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8 January 2019 Experimental demonstration of an indoor positioning system based on artificial neural network
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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.
© 2019 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2019/$25.00 © 2019 SPIE
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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