The Research of Indoor Positioning Based on Visible Light Communication

The key techniques in indoor positioning based on visible light communication and the state of the art of this research were surveyed. First, the significance of indoor positioning based on visible light communication from two aspects of the limitations of current indoor positioning technology and the advantages of visible light communication was discussed; And then, the main four technology of indoor positioning based on visible light communication were summarized and the triangulation of RSS method and the principle of image positioning were introduced in detail; Next, the performance characteristics of various typical algorithms were compared and analyzed; In the end, several suggestions on future research of indoor positioning based on visible light communication were given.

An Indoor Positioning Scheme for Visible Light Using Fingerprint Database with Multi.Parameters

This paper proposes a novel indoor positioning scheme based on visible light communication(VLC).A new indoor VLC positioning scheme using fingerprint database with multi-parameters have been raised.We conduct simulation and experimental research on the illumination intensity distribution of several direction parameters.In the experiment,four LED matrixes are identified by LED-ID with room dimensions of 3.75×4.00×2.7 m^3.The results show that the mean of the location error is 0.22 m in the receiving plane,verifying the correctness and feasibility of the positioning scheme.

HY-PC:Enabling Consistent Positioning and Communication Using Visible Light

Visible light(VL)plays an important role in achieving high-precision positioning and low bit error radio(BER)data communication.However,most VL-based systems can not achieve positioning and communication,simultaneously.There are two problems:1)the hybrid systems are difficult to extract distinguishable positioning beacon features without affecting communication performance,2)in the hybrid systems,the lost data bits in the inter-frame gap(IFG)are hard to recover,which affects positioning and communication performance.Therefore,in this article,we propose a novel VL-based hybrid positioning and communication system,named HY-PC system,to solve the above problems.First,we propose the robust T-W mapping for recognizing specific Light Emitting Diodes(LEDs),which can provide stable LED recognition accuracy without adding extra beacon data and does not decrease the communication rate.Furthermore,we also propose the novel linear block coding and bit interleaving mechanism,which can recover the lost data bits in the IFG and improve data communication performance.Finally,we use commercial off-the-shelf devices to implement our HY-PC system,extensive experimental results show that our HY-PC system can achieve consistent high-precision positioning and low-BER data communication,simultaneously.

Dynamic Visible Light Positioning Based on Enhanced Visual Target Tracking

In visible light positioning systems,some scholars have proposed target tracking algorithms to balance the relationship among positioning accuracy,real-time performance,and robustness.However,there are still two problems:(1)When the captured LED disappears and the uncertain LED reappears,existing tracking algorithms may recognize the landmark in error;(2)The receiver is not always able to achieve positioning under various moving statuses.In this paper,we propose an enhanced visual target tracking algorithm to solve the above problems.First,we design the lightweight recognition/demodulation mechanism,which combines Kalman filtering with simple image preprocessing to quickly track and accurately demodulate the landmark.Then,we use the Gaussian mixture model and the LED color feature to enable the system to achieve positioning,when the receiver is under various moving statuses.Experimental results show that our system can achieve high-precision dynamic positioning and improve the system’s comprehensive performance.

Real-Time Video Transmission of Visible Light Communication Based on LED

In order to realize the video image transmission and the excellent lighting function of the visible light communication system, a LED-based visible light communication method and system is proposed. Based on the field programmable gate array (FPGA) hardware, the RS channel coding is applied to the visible light communication system. A pulse position decision algorithm is proposed, which is applied to the receiver of the visible light communication system to meet the error-free decision of the signal. The design of the system is based on the analog-to-digital conversion circuit, which provides a large signal dynamic range for the pulse position decision algorithm, and designs the LED driver based on the bias circuit to realize the fast broadband modulation of the signal. The test results show that the combined application of pulse position decision algorithm and Reed-Solomon codec can reduce the error of system signal and meet the real-time and reliable transmission of signal. The system can display the received video in real time from the receiver, and the whole system communication distance up to 5 m.

基于SSK的室内VLPC系统设计及性能分析

本文设计了一个多输入单输出(Multiple-Input Single-Output,MISO)的三维室内可见光定位通信一体化(Visible Light Position and Communication,VLPC)系统,该系统在接收端基于接收信号强度(Received Signal Strength,RSS)的三维可见光定位(Visible Light Position,VLP)算法获得定位数据,同时估计信道状态信息(Channel State Information,CSI)并上传给发射端进行定向通信.该系统的发射端基于空移键控(Space Shift Keying,SSK)的室内可见光通信(Visible Light Communication,VLC)技术实现系统的通信功能.另外,本方案可以完全避免通信与定位子系统之间的干扰.同时,通过推导定位误差的克拉美罗下界(Cramér-Rao Lower Bound,CRLB)和SSK-VLC的通信可达速率来评估本文提出的VLPC系统的性能.仿真结果验证了本文所提方案的有效性.

