WSN Localization Research Articles

Weighted Centroid Range Free Localization Algorithm based on IOT

Today, IOT (Internet of Things or Internet of Objects) is popular upcoming topic in Wireless network and in Wireless Network. Localization has become a crucial factor for various monitoring applications such as search, rescue, disaster relief, target tracking etc. Various WSN localization technologies are designed for calculating location of the unknown node. IOT is a latest approach where it combines many technologies, such as network technology, communication technology, database technology (Internet, Bluetooth, infrared, Wi-Fi, GPRS, 3G, SQL, etc) to provide location based service which enables different ways to obtain the location information of various objects. In this paper, we focus on to achieve higher localization accuracy based on services in which we deploy sensing devices to calculate the information of sensor nodes and its surrounding nodes where it requires less hardware and less implementation, To improve the localization accuracy, we propose a Weighted Centroid based on IOT mechanism capable to give accurate calculation between Anchor node and Unknown node.

WSN Localization Algorithm Based on Fast SVM

Localization of sensor nodes is essential for wireless sensor network when it is applied to the special applications.This paper proposed a rang-free localization algorithm based on SVM. In this algorithm, multi-class SVMs are applied. So to improve the performance, a fast SVM algorithm is proposed in this paper.Finally, the experimental results demonstrate the algorithm proposed has small localization error, and it is robust and stable.

The Application Research of Multi-hop 3D AOA with Space-based Angle Transmission Localization Algorithm in Terrain Modeling

Node’s localization is a key technology in Wireless Sensor Networks. There are only quite a few studies on 3D localization which is suffered in slow progress, actually, is one of the main difficulties in WSN localization. Based on the study of the application of terrain modeling, localization algorithm for sensor nodes in 3D condition has been focus on as well as the application of terrain model. The paper proposed a new algorithm named Multi-hop 3D AOA With Space-based Angle Transmission, and then combined the new algorithm with Delaunay triangulation algorithm for terrain modeling. The results of simulation have shown that as the ratio of beacon nodes and their communication radius changes, the algorithm’s localization error rate range from 7% to 27%, and has a good terrain modeling accuracy, range from 59% to 98%.

A Localization Algorithm of Multi-Hop Three Dimensional AOA with Space-Based Angle Transmission and its Application

Wireless sensor node's localization is a funda-mental technology in Wireless Sensor Networks. There are only quite a few study on three-dimensional (3D) localization which is suffered in slow progress, actually, is one of the main difficulties in WSN localization. Based on the study of the existing two-dimensional positioning algorithm and the application of terrain modeling, localization algorithm for sensor nodes in (3D) condition has been focus on as well as the application of terrain model. Using the idea proposed by representative algorithm--APS multi-hop AOA (Angle of Arrival), this paper proposed a new algorithm named Multi-hop Three Dimensional AOA With Space-based Angle Trans-mission (MSAT3D AOA). Using this technology, target nodes can use information of anchor nodes which are more than one hop away form. This paper also combined MSAT3D AOA algorithm with Delaunay triangulation algorithm for terrain modeling.

Pseudo‐3D RSSI‐based WSN localization algorithm using linear regression

AbstractReceiver Strength Signal Indication based Wireless Sensor Networks offer a cheap solution for location‐aware applications. For a final breakthrough these systems need fast deployment and easy auto‐configuration. In this study, we use the real‐life iMinds test bed to expand a two‐dimensional localization algorithm to the pseudo third dimension with very low additional computational time. Our experiments show that this fast three‐dimensional algorithm has no outliers and avoids manual calibration. Our algorithm has lower position errors than a maximum likelihood algorithm with a mean square error cost function. Furthermore, with non‐parametric statistical tests, we show that our previously designed two‐dimensional preprocessing performs equally well in pseudo‐three dimensions: the preprocessing reduces the position error in a statistically significant way.Copyright © 2013 John Wiley & Sons, Ltd.

WSN Node Localization Algorithm Based on SA Algorithm

we have realized network node of WSN localization algorithm through SA algorithm，and this paper puts forward a method.This method calculate network node and other relevant information through SA algorithm first and then use then as parameters to calculate again.The second calculation is Using BP neural network algorithm. The accuracy of the result has been multiplied compared with the method that does not use BP neural network algorithm

Graph Rigidity Application for Localization in WSN

Graph Rigidity Application for Localization in WSN

AOD estimation in WSN localization system with synthetic aperture technique

Angel of departure (AOD) based distributed localization scheme in wireless sensor networks allows the single antenna sensor node to estimate its own AOD information by an equivalent antenna array for further position calculation. However, the condition that the number of antennas at the multi-antenna agent/anchor node should be larger than the number of multipath signal components (MPCs) constrains its actual application. In this paper, we provide a more practical approach to achieve AOD information estimation under multipath environment. Given that the sensor node can not identify the line of sight (LOS) signal component due to the insufficient degree of freedom, which is determined by the above limiting condition, we introduce a synthetic aperture technique with the aid of a fast moving multi-antenna agent/anchor node. This operation greatly enlarges the degree of freedom of the equivalent antenna array constructed at sensor node end but without requiring other extra physical antennas equipped at agent/anchor node or sensor node end, which means that it relaxes the limiting condition. Therefore, the AOD information of LOS signal component can be estimated and extracted successfully in complex multipath environment. Theoretical analysis proves the effectiveness of our proposed synthetic aperture technique and numerical simulations show great performance improvement.

Modeling Parameters Optimization for Target Localization in WSN Based on LSSVR by Sampling Measurement Data

Modeling Parameters Optimization for Target Localization in WSN Based on LSSVR by Sampling Measurement Data

The Effects of Stitching Orders in Patch-and-Stitch WSN Localization Algorithms

A "patch-and-stitchrdquo localization algorithm divides the network into small overlapping subregions. Typically, each subregion consists of a node and all or some of its neighbors. For each subregion, the algorithm builds a local map, called a patch, which is actually an embedding of the nodes it spans in a relative coordinate system. Finally, the algorithm stitches those patches to form a single global map. In a patch-and-stitch algorithm, the stitching order makes an influence on both the performance and the complexity of the algorithm. In this paper, we present a formal framework to deal with stitching orders in patch-and-stitch localization algorithms. In our framework, the stitching order is determined by a stitching scheme and the stitching scheme consists of a stitching policy and a potential function. The potential function is to predict how well a patch will be stitched if patches are stitched according to a given partial order. The stitching policy is a mechanism that determines the stitching order based on the predictions by the potential function. We present various stitching schemes and evaluate them through simulations. In addition, we apply the patch-and-stitch strategy into the anchor-based localization and propose a clustering-based localization algorithm. A potential function is used to partition the network into clusters each of which is centered at an anchor node. For each cluster, a cluster map is constructed via the anchor-free localization algorithm. Then, those cluster maps are combined to form a single global map. We propose a stitching technique for combining those cluster maps and analyze the performance of the algorithm by simulations.

A Newton Iteration Based WSN Localization System in Underground Tunnels

One of the main concerns in under construction tunnels is ensuring the safety of the workers and their equipment. Being aware of the real-time position of personnel in such harsh environment is challenging and usually requires a sophisticated localization system. With traditional Received Signal Strength Indicator (RSSII) failing to accurately estimate the distance between nodes due to multipath effect in such long and narrow space, Radio Frequency Time-of-Flight (RF-TOF) is proved to be an alternative method for more accurate distance estimation. To reduce the communication cost, a distributed localization system is proposed, where a simple Newton Iteration location estimation algorithm is embedded in the blind node. Linear least square estimation is used as the initial value to accelerate the convergence of the iteration. Experimental results show the effectiveness of the proposed system