A Parametric Study on Gauss-Newton Iterations for Wireless Sensor Network Localization

2020 ◽  
Author(s):  
Alireza Jahangiri ◽  
Meysam Mohammadi-Amin ◽  
Ghasem Kahe
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Parametric Study ◽  
Wireless Sensor ◽  
Sensor Network Localization ◽  
Network Localization ◽  
Newton Iterations

A Recursive Shortest Path Routing Algorithm With Application for Wireless Sensor Network Localization

2016 ◽  
Vol 16 (11) ◽  
pp. 4631-4637 ◽  
Author(s):  
Juan Cota-Ruiz ◽  
Pablo Rivas-Perea ◽  
Ernesto Sifuentes ◽  
Rafael Gonzalez-Landaeta
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Shortest Path ◽  
Routing Algorithm ◽  
Wireless Sensor ◽  
Sensor Network Localization ◽  
Shortest Path Routing ◽  
Network Localization

scholarly journals Cooperative method for wireless sensor network localization

2016 ◽  
Vol 40 ◽  
pp. 61-72 ◽  
Author(s):  
Angel Stanoev ◽  
Sonja Filiposka ◽  
Visarath In ◽  
Ljupco Kocarev
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Sensor Network Localization ◽  
Network Localization

scholarly journals An RSSI-based Wireless Sensor Network Localization Algorithm with Error Checking and Correction

2017 ◽  
Vol 13 (12) ◽  
pp. 52 ◽  
Author(s):  
Bo Guan ◽  
Xin Li
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Sensor Network Localization ◽  
Anchor Node ◽  
Network Localization ◽  
Error Checking

<p style="margin: 1em 0px;"><span style="font-family: Times New Roman; font-size: medium;">This paper studies the wireless sensor network localization algorithm based on the received signal strength indicator (RSSI) in detail. Considering the large errors in ranging and localization of nodes made by the algorithm, this paper corrects and compensates the errors of the algorithm to improve the coordinate accuracy of the node. The improved node localization algorithm performs error checking and correction on the anchor node and the node to be measured, respectively so as to make the received signal strength value of the node to be measured closer to the real value. It corrects the weighting factor by using the measured distance between communication nodes to make the coordinate of the node to be measured more accurate. Then, it calculates the mean deviation of localization based on the anchor node close to the node to be measured and compensates the coordinate error. Through the simulation experiment, it is found that the new localization algorithm with error checking and correction proposed in this paper improves the localization accuracy by 5%-6% compared with the weighted centroid algorithm based on RSSI.</span></p>

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