VLC-Based Indoor Positioning Algorithm Combined with OFDM and Particle Filter

Visible light communications(VLC) have recently attracted a growing interest and can be a potential solution to realize indoor positioning,however,the performance of existing indoor positioning system is limited by multipath distortion inside a room.In order to combat the effect of multipath distortion,this paper proposes an LED-based indoor positioning algorithm combined with hybrid OFDM(HOFDM),in which asymmetrically clipped optical OFDM(ACOOFDM) is transmitted on the odd subcarriers while using pulse amplitude modulated discrete multitone(PAM-DMT) to modulate the imaginary part of each even subcarrier.In this scheme,we take a combined approach where a received-signal-strength(RSS) technique is employed to determine the location of the receiver and realize the 3-D positioning by Trust-region-based positioning.Moreover,a particle filter is used to further improve the positioning accuracy.Results confirm that this proposed positioning algorithm can achieve high accuracy even with multipath distortion,and the algorithm has better performance when combined with particle filter.

An indoor positioning system for mobile target tracking based on VLC and IMU fusion

An indoor positioning system( IPS) is designed to realize positioning and tracking of mobile targets,by taking advantages of both the visible light communication( VLC) and inertial measurement unit( IMU). The platform of the IPS is designed,which consists of the light-emitting diode( LED)based transmitter,the receiver and the positioning server. To reduce the impact caused by measurement errors,both inertial sensing data and the received signal strength( RSS) from the VLC are calibrated. Then,a practical propagation model is established to obtain the distance between the transmitter and the receiver from the RSS measurements. Furthermore,a hybrid positioning algorithm is proposed by using the adaptive Kalman filter( AKF) and the weighted least squares( WLS)trilateration to estimate the positions of the mobile targets.Experimental results show that the developed IPS using the proposed hybrid positioning algorithm can extend the localization area of VLC,mitigate the IMU drifts and improve the positioning accuracy of mobile targets.

Artificial neural-network-based visible light positioning algorithm with a diffuse optical channel

Visible light positioning becomes popular recently. However, its performance is degraded by the indoor diffuse optical channel. An artificial neural-network-based visible light positioning algorithm is proposed in this Letter, and a trained neural network is used to achieve positioning with a diffuse channel. Simulations are made to evaluate the proposed positioning algorithm. Results show that the average positioning error is reduced about 13 times, and the positioning time is reduced about two magnitudes. Moreover, the proposed algorithm is robust with a different field-of-view of the receiver and the refiectivity of the wall, which is suitable for various position- ing applications.

Visible light positioning: moving from 2D planes to 3D spaces [Invited]

The global navigation satellite system(GNSS) is a well-established outdoor positioning system with industry-wide impact due to the multifaceted applications of navigation, tracking, and automation. At large, however, is the indoor equivalent. One hierarchy of solutions, visible light positioning(VLP) with its promise of centimeter-scale accuracy and widespread coverage indoors, has emerged as a viable, easy to configure, and inexpensive candidate. We investigate how the state-of-the-art VLP systems fare against two hard barriers in indoor positioning: the need for high accuracy and the need to position in the threedimensions(3D). We find that although most schemes claim centimeter-level accuracy for some proposed space or plane, those accuracies do not translate into a realistic 3D space due to diminishing field-of-view in 3D and assumptions made on the operating space. We do find two favorable solutions in ray–surface positioning and gain differentials. Both schemes show good positioning errors, low-cost potential, and single-luminaire positioning functionality.

United block sequence mapping-based visible light positioning for dense small cell deployment

Visible light positioning （VLP） is an emerging candidate for indoor positioning, which carl simultaneously meet the requirements for accuracy, cost, coverage area, and security. However, intercell interference causcd by light intensity superposition linfits the application of VLP. In this Letter, we propose a united block sequence mapping （UBSM）-based VLP that utilizes superposition to integrate the multidimensional information from dense small cells into 2D information. The experimental result shows that UBSM-based VLP can achieve an accuracy of 1.5 cm with a 0.4 m row spacing and 0.35 m column spacing of LED lights.

