Research On 3D Indoor Positioning Algorithm Based On Visible Light

With the development of society,people’s demand for location services is increasing.The existing positioning technologies,such as infrared,image sensing,radio frequency and Bluetooth,have problems such as complex positioning equipment,low positioning accuracy,and susceptibility to electromagnetic interference,which cannot better realize indoor visible light positioning.Visible Light communation(VLC)technology emerges as The times require.VLC technology has the advantages of simple equipment,high transmission rate,green efficiency and so on.Visible light positioning technology emerges on the basis of visible light communication technology.At present,there are some problems in visible light positioning technology: how to ensure that the light source arrangement scheme can meet the lighting demand and make the receiving plane receive power more uniform;The existing swarm intelligence algorithm has the problem of premature convergence,which is easy to fall into local optimal.How to optimize the localization algorithm and improve the localization accuracy and speed? To solve the above problems,this paper proposes to optimize the transmission power based on the position fusion optimization factor of improved golden sine optimization lamp source arrangement,so as to reduce the received optical power fluctuation of the receiving plane.In order to solve the problems of intelligent algorithm,Gaussian mutation strategy,leapfrog algorithm,adaptive movement factor and Levy flight mutation strategy are proposed to optimize intelligent algorithm,improve the global search ability and positioning accuracy of the algorithm.This paper uses Matlab to conduct simulation analysis,and the specific work content is as follows:(1)A simulation space of 10m×10m×3m is set up.By comparing common light source arrangement schemes,a light source arrangement scheme with strong applicability is obtained.On this basis,transmission power optimization factor is added to make the light power distribution uniform and flat on the premise of satisfying lighting.(2)On the basis of the selected light source arrangement scheme,the light source position optimization and transmission power optimization were carried out,and an improved golden sine algorithm based on the adaptive movement factor was proposed.Through the algorithm,the light power fluctuation small arrangement scheme was found by changing the light source position optimization in the search space,and the light source position coordinates were output as the optimized light source arrangement scheme.The optimal solution is introduced into the receiving power calculation to reduce the receiving power fluctuation and further improve the uniformity of indoor power distribution.The simulation results show that the receiving power fluctuation ranges from-10.9d Bm to-7.9d Bm.Compared with the unoptimized receiving optical power distribution,the power fluctuation decreases obviously.The power distribution in the receiving plane is more uniform,meeting the lighting requirements.(3)An intelligent localization Algorithm based on RSSI was proposed.This dissertation mainly optimized Flower Pollination Algorithm and Atom Search Optimization algorithms.The FPA localization algorithm mainly has the problem that the step size cannot be changed.Gaussian mutation operator is introduced to improve the global search ability of FPA and improve the stability of the algorithm.ASO localization algorithm uses leapfrog algorithm to optimize the initial population position,weaken repulsive force,and make the algorithm converge faster.Adaptive movement factor optimization is combined to improve the proximity of atoms to the optimal individual and avoid the algorithm falling into local optimal.It can be seen from the simulation that the positioning speed and accuracy after optimization have been improved in different degrees,and the positioning error can reach the level of millimeter.The optimization algorithm is also used for multi-point curve positioning,and the average positioning error is about 1cm.The improved algorithm has stronger generalization and is suitable for large indoor places.