基于双BP神经网络的室内可见光定位算法

为提高室内可见光定位的精度,提出了一种基于双反向传播(BP)神经网络的单发光二极管(LED)灯室内定位算法.首先在定位区域内使用BP神经网络确定待测目标粗略的位置范围,然后以该位置范围为限制条件,再次使用BP神经网络实现更精确的定位.室内定位系统采用单个LED灯作为发射器,3个水平光电探测器作为接收器接收光功率,避免了...     

基于新型开关键控编码脉冲对的异步可见光定位方法

发光二极管(LED)照明的普及为高精度室内定位提供了一种绿色低成本的解决方案,作为最经济的LED调制方式,开关键控(OOK)由于开关速度、响应时间和节点间同步等的限制,存在定位精度差等问题。该文提出一种基于新型开关键控编码脉冲对的室内信标构造方法及其对应的异步可见光定位模型,各LED仅需按所提规则进行开关键控,光电探测器(PD)端可以获得最大后验概率准则下的最优位置估计。经验证,当信道(含LED和接收机)具有理想带宽、200 MHz和100 MHz带宽时,在30 dB的信噪比(SNR)条件下,终端以90%的概率使得定位精度分别可以达到6 mm, 7 mm和1 cm。在相同条件下,与异步码分多址(CDMA)进行定位、传统OOK基于指纹进行定位以及传统OOK基于接收信号强度进行定位这3种方法相比,该文提出的方法可以获得明显较好的定位效果。另外,当带内信噪比从30 dB恶化至15 dB时,终端的定位精度还能稳健地保持在厘米量级。     

高精度室内可见光定位算法

针对目前室内定位算法精度不高、实现复杂等问 题,提出了一种基于白光LED的可见光室内定位方 法。首先利用由室内不同LED发出的定位参考信号到达定位终端的时间差(TDOA )的测量估计,得 到定位终端到达两个LED的传输距离之差,以此构造距离估计目标函数,然后采用有约束非 线性规划算法得到 定位终端的位置坐标,从而有效地解决了室内噪声环境中常规TDOA定位算法不收敛或误差偏大的问题。 同时,为了进一步优化定位性能,将距离信息引入加权因子中,提出了质心加权混合定位算 法。将提出的 定位算法在5m×5m×3m的空间区域中进行了仿真实验,同时考虑噪声因素的影响,结果 表明,提出的距离 估计目标函数法在信噪比(SNR)为2dB的条件下可以达到平 均5cm的定位误差,采用质心加权处理后平均定位误 差仅为3cm,有效地提高了室内定位精度和系统应用的普适性及鲁棒性。     

LiPro: light-based indoor positioning with rotating handheld devices

In this paper, an indoor positioning method, namely LiPro, is proposed for handheld devices such as smartphones. Based on an empirical light intensity model, we propose a rotating multi-face positioning method that enables a receiver to locate itself in ill-conditioned scenarios which would otherwise make the traditional multilateration impossible—for example when less than three LED lamps are visible to the receiver. In this method, the user manually performs three rotations of the receiver around three orthogonal axes, in a manner similar to the calibration process of a compass. During this process, the receiver continuously collects RSS and magnetic field strength, which are then used to solve for the receiver’s position. LiPro can work with a single source of light, making it a more cost-effective and less demanding than previous approaches. Our experiments show that LiPro achieves a median error of 0.59 m in a corridor with linearly deployed LEDs, and 0.45 m in an office. Moreover, LiPro is shown to be robust against interference from ambient light sources.     

基于朗伯模型参数估计的VLC室内定位优化算法

为实现高精度室内定位,本文设计了一种可见光 通信(VLC)室内定位系统,并通过 结合优化的朗伯模型、码分多址技术(CDMA)、三边定位算法而有效提升了定位精度和系统 扩展性。首先,每个发光二极管(LED)的ID信息经过直接序列调制后加载到LED驱动电路上 ,LED发出带有自身ID信息的灯光信号。在接收端通过光电探测器(PD)接收灯光信号,并 根据扩频码的正交性恢复出ID信息及接收信号强度(RSS),以此提高信道容量并增强系统 抗干扰能力。然后,根据朗伯光源模型,由三边定位算法得出待定位点的定位估计坐标。为 进一步提高精度,引入k最近邻(KNN)思想,采集适当的指纹点并由指纹点信息对每盏灯在 定位估计坐标处的朗伯光源模型参数进行估计,由优化后的朗伯模型计算出精度更高的定位 坐标。在1m×1m×1.35 m的空间区域中,进行本VLC室内定位系统 的实验测试。结果表明,提 出的高精度VLC室内定位系统的平均定位误差降低至2cm左右,其定位精度相比于传统三边 定 位算法提升了30%。此外,该系统方案所采用基于指纹点信息优化朗 伯模型参数的方法具备良好的实用扩展性,可实现广阔的应用场景。     

