一种移动终端多天线方向图重构快速选择算法与基于滑动时间窗的加速实现

 多输入多输出(MIMO)系统中,天线选择技术可以在降低复杂度的同时,有效地提高系统的性能.但对于天线安装空间受限的小型终端,天线的数目将受到很大限制,本文结合方向图可重构技术,考虑基于线性接收机的空间复用系统,通过在已选择的发射天线上采用等功率分配等增益传输以减少反馈信息量.在此条件下,推导出空间相关衰落信道下自适应发射天线选择的统计容量公式下限,然后,在此基础上提出基于方向图重构的发射天线快速选择方法以最大化该容量值.此外,在实现中提出了一种基于滑动时间窗的梯度更新估计模型,缩短了算法所需时间.     

基于多任务贝叶斯压缩感知的稀疏可重构天线阵的优化设计

建立方向图可重构天线的联合稀疏模型,基于多任务贝叶斯压缩感知理论提出一种稀疏可重构天线阵的优化设计方法.该方法在实现方向图精确重构的同时可以大幅减少天线数量,节省平台空间,降低设计成本.首先基于多任务贝叶斯压缩感知理论建立多目标方向图的稀疏优化模型,根据权值向量的先验概率分布,利用快速相关向量机估计超参数的最大后验概率来得到多组阵元位置及其激励,实时改变激励以获得不同方向图的稀疏逼近.仿真验证了该方法能够以较少的阵元个数和较高的方向图拟合精度快速实现方向图重构.     

唯相位方法实现方向图可重构阵列天线

使用唯相位方法设计方向图可重构天线,对阵列的激励电流幅度和相位同时进行优化,得到一组电流幅度值,使它适用于多种形状的方向图,同时得到与每种方向图对应的相位值。优化算法选用实数编码的遗传算法。为了把设计结果应用于实践,文中还对电流幅度的分布进行了一定的限制,设计出了具有2种工作状态的方向图可重构天线,最后给出了仿真结果,结果表明,文中讨论的方法在设计方向图可重构天线方面是有效的。     

宽带极化与方向图可重构天线研究

随着无线通信系统的快速发展, 宽带可重构天线将在未来发挥巨大作用.文中综述了四种宽带极化与方向图可重构天线, 它们都具有提高通信系统容量, 消除极化失配, 扩大辐射范围等特点.首先介绍了一种宽带的多线极化可重构天线.此款天线基于L型探针馈电的贴片天线, 实现了0°, 45°, 90°以及—45°极化的选择, 具有宽带、低剖面、高增益的特点.其次, 同样基于L型探针馈电的贴片天线, 通过引入一个输出相位可重构的功分馈电网络, 实现了宽带的圆极化可重构天线, 其同样具有宽带、低剖面、高增益的特点.除了极化可重构天线, 文中还介绍了两款方向图可重构天线, 可分别实现线极化以及圆极化的全向锥状波束以及定向辐射波束的方向图可重构.前者是基于宽带的单极子贴片天线跟L型探针馈电的贴片天线的有机结合.后者是基于环缝隙的贴片天线配合激励端口可重构的功分馈电网络的组合.此两款天线均具有结构紧凑、宽带、增益稳定的特点.     

车载多天线系统实用仿真方向图的生成研究

论述了研制车载通信系统EMC仿真分析软件所用天线方向图的生成技术.针对方向图的生成,建立了场强的计算空间,给出了方向图场强数据的计算方法,提出并实现了通信车车形及天线位置在方向图上的自动叠加.工程实践表明,文中生成的方向图实用、可靠.     

一种高增益的可重构广角天线研制

文章提出一种新型的形似"大"字的高增益、方向图可重构广角天线,研究了天线的重构机理,天线E面和H面的3dB角宽分别达到120°和115°,并同时保持7dB的高增益。本文制作和测试了2.4GHz的天线模型,测量结果与仿真值吻合良好,证明了天线结构的有效性并实现了方向图的可重构。     

MEMS开关在不同功能可重构天线中的应用

在介绍了可重构天线的基本原理和主要特点的基础上,针对具体功能的不同,介绍了MEMS开关在频率可重构天线、方向图可重构天线、以及频率和方向图同时可重构天线中的应用方法。     

可重构轨道角动量天线的研究进展

可重构轨道角动量（Orbital Angular Momentum，OAM）天线技术是突破通信瓶颈的关键技术之一，其在视距（Line of Sight,LOS）通信中的优势可以广泛应用于数据中心的信息交换、无人机空对地通信、无线回程通信和雷达探测等领域。总结了目前常见的模数、极化、方向图和混合可重构OAM天线及其实现形式，比较了当前可重构OAM天线的性能，展望了未来可重构OAM天线在无线通信领域的发展方向，为新型可重构OAM天线的研究与优化提供参考。可重构OAM天线的研究对无线通信系统的发展具有重要意义，在可重构OAM天线下一步的发展中，需要将新型材料与金属结构相结合，基于均匀环形阵列（Uniform Circular Array,UCA）原理的新型可重构OAM天线仍是研究重点。     

