基于稀疏度自适应和位置指纹的可见光定位算法  

Visible Light Positioning Algorithm Based on Sparsity Adaptive and Location Fingerprinting

作　　者：徐世武[1,2] 吴怡 王徐芳[1] Xu Shiwu;Wu Yi;Wang Xufang(Key Laboratory of Opto-Electronic Science and Technology for Medicine,Ministry of Education,Fujian Key Laboratory of Photonics Technology,Fujian Normal University,Fuzhou,Fujian 350007,China;Concord University College,Fujian Normal University,Fuzhou,Fujian 350117,China)

机构地区：[1]福建师范大学医学光电科学与技术教育部重点实验室暨福建省光子技术重点实验室,福建福州350007 [2]福建师范大学协和学院,福建福州350117

出　　处：《光学学报》2020年第18期32-40,共9页Acta Optica Sinica

基　　金：国家自然科学基金(61871131,61701118,61901117,61571128);国家自然科学基金促进海峡联合基金(U1805262);福建省科技计划(2019J01267);福建省高校产学合作项目(2018H6007);福建省海洋经济发展补助资金(ZHHY-2020-3);福建省光电传感应用工程技术研究中心开放课题(2018003)。

摘　　要：基于可见光通信的指纹定位,提出一种低复杂度、稀疏度自适应的压缩感知算法。首先,利用位置指纹的稀疏性,将定位问题转换为稀疏矩阵的重构问题。其次,根据重构的残差值,自适应地计算近邻值。最后,详细分析指纹采样间距、信噪比、调制带宽及发射功率对定位误差的影响,详细分析所提定位算法的时间复杂度、最优近邻值的分布、发光二极管个数及最大近邻指纹数对定位误差的影响。仿真结果表明,所提定位算法的平均计算时间低、定位误差小,当信噪比为10 dB,指纹点之间的间距为40 cm时,所提定位算法的平均定位误差为1.56 cm,显著低于现有的同类算法。In this paper,a low-complexity,sparsity adaptive compressed sensing algorithm is proposed based on fingerprint localization of visible light communication.First,the localization problem is transformed into a sparse matrix reconstruction problem based on the sparsity of location fingerprints.Second,the nearest neighbor value is adaptively calculated based on the reconstructed residual value.Finally,the impact of fingerprint sampling interval,signal-to-noise ratio,modulation bandwidth,and transmission power on positioning errors are analyzed in detail.Moreover,the time complexity,distribution of the optimal nearest neighbor values,number of the light-emitting diodes,and maximum number of nearest neighbor fingerprints of the proposed positioning algorithm on positioning errors are also analyzed.The simulation results show that the proposed positioning algorithm has comparatively low average calculation time and small positioning error.When the signal-to-noise ratio and the distance between the fingerprints are 10 dB and 40 cm,respectively,the average positioning error of the proposed positioning algorithm is 1.56 cm,which is significantly lower than those of existing algorithms.

关 键 词：光通信 可见光通信 接收信号强度指示 位置指纹 室内定位 压缩感知 

分 类 号：TN929.12[电子电信—通信与信息系统]