基于反向学习策略的自适应花授粉接收信号强度指示室内可见光定位

为提高大型室内场所的定位精度,提出一种基于改进自适应花授粉算法的接收信号强度指示(RSSI)可见光定位方案。利用固定在屋顶呈网格型排布的LED发送位置信息,接收端采用基于反向学习策略和自适应花授粉算法的RSSI定位方法实现精确定位。传统花授粉算法具有易陷入局部最优、缺乏变异机制等缺点,利用反向学习策略可使初始种群分布更加均匀,通过提高种群多样性可使算法跳出局部最优;采用有利于全局广泛搜索的自适应移动因子提高收敛速度。在100 m×100 m×100 m大型室内场所的一层100 m×100 m×10 m的空间中,考虑热噪声和散射噪声干扰的情况,经过多次仿真可得,相比于传统定位算法,随机灯排布下采用改进花授粉的RSSI算法的定位误差小于±1 cm;采用网格型灯排布结合改进定位算法的室内可见光定位系统时,定位精度得到明显提升,定位时间大幅缩短。该方案具有定位精度更高、计算速度更快、工作稳定等优点。     

基于多LED的高精度室内可见光定位方法

针对可见光室内定位问题,该文基于接收信号强度(RSS)定位技术,提出一种利用多个LED发射端实现室内定位的方法,即MLED-RSS定位算法。该方法在充分考虑LED拓扑结构对定位性能影响的基础上,利用部署在室内的多个LED,合理选择其中3个LED作为发射节点,采用改进的三边定位法获得定位目标位置信息。定位算法可以有效地解决可见光定位存在的遮挡效应。仿真实验表明,MLED-RSS算法可以实现高定位精度。     

多照明区域协作的室内可见光定位

考虑室内存在障碍物遮挡及背景光和反射光干扰 较强的实际定位场景,提出了一种基于多照明区域 协作的LED可见光室内定位方法。本文方法引入多照明区域联合定位思想,利用分布于室内 不同区域的LED 发出的参考信号估计定位节点到各LED的信号传输时间差,构造协作定位距离估计目标函数 ,并通过非线 性最小二乘(NLLS)算法获得定位目标的位置估计。将提出的定位算法在10m×3m的空间区域中进行定位仿 真,在5W LED照明、双区域协作条件下,获得了平均定位误差7.41 cm的定位精度。结果表明:提出的协 作算法不仅提高了室内定位精度和系统应用的普适性及鲁棒性,而且有效地解决了室内可见 光定位存在的遮挡效应;此外,对动态定位追踪也有一定的效果。     

MEMS IMU Based Pedestrian Indoor Navigation for Smart Glass

In open air environment, Global Positioning System (GPS) receiver can determine its position with very high accuracy. Inside a building the GPS signal is degraded, the position estimation from the GPS receiver is very erroneous and of no practical use. In this paper, we present an indoor navigation system to track the position of a pedestrian by using built-in inertial measurement unit (IMU) sensors of a smart eyeglass. The device used for this project was an intelligent eye-wear “JINS MEME”. Here algorithm for step detection, heading and stride estimation are used to estimate the position based on the known locations of the walker using Pedestrian Dead Reckoning method (PDR). We have used extended Kalman filters as sensor fusion algorithm, where measurements of acceleration and orientation from IMU are used to track user’s movement, pace, and heading. The results showed that the level of accuracy was entirely acceptable. Average deviancy between the estimated and real position was less than 1.5 m for short range of walk was accomplished. There are some ideas for further development. Increasing the accuracy of the position estimation by palliation of stride length estimation error was identified as the most essential.     

基于偏振态变化时延估计的分布式光纤传感系统

提出一种基于偏振态（SOP）变化时延差估计的分布式光纤传感系统。本系统采用两个直流光信号在传感光纤中双向注入,振动会对正向和逆向光造成SOP变化,在各自的尾端利用起偏器检测SOP变化并转换为光强信息。两路信号间的时延差表明了振动的位置信息。对时延差形成的原因进行了理论分析,并阐明利用互相关算法计算该时延差并进行分布式传...     

