Wu Liming
School of Information Engineering, Guangdong University of Technology, 510006, Guangzhou, China
Li Fujian
School of Information Engineering, Guangdong University of Technology, 510006, Guangzhou, China
Chen Sicheng
School of Information Engineering, Guangdong University of Technology, 510006, Guangzhou, China
ABSTRACT
In order to solve the problem of poor performance of Chan location algorithm based on TDOA parameters in NLOS communication environment, an improved wireless location algorithm is proposed. The fast study and non-linear approach capacity of Radial Basis Function (RBF) neural network is made use of to amend the NLOS error of TDOA measurements and using Chan location algorithm estimates the position. The simulation results show that the algorithm restrained the error of NLOS effectively and improved the positioning accuracy of NLOS propagation environment. Its performance is better than the Chan algorithm and Taylor algorithm and the algorithm has great practical value.
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How to cite this article
Wu Liming, Li Fujian and Chen Sicheng, 2013. A Improved Wireless Location Algorithm in Nlos Environment. Information Technology Journal, 12: 8563-8569.
DOI: 10.3923/itj.2013.8563.8569
URL: https://scialert.net/abstract/?doi=itj.2013.8563.8569
DOI: 10.3923/itj.2013.8563.8569
URL: https://scialert.net/abstract/?doi=itj.2013.8563.8569
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