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1.
In large‐scale wireless sensor networks, cost‐effective and energy‐efficient localization of sensor nodes is an important research topic. In spite of their coarse accuracy, range‐free (connectivity‐based) localization methods are considered as cost‐effective alternatives to the range‐based localization schemes with specialized hardware requirements.In this paper, we derive closed‐form expressions for the average minimum transmit powers required for the localization of sensor nodes, under deterministic path loss, log‐normal shadowing, and Rayleigh fading channel models. The impacts of propagation environment and spatial density of anchor nodes on the minimum transmit power for node localization are evaluated analytically as well as through simulations. Knowledge of the minimum transmit power requirements for localizability of a sensor node enables improving energy efficiency and prolonging lifetime of the network. We also propose a novel distance metric for range‐free localization in large‐scale sensor networks. The target and anchor nodes are assumed to be positioned according to two statistically independent two‐dimensional homogeneous Poisson point processes. Analytical expression for the average distance from a target node to its kth nearest neighbor anchor node is derived and is used for estimating the target‐to‐anchor node distances for localization. The Cramér–Rao lower bound on the localization accuracy for the new distance estimator is derived. Simulation results show the accuracy of the proposed distance estimate compared with some existing ones for range‐free localization. The results of our investigation are significant for low‐cost, energy‐efficient localization of wireless sensor nodes. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

2.
Wireless sensor networks find extensive applications, such as environmental and smart city monitoring, structural health, and target location. To be useful, most sensor data must be localized. We propose a node localization technique based on bilateration comparison (BACL) for dense networks, which considers two reference nodes to determine the unknown position of a third node. The mirror positions resulted from bilateration are resolved by comparing their coordinates with the coordinates of the reference nodes. Additionally, we use network clustering to further refine the location of the nodes. We show that BACL has several advantages over Energy Aware Co‐operative Localization (EACL) and Underwater Recursive Position Estimation (URPE): (1) BACL uses bilateration (needs only two reference nodes) instead of trilateration (that needs three reference nodes), (2) BACL needs reference (anchor) nodes only on the field periphery, and (3) BACL needs substantially less communication and computation. Through simulation, we show that BACL localization accuracy, as root mean square error, improves by 53% that of URPE and by 40% that of EACL. We also explore the BACL localization error when the anchor nodes are placed on one or multiple sides of a rectangular field, as a trade‐off between localization accuracy and network deployment effort. Best accuracy is achieved using anchors on all field sides, but we show that localization refinement using node clustering and anchor nodes only on one side of the field has comparable localization accuracy with anchor nodes on two sides but without clustering.  相似文献   

3.
基于几何学的无线传感器网络定位算法   总被引:1,自引:0,他引:1  
刘影 《光电子.激光》2010,(10):1435-1438
提出一种基于几何学的无线传感器网络(WSN)定位算法。把网络区域中的节点分为锚节点和未知节点,假设在定位空间中有n个锚节点,由于受到几何学的限制,实际可行的锚节点序列是有限的,因此利用一种几何方法判断锚节点间的位置关系,从而选取最优的锚节点序列,能够更精确地确定未知节点的位置,并且分析了待定位节点的邻居锚节点数量对定位精度的影响。仿真结果表明,与已有的APS(Ad-Hoc positioning system)定位算法相比,该算法可有效地降低平均定位误差和提高定位覆盖度。  相似文献   

