Research on Improved Multidimensional Scaling Localization Algorithm for Wireless Sensor Network

2010 ◽  
Vol 44-47 ◽  
pp. 3932-3936
Author(s):  
Liang Tao ◽  
Shuai Xu ◽  
Hai Yong Chen ◽  
He Xu Xun
Keyword(s):  
Multidimensional Scaling ◽  
Search Algorithm ◽  
Correction Method ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Wireless Sensor Nodes ◽  
Anchor Nodes ◽  
Hardware Configuration ◽  
Positioning Algorithm

Wireless sensor networks, which are energy limited, low hardware configuration and proneness to invalidation, puts a high demand on the positioning algorithm. Therefore the improved multidimensional scaling (IMDS) algorithm is proposed. In IMDS, firstly, local positioning areas (LPA) are established by an adaptive search algorithm. So the centralized multidimensional scaling (MDS) algorithm is changed into a distributed one. Then the shortest path distances between nodes on LPA are corrected with the geometric correction method (GCM) and adjusting weight correction method (AWCM). The distances between nodes become more accurate. Finally, with information of the public nodes of LPA and anchor nodes, we get the wireless sensor nodes coordinates through coordinate transformation by the SMACOF algorithm and the classical MDS algorithm.

scholarly journals A Combined Localization Algorithm for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaogang Qi ◽  
Xiaoke Liu ◽  
Lifang Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
State Of The Art ◽  
Sensor Nodes ◽  
Vehicle Tracking ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Environment And Health ◽  
Anchor Nodes ◽  
Positioning Algorithm

Wireless sensor networks (WSNs) are widely used in various fields to monitor and track various targets by gathering information, such as vehicle tracking and environment and health monitoring. The information gathered by the sensor nodes becomes meaningful only if it is known where it was collected from. Considering that multilateral algorithm and MDS algorithm can locate the position of each node, we proposed a localization algorithm combining the merits of these two approaches, which is called MA-MDS, to reduce the accumulation of errors in the process of multilateral positioning algorithm and improve the nodes’ positioning accuracy in WSNs. It works in more robust fashion for noise sparse networks, even with less number of anchor nodes. In the MDS positioning phase of this algorithm, the Prussian Analysis algorithm is used to obtain more accurate coordinate transformation. Through extensive simulations and the repeatable experiments under diverse representative networks, it can be confirmed that the proposed algorithm is more accurate and more efficient than the state-of-the-art algorithms.

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

2013 ◽  
Vol 756-759 ◽  
pp. 3562-3567
Author(s):  
Qing Zhang Chen ◽  
Yun Feng Ni ◽  
Xing Hua Li ◽  
Rong Jie Wu ◽  
Yan Jing Lei ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Terrain Modeling ◽  
Terrain Model ◽  
Anchor Nodes ◽  
Slow Progress ◽  
Positioning Algorithm

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.

Optimization of the Wireless Sensor Nodes Localization Algorithm Based on Genetic Algorithm

2014 ◽  
Vol 6 (4) ◽  
pp. 55-64
Author(s):  
Tan Zhi ◽  
Zhang Yuting
Keyword(s):  
Genetic Algorithm ◽  
Fitness Function ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Initial Population ◽  
Localization Algorithm ◽  
Node Localization ◽  
Anchor Nodes ◽  
Reference Weight ◽  
Positioning Algorithm

The node localization technology is a foundation for practical application in wireless sensor networks. According to DV-HOP positioning algorithm in wireless sensor network low precision, the defect of inaccurate positioning, this paper presents an optimization algorithm of improved DV-HOP based on genetic algorithm. The algorithm is to redefine the scope of initial population, the reference weight, redesigned the fitness function and selection of anchor nodes. The simulation results show that compared with the traditional DV - HOP algorithm, the algorithm without any increase in the node hardware overhead on the basis of significantly higher positioning accuracy.

scholarly journals NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2991 ◽  
Author(s):  
Jingyu Hua ◽  
Yejia Yin ◽  
Weidang Lu ◽  
Yu Zhang ◽  
Feng Li
Keyword(s):  
Hypothesis Test ◽  
Intermediate Position ◽  
Wireless Sensor ◽  
Line Of Sight ◽  
Localization Algorithm ◽  
Target Node ◽  
Localization Algorithms ◽  
Anchor Nodes ◽  
Positioning Algorithm ◽  
Non Line Of Sight

