Self-localization algorithm for sensor networks using SVM classification region

2009 ◽  
Vol 29 (4) ◽  
pp. 1064-1067 ◽  
Author(s):  
Ming LIU ◽  
Ting-ing WANG ◽  
Xiao-an HUANG ◽  
Rui LIU
2015 ◽  
Vol 10 (10) ◽  
pp. 1062
Author(s):  
A. Mesmoudi ◽  
Mohammed Feham ◽  
Nabila Labraoui ◽  
Chakib Bekara

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2830
Author(s):  
Sili Wang ◽  
Mark P. Panning ◽  
Steven D. Vance ◽  
Wenzhan Song

Locating underground microseismic events is important for monitoring subsurface activity and understanding the planetary subsurface evolution. Due to bandwidth limitations, especially in applications involving planetarily-distributed sensor networks, networks should be designed to perform the localization algorithm in-situ, so that only the source location information needs to be sent out, not the raw data. In this paper, we propose a decentralized Gaussian beam time-reverse imaging (GB-TRI) algorithm that can be incorporated to the distributed sensors to detect and locate underground microseismic events with reduced usage of computational resources and communication bandwidth of the network. After the in-situ distributed computation, the final real-time location result is generated and delivered. We used a real-time simulation platform to test the performance of the system. We also evaluated the stability and accuracy of our proposed GB-TRI localization algorithm using extensive experiments and tests.


IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 380-399
Author(s):  
Jiaxing Chen ◽  
Wei Zhang ◽  
Zhihua Liu ◽  
Rui Wang ◽  
Shujing Zhang

2015 ◽  
Vol 57 ◽  
pp. 1432-1439 ◽  
Author(s):  
Aarti Singh ◽  
Sushil Kumar ◽  
Omprakash Kaiwartya

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