室内可见光通信高精度定位系统设计
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摘要
基于接收信号强度算法的可见光室内定位系统具有结构简单的特点,但是由于漫反射信道、系统噪声等因素,其定位精度受到很大限制,为此提出使用人工神经网络对室内可见光信道参数进行学习,拟合室内信道参数的真实值,实现高精度定位。首先,使用CDMA调制技术消除室内可见多参考点光通信带来的码间干扰问题,CDMA解扩信号经过归一化操作后输入人工神经网络对坐标函数进行训练,使之拟合室内可见光通信信道参数,估计出接收机到各个LED参考点之间的空间距离。其次,由于神经网络训练数据噪声及接收机信号噪声会影响定位精度,我们提出使用Newton-Raphson迭代法,进一步逼近测试点的真实坐标。实验结果表明,在1 m×1 m×1. 2 m的室内可见光通信定位系统模型中,本系统在二维定位应用时平均定位误差为0. 87 cm;在三维定位应用时平均定位误差为1. 47 cm。本文提出的基于接收信号强度的可见光室内定位系统,使用CDMA调制技术,接收信号经过解扩后输入人工神经网络对信道参数进行距离估计,为了进一步地减小噪声等随机过程带来的定位误差,提出一种定位专用的定位坐标解迭代逼近算法,结果表明本系统在二维定位及三维定位均可实现很高的定位精度。
The visible light indoor positioning system based on the received signal strength algorithm has a simple structure. However,due to diffuse reflection channels,system noise and other factors,the positioning accuracy is greatly limited. Therefore,this paper proposes to use artificial neural network to learn indoor visible light channel parameters,and to fit the real value of indoor channelparameters as well as achieve high-precision positioning. Firstly,the CDMA modulation technique is used to eliminate the problem of inter-symbol interference caused by visible multi-reference optical communications in the room. Then the CDMA despreading signal is normalized and input to an artificial neural network to train the coordinate function so as to fit the indoor visible light communication channel parameters. Finally,the spatial distance between the receiver and each LED reference point is estimated. Besides,because the neural network training data noise and the receiver signal noise will affect the positioning accuracy,the Newton-Raphson iterative method is used to further approximate the true coordinates of the test points. The experimental results show that in the 1 m × 1 m ×1. 2 m indoor visible light communication positioning system model,the average positioning error of this system in the two-dimensional positioning application is 0. 87 cm; in the three-dimensional positioning application,the average positioning error is 1. 47 cm. In this paper,a visible light indoor positioning system based on received signal strength is proposed. This system uses CDMA modulation technology. The received signal is despreaded and input artificial neural network to estimate the channel parameters. To further reduce the positioning error caused by random processes such as noise,an iterative approximation algorithm for positioning-based coordinate solutions is proposed.The results show that the system can achieve high positioning accuracy in both two-dimensional positioning and three-dimensional positioning.
The visible light indoor positioning system based on the received signal strength algorithm has a simple structure. However,due to diffuse reflection channels,system noise and other factors,the positioning accuracy is greatly limited. Therefore,this paper proposes to use artificial neural network to learn indoor visible light channel parameters,and to fit the real value of indoor channelparameters as well as achieve high-precision positioning. Firstly,the CDMA modulation technique is used to eliminate the problem of inter-symbol interference caused by visible multi-reference optical communications in the room. Then the CDMA despreading signal is normalized and input to an artificial neural network to train the coordinate function so as to fit the indoor visible light communication channel parameters. Finally,the spatial distance between the receiver and each LED reference point is estimated. Besides,because the neural network training data noise and the receiver signal noise will affect the positioning accuracy,the Newton-Raphson iterative method is used to further approximate the true coordinates of the test points. The experimental results show that in the 1 m × 1 m ×1. 2 m indoor visible light communication positioning system model,the average positioning error of this system in the two-dimensional positioning application is 0. 87 cm; in the three-dimensional positioning application,the average positioning error is 1. 47 cm. In this paper,a visible light indoor positioning system based on received signal strength is proposed. This system uses CDMA modulation technology. The received signal is despreaded and input artificial neural network to estimate the channel parameters. To further reduce the positioning error caused by random processes such as noise,an iterative approximation algorithm for positioning-based coordinate solutions is proposed.The results show that the system can achieve high positioning accuracy in both two-dimensional positioning and three-dimensional positioning.
