传统的基于可见光通信（VLC）的室内定位算法, 精度相对较低, 误差较大。提出一种RSSI和粒子群混合VLC室内精确定位方法, 该方法通过RSSI算法进行未知节点的初定位, 并利用高斯分布函数剔除误差较大的定位数据, 减少了其对最终定位结果的影响。同时, 通过自适应权重粒子群算法搜索未知节点的最优解, 使得该算法前期较长时间具有最优全局搜索能力, 后期较长时间具有最优局部搜索能力, 能尽快找到未知节点的精确位置。仿真结果表明, 该定位方法比传统的RSSI算法和粒子群算法的定位误差小, 可以大大提高VLC室内定位的精度。

The traditional indoor location algorithm based on VLC has relatively poor location accuracy and high location error. In the paper, a VLC indoor accurate location method was proposed based on RSSI and particle swarm mixing. The method uses RSSI algorithm to initially locate the unknown nodes and uses the Gaussian distribution function to eliminate the high error location data. The VLC indoor accurate location method based on RSSI and particle swarm mixing uses adaptive weighted particle swarm algorithm to search for the optimal solution of unknown nodes. It makes the algorithm have optimal global search ability in an early long period of time and optimal local search capability in a later long period of time. It can find the unknown nodes as soon as possible and get the precise location. Simulation results show that the location error of VLC indoor accurate location method based on RSSI and particle swarm mixing is less than that of both the traditional RSSI algorithm and the traditional particle swarm optimization algorithm. It shows that the method can greatly improve the accuracy of VLC indoor location.