4.
Recent advancement in wireless sensor network has contributed greatly to the emerging of low‐cost, low‐powered sensor nodes. Even though deployment of large‐scale wireless sensor network became easier, as the power consumption rate of individual sensor nodes is restricted to prolong the battery lifetime of sensor nodes, hence the heavy computation capability is also restricted. Localization of an individual sensor node in a large‐scale geographic area is an integral part of collecting information captured by the sensor network. The Global Positioning System (GPS) is one of the most popular methods of localization of mobile terminals; however, the use of this technology in wireless sensor node greatly depletes battery life. Therefore, a novel idea is coined to use few GPS‐enabled sensor nodes, also known as anchor nodes, in the wireless sensor network in a well‐distributed manner. Distances between anchor nodes are measured, and various localization techniques utilize this information. A novel localization scheme Intersecting Chord‐Based Geometric Localization Scheme (ICBGLS) is proposed here, which loosely follows geometric constraint‐based algorithm. Simulation of the proposed scheme is carried out for various communication ranges, beacon broadcasting interval, and anchor node traversal techniques using Omnet++ framework along with INET framework. The performance of the proposed algorithm (ICBGLS), Ssu scheme, Xiao scheme, and Geometric Constraint‐Based (GCB) scheme is evaluated, and the result shows the fact that the proposed algorithm outperforms the existing localization algorithms in terms of average localization error. The proposed algorithm is executed in a real‐time indoor environment using Arduino Uno R3 and shows a significant reduction in average localization time than GCB scheme and similar to that of the SSU scheme and Xiao scheme.  相似文献   

5.
In order to better solve the contradiction between precision of localization and the number of anchor nodes in wireless sensor network,a mobile anchor node localization technology based on connectivity was proposed.First,the coverage characteristic of the network nodes was analyzed,and a critical value was found between the mobile step and the anchor node communication radius,mobile anchor nodes' coverage characteristic would change when near this critical value.Second,a mobile anchor node followed a planning path to form a positioning area seamless coverage was used.Finally,when there was no need for high-precision technology,node position would been estimated according with the connectivity of the network and the receiving information of the node.The simulation results show that the proposed algorithm can realize coarse-grained localization,and paths perform complete localization.  相似文献   

6.
Many improved DV-Hop localization algorithm have been proposed to enhance the localization accuracy of DV-Hop algorithm for wireless sensor networks. These proposed improvements of DV-Hop also have some drawbacks in terms of time and energy consumption. In this paper, we propose Novel DV-Hop localization algorithm that provides efficient localization with lesser communication cost without requiring additional hardware. The proposed algorithm completely eliminates communication from one of the steps by calculating hop-size at unknown nodes. It significantly reduces time and energy consumption, which is an important improvement over DV-Hop—based algorithms. The algorithm also uses improvement term to refine the hop-size of anchor nodes. Furthermore, unconstrained optimization is used to achieve better localization accuracy by minimizing the error terms (ranging error) in the estimated distance between anchor node and unknown node. Log-normal shadowing path loss model is used to simulate the algorithms in a more realistic environment. Simulation results show that the performance of our proposed algorithm is better when compared with DV-Hop algorithm and improved DV-Hop—based algorithms in all considered scenarios.  相似文献   

7.
The existing mobility strategy of the anchor node in wireless sensor network (WSN) has the shortcomings of too long moving path and low positioning accuracy when the anchor node traverses the network voids area.A new mobility strategy of WSN anchor node was proposed based on an improved virtual forces model.The number of neighbor nodes and the distance between the neighbor nodes to the anchor nodes were introduced as their own dense weight attributes.The unknown nodes intensity was used as weights to improve the traditional virtual force model.Meantime the distance-measuring error ε was taken into account.The optimal distribution,direction selection,shift step length and fallback strategy of anchor node could be analyzed by the trilateration.Using the number of virtual beacon received by the unknown node and the distance between the unknown node to the anchor node calculate the virtual force.Then according to the virtual force,the direction was chosen and the anchor nodes were moved.Simulation experiments show that the strategy can make the anchor nodes move according to the specific circumstances of unknown node distribution.It has a high positioning accuracy and strong adaptability.It can successfully shorten the path of the anchor node movement and reduce the number of virtual beacon.Moreover it can effectively avoid the anchor node to enter the network voids area and reduce the number of collinear virtual anchor nodes.  相似文献   