基于序列二阶锥的平面稀疏阵方向图重构

针对稀疏阵列天线多方向图可重构问题提出了一种基于序列二阶锥的算法。通过引入共轭对称激励,将方向图的上下界约束转化成凸问题;通过辅助变量的迭代加权,将稀疏阵列的阵元位置优化和多方向图的赋形转化为序列二阶锥问题。文中将算法从线阵推广至面阵,在任意主瓣宽度、响应波纹、零陷及副瓣电平的约束下,通过改变阵元的激励,皆可优化阵元位置排布。仿真结果验证了算法的有效性,可以达到降低天线系统成本的目的。     

带限周期函数的Fourier插值法在天线测量中的应用

天线远场测量是获得其辐射特性的一种常用方法,为得到方向图的细节,测量方向图的角度间隔一般应小于待测天线半功率波束宽度的1/10,否则会导致方向图相关参数如半功率波束宽度、副瓣电平等的不准确. 针对高增益、窄波束天线的远场测量,为了得到精确测量结果,测量间隔要求非常小,导致测试时间长,测试效率低下. 文中提出了一种基于带限周期函数的Fourier插值法的高效率方向图测试方法,此方法将采样间隔增加到待测天线半功率波束宽度量级,仍然可以准确重构出角度间隔任意小的方向图,从而能够显著提高测试效率. 仿真和实测结果证明了本方法的可行性.     

Pattern Matching Performance Analysis Based on Linear Models with Information Backscattered from RFID Tags

Pattern matching localization algorithms are commonly proposed in complex indoor environments. Received signal strength indicator (RSSI) of radio signals backscattered from passive ultra high frequency radio frequency identification (RFID) tags is commonly used as the pattern in matching process. Considering RSSI is severely affected by multipath propagation and noise, etc., more types of patterns will be a better choice for further study. In recent years, phase information is becoming more and more important for RFID-based systems. As for the period ambiguity problem of wrapped phase information, phase difference of arrival (PDOA) of double-frequency signals can be utilized as a type of pattern instead of phase of arrival corresponding to the propagation distance. In this paper, we combine RSSI and PDOA as a brand new type of pattern named RP. In previous study, only localization accuracy is considered to prove effective. It is hard to show the matching performance of the type of pattern with the following process of localization algorithms. Here we take advantage of the linear relationship between pattern Euclidean distance and geographic locations Euclidean distance of tags fixed in reference points to evaluate the distinctiveness performance of RP in matching. The linear correlation of the model is tested at each reference point with experimental data captured from indoor scenario. By evaluating these models statistically, we think RP is better than RSSI and PDOA as a pattern.     

Pedestrian Navigation Based on Inertial Sensors, Indoor Map, and WLAN Signals

As satellite signals, e.g. GPS, are severely degraded indoors or not available at all, other methods are needed for indoor positioning. In this paper, we propose methods for combining information from inertial sensors, indoor map, and WLAN signals for pedestrian indoor navigation. We present results of field tests where complementary extended Kalman filter was used to fuse together WLAN signal strengths and signals of an inertial sensor unit including one gyro and three-axis accelerometer. A particle filter was used to combine the inertial data with map information. The results show that both the map information and WLAN signals can be used to improve the pedestrian dead reckoning estimate based on inertial sensors. The results with different combinations of the available sensor information are compared.     

多元检测线圈在石油拼接套管的远场涡流检测中的应用

在基于远场涡流的拼接套管检测中,拼接套管各管道分析的复杂性会因为远场涡流两次穿透套管壁的特性而增加.当发射线圈处于缺陷位置时,作者已提出基于双接收线圈的伪峰移除方法.当发射线圈处于正常管道位置时,伪峰移除方法并不能移除检测信号中发射线圈处管道的信息,所以本文提出弥补该不足点的方法.该方法首先通过去伪峰方法将检测信号中发射线圈附近的管道情况统一转化为无缺陷的情况;然后,采用维纳去卷积滤波器获取拼接套管上缺陷（接箍可视为缺陷）的位置信息,并根据缺陷位置反向定位拼接套管正常位置.最后,统一移除检测信号中发射线圈处管道的信息.该方法通过仪器测试科索#1井得到验证,有利于提高远场涡流在拼接套管检测分析中的实用性.     

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。     

电磁敏感场景可见光智慧照明及环境监测系统

传统无线通信的方式在电磁敏感场景下难免会对信号造成干扰, 为了不影响通信系统的稳定性与可靠性, 结合可见光具有对电磁不敏感的特性, 搭建了以可见光作为信息载体在电磁敏感环境下实现兼顾照明的智慧系统。首先采用以0.5m×0.5m×0.3m的立体空间作为房间模型、对室内光源布局进行合理的布局优化方法, 使其达到国际化室内照明标准; 其次设计了系统的上下行链路以及信号帧结构, 实现了稳定的信息传输; 最后搭建了系统的实物模型, 并对系统进行了调试。结果表明, 本系统可稳定地实现照明及室内环境参量的实时监控与数据传输, 误比特率低于10-6, 能够稳定通信10h以上。该研究为大场景的布设参量提供了参考。     

