-SVD) algorithms. It is shown that the proposed algorithm performs better than these algorithms even when the anchor geometry about an unlocalized node is poor.展开更多
无线传感器网络是通过布设许多移动或固定的传感器,采用多跳和自组织的形式构建的无线网络。在网络区域内,对象的信息通过探知、收集、处理和传输传递给网络的所属者。文章重点研究无线传感器网络定位技术,通过对到达时间差TDOA(Time Di...无线传感器网络是通过布设许多移动或固定的传感器,采用多跳和自组织的形式构建的无线网络。在网络区域内,对象的信息通过探知、收集、处理和传输传递给网络的所属者。文章重点研究无线传感器网络定位技术,通过对到达时间差TDOA(Time Difference of Arrival,TDOA)定位技术的研究,提出了移动目标的被动定位算法和定位中心主动定位算法,并在MATLAB平台上进行仿真研究,对可能影响定位精度的因素进行了分析。展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 10832006 and 60872093)
文摘Node positioning is a fundamental problem in applications of wireless sensor networks (WSNs). In this paper, a new range-free algorithm, called spring swarm localization algorithm (SSLA), is proposed for positioning WSNs. To determine the locations of sensor nodes, the proposed algorithm uses network topology information and a small fraction of sensor nodes which know their locations. Numerical simulations show that high positioning accuracy can be obtained by using the algorithm. Some examples are given to illustrate the effectiveness of the algorithm.
文摘车联网(Internet of Vehicles,Io V)被认为是物联网中最有可能率先突破应用的一个重要分支,成为目前研究的重点和热点.其中,车辆节点的定位和位置感知技术是车联网的技术核心,不仅关系到车辆行驶过程中的安全,而且影响着车联网的发展前景.首先,提出了车联网定位和位置感知的评价标准,介绍了无线定位测距技术的实现原理和方法.在此基础上,重点阐述了车联网的定位和位置感知技术,讨论了相关算法以及在车联网中的应用特点.最后,在综合分析了现有研究成果的同时,对未来的研究方向进行了展望.
文摘Localization using a Wireless Sensor Network (WSN) has become a field of interest for researchers in the past years. This information is expected to aid in routing, systems maintenance and health monitoring. For example, many projects aiming to monitor the elderly at home include a personal area network (PAN) which can provide current location of the patient to the medical staff. This article presents an overview of the current trends in this domain. We introduce the mathematical tools used to determine position then we introduce a selection of range-free and range-based proposals. Finally, we provide a comparison of these techniques and suggest possible areas of improvement.
文摘Node localization is commonly employed in wireless networks. For example, it is used to improve routing and enhance security. Localization algorithms can be classified as range-free or range-based. Range-based algorithms use location metrics such as ToA, TDoA, RSS, and AoA to estimate the distance between two nodes. Proximity sensing between nodes is typically the basis for range-free algorithms. A tradeoff exists since range-based algorithms are more accurate but also more complex. However, in applications such as target tracking, localization accuracy is very important. In this paper, we propose a new range-based algorithm which is based on the density-based outlier detection algorithm (DBOD) from data mining. It requires selection of the K-nearest neighbours (KNN). DBOD assigns density values to each point used in the location estimation. The mean of these densities is calculated and those points having a density larger than the mean are kept as candidate points. Different performance measures are used to compare our approach with the linear least squares (LLS) and weighted linear least squares based on singular value decomposition (WLS-SVD) algorithms. It is shown that the proposed algorithm performs better than these algorithms even when the anchor geometry about an unlocalized node is poor.
文摘无线传感器网络是通过布设许多移动或固定的传感器,采用多跳和自组织的形式构建的无线网络。在网络区域内,对象的信息通过探知、收集、处理和传输传递给网络的所属者。文章重点研究无线传感器网络定位技术,通过对到达时间差TDOA(Time Difference of Arrival,TDOA)定位技术的研究,提出了移动目标的被动定位算法和定位中心主动定位算法,并在MATLAB平台上进行仿真研究,对可能影响定位精度的因素进行了分析。
