Experimental demonstration of an indoor positioning system based on artificial neural network

8 January 2019 Experimental demonstration of an indoor positioning system based on artificial neural network

Bangjiang Lin, Qingyang Guo, Chun Lin, Xuan Tang, Zhenlei Zhou, Zabih Ghassemlooy

Author Affiliations +

Funded by: National Natural Science Foundation of China (NSFC), National Science Foundation of China, Natural Science Foundation of China, National Science Foundation NSF CBET, Natural Science Foundation of Fujian Province, Fujian Science Foundation, Chinese Academy of Sciences, External Cooperation Program of Chinese Academy of Sciences, Instrument Developing Project of the Chinese Academy of Sciences

Optical Engineering, Vol. 58, Issue 1, 016104 (January 2019). https://doi.org/10.1117/1.OE.58.1.016104

Abstract

We propose a 2-D visible light positioning system based on the artificial neural network (ANN), where the light-emitting diodes are grouped into blocks and the block coordinates are encoded with under-sampled modulation. A camera is used to decode the block coordinate in the receiver. The receiver’s position is approximately and precisely estimated using the decoded block coordinate and a typical back propagation ANN, respectively. The experimental results show that the proposed scheme offers a mean positioning error of 1.49 cm.

Citation Download Citation

Bangjiang Lin, Qingyang Guo, Chun Lin, Xuan Tang, Zhenlei Zhou, and Zabih Ghassemlooy "Experimental demonstration of an indoor positioning system based on artificial neural network," Optical Engineering 58(1), 016104 (8 January 2019). https://doi.org/10.1117/1.OE.58.1.016104

Received: 4 June 2018; Accepted: 18 December 2018; Published: 8 January 2019

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