基于微惯导与VLC的室内高精度定位技术研究

高精度室内定位在很多场合的实用性和必要性日趋显著,其应用前景广阔,已成为研究前沿.基于微惯导技术的室内定位,是目前最为精确和有效的一项定位技术,但由于微惯导测量组件存在不可避免的漂移现象,使其无法长时间独立用于目标的定位.在此背景下,提出了一种基于微惯导(Micro-Inertial Navigation System,Micro-INS)与可见光通信(VLC)系统相结合的定位方法.在该方法中,首先通过微惯导测量组件进行航位推算,然后利用获取的VLC信号对微惯导系统的位置信息进行校准,补偿微惯导系统的定位累积误差.定位实验结果表明,文章所提出的方法可有效地提高系统定位精度,实现室内的长时间精确定位.     

Characterising indoor positioning estimation using experimental data from an active RFID-based real-time location system

Indoor positioning has attracted much research effort due to many potential applications such as human or object tracking and inventory management. Whilst there are a number of indoor positioning techniques and algorithms developed to improve positioning estimation, there is still no systematic way to characterise the estimation. In this paper, we propose a method comprising of three characteristics to characterise indoor positioning estimation. We conducted experiments on an active radio frequency identification (RFID)-based real-time location system in different environmental conditions. We used both a human and a robot to traverse two experimental areas and collected positioning results at different fixed points along the traversal path. Using this basic positioning data, we were able to characterise positioning estimation using three characterisations: position accuracy, centroid consistency and angular distribution. We demonstrate the use of these characteristics for examining different points in a travelling path and different measurements.     

RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers

Solutions for indoor tracking and localization have become more critical with recent advancement in context and location-aware technologies. The accuracy of explicit positioning sensors such as global positioning system (GPS) is often limited for indoor environments. In this paper, we evaluate the feasibility of building an indoor location tracking system that is cost effective for large scale deployments, can operate over existing Wi-Fi networks, and can provide flexibility to accommodate new sensor observations as they become available. This paper proposes a sigma-point Kalman smoother (SPKS)-based location and tracking algorithm as a superior alternative for indoor positioning. The proposed SPKS fuses a dynamic model of human walking with a number of low-cost sensor observations to track 2-D position and velocity. Available sensors include Wi-Fi received signal strength indication (RSSI), binary infra-red (IR) motion sensors, and binary foot-switches. Wi-Fi signal strength is measured using a receiver tag developed by Ekahau, Inc. The performance of the proposed algorithm is compared with a commercially available positioning engine, also developed by Ekahau, Inc. The superior accuracy of our approach over a number of trials is demonstrated.     

LED clipping distortion compensation in optical wireless communication via multiple transmit LEDs

A method to reduce signal clipping distortion in indoor optical wireless communication systems based on orthogonal frequency division multiplexing (OFDM) modulation is presented in this paper. Compensating the resulting clipping distortion due to LED operational constrains is achieved through the use of iterative signal clipping (ISC) and multiple light emitting diodes (LED) at the transmitter. ISC technique is based on iterative clipping of the time domain OFDM signal and transmission from a multiple LED transmitter. Transmit LEDs are synchronized, located close to each other, and placed to emit light in the same direction. Hence, the channel path gains from each LED to the receiver photo diode are similar. The received signals from the different LEDs add coherently at the receiver. Reported results demonstrate that the effect of distortion due to clipping is eliminated or significantly reduced based on the considered number of LEDs.     

LED通信中利用蚁群算法优化光功率

室内可见光通信(VLC)的多光源阵列对称放置在房间的天花板上,光从LED光源出发经过直射、反射到达接收机端,在同一接收平面用户的接收光功率和照明强度不相等致使不能享受同等的通信服务质量,难以保证通信的公平性。针对通信系统中光源放置位置导致接收平面的接收光功率和照明强度分布由房间中心向周围快速衰减的问题,通过在4×4LED发射阵列端配备功率调节因子,利用蚁群算法建立与接收光功率和照明强度相对应的节点和路径的模型,提出使用方差作为评价接收光功率和照明强度均匀化的目标函数,构建能见度表达式据此推导出状态转移概率公式,并根据LED发射阵列和接收机位置对称的要求选取一组优化功率调节因子值。仿真结果表明,接收光功率和照明强度的方差分别从优化前的168 252和653 742降低到优化后的19.266 3和74.859 2,接收平面接收光功率和照明强度分布不均匀性得到明显改善。     

