scholarly journals A Time Difference of Arrival-based Localization Algorithm for Wireless Sensor Networks

2016 ◽  
Vol 12 (11) ◽  
pp. 80 ◽  
Author(s):  
Songbo Ji
Keyword(s):  
Wireless Sensor Networks ◽  
Electromagnetic Wave ◽  
Sensor Networks ◽  
Large Scale ◽  
Time Difference ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Time Difference Of Arrival ◽  
Positioning Accuracy ◽  
Simulation Results

<p class="Abstract"><span lang="EN-US">Aimed at solving the problem of local divergence and low data accuracy, this paper introduces a new Time Difference of Arrival(TDOA)-based localization algorithm (TBL) for the large-scale, high-density wireless sensor networks which are designed for real-time surveillance and unexpected incidents management. In particular, several means to improve the accuracy of distance measurement are investigated, and the TDOA method, based on the sound wave and electromagnetic wave to locate in the large-scale WSN, is discussed. Also, the well-designed circular location process has the advantage of better positioning accuracy and coverage percentage. Simulation results have confirmed the effectiveness of the formed TBL algorithm.</span></p>

Localization Algorithm Based on DV-HOP for Wireless Sensor Network

2011 ◽  
Vol 128-129 ◽  
pp. 909-913
Author(s):  
Yu Hu ◽  
Xue Mei Li
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Weighted Average ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Positioning Accuracy ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Improved Algorithm

An improved DV-HOP localization algorithm is proposed in the paper, aiming at the traditional DV-HOP localization algorithm. 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 improved localization algorithm effectively improves the positioning accuracy compared with the traditional DV-HOP localization algorithm, it is an effective localization algorithm for the wireless sensor networks.

Based on RSSI Ranging Technology for DV-Hop Localization Algorithm of Wireless Sensor Network

2012 ◽  
Vol 442 ◽  
pp. 360-365 ◽  
Author(s):  
Yang Jun Zhong
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Approximate Calculation ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Positioning Accuracy ◽  
Original Algorithm ◽  
Approximate Distance ◽  
Anchor Nodes ◽  
Simulation Results

For the DV-Hop algorithm of wireless sensor networks,there is an error arising problem that anchor nodes and location node hop distance is only an approximate calculation. A method based on the original Algorithm introducing RSSI ranging technique is proposed.Using RSSI ranging technology,we accord that if the anchor nodes is only a hop away from the location node,then decide whether using the DV-Hop algorithm to approach to the approximate distance between them. Simulation results show that the algorithm can effectively improve the error problems of calculating the hop distance between the anchor nodes and the location nodes, meanwhile improve the positioning accuracy of the node.

scholarly journals Secure and Robust 3D Localization in Wireless Sensor Networks

2019 ◽  
Vol 9 (1S) ◽  
pp. 104-111
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Malicious Nodes ◽  
3D Localization ◽  
Secure Localization ◽  
Simulation Results ◽  
Two Phases

The fundamental capacity of a sensor system is to accumulate and forward data to the destination. It is crucial to consider the area of gathered data, which is utilized to sort information that can be procured using confinement strategy as a piece of Wireless Sensor Networks (WSNs).Localization is a champion among the most basic progressions since it agreed as an essential part in various applications, e.g., target tracking. If the client can't gain the definite area information, the related applications can't be skillful. The crucial idea in most localization procedures is that some deployed nodes with known positions (e.g., GPS-equipped nodes) transmit signals with their coordinates so as to support other nodes to localize themselves. This paper mainly focuses on the algorithm that has been proposed to securely and robustly decide thelocation of a sensor node. The algorithm works in two phases namely Secure localization phase and Robust Localization phase. By "secure", we imply that malicious nodes should not effectively affect the accuracy of the localized nodes. By “robust”, we indicate that the algorithm works in a 3D environment even in the presence of malicious beacon nodes. The existing methodologies were proposed based on 2D localization; however in this work in addition to security and robustness, exact localization can be determined for 3D areas by utilizing anefficient localization algorithm. Simulation results exhibit that when compared to other existing algorithms, our proposed work performs better in terms of localization error and accuracy.

