scholarly journals MNCE: Multi-Hop Node Localization Algorithm for Wireless Sensor Network Based on Error Correction

Information ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 269
Author(s):  
Yinghui Meng ◽  
Yuewen Chen ◽  
Qiuwen Zhang ◽  
Weiwei Zhang
Keyword(s):  
Error Correction ◽  
Large Error ◽  
Least Square ◽  
Localization Algorithm ◽  
Target Node ◽  
Node Localization ◽  
Simulation Experiments ◽  
Connectivity Information ◽  
Localization Algorithms ◽  
Anchor Nodes

Considering the problems of large error and high localization costs of current range-free localization algorithms, a MNCE algorithm based on error correction is proposed in this study. This algorithm decomposes the multi-hop distance between nodes into several small hops. The distance of each small hop is estimated by using the connectivity information of adjacent nodes; small hops are accumulated to obtain the initial estimated distance. Then, the error-correction rate based on the error-correction concept is proposed to correct the initial estimated distance. Finally, the location of the target node is resolved by total least square methods, according to the information on the anchor nodes and estimated distances. Simulation experiments show that the MNCE algorithm is superior to the similar types of localization algorithms.

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 Incremental Localization Algorithm Based on Regularized Iteratively Reweighted Least Square

2016 ◽  
Vol 41 (3) ◽  
pp. 183-196 ◽  
Author(s):  
Xiaoyong Yan ◽  
Zhong Yang ◽  
Yu Liu ◽  
Xiaoduo Xu ◽  
Huijun Li
Keyword(s):  
High Stability ◽  
Simulation Experiment ◽  
High Accuracy ◽  
Least Square ◽  
Localization Algorithm ◽  
Localization Method ◽  
Localization Algorithms ◽  
Anchor Nodes ◽  
Regularized Method ◽  
Collinearity Problem

AbstractIncremental localization algorithm is a distributed localization method with excellent characteristics for wireless network. However, its estimated result is generally influenced by the heteroscedasticity arising from cumulative errors and the collineation among anchor nodes. We have proposed a novel incremental localization algorithm with consideration to cumulative errors and collinearity among anchors. Using iteratively reweighted and regularized method, the algorithm reduces the influences of errors accumulation and avoids collinearity problem between anchors. Simulation experiment results show that compared with the previous incremental localization algorithms, the proposed algorithm obtains a localization solution which not only has high accuracy but also high stability. Therefore, the proposed algorithm is suitable for different deployment environments and has high adaptability.

Intelligent Three-dimensional Node Localization Algorithm Using Dynamic Path Planning

2021 ◽  
Vol 14 ◽  
Author(s):  
Songhao Jia ◽  
Cai Yang ◽  
Xing Chen ◽  
Yan Liu ◽  
Fangfang Li
Keyword(s):  
Path Planning ◽  
Dynamic Stiffness ◽  
Three Dimensional ◽  
Localization Algorithm ◽  
Node Localization ◽  
Positioning Accuracy ◽  
Dynamic Path Planning ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Dynamic Path

Background: In the applications of wireless sensor network technology, three-dimensional node location technology is crucial. The process of node localization has some disadvantages, such as the uneven distribution of anchor nodes and the high cost of the network. Therefore, the mobile anchor nodes are introduced to effectively solve accurate positioning. Objective: Considering the estimated distance error, the received signal strength indication technology is used to optimize the measurement of the distance. At the same time, dynamic stiffness planning is introduced to increase virtual anchor nodes. Moreover, the bird swarm algorithm is also used to solve the optimal location problem of nodes. Method: Firstly, the dynamic path is introduced to increase the number of virtual anchor nodes. At the same time, the improved RSSI distance measurement technology is introduced to the node localization. Then, an intelligent three-dimensional node localization algorithm based on dynamic path planning is proposed. Finally, the proposed algorithm is compared with similar algorithms through simulation experiments. Results: Simulation results show that the node coordinates obtained by the proposed algorithm are more accurate, and the node positioning accuracy is improved. The execution time and network coverage of the algorithm are better than similar algorithms. Conclusion: The proposed algorithm significantly improves the accuracy of node positioning. However, the traffic of the algorithm is increased. A little increase in traffic in exchange for positioning accuracy is worthy of recognition. The simulation results show that the proposed algorithm is robust and can be implemented and promoted in the future.