8.
一种基于网络密度分簇的移动信标辅助定位方法   总被引:1,自引:0,他引:1  
赵方  马严  罗海勇  林权  林琳 《电子与信息学报》2009,31(12):2988-2992
现有移动信标辅助定位算法未充分利用网络节点分布信息,存在移动路径过长及信标利用率较低等问题。该文把网络节点分簇、增量定位与移动信标辅助相结合,提出了一种基于网络密度分簇的移动信标辅助定位算法(MBL(ndc))。该算法选择核心密度较大的节点作簇头,采用基于密度可达性的分簇机制把整个网络划分为多个簇内密度相等的簇,并联合使用基于遗传算法的簇头全局路径规划和基于正六边形的簇内局部路径规划方法,得到信标的优化移动路径。当簇头及附近节点完成定位后,升级为信标,采用增量定位方式参与网络其它节点的定位。仿真结果表明,该算法定位精度与基于HILBERT路径的移动信标辅助定位算法相当,而路径长度不到后者的50%。  相似文献   

9.
In wireless sensor networks (WSNs), many applications require sensor nodes to obtain their locations. Now, the main idea in most existing localization algorithms has been that a mobile anchor node (e.g., global positioning system‐equipped nodes) broadcasts its coordinates to help other unknown nodes to localize themselves while moving according to a specified trajectory. This method not only reduces the cost of WSNs but also gets high localization accuracy. In this case, a basic problem is that the path planning of the mobile anchor node should move along the trajectory to minimize the localization error and to localize the unknown nodes. In this paper, we propose a Localization algorithm with a Mobile Anchor node based on Trilateration (LMAT) in WSNs. LMAT algorithm uses a mobile anchor node to move according to trilateration trajectory in deployment area and broadcasts its current position periodically. Simulation results show that the performance of our LMAT algorithm is better than that of other similar algorithms. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

10.
针对无线传感器网络(Wireless Sensor Networks,WSN)的低成本、低耗能以及准确定位的需求,提出了一种射频干涉与测量多普勒频偏相结合的节点定位方法。该方法中移动锚节点通过2次交叉运动,产生多普勒效应并与静止锚节点形成射频干涉场;未知节点通过测量自身低频干涉信号的瞬时频率的变化规律,获得定位相关信息进而实现节点定位。仿真实验结果表明该方法可以实现预期的定位,且定位精度较高;同时,定位算法简单,运算量小,能耗小,尤其适用于大范围分布的大量节点进行定位。  相似文献   

11.
In operating and managing wireless sensor networks (WSNs) and their applications, the high accuracy of localization and the low operating costs are considered the substantial and key issues. The literature is rich in algorithms for localized WSN devices in hostile and unreachable outdoor environment. Majority of the literature considered mobile anchor as one of the solutions in locating sensor nodes. In this situation, the critical issue is the trajectory planning. All algorithms supposed that the mobile anchor should travel following the shortest path to determine the positions of sensor nodes with minimum localization error. A localization algorithm, which is called efficient localization algorithm based path planning for mobile anchors (ELPMA), is proposed. ELPMA is based on a one-mobile anchor moving in adjustable circular trajectory to scan the target area. It considers that the received signal strength indicator is the ranging function to determine the distance between mobile anchor and sensor nodes. ELPMA supposed the mobile anchor starts the motion from the center of the target area. The travelling paths are planned in advance by ELPMA based on the distance measurements between the mobile anchor and the sensor nodes. Simulation results demonstrate that ELPMA has better performance compared to other algorithms based on static path. This performance was evident in the localization accuracy and trajectory planning.  相似文献   

12.
The n-Hop Multilateration Primitive for Node Localization Problems   总被引:1,自引:0,他引:1  
The recent advances in MEMS, embedded systems and wireless communication technologies are making the realization and deployment of networked wireless microsensors a tangible task. In this paper we study node localization, a component technology that would enhance the effectiveness and capabilities of this new class of networks. The n-hop multilateration primitive presented here, enables ad-hoc deployed sensor nodes to accurately estimate their locations by using known beacon locations that are several hops away and distance measurements to neighboring nodes. To prevent error accumulation in the network, node locations are computed by setting up and solving a global non-linear optimization problem. The solution is presented in two computation models, centralized and a fully distributed approximation of the centralized model. Our simulation results show that using the fully distributed model, resource constrained sensor nodes can collectively solve a large non-linear optimization problem that none of the nodes can solve individually. This approach results in significant savings in computation and communication, that allows fine-grained localization to run on a low cost sensor node we have developed.  相似文献   