引文
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[13]章海兵,刘士荣,张波涛. H-S直方图反向投影结合特征点提取的双目视觉定位算法[J].控制理论与应用,2014,31(5):614-623.ZHANG H B,LIU S R,ZHANG B T. Binocular vision position algorithm using hue-saturation histogram back-project combined with feature point extraction[J]. Contr. Theory Appl.,2014,31(5):614-623.(in Chinese)
[14]李桢,黄劲松.基于RSSI抗差滤波的Wi Fi定位[J].武汉大学学报(信息科学版),2016,41(3):361-366.LI Z,HUANG J S. Wi Fi positioning using robust filtering with RSSI[J]. Geomat. Inf. Sci. Wuhan Univ.,2016,41(3):361-366.(in Chinese)
[15]SAHIN A,EROGLU Y S,GUVENC I,et al.. Accuracy of AOA-based and RSS-based 3D localization for visible light communications[C]. 2015 IEEE 82nd Vehicular Technology Conference,Boston,MA,USA,2015:1-5.
[16]DO T H,YOO M. TDOA-based indoor positioning using visible light[J]. Photonic Netw. Commun.,2014,27(2):80-88.
[17]NAZ A,ASIF H M,UMER T,et al.. PDOA based indoor positioning using visible light communication[J]. IEEE Access,2018,6:7557-7564.
[18]JEONG E M,YANG S H,KIM H S,et al.. Tilted receiver angle error compensated indoor positioning system based on visible light communication[J]. Electron. Lett.,2013,49(14):890-892.
[19]ZHANG X L,DUAN J Y,FU Y G,et al.. Theoretical accuracy analysis of indoor visible light communication positioning system based on received signal strength indicator[J]. J. Lightw. Technol.,2014,32(21):4180-4186.
[20]SERTTHIN C,OHTSUKI T,NAKAGAWA M. 6-axis sensor assisted low complexity high accuracy-visible light communication based indoor positioning system[J]. IEICE Trans. Commun.,2010,E93-B(11):2879-2891.
[21]YANG C,WANG Y Q,WANG Y G,et al.. Demonstration of high-speed multi-user multi-carrier CDMA visible light communication[J]. Opt. Commun.,2015,336:269-272.
[2]逄涵涵.基于LED的高速水下光通信系统的设计与实现[D].青岛:中国海洋大学,2013.PANG H H. The Design and Implementation of LED-based High-speed Underwater Optical Communication System[D].Qingdao:Ocean University of China,2013.(in Chinese)
[3]迟楠,卢星宇,王灿,等.基于LED的高速可见光通信[J].中国激光,2017,44(3):300001-1-12.CHI N,LU X Y,WANG C,et al.. High-speed visible light communication based on LED[J]. Chin. J. Lasers,2017,44(3):300001-1-12.(in Chinese)
[4]WANG Z X,YU C Y,ZHONG W D,et al.. Performance of a novel LED lamp arrangement to reduce SNR fluctuation for multi-user visible light communication systems[J]. Opt. Express,2012,20(4):4564-4573.
[5]CHI N,WANG Y Q,WANG Y G,et al.. Ultra-high-speed single red-green-blue light-emitting diode-based visible light communication system utilizing advanced modulation formats[J]. Chin. Opt. Lett.,2014,12(1):010605-1-4.
[6]CHI Y C,HSIEH D H,TSAI C T,et al.. 450-nm Ga N laser diode enables high-speed visible light communication with 9-Gbps QAM-OFDM[J]. Opt. Express,2015,23(10):13051-13059.
