基于改进免疫粒子群优化算法的室内可见光通信三维定位方法

针对室内可见光通信中3维定位精度不高和定位时间较长的问题，该文提出基于改进免疫粒子群(IIMPSO)算法的室内可见光通信(VLC) 3维定位方法。通过分析室内多径效应，选取合适的视场角(FOV)以减少反射影响，同时完善了倾斜状态下的定位模型，并采用卡尔曼滤波算法以降低环境干扰对接收功率的影响，在此基础上与改进的免疫粒子群算法相融合。仿真结果表明，在5 m×5 m×3 m的室内环境中，该文所提出的3维定位系统平均定位误差为0.031 m，定位时长为2.3 s。与现有的3维定位系统进行比较，其定位精度与收敛速度均得到明显改善。

Indoor Three-dimensional Positioning System Based on Visible Light Communication Using Improved Immune PSO Algorithm

For the problem that the three-dimensional positioning accuracy is not high and the positioning time is too long in indoor Visible Light Communication(VLC). An indoor visible light three-dimensional positioning system based on Improved IMmune Particle Swarm Optimization(IIMPSO) algorithm is proposed. By analyzing the indoor multipath effects, the fitter Field Of View (FOV) is selected to reduce the influence of the reflection. Meanwhile, the positioning model under the tilt state is improved. The Kalman filter algorithm is used to reduce the impact of environmental interference on the received power. On the basis, it is integrated with the improved immune particle swarm algorithm. Simulation results show the average positioning error of the indoor three-dimensional positioning system is 0.031 m, and the positioning time is 2.3 s in the indoor of 5 m × 5 m × 3 m. Compared with the existing three-dimensional positioning system, the positioning accuracy and convergence speed are significantly improved.