可见光通信的定位与定向系统设计及性能分析

Design and Performance Analysis of Positioning and Orientating System for Visible Light Communication

针对可见光通信的3D定位与定向问题,提出了一种自适应参数与自适应变异粒子群优化的3D定位与定向方法。首先,分析了一种在复杂环境下的基于测距模型的混合3D可见光定位模型,并将定位问题转化为联合概率密度函数的优化问题。其次,通过计算粒子解与种群最优解之间的模糊贴近度,设计了一种自适应参数与自适应变异粒子群优化方法。最后,通过数学方法精确解析了所提3D可见光定位模型的定位与定向误差的理论下边界,即克拉-美罗(Cramer-Rao)下界。结果表明,所提算法的时间复杂度较低,且定位与定向误差都非常接近Cramer-Rao下界,其平均定位与平均定向收敛误差分别为5.99 cm与6.65°,显著优于另外四种基于迭代的可见光定位算法。

A three-dimensional(3D)positioning and orientating method based on an adaptive parameter and adaptive mutation particle swarm optimization is proposed in this study to solve the 3D positioning and orientating problem in visible light communication.First,a hybrid 3D visible light positioning(VLP)model based on a ranging model in a complex environment is analyzed,and the positioning problem is transformed into an optimization problem of the joint probability density function.Second,an adaptive parameter and adaptive mutation particle swarm optimization method are designed by calculating the fuzzy closeness between the solution of the particle and the optimal solution of the population.Finally,the theoretical lower bound of the positioning and orientating error of the proposed 3D VLP model,called the Cramer-Rao lower bound(CRLB),is accurately analyzed using mathematical methods.The results show that the time complexity of the proposed algorithm is low,and the positioning and orientating errors are close to the CRLB.The average positioning and average orientating convergence errors of the proposed algorithm are 5.99 cm and 6.65°,respectively,which are significantly better than those of four other iterative-based VLP algorithms.