Effect of LED Radiation Pattern on BER Performance in Indoor Multipath MIMO-VLC System

The present paper investigates the impact of three radiation patterns of LED namely Lambertian, Batwing, Elliptical on the BER performance of 4 × 4 indoor multiple-input multiple-output (MIMO) visible light communication (VLC) system. The BER simulation has been done using LOS and LOS plus first reflection (L-R1) signals for ceiling-mounted and wall-mounted LEDs. For the case of ceiling-mounted LEDs, impulse response and BER have been computed using those radiation patterns at the centre and corner of a room (5 m × 5 m × 3 m). It has been found that LED having Elliptical radiation profile is more suitable for LOS signal when receiver is placed at the centre position whereas, Batwing radiation is suitable for L-R1 signal, both at the centre and corner positions. In the case of wall-mounted LEDs, impulse response and BER have been determined at the centre of the room using LOS and L-R1 signals. The results show that Batwing has least BER using LOS signal due to its wide radiation beam, but for L-R1 signal, the Elliptical profile having its narrow radiation beam has provided better BER performance. The present study shows that the BER in MIMO-VLC system not only depends on the transmitter and receiver position but also on the radiation patterns of LED and higher order reflection signals.

     

Weighted average indoor positioning algorithm that uses LEDs and image sensors

We propose a weighted average indoor positioning algorithm, which is an improved version of the M.S. Rahman’s algorithm, for the calculation of unknown positions in a visible light communication system consisting of light-emitting diodes (LEDs) and image sensors. The algorithm considers the LED illumination intensity as a key factor, and the generalized Lambert illumination model is adopted to estimate the LED illumination intensity of each pixel in the images obtained at the sensors. The LED illumination intensity is normalized as a weighting factor, following the determination of the center position of the LED image. Simulations showed that the average signal-to-noise ratio in our positioning system was 19.3 dB. The simulation results also showed that the root mean square positioning error was reduced from 6.6 to 3.7 cm when the resolution of the image sensor was 3000 pixels per cm, which is comparable to the error in the widely used M.S. Rahman’s algorithm. The distance between the centers of the lenses and the focal lengths of the lenses also affects the positioning error. After the simulations, the relationship between the positioning error and the lens distance or focal length is deduced. It is observed that this algorithm has lesser positioning errors than the M.S. Rahman’s algorithm.     

Tunnel lane‐positioning system for autonomous driving cars using LED chromaticity and fuzzy logic system

Currently, studies on autonomous driving are being actively conducted. Vehicle positioning techniques are very important in the autonomous driving area. Currently, the global positioning system (GPS) is the most widely used technology for vehicle positioning. Although technologies such as the inertial navigation system and vision are used in combination with GPS to enhance precision, there is a limitation in measuring the lane and position in shaded areas of GPS, like tunnels. To solve such problems, this paper presents the use of LED lighting for position estimation in GPS shadow areas. This paper presents simulations in the environment of three‐lane tunnels with LEDs of different color temperatures, and the results show that position estimation is possible by the analyzing chromaticity of LED lights. To improve the precision of positioning, a fuzzy logic system is added to the location function in the literature [1]. The experimental results showed that the average error was 0.0619 cm, and verify that the performance of developed position estimation system is viable compared with previous works.     

GPS／ODO列车组合定位系统

阐述一种利用多传感器融合技术来提高定位精度和可靠度的方法。将GPS定位技术引入到现有的基于里程计的列车定位方法中,降低里程计单独定位时的误差。分析了数据信息的同步问题并利用GPS接收机的秒脉冲信号实现数据信息的同步。当GPS信号短暂失锁时,采用里程计单独定位,GPS信号一旦重获就对里程计定位误差进行修正,从而提高列车定位系统的定位性能。现场实验结果证明该列车定位系统能够以一种简单的方法提高列车定位系统的精度、可靠度和连续性。     

一种新的单基准站钟差估计方法

基准站钟差是卫星定位系统定位误差的重要来源。为了准确校正基准站钟差以提高定位精度,提出一种基于三参数时钟模型、Singer运动目标模型和Kalman模型的基准站钟差估计算法。实验采用NOVATEL高精度接收机接收卫星的GPS实时数据以提高实验的可靠性。基于Matlab平台对钟差参数、定位坐标和定位误差进行仿真计算,结果证明其能有效提高GPS定位精度。