The problem of target localization in WSN (wireless sensor network) has received much attention in recent years. However, the performance of traditional localization algorithms will drastically degrade in the non-line of sight (NLOS) environment. Moreover, variable methods have been presented to address this issue, such as the optimization-based method and the NLOS modeling method. The former produces a higher complexity and the latter is sensitive to the propagating environment. Therefore, this paper puts forward a simple NLOS identification and localization algorithm based on the residual analysis, where at least two line-of-sight (LOS) propagating anchor nodes (AN) are required. First, all ANs are grouped into several subgroups, and each subgroup can get intermediate position estimates of target node through traditional localization algorithms. Then, the AN with an NLOS propagation, namely NLOS-AN, can be identified by the threshold based hypothesis test, where the test variable, i.e., the localization residual, is computed according to the intermediate position estimations. Finally, the position of target node can be estimated by only using ANs under line of sight (LOS) propagations. Simulation results show that the proposed algorithm can successfully identify the NLOS-AN, by which the following localization produces high accuracy so long as there are no less than two LOS-ANs.

scholarly journals Improvement of Localization Algorithm for Wireless Sensor Networks Based on DV-Hop

2019 ◽  
Vol 15 (06) ◽  
pp. 53 ◽  
Author(s):  
Xin Qiao ◽  
Fei Chang ◽  
Jing Ling
Keyword(s):  
Estimation Method ◽  
Likelihood Estimation ◽  
Mean Value ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Anchor Node ◽  
Jump Distance ◽  
Anchor Nodes ◽  
Unknown Node ◽  
Positioning Algorithm

In order to solve the problem that the DV-Hop localization algorithm has large errors in the wireless sensor network environment, this paper uses the minimum mean square criterion to determine the average hop distance of anchor nodes, and then calculates the mean value of the original average hop distance, which ensures that the improved average hop distance is closer to the real average hop distance of the whole network. The estimated distances between nodes are calculated by using the correction value corresponding to the average jump distance of the anchor node; in the positioning stage, when the anchor node is small, the estimated coordinates of unknown nodes are obtained by the minimum-maximum method; when the number of anchor nodes is large, the coordinates of unknown nodes are calculated by the maximum likelihood estimation method; this not only reduces the amount of calculation, but also the accuracy is more stable. This step is not only suitable for DV-Hop algorithm, but also can be used to estimate the coordinates when the distance between the unknown node and the anchor node is known. However, this improved method is only applicable to the premise that the simulation area is not large, so this improvement has its scope of adaptation, according to the needs of choice. Finally, the unknown node coordinates are iteratively optimized by using the quasi Newton method. Simulation results show that the proposed positioning algorithm has higher accuracy and better stability.

Advanced Sequence-Based Localization Algorithm in Wireless Sensor Networks

2014 ◽  
Vol 651-653 ◽  
pp. 387-390 ◽  
Author(s):  
Fu Bin Zhou ◽  
Shao Li Xue
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Measuring Devices ◽  
Localization Algorithms ◽  
Positioning Algorithm ◽  
Range Free

As an important application of Internet of Things , Wireless Sensor Networks utilized in surveillance and other case.Localization of nodes in wireless sensor networks is the prerequisite and base of target tracking in some surveillance applications, so localization error of sensor nodes is a key. However, due to limited energy, unreliable link and limited communication ranges of sensor nodes, high accurate positioning is difficult to achieve, which made it hot and full of challenging for wireless sensor nodes to localize without any auxiliary facilities. Range-based localization algorithm , could achieve good accuracy but require measuring devices, thus it is not appropriate for large-scale wireless sensor networks.So range-free localization algorithms are more popular.This paper analyses the algorithms in range-free localization,and proposed Advanced Sequence-Based Localization algorithm to improve the performance of positioning algorithm in wireless sensor network.

scholarly journals Improved DV-Hop Localization Algorithm for Wireless Sensor Networks

2020 ◽  
Vol 9 (5) ◽  
pp. 1324-1330
Keyword(s):  
Mean Squared Error ◽  
Classical Method ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Minimum Mean Squared Error ◽  
Squared Error ◽  
Minimum Number ◽  
Anchor Nodes ◽  
Error Method

Considering the emerging applications of Wireless Sensor Network, the localization of sensor nodes is very important in some applications. Hence in this paper, proposed an improved Distance-Vector hop technique to reduce the localization error generated in the classical method of range free DV-hop algorithm. The proposed algorithm targets to minimize the error introduced in the average hop-size value by the series of mathematical corrections like minimum mean squared error method, modifying the average hop-value value calculated between known sensor nodes with respect to error-term calculated by comparing the estimated distance with actual distance or Euclidean value of anchor nodes, by using dynamic coefficient of weight with respect to minimum number of hopes, calculating x and y co-ordinates of unknown by using 2-D-hyperbolic method. The final corrections on the x and y values are done by using some geometrical methods. Simulations and results are executed on three different evolution models of network by varying radius of communication range, anchor node percentage and number of sensor nodes

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