Title :
RSSI localization algorithm based on RBF neural network
Author :
Tian, Jiannan ; Xu, Zhan
Author_Institution :
Res. Inst. of Electron. Sci. & Technol., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
This paper proposes a algorithm method of RBF neural network based on RSSI localization algorithm. It solves the question which through traditional filter algorithm, redundancy algorithm can not solve base on effect of multi-route propagation, and the complexity of signal attenuation environment. Simulation results demonstrate the validity of the algorithm, it can mitigate the effect of multi-route propagation, and localization precision can reach one meter or higher. On the side, this algorithm have higher convergence speed, it fits in embedded application. It can be designed as self-study and closed loop neural network in future.
Keywords :
Global Positioning System; filtering theory; radial basis function networks; telecommunication computing; RBF neural network; RSSI localization algorithm; closed loop neural network; convergence speed; embedded application; filter algorithm; multiroute propagation; receive signal strength indication; redundancy algorithm; signal attenuation environment; wireless positioning technology; Flowcharts; Artificial intelligence; Localization Algorithm; NLOS; RBF Neural Network; The Internet of things;
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2012 IEEE 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2007-8
DOI :
10.1109/ICSESS.2012.6269470