室内可见光定位算法研究

Research on Indoor Visible Light Localization Algorithm

针对室内场所定位精度低的问题,提出一种基于改进粒子群算法的RSSI(Received Signal Strength Indication:接收信号强度指示)可见光定位方法.采用莱维飞行算法对粒子群算法进行改进,解决了标准粒子群算法易陷入局部最优的问题,提高了算法的收敛速度和定位精度.在5 m×5 m×3 m的室内环境下,经过仿真测试,改进后的粒子群算法结合RSSI定位方法定位精度可以达到0.038241 m,算法稳定度上升,定位精度更高,更适合在室内定位中使用.

Aiming at the problem of low positioning accuracy in indoor places,this paper proposes a RSSI(Received Signal Strength Indication)visible light positioning method based on improved particle swarm optimization algorithm.The Lévy flight algorithm is used to improve the particle swarm optimization algorithm,which solves the problem that the standard particle swarm optimization algorithm is easy to fall into the local optimum,and improves the convergence speed and positioning accuracy of the algorithm.In the indoor environment of 5 m×5 m×3 m,after simulation test,the improved particle swarm optimization algorithm combined with RSSI positioning method can reach a positioning accuracy of 0.038241 m,the algorithm stability is improved,the positioning accuracy is higher,and it is more suitable for indoor positioning.