[7]WU F M,LIN C T,WEI C C,et al.. 1. 1-Gb/s White-LED-based visible light communication employing carrier-less amplitude and phase modulation[J]. IEEE Photon. Technol. Lett.,2012,24(19):1730-1732.
[8]LUO P F,ZHOU M,ZHANG X,et al.. An indoor visible light communication positioning system using dual-tone multi-frequency technique[C]. 2013 2nd International Workshop on Optical Wireless Communications,Newcastle upon Tyne,UK,2013:25-29.
[9]KIM H S,KIM D R,YANG S H,et al.. An indoor visible light communication positioning system using a RF carrier allocation technique[J]. J. Lightw. Technol.,2013,31(1):134-144.
[10]WEI L,ZHANG H M,YU B Y,et al.. High-accuracy indoor positioning system based on visible light communication[J].Opt. Eng.,2015,54(11):110501.
[11]LATIFF L A,ALI A,CHIA-CHING O,et al.. Development of an indoor GPS-free self-positioning system for mobile Ad Hoc network(MANET)[C]. 2005 13th IEEE International Conference on Networks Jointly Held with The 2005 IEEE 7th Malaysia International Conference on Communication,Kuala Lumpur,Malaysia,2005.
[12]李军怀,张果谋,于蕾,等.基于虚拟信号强度的RFID定位方法研究[J].计算机科学,2012,39(4):67-70.LI J H,ZHANG G M,YU L,et al.. Efficient RFID location method based on virtual signal strength[J]. Comput. Sci.,2012,39(4):67-70.(in Chinese)
[13]章海兵,刘士荣,张波涛. H-S直方图反向投影结合特征点提取的双目视觉定位算法[J].控制理论与应用,2014,31(5):614-623.ZHANG H B,LIU S R,ZHANG B T. Binocular vision position algorithm using hue-saturation histogram back-project combined with feature point extraction[J]. Contr. Theory Appl.,2014,31(5):614-623.(in Chinese)
[14]李桢,黄劲松.基于RSSI抗差滤波的Wi Fi定位[J].武汉大学学报(信息科学版),2016,41(3):361-366.LI Z,HUANG J S. Wi Fi positioning using robust filtering with RSSI[J]. Geomat. Inf. Sci. Wuhan Univ.,2016,41(3):361-366.(in Chinese)
[15]SAHIN A,EROGLU Y S,GUVENC I,et al.. Accuracy of AOA-based and RSS-based 3D localization for visible light communications[C]. 2015 IEEE 82nd Vehicular Technology Conference,Boston,MA,USA,2015:1-5.
[16]DO T H,YOO M. TDOA-based indoor positioning using visible light[J]. Photonic Netw. Commun.,2014,27(2):80-88.
[17]NAZ A,ASIF H M,UMER T,et al.. PDOA based indoor positioning using visible light communication[J]. IEEE Access,2018,6:7557-7564.
[18]JEONG E M,YANG S H,KIM H S,et al.. Tilted receiver angle error compensated indoor positioning system based on visible light communication[J]. Electron. Lett.,2013,49(14):890-892.
[19]ZHANG X L,DUAN J Y,FU Y G,et al.. Theoretical accuracy analysis of indoor visible light communication positioning system based on received signal strength indicator[J]. J. Lightw. Technol.,2014,32(21):4180-4186.
[20]SERTTHIN C,OHTSUKI T,NAKAGAWA M. 6-axis sensor assisted low complexity high accuracy-visible light communication based indoor positioning system[J]. IEICE Trans. Commun.,2010,E93-B(11):2879-2891.
[21]YANG C,WANG Y Q,WANG Y G,et al.. Demonstration of high-speed multi-user multi-carrier CDMA visible light communication[J]. Opt. Commun.,2015,336:269-272.
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