TRM-FMM室内无线定位技术

在室内多径环境下信号视距传播易受障碍物影响,导致现有的一些室内定位技术对室内环境分布的估计较为困难。时间反转镜( TRM)室内无线定位技术可以有效地减少室内多径效应对信号的影响以及复杂环境造成的延时。但是,若没有信号传输信道的信息,常规TRM技术的定位精度就会大打折扣。针对该问题,给出了一种基于快速行进算法( FMM)的TRM室内无线定位方法。该方法首先利用FMM和同时代数重建算法( SART )迭代更新计算室内环境分布,然后使用估计结果进行TRM定位。仿真结果显示,对于小型规模的目标物体定位误差约为1.84 cm,在未知室内信道信息的仿真环境下,该方法比常规TRM技术的定位精度提高约32.90倍。     

Location determination using WiFi fingerprinting versus WiFi trilateration

Many applications in the area of location-based services and personal navigation require nowadays the location determination of a user not only in an outdoor environment but also an indoor. Typical applications of location-based services (LBS) mainly in outdoor environments are fleet management, travel aids, location identification, emergency services and vehicle navigation. LBS applications can be further extended if reliable and reasonably accurate three-dimensional positional information of a mobile device can be determined seamlessly in both indoor and outdoor environments. Current geolocation methods for LBS may be classified as GNSS-based, cellular network-based or their combinations. GNSS-based methods rely very much on the satellite visibility and the receiver-satellite geometry. This can be very problematic in dense high-rise urban environments and when transferring to an indoor environment. Especially, in cities with many high-rise buildings, the urban canyon will greatly affect the reception of the GNSS signals. Moreover, positioning in the indoor/outdoor transition areas would experience signal quality and signal reception problems, if GNSS systems alone are employed. The authors have proposed the integration of GNSS with wireless positioning techniques such as WiFi and UWB. In the case of WiFi positioning, the so-called fingerprinting method based on WiFi signal strength observations is usually employed. In this article, the underlying technology is briefly reviewed, followed by an investigation of two WiFi-positioning systems. Testing of the system is performed in two localisation test beds, one at the Vienna University of Technology and another one at the Hong Kong Polytechnic University. The first test showed that the trajectory of a moving user could be obtained with a standard deviation of about ±3–5 m. The main disadvantage of WiFi fingerprinting, however, is the required time consuming and costly signal strength system calibration in the beginning. Therefore, the authors have investigated if the measured signal strength values can be converted to the corresponding range to the access point. A new approach for this conversion is presented and analysed in typical test scenarios.     

基于ES-DOA估计的室内非法信号源定位方法

针对室内非法信号源定位应用的特点,提出一种基于到达方向(DOA)估计的无源定位方法。采用具有解相干能力的基于特征空间的到达角(ES-DOA)估计算法估计来波到达角度空间谱和对应的信号功率;采用一种新的直达路径集成搜寻算法判断信号的直达路径方向,并通过交叉测量法估计非法信号源的位置。仿真实验表明,ES-DOA算法在处理相干阵列信号时,具有高分辨力和较强的抗噪声能力,提出的直达路径识别算法能够在不同室内环境中准确识别信号的直达路径方向,具有较强的鲁棒性。研究证明,该定位方法具有较强的系统可实现性,既能单站定位,又可多站协同工作,部署方便,使用灵活,是一种有效的室内非法信号源定位解决方案。     

Pseudolites/repeaters infrastructure autopositioning approach—mathematics and first simulation-based results

In the various infrastructure-based indoor positioning systems using Global Navigation Satellite System signals, i.e. pseudolites, repeaters, and repealites, there is the need for the terminal to know the positions of the various transmitters. Some techniques have been proposed for high accuracy pseudolite systems, but they require carrier phase measurements and a careful choice of some specific test locations. Other approaches consider that these data are simply available by any means: Of course, this can be achieved through manual distance measurements and the use of maps of the indoor environment. In this paper, we describe a new method that is based on a two-step approach. The first one consists in deploying the system. The second one is the calculation of the position of the transmitters through classic code measurements for a few specific chosen locations. Thus, the system can be deployed without any constraint and the locations of the transmitters calculated through a basic set of elementary measurements. The theoretical method is first described and the resulting accuracy of the position of the transmitters is then evaluated through theoretical calculations. In addition, electromagnetic simulations are carried out in order to estimate the pseudo-range errors of the proposed measurements: The accuracy of the determination of the position of the transmitters is then estimated (note that two receiver tracking loop implementations are considered). Thus, the accuracy of the proposed method is evaluated theoretically and through simulations.     

TDOA-based indoor positioning using visible light

In this paper, we propose an indoor positioning system in which the visible light radiated from LEDs is used to locate the position of receiver. Compared to current indoor positioning systems using LED light, our system has the advantages of simple implementation, low cost, and high accuracy. In our system, a single photo diode receives pilot signals from LED panels on the ceiling. Then, the time differences of arrival of these pilot signals are used to estimate the position of the receiver. The system can be employed easily because it does not require embedding any ID to the pilot signal. In the paper, the estimation accuracy of the proposed system is analyzed through the simulation. The causes of estimation error are analyzed, and the estimation accuracy of the system in various conditions is shown by simulations.