基于蚁群算法的室内可见光高精度三维定位系统

吴兴邦; 文尚胜; 华珺

doi:doi:10.3788/gzxb20174612.1206004

光子学报, 2017, 46 (12): 1206004, 网络出版: 2017-11-23

基于蚁群算法的室内可见光高精度三维定位系统

High Precision 3D Positioning System Design Using Visible Light Communication Based On Ant Colony Algorithm

论文大纲

吴兴邦 ^1,2,*文尚胜 ^1,2华珺 ¹

作者单位

¹ 华南理工大学材料科学与工程学院, 广州 510000

² 华南理工大学发光材料与器件国家重点实验室, 广州 510000

摘要

为了提高室内定位精度, 实现三维定位, 提出一种基于蚁群算法的的可见光通信室内高精度三维定位系统。本系统采用了码分多址(Code Division Multiple Access, CDMA)调制技术,解决了室内可见光通信多信号源之间的符号间干扰.系统中与发光二极管(Light Emitting Diode, LED)光信号源地理位置相关的ID信息码经过直接扩频调制后加载至发光二极管驱动电路, 以光信号的形式在室内传播.光信号经过放大、滤波、采样处理后, 根据码分多址调制技术中扩频码的正交性恢复出ID信息及光强衰减信息.经过计算获得来自不同发光二极管的信号光强衰减因子, 利用蚁群算法的全局搜索性确定最优定位点.引入误差修复因子, 利用蚁群算法的并行搜索性对光强衰减因子偏差进行修正.仿真结果表明, 信噪比为30 dB, 20 dB, 10 dB的条件下, 算法的定位精度分别为2 cm, 4 cm, 8 cm.当计算的精度高于45 cm时, 蚁群算法定位解的搜索效率明显高于遍历法.在10 dB的信噪比条件下, 对光强衰减因子进行修正后100%的测试点都实现了5 cm 定位精度.实验结果表明, 20 dB信噪比条件下, 92.59%的测试点的定位误差小于8 cm, 96.29%的测试点定位误差小于10 cm, 最大定位误差为11.30 cm.经过误差修复后, 96.2%的测试点实现了3 cm的定位精度, 61.6%的测试点实现了2 cm的定位精度.本算法在实现了高精度定位, 减少了获得最优定位解的计算量.

Abstract

In order to improve indoor localization accuracy and realize three dimensional positioning, a high precision three dimensional positioning system for visible light communication based on ant colony algorithm is proposed. This system adopts Code Division Multiple Access (CDMA) modulation technology and solves the inter symbol interference between multiple signal sources in visible light communication. In the system, the ID information related to the geographical position of LED signal sourses are loaded directly to the LED drive circuit through direct spread spectrum modulation. After the optical signal is amplified, filtered and sampled, the ID information and the intensity attenuation information can be recovered according to the orthogonality of the spread spectrum code in the Code division multiple access modulation technology. After calculation, the signal intensity attenuation factors are obtained from different LEDs and the global searching property of ant colony algorithm is used to determine the optimum location point. The error correction factor is introduced and the parallel search of ant colony algorithm is used to correct the deviation of the intensity attenuation factors.The simulation results show that the positioning accuracy of the algorithm are 2 cm, 4 cm, 8 cm respectively when the condition of signal-to-noise ratio are 30 dB, 20 dB and 10 dB. When the computation accuracy is higher than 45 cm, the searching efficiency of the ant colony algorithm is higher than that of the ergodic method. After correcting the attenuation factor of light intensity, 100% of test points can reach the positioning accuracy of 5 cm under the signal-to-noise ratio condition of 10 dB. The experimental results show that under the condition of 20 dB signal-to-noise ratio, the positioning error of 92.59% of test points is 8 cm and 96.29% of the test points have three dimensional localization error of less than 10 cm. The maximum localization error is 11.30 cm. After error correction, 96.2% of the test points achieve the precision of 3 cm and 61.6% of the test points achieve the precision of 2 cm. The algorithm reduces the computation of the optimal localization solution and achieves high-precision positioning.

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吴兴邦, 文尚胜, 华珺. 基于蚁群算法的室内可见光高精度三维定位系统[J]. 光子学报, 2017, 46(12): 1206004. WU Xing-bang, WEN Shang-shen, HUA Jun. High Precision 3D Positioning System Design Using Visible Light Communication Based On Ant Colony Algorithm[J]. ACTA PHOTONICA SINICA, 2017, 46(12): 1206004.

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