scholarly journals Mean Shift-Based Mobile Localization Method in Mixed LOS/NLOS Environments for Wireless Sensor Network

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaosheng Yu ◽  
Peng Ji ◽  
Ying Wang ◽  
Hao Chu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Mean Shift ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Method ◽  
Mean Shift Algorithm ◽  
Mobile Localization ◽  
Significant Research ◽  
The Mean

Mobile localization estimation is a significant research topic in the fields of wireless sensor network (WSN), which is of concern greatly in the past decades. Non-line-of-sight (NLOS) propagation seriously decreases the positioning accuracy if it is not considered when the mobile localization algorithm is designed. NLOS propagation has been a serious challenge. This paper presents a novel mobile localization method in order to overcome the effects of NLOS errors by utilizing the mean shift-based Kalman filter. The binary hypothesis is firstly carried out to detect the measurements which contain the NLOS errors. For NLOS propagation condition, mean shift algorithm is utilized to evaluate the means of the NLOS measurements and the data association method is proposed to mitigate the NLOS errors. Simulation results show that the proposed method can provide higher location accuracy in comparison with some traditional methods.

scholarly journals V2X-Based Mobile Localization in 3D Wireless Sensor Network

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Iram Javed ◽  
Xianlun Tang ◽  
Kamran Shaukat ◽  
Muhammed Umer Sarwar ◽  
Talha Mahboob Alam ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Three Dimensional ◽  
Link Quality ◽  
Wireless Sensor ◽  
Localization Error ◽  
Localization Algorithm ◽  
Position Information ◽  
Mobile Anchor ◽  
Anchor Nodes

In a wireless sensor network (WSN), node localization is a key requirement for many applications. The concept of mobile anchor-based localization is not a new concept; however, the localization of mobile anchor nodes gains much attention with the advancement in the Internet of Things (IoT) and electronic industry. In this paper, we present a range-free localization algorithm for sensors in a three-dimensional (3D) wireless sensor networks based on flying anchors. The nature of the algorithm is also suitable for vehicle localization as we are using the setup much similar to vehicle-to-infrastructure- (V2I-) based positioning algorithm. A multilayer C-shaped trajectory is chosen for the random walk of mobile anchor nodes equipped with a Global Positioning System (GPS) and broadcasts its location information over the sensing space. The mobile anchor nodes keep transmitting the beacon along with their position information to unknown nodes and select three further anchor nodes to form a triangle. The distance is then computed by the link quality induction against each anchor node that uses the centroid-based formula to compute the localization error. The simulation shows that the average localization error of our proposed system is 1.4 m with a standard deviation of 1.21 m. The geometrical computation of localization eliminated the use of extra hardware that avoids any direct communication between the sensors and is applicable for all types of network topologies.

scholarly journals Novel Scheme for Minimal Iterative PSO Algorithm for Extending Network Lifetime of Wireless Sensor Network

2018 ◽  
Vol 8 (2) ◽  
pp. 1084
Author(s):  
Hemavathi P ◽  
Nandakumar A. N.
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Dynamic Network ◽  
Cost Effective ◽  
Pso Algorithm ◽  
Wireless Sensor ◽  
Cost Effective Method ◽  
Significant Research

Clustering is one of the operations in the wireless sensor network that offers both streamlined data routing services as well as energy efficiency. In this viewpoint, Particle Swarm Optimization (PSO) has already proved its effectiveness in enhancing clustering operation, energy efficiency, etc. However, PSO also suffers from a higher degree of iteration and computational complexity when it comes to solving complex problems, e.g., allocating transmittance energy to the cluster head in a dynamic network. Therefore, we present a novel, simple, and yet a cost-effective method that performs enhancement of the conventional PSO approach for minimizing the iterative steps and maximizing the probability of selecting a better clustered. A significant research contribution of the proposed system is its assurance towards minimizing the transmittance energy as well as receiving energy of a cluster head. The study outcome proved proposed a system to be better than conventional system in the form of energy efficiency.

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