scholarly journals Research on Algorithm of Three-Dimensional Wireless Sensor Networks Node Localization

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Jiang Minlan ◽  
Luo Jingyuan ◽  
Zou Xiaokang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Optimization Method ◽  
Wireless Sensor ◽  
Minimum Problem ◽  
Localization Algorithm ◽  
Node Localization ◽  
Anchor Nodes

This paper proposes a three-dimensional wireless sensor networks node localization algorithm based on multidimensional scaling anchor nodes, which is used to realize the absolute positioning of unknown nodes by using the distance between the anchor nodes and the nodes. The core of the proposed localization algorithm is a kind of repeated optimization method based on anchor nodes which is derived from STRESS formula. The algorithm employs the Tunneling Method to solve the local minimum problem in repeated optimization, which improves the accuracy of the optimization results. The simulation results validate the effectiveness of the algorithm. Random distribution of three-dimensional wireless sensor network nodes can be accurately positioned. The results satisfy the high precision and stability requirements in three-dimensional space node location.

Centroid Localization Algorithm Based on the Anchor Nodes Cellular Distribution

2013 ◽  
Vol 475-476 ◽  
pp. 579-582 ◽  
Author(s):  
Dong Yao Zou ◽  
Teng Fei Han ◽  
Dao Li Zheng ◽  
He Lv
Keyword(s):  
Wireless Sensor Networks ◽  
Cellular Network ◽  
Wireless Sensor ◽  
Cellular Distribution ◽  
Localization Algorithm ◽  
Matlab Simulation ◽  
Node Localization ◽  
Key Technologies ◽  
Anchor Nodes ◽  
Simulation Results

The node localization is one of the key technologies in wireless sensor networks. To the accurate positioning of the nodes as the premise and foundation, this paper presents a centroid localization algorithm based on Cellular network. First, the anchor nodes are distributed in a regular hexagonal cellular network. Unknown nodes collect the RSSI of the unknown nodes nearby, then select the anchor nodes whose RSSI is above the threshold. Finally, the average of these anchor nodes coordinates is the positioning results. MATLAB simulation results show that localization algorithm is simple and effective, it applies to the need for hardware is relatively low.

scholarly journals Localization Algorithm for 3D Sensor Networks: A Recursive Data Fusion Approach

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7626
Author(s):  
Rafaela Villalpando-Hernandez ◽  
Cesar Vargas-Rosales ◽  
David Munoz-Rodriguez
Keyword(s):  
Sensor Networks ◽  
Data Fusion ◽  
Assisted Living ◽  
Ad Hoc ◽  
Location Estimation ◽  
Localization Algorithm ◽  
Noisy Information ◽  
Localization Algorithms ◽  
Anchor Nodes ◽  
Recursive Data

Location-based applications for security and assisted living, such as human location tracking, pet tracking and others, have increased considerably in the last few years, enabled by the fast growth of sensor networks. Sensor location information is essential for several network protocols and applications such as routing and energy harvesting, among others. Therefore, there is a need for developing new alternative localization algorithms suitable for rough, changing environments. In this paper, we formulate the Recursive Localization (RL) algorithm, based on the recursive coordinate data fusion using at least three anchor nodes (ANs), combined with a multiplane location estimation, suitable for 3D ad hoc environments. The novelty of the proposed algorithm is the recursive fusion technique to obtain a reliable location estimation of a node by combining noisy information from several nodes. The feasibility of the RL algorithm under several network environments was examined through analytic formulation and simulation processes. The proposed algorithm improved the location accuracy for all the scenarios analyzed. Comparing with other 3D range-based positioning algorithms, we observe that the proposed RL algorithm presents several advantages, such as a smaller number of required ANs and a better position accuracy for the worst cases analyzed. On the other hand, compared to other 3D range-free positioning algorithms, we can see an improvement by around 15.6% in terms of positioning accuracy.

scholarly journals Wireless Sensor Network Target Localization Algorithm Based on Two- and Three-Dimensional Delaunay Partitions

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Chenguang Shao
Keyword(s):  
Three Dimensional ◽  
Target Localization ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Target Node ◽  
Localization Accuracy ◽  
Localization Method ◽  
Anchor Nodes ◽  
2D And 3D ◽  
The Relationship

