Indoor Three-dimensional Positioning System Based on Visible Light Communication Using Improved Immune PSO Algorithm
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摘要:
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。
Abstract: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.
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表 1 免疫粒子群与3维定位问题的映射关系
免疫算法 粒子群算法 3维定位问题 抗原 适应度函数 定位误差和约束条件 抗体 粒子 可行的定位位置 抗原的识别 粒子的适应度值评估 3维定位问题的分析 亲和度 适应度值 可行解的匹配程度 细胞活化 粒子选择 选择高质量的可行解 记忆细胞 全局最优粒子 定位搜索过程中的最优解 免疫调节 对当前解浓度和亲和度控制 
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表 2 IIMPSO算法参数表
符号 参数 数值 c1max, c2max 学习因子最大值 2.2 c1min, c2min 学习因子最小值 0.2 N 粒子群数目 30 titer 最大迭代次数 100 Pc 交叉概率 0.30 Pm 变异概率 0.05 vmax 最大速度限制 0.3 cth 粒子相似度阈值 0.1 α 协调系数 0.5 fth 适应度值阈值 0.4
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表 4 IIMPSO算法参数表
参数 符号 值 房间大小 L×W×H 5 m×5 m×3 m 接收端高度 H 1 m 发射功率 Pt 452 mW 半功率角 Φ1/2 70° 阵列中LED的数目 – 3×3 LED的间隔 – 0.01 m 集中器增益 Ts(Ψ) 1 PD的接收面积 A 1 cm2 O/E 转换效率 – 0.53 A/W PD的折射率 n 1.5 LED中心发光强度 I(0) 23.81cd
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