基于深度学习的可见光通信系统室内三维定位

针对目前室内可见光通信系统三维定位的准确率与定位速度依然不佳的问题,提出一种基于深度学习的可见光通信系统室内定位方法。首先,设计了一个神经网络将指纹数据编码成二维阵列,利用卷积神经网络学习指纹阵列与目标位置之间的关系;然后,通过粒子群优化算法自动搜索卷积神经网络的超参数,以降低深度神经网络的训练难度。此外,设计了定位数据训练集、验证集与测试集的划分方法,有助于缓解神经网络的过拟合问题,并提高定位准确性。仿真结果表明,所提方法在6×6×4m3室内环境下的平均定位误差为0.024m,平均定位时间为0.478s。

一种基于SO-CNN模型的可见光室内定位优化方法

针对基于机器学习的可见光室内定位方法存在的手工调参、定位精度低等问题,结合蛇优化(Snake Optimization,SO)算法的寻优能力与卷积神经网络(Convolutional Neural Network,CNN)处理复杂非线性问题的能力,提出了一种基于SO-CNN模型的可见光室内定位优化方法。在考虑多径效应影响的情况下,采集每个位置点处的信噪比和对应位置坐标构建指纹数据库,对SO-CNN模型进行训练和测试,以得到最佳定位模型。实验结果表明,在5 m×5 m×3 m的房间中,与未经优化的CNN相比,该方法的平均定位误差降低了35.13%;与反向传播神经网络(Back Propagation Neural Network,BPNN)、多层感知器(Multilayer Perceptron,MLP)、SO-MLP相比,该方法的平均定位误差分别降低了54.75%,48.08%,37.01%。

可见光室内定位技术研究进展

可见光赋能的定位技术具有无电磁辐射、成本低、精度高、安全性高、不易受电磁干扰等优势,故近年来可见光室内定位技术(Visible Light Indoor Positioning,VLIP)受到了学界和业界的广泛关注。为了展示VLIP的研究进展和发展全貌,阐述了VLIP的系统架构及相关通信技术,对VLIP基础定位方法及其相关辅助定位技术进行了详细地梳理、分类和对比分析,针对VLIP当前面临的挑战分析了潜在的解决方案,展望了VLIP未来研究方向。

基于多源信息融合的RBF神经网络室内可见光定位算法

针对基于接收信号强度(RSS)的定位技术易受环境干扰而导致定位精度不高和稳定性较差的问题,提出了一种基于多源信息融合的径向基函数(RBF)神经网络室内可见光定位算法。通过将图像的颜色矩特征与RSS矩特征融合,构建指纹库,并采用RBF神经网络进行预测,实现了图像与RSS之间的优势互补,最后对定位算法进行了验证。实验结果表明,经过优化的多源信息融合定位算法较单一RSS定位算法的定位精度提高了9.4%。

零速修正辅助的可见光通信列车连续定位方法

精确的列车位置信息是基于通信的列车控制(CBTC)系统实现安全行车、间隔控制的基础。现有的可见光通信列车定位相关研究往往关注列车处于静止或匀速运动的情况,较少考虑惯性测量单元(IMU)的累积误差及列车静止后IMU的零速偏移。为了实现隧道环境下地铁列车连续定位,提出一种借助零速修正的可见光通信列车定位方法。根据可见光通信(VLC)原理,安装在列车头部顶端的相机连续接收隧道壁上发光二极管(LED)光源的光信号,即LED光源闪烁的频率信息,获取LED光源对应的位置信息,进而推算列车的实际位置。同时,根据列车运行的速度、加速度等参数,采用零速修正算法,判断列车处于运动或零速状态;通过无迹卡尔曼滤波,对运动区段内列车恒定速度模型和恒定加速度模型下的列车定位结果进行优化,并对列车停站时IMU的零速偏移进行校正,补偿列车接收端位置和姿态估计精度的发散,实现隧道环境下列车高精度连续定位。实验结果表明:运动区段内,列车以40、60和80 km/h的速度匀速直线运行时,最大定位误差分别为15.27、16.93和19.57 cm;以80 km/h为最大目标速度时,匀加速和匀减速运动的最大定位误差分别为18.48和18.24 cm;利用零速修正和卡尔曼滤波优化列车定位结果,列车停站时的平均定位误差由11.35 cm降低至6.05 cm。所提方法有效抑制了IMU的零速偏移,满足IEEE 1474.1—2004标准对列车定位精度的要求,可为面向车车通信的CBTC系统实现列车定位提供一定的参考。

