Visible Light Indoor Positioning Algorithm Base on the Fruit Fly Modified DV-hop Method

Multi-directional light-emitting diode aided visible light positioning system exploiting regular pyramid: design and demonstration

“…1. The integration of multiple LEDs on a pyramid-shaped metal block simplifies the LED distributed deployment of the traditional nVLP system, [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35] enabling the integrated single lamp to perform positioning function. 2.…”

“…Furthermore, to mitigate the adverse effects of inaccurate model and light intensity variation on the system performance, classical intelligent algorithms are increasingly utilized by researchers to solve the localization problem of the nVLP model, such as machine learning (ML), 22 , 23 artificial neural network (ANN), 24 – 27 and some heuristic algorithms 28 – 35 Specifically, in Ref. 26, the gated recurrent unit neural network (GRU-NN) was employed to deal with the nonlinearity of the nVLP system, resulting in an improvement of average localization accuracy.…”

“…33, two heuristic algorithms of grey wolf optimizer (GWO) and particle swarm optimization (PSO) were adopted to optimize the ELM parameters respectively in order to obtain higher classification accuracy, namely, EML-GWO and EML-PSO algorithms, which have a better positioning performance and robustness than the basic EML algorithm. In addition, some heuristic algorithms such as PSO algorithm, 28 fruit fly algorithm, 30 modified genetic algorithm (GA), 31 , 34 differential evolution algorithm, 32 and improved adaptive cuckoo search (IACS) algorithm 35 were also widely employed in nVLP models to enhance performance.…”