Visible light indoors positioning algorithm based on deep learning and RSS filtering
To improve the accuracy and stability of the visible light indoors three dimensional positioning,a visible light indoors positioning method based on deep learning and received signal strength indication filtering is proposed.First-ly,all received signal strength indication samples acquired on each reference point are collected,a clustering algorithm is used to filter the received signal strength indication samples,the received signal strength indication samples with signifi-cant deviation in the low value cluster and high value cluster are eliminated;then,the deep neural networks regression model is trained on the high accuracy radio map,so as to learn the statistical relationship between the receiver position and the receive signal strength.Simulation results show that the average positioning error of the proposed method is lower than 4cm in a 6mX6mX3m room,it also has the ability of LED scalability.
deep learningdata clusteringradio mapreceived signal strength indicationdata filtering
NETL
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