基于RSSR融合RNGO-Elman神经网络的室内可见光定位

针对动态环境下基于接收信号强度的传统可见光定位方法定位精度低、稳定性差等问题,提出一种基于接收信号强度比的改进北方苍鹰算法(NGO)优化Elman神经网络(RNGOElman)的室内可见光定位系统。提出选择一个辅助参考点,将待测参考点与辅助参考点的接收信号强度比值和接收机的真实位置作为训练集数据,建立不受动态环境影响的指纹数据库。针对NGO算法收敛速度慢、容易陷入局部最优等问题,利用折射反向学习策略初始化种群,增加种群多样性,引入非线性权重因子来加快收敛速度,避免陷入局部最优。使用优化后的NGO算法来优化Elman神经网络的初始权值和阈值,构建RNGO-Elman动态定位预测模型。仿真结果表明,在4m×4m×3m的实验空间下,优化后的RNGO-Elman定位模型平均定位误差为1.34cm,定位精度相较于Elman定位算法、NGO-Elman定位算法分别提高了82%,21%。在LED发射功率波动时,基于RSSR的RNGO-Elman定位误差为1.29cm,1.38cm。所提可见光定位方法具有定位精度高、定位性能稳定等优点。

一种基于SSA-DBN的室内可见光指纹定位算法

室内可见光定位在精度方面有着较高的要求,针对这一问题,文中提出了一种麻雀搜索算法(Sparrow Search Algorithm,SSA)优化深度置信网络(Deep Belief Network,DBN)的室内可见光指纹定位算法。首先,采用信号强度特征值与位置坐标建立离线指纹库;其次,利用麻雀搜索算法较好的全局探索和局部开发的能力,对深度置信网络的初始权阈值进行优化,建立网络训练模型,对待定位目标的位置进行预测,避免了DBN陷入局部最优以及收敛速度较慢的问题。最后,利用已建立的离线指纹库数据,计算定位误差并分析。在4 m×4 m×2.5 m的空间中进行实验,结果表明:文中算法的平均定位误差为3.51 cm,定位误差在6 cm以内的概率为89.9%,与DBN定位算法相比,平均定位误差下降了约22.5%。

基于卷积神经网络视觉成像可见光室内位置感知模型与光源布局

针对基于接收信号强度(RSS)的可见光室内位置感知系统部署复杂、稳健性差、定位精度低的问题,提出一种基于卷积神经网络(CNN)视觉成像的可见光室内位置感知模型,并研究了光源布局方式。首先,基于环境光和普通发光二极管光源进行了可见光视觉成像位置感知模型的设计和搭建;然后,通过CNN预训练模型提取图像深度特征;在此基础上通过研究不同光源布局模型中定位精度与光源数量、光源间距之间的关系,优化基于CNN视觉成像的室内位置感知模型的定位精度模型。实验结果表明:与基于RSS的室内位置感知模型相比,当定位误差分别小于2.1 cm和3.9 cm时,所提模型的置信概率分别提高了10%和6.7%;同时,与矩形布局方式和三角布局方式相比,十字布局方式的定位精度分别提高了9.5%和16%。

多LED可见光定位通信一体化稳健功率分配

为了实现可见光定位(VLP)与可见光通信(VLC)一体化信号传输,保证稳健通信和有效定位,该文提出一种基于频分复用(FDM)的可见光定位通信一体化(VLPC)信号传输方案,并设计了一种多LED VLPC稳健功率分配方案。首先提出了一种基于频分复用的VLPC传输方案,实现两种信号一体化传输,频谱资源独立分配,从而降低传输时延,提高定位实时性;然后基于定位结果进行可见光信道估计,揭示了信道估计误差、通信速率与实际定位误差之间耦合关系与统计特性;更进一步,基于所得到的耦合关系,研究了多LED VLPC联合功率分配问题,从而最小化定位误差克拉默-拉奥下界(CRLB),并满足功率约束和通信速率中断概率约束,并利用半正定松弛、最差情况条件风险值和连续凸近似等方法,将难以求解的非凸问题转化为一系列凸半正定规划问题进行迭代求解,并获得高质量可行解;最后,经过数值仿真验证,所提出的方案能够同时实现稳健通信和有效定位。稳健传输速率超过350 Mbit/s,并且当最小速率门限为200 Mbit/s,最大中断概率门限为0.01时,在直射路径加散射路径场景中,可以实现厘米级定位。