A Collaborative Multilateral Localization Algorithm for Wireless Sensor Networks

2013 ◽  
Vol 303-306 ◽  
pp. 201-205
Author(s):  
Shao Ping Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Optimization Method ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Localization Method ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Unknown Node

Localization technology is one of the key supporting technologies in wireless sensor networks. In this paper, a collaborative multilateral localization algorithm is proposed to localization issues for wireless sensor networks. The algorithm applies anchor nodes within two hops to localize unknown nodes, and uses Nelder-Mead simplex optimization method to compute coordinates of the unknown nodes. If an unknown node can not be localized through two-hop anchor nodes, it is localized by anchor nodes and localized nodes within two hops through auxiliary iterative localization method. Simulation results show that the localization accuracy of this algorithm is very good, even in larger range errors.

A GPS-Less Cell-Based Localization Technique for Wireless Sensor Networks

2012 ◽  
Vol 601 ◽  
pp. 376-382
Author(s):  
Xue Jun Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Power Level ◽  
Wireless Sensor ◽  
Transmission Power ◽  
Localization Algorithm ◽  
Localization Technique ◽  
Simulation Results

This paper presents a localization algorithm, namely Circle Based Localization (CBL) for GPS-less wireless sensor networks. CBL works by finding the centroid of intersection of any two circles. Furthermore, we study the effect of power level mismatch among anchors. Simulation results show that CBL can significantly improve the accuracy by 5% while reducing the transmission power of anchors.

An Improved Sensor Positioning for Wireless Sensor Networks

2014 ◽  
Vol 716-717 ◽  
pp. 1322-1325
Author(s):  
Jin Tao Lin ◽  
Guang Yu Fan ◽  
Wen Hong Liu ◽  
Ying Da Hu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Signal Strength ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Positioning Accuracy ◽  
Positioning Method ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Sensor Positioning

Sensor positioning is a fundamental block in various location-dependent applications of wireless sensor networks. In order to improve the positioning accuracy without increasing the complex and cost of sensor nodes, an improve sensor positioning method is proposed for wireless sensor networks. In the method, after receiving the broadcasting message of the neighboring anchor nodes, the sensor nodes calculate a modifying factor of the change of the signal strength. And they modify the distances between themselves and neighboring anchor nodes with the modifying factor. Simulation results show that the proposed method can obtain a high positioning accuracy.

Localization in Wireless Sensor Networks in Beacon Drifting Scenarios

2012 ◽  
Vol 562-564 ◽  
pp. 1234-1239
Author(s):  
Ming Xia ◽  
Qing Zhang Chen ◽  
Yan Jin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Probability Density ◽  
Sensor Nodes ◽  
Density Model ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Scenarios Simulation ◽  
Simulation Results

The beacon drifting problem occurs when the beacon nodes move accidentally after deployment. In this occasion, the localization results of sensor nodes in the network will be greatly affected and become inaccurate. In this paper, we present a localization algorithm in wireless sensor networks in beacon drifting scenarios. The algorithm first uses a probability density model to calculate the location reliability of each node, and in localization it will dynamically choose nodes with highest location reliabilities as beacon nodes to improve localization accuracy in beacon drifting scenarios. Simulation results show that the proposed algorithm achieves its design goals.

Performance of Wireless Sensor Networks for Different Mobile Event Path Scenarios

2012 ◽  
pp. 55-68
Author(s):  
Tao Yang ◽  
Gjergji Mino ◽  
Leonard Barolli ◽  
Makoto Ikeda ◽  
Fatos Xhafa ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Network ◽  
Energy Characteristic ◽  
Large Scale ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Movement Path ◽  
Random Movement ◽  
Simulation Results

In this paper, the authors investigate how the sensor network performs when the event moves with special movement path. Simulation results are compared with four scenarios: when the event is stationary, moving randomly, moving with simple 4 path, and boids path. The simulation results show that for the case when the event is moving randomly, the performance is the worst in the four scenarios. The characteristic of goodput decreases with the increase of number of sensor nodes. In the case of the boids model, the goodput is unstable when the is lower than 10 pps. The consumed energy characteristic increases with the increase of Simulation results show that the consumed energy of random movement is the worst among the four scenarios. The consumed energy of boids model is the lowest in four cases. This shows that the event movement with boids model can decrease the consumed energy in large scale WSNs.

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