Practical Led-Based High-Precision Indoor Positioning Algorithm Research

With the development of the Internet of Things and wireless communication technology,the demand for Location-Based Service(LBS)is in rapid growth,and indoor positioning technology is the key technology of "last 1 meter" in LBS.At the same time,LED-based visible light communication(VLC)has deposited a good infrastructure for a long time,received extensive attention and research in the field of indoor positioning.Compared to the other positioning technologies,visible light positioning(VLP)has many advantages such as high precision,low cost,low power consumption,high security,and so on.There are many algorithms in the VLP field,and the algorithms based on the received signal strength indication(RSSI)are relatively common and cost-effective,which can achieve centimeter positioning accuracy in an ideal indoor environment.However,in an actual environment,the measurement of RSSI value is easily affected by the non-line of sight(NLOS)link,resulting in a large positioning deviation.Therefore,considering the practical application,this paper analyzes the influence of various factors in the RSSI positioning systems on performance,and proposes an RSSI positioning algorithm based on Bayesian detection theory when taking the NLOS link into account.After that it also optimizes the proposed algorithm.The main research contents are as follows:1.Based on the existing VLC channel model,multiple parameters such as reflection,signalto-noise ratio,the field of view,Lambert index,the height of the receiver,and room geometry are taken into consideration.This paper quantitatively studies the influence of these factors on distance estimation by RSSI.The simulation results show that the NLOS link is the most critical factor.Taking the traditional RSSI algorithm as an example,the error can reach up to 80 cm by using the Line of Sight(LOS)link channel to estimate the distance between the receiver and transmitter with the effect of NLOS link.Based on the above analysis,this paper proposes a location algorithm based on Bayesian theory.Firstly,we use a Gaussian filter to reduce the accidental error caused by the receiver noise.Then,we take the filtered RSSI value as a priori information,calculate the posterior probability of each grid point divided in advance,and the point with the maximum sum-probability of 3 LEDs is the estimated coordinate.Considering the running time cost,parts of unnecessary grid points are screened out when calculating the probability distribution for each LED.In a typical VLP system,the simulation results of 100 random test points show that the average error of the proposed method can be reduced from 44 cm to 19 cm compared to the traditional method,and the average positioning time cost is only 1.44 ms.2.Further,this paper optimizes the above algorithm in two aspects.Firstly,a grid partitioning strategy that RSSI theoretical values are sparsely stored is proposed to improve the cost performance between accuracy and calculation consumption.Secondly,the LOS link components are separated by the initial location results based on Bayesian theory,and the location accuracy is further improved by using the trilateration method for the secondary location.Simulation results show that the average error of the optimized algorithm decreases again from 19 cm to 8cm,and the average positioning time consumption is 2.67 ms.