The target localization algorithm is critical in the field of wireless sensor networks (WSNs) and is widely used in many applications. In the conventional localization method, the location distribution of the anchor nodes is fixed and cannot be adjusted dynamically according to the deployment environment. The resulting localization accuracy is not high, and the localization algorithm is not applicable to three-dimensional (3D) conditions. Therefore, a Delaunay-triangulation-based WSN localization method, which can be adapted to two-dimensional (2D) and 3D conditions, was proposed. Based on the location of the target node, we searched for the triangle or tetrahedron surrounding the target node and designed the localization algorithm in stages to accurately calculate the coordinate value of the target. The relationship between the number of target nodes and the number of generated graphs was analysed through numerous experiments, and the proposed 2D localization algorithm was verified by extending it the 3D coordinate system. Experimental results revealed that the proposed algorithm can effectively improve the flexibility of the anchor node layout and target localization accuracy.

Incremental Multi-Hop Localization Algorithm Based on Regularized Weighted Least Squares

2019 ◽  
Vol 33 (09) ◽  
pp. 1959032 ◽  
Author(s):  
Ru-Lin Dou ◽  
Bo Hu ◽  
Wei-Juan Shi
Keyword(s):  
Least Squares ◽  
High Efficiency ◽  
Least Squares Method ◽  
Weighted Least Squares ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Weighted Least Squares Method ◽  
Localization Algorithms ◽  
Anchor Nodes ◽  
Regularized Method

Incremental multi-hop localization algorithm applies to networks with broad range and low density of anchor nodes. However, during the localization process, it tends to be affected by accumulative errors and collinear problem between anchor nodes. We have proposed an incremental multi-hop localization algorithm based on regularized weighted least squares method, and the algorithm uses weighted least squares method to reduce the influence of accumulative errors and uses regularized method to weaken the collinear problem between anchor nodes. The results of both real experiment and simulative experiment show that compared to previous incremental multi-hop localization algorithms, the algorithm proposed in this paper can not only well solve the accumulated errors problem and obtain high localization accuracy, but it has also considered the influence of collinear problem on localization computation during the localization process. We evaluate our method based on various network scenes, and analyze its performance. We also compare our method with several existing methods, and demonstrate the high efficiency of our proposed method.

scholarly journals An Algorithm of Mobile Robot Node Location Based on Wireless Sensor Network

2017 ◽  
Vol 13 (05) ◽  
pp. 4 ◽  
Author(s):  
Peng An
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Node Localization ◽  
Simulation Experiments ◽  
Localization Accuracy ◽  
Node Location ◽  
Classical Localization ◽  
Localization Precision

In the wireless sensor network, there is a consistent one-to-one match between the information collected by the node and the location of the node. Therefore, it attempts to determine the location of unknown nodes for wireless sensor networks. At present, there are many kinds of node localization methods. Because of the distance error, hardware level, application environment and application costs and other factors, the positioning accuracy of various node positioning methods is not in complete accord. The objective function is established and algorithm simulation experiments are carried out to make a mobile ronot node localization.  The experimnettal results showed that  the proposed algorithm can achieve higher localization precision in fewer nodes. In addition, the localization algorithm was compared with the classical localization algorithm. In conclusion, it is verified that the localization algorithm proposed in this paper has higher localization accuracy than the traditional classical localization algorithm when the number of nodes is larger than a certain number

An Immune-Based Node Localization Algorithm for WSN

2012 ◽  
Vol 490-495 ◽  
pp. 1207-1211
Author(s):  
Nan Zhang ◽  
Jian Hua Zhang ◽  
Jian Ying Chen ◽  
Xiao Mei Qu
Keyword(s):  
Wireless Sensor ◽  
Localization Algorithm ◽  
Node Localization ◽  
Power Requirement ◽  
The Third ◽  
Third Stage ◽  
Additional Amount ◽  
Node Location ◽  
Anchor Nodes ◽  
Additional Hardware

Node localization technology is the premise and foundation of all applications in wireless sensor network. An improved DV-Hop algorithm was proposed aimed at the low-power requirement of wireless sensor networks. The distances between nodes and anchor nodes were used to calculate the node location in DV-Hop algorithm, and the immune algorithm was used to optimize the estimated location in the third stage of DV-Hop algorithm. The improved algorithm does not require additional hardware devices, and has smaller additional amount of communication and computation.

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