13.
In this paper, a received signal strength indicator (RSSI)-based weighted centroid localization (WCL) method for indoor corridor scenarios is developed and tested. The contribution of the proposed system is that, to scope the area of an unknown target position, the possible corridor area where the target node should be located is automatically selected, and only reference nodes deployed in such an area are applied for position estimation. Additionally, to improve the estimation precision, distance values converted from measured RSSIs and used for the WCL are also compensated to alleviate the RSSI variation problem caused by physical environments. Therefore, our methods can save a number of reference nodes to be used, while localization accuracy can also be achieved. Experiments in the corridor environment using a 2.4 GHz IEEE 802.15.4 wireless sensor network with four reference nodes deployed in the test field dimension of 22 m × 9.3 m have been performed. Experimental results demonstrate that the proposed method, which requires only two reference nodes, outperforms the original WCL method with four reference nodes by 53.053%, as indicated by average localization errors. The results also reveal that the proposed method provides error distances lower than the WCL method for all test target positions, while all estimated positions fall within the corridor areas by 100%.  相似文献   

14.
传感器网络的粒子群优化定位算法   总被引:1,自引:0,他引:1  
陈志奎  司威 《通信技术》2011,44(1):102-103,108
无线传感器网络定位问题是一个基于不同距离或路径测量值的优化问题。由于传统的节点定位算法采用最小二乘法求解非线性方程组时很容易受到测距误差的影响,为了提高节点的定位精度,将粒子群优化算法引入到传感器网络定位中,提出了一种传感器网络的粒子群优化定位算法。该算法利用未知节点接收到的锚节点的距离信息,通过迭代方法搜索未知节点位置。仿真结果表明,该算法有效地抑制了测距误差累积对定位精度的影响,提高了节点的定位精度。  相似文献   

15.
节点位置定位是无线传感器网络应用的基本要求之一。针对无线传感器网络在开放性环境中应用容易遭受恶意节点欺骗攻击的问题,设计了一种抗欺骗的节点安全定位算法。算法将参考节点进行分组划分,并通过不同分组之间定位结果的比较,排除其中可能存在的恶意节点。在分组过程中,算法同时考虑了参考节点的优选问题,避免不良拓扑结构造成的定位偏差。仿真试验分析表明,算法能够有效地抵抗恶意节点的定位信息欺骗,大大提高了网络节点的定位精度。  相似文献   

16.
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   

17.
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。  相似文献   

18.
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   

19.
Localization of nodes in a sensor network is essential for the following two reasons: (i) to know the location of a node reporting the occurrence of an event, and (ii) to initiate a prompt action whenever necessary. Different localization techniques have been proposed in the literature. Most of these techniques use three location aware nodes for localization of an unknown node. Moreover, the localization techniques also differ from environment to environment. In this paper, we proposed a localization technique for grid environment. Sensor nodes are deployed in a grid pattern and localization is achieved using a single location aware or anchor node. We have identified three types of node in the proposed scheme: (i) Anchor node, (ii) Unknown node and (iii) Special node. First, the special nodes are localized with respect to the anchor node, then the unknown nodes are localized using trilateration mechanism. We have compared the proposed scheme with an existing localization algorithm for grid deployment called Multiduolateration. The parameters considered for localization are localization time and localization error. It is observed that localization time and error in the proposed scheme is lower than that of Multiduolateration.  相似文献   

20.
Localization is essential for wireless sensor networks (WSNs). It is to determine the positions of sensor nodes based on incomplete mutual distance measurements. In this paper, to measure the accuracy of localization algorithms, a ranging error model for time of arrival (TOA) estimation is given, and the Cramer—Rao Bound (CRB) for the model is derived. Then an algorithm is proposed to deal with the case where (1) ranging error accumulation exists, and (2) some anchor nodes broadcast inaccurate/wrong location information. Specifically, we first present a ranging error‐tolerable topology reconstruction method without knowledge of anchor node locations. Then we propose a method to detect anchor nodes whose location information is inaccurate/wrong. Simulations demonstrate the effectiveness of our algorithm. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

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