散射环境下宽带移动通信衰落信道扩展模型

介绍了采用高精度信道测试设备进行室外100 MHz宽带无线信道测试;针对传统多径衰落无线信道测量模型中易忽略的漫散射效应,提出了包含漫散射指数衰落特性的宽带无线信道扩展模型;基于实测数据提取了相应的扩展模型参数和更准确的时延特性,验证了宽带扩展模型的有效性和必要性.宽带移动通信信道扩展模型能够高精度地描述宽带信道衰落特性,对第四代宽带移动通信系统的设计乃至实际散射环境下的现场试验均有重要意义.     

办公室环境下的超宽带信道测量与建模

依据广泛的频域信道测量数据,提出了符合中国超宽带(UWB)技术频率使用规定的办公室室内信道模型。信道总体模型采用修正Saleh-Valenzuela(S-V)模型。在信道测量信号的后处理中,使用过渡带为高斯滚降特性的类高斯窗来提取符合中国超宽带频谱规范的测量信号。利用CLEAN算法从时域测量数据中提取高分辨率的离散信道响应,并为信道时域测量信号提出了一种基于小波分析的自动分簇算法,统计提取出了大尺度和小尺度信道模型参数。结果表明:提出的办公室超宽带信道模型和实测数据具有相近的时延扩展特性和平均多径数量,可以比IEEE802.15.4a信道模型更好地反映中国办公室环境下的UWB信道特性。     

室内60 GHz毫米波无线信道参数及其相关性研究

基于典型的室内走廊环境,对60 GHz毫米波通信信道参数及其相关特性进行了研究.在视距和非视距条件下,分析了信道参数包括多径个数、均方根时延扩展、莱斯因子、阴影衰落的特点及其分布模型,研究了信道参数之间的相关特性.结果表明:在视距条件下各参数之间普遍具有较强的相关性,而在非视距条件下只有均方根时延扩展和多径个数之间的相关性较强.利用信道参数的相关特性可从一个参数来预测另一参数,为60 GHz无线通信系统的设计提供有用信息.     

OFDM系统基于导频的信道多径时延估计

本文针对宽带正交频分复用(OFDM)系统,分析了多径时延扩展与循环前缀(cP)长度及导频数目的关系.随后利用导频的频域相关性估计得到信道时域功率时延谱(PDP),并根据PDP提出信道均方根(RMS)时延及最大多径时延门限值的估计算法.最终实现OFDM系统对信道多径参量的实时跟踪,有利于系统参数自适应调整.仿真结果表明,本文算法在低复杂度条件下可以有效获知当前传输信道模型多径时延参数的近似统计信息.     

室内走廊环境高频段宽带无线信道测量与建模

为了验证在高频段进行宽带无线通信的可行性,介绍了针对室内走廊环境进行的14GHz宽带无线信道测量和所获取的信道特征。基于频域信道冲激响应测量方法,设计搭建了宽带无线信道测量平台,较好地克服了高频段电波传播能量实时测量采集的难度。基于实测数据提取信道参数化模型,获取了高频段电波传播特性参数统计分析结果,包括路径损耗与阴影衰落、时延扩展、角度扩展。测试与分析结果表明:高频段电波传播时延小、方向性强,适用于宽带互联通信。     

超短波频段复杂城区场景的信道测量与建模

为了准确反映复杂城区环境下移动自组织网络（mobile ad hoc network,MANET）通信节点间的无线信道传播特性,以150 MHz频点为例对山东省青岛市典型城区场景的超短波无线信道进行了外场测量.基于测量数据开展统计分析,提取了路径损耗指数、阴影衰落标准差、多径时延拓展以及频率相关性等信道参数,并针对准视距（quasi-light-of-sight,QLOS）区和非视距（non-light-of-sight,NLOS）区建立了大尺度衰落模型和小尺度抽头延迟线模型.分析和建模结果表明:在MANET城市通信场景下,路径损耗指数随距离增加呈现出双斜率特性;当累积分布函数（cumulative distribution function,CDF）为0.9时,均方根时延在QLOS区为726 ns,在阻挡严重的NLOS区为967 ns;相关带宽在QLOS区和NLOS区分别为700 kHz和300 kHz.论文所建信道模型有利于准确衡量MANET通信设备在复杂城区的通信性能,并为相关通信系统设计提供参考.     

5G毫米波频段不同天线形式信道参数测量及对比分析

基于5G毫米波应用频段,开展了全向天线、喇叭天线以及阵列天线的信道测量与信道参数对比分析研究. 利用空间交替广义期望最大化(space-alternating generalized expectation-maximization, SAGE)算法提取了多径信道参数,包括多径时延、到达角、多径强度等,基于多径分量距离（multipath component distance, MCD）对多径分量进行了分簇结果的对比,对比分析了相同测量点处不同天线形式得到的信道参数差异. 结果表明,同场景下不同天线的信道参数测量结果会有较大差别,全向天线路损指数最小,阵列天线均方根(root-mean-square, RMS)时延扩展和RMS角度扩展均最小,喇叭天线可以得到较多的簇. 本文为5G毫米波频段信道建模提供了不同天线形式信道参数结果对比分析数据.     

超宽带室内LOS环境信道模型研究

分析了室内LOS环境下信号传播规律,多径分量成簇到达.文章针对该特定环境,在S-V模型的基础上,提出将模型中簇的个数定义为两个,并对其进行仿真.仿真结果表明,该模型与IEEE802.15.3a信道模型相比,能较好的反应UWB室内LOS环境信道的特征参数.在其它参数不变的情况下,能减少平均超量延时和均方根时延扩展,对提高...     

OFDM系统基于信道多径时延检测的自适应信道估计

针对宽带正交频分复用(OFDM)系统,提出了一种基于信道多径时延估计的自适应信道估计算法.文章分析了无线信道的特性,随后利用导频频域相关性进行多径时延估计,提出通过动态跟踪信道时延估计参数自适应选择信道估计中适宜的导频数目的方法,同时实现循环前缀(CP)长度的实时调整.仿真结果表明,在时变环境下,本文算法可以有效获知当前信道时延参数的近似统计信息,实现对系统冗余信息的优化.     

太赫兹频段室内场景空-时域信道特性测量与建模研究

掌握太赫兹频段室内信道特性及模型,是太赫兹室内通信系统设计和技术评估的前提。为了解太赫兹频段室内空-时域的信道特性,选取典型室内办公室场景,分别完成视距(Line of Sight, LoS)和非视距(Non Line of Sight, NLoS)场景下100 GHz频段、带宽为1.2 GHz的信道测量。通过分析结果,发现两场景的均方根时延扩展值和均方根角度扩展值都服从正态分布,且NLoS场景的两种参数值都比LoS场景大。此外,由于太赫兹频段多径信号分量较少,且测量场景尺寸较小,使得实测的均方根时延扩展值的测量结果比3GPP标准值约小12 ns。通过建立对数距离模型探讨测量距离对两种参数的影响,发现均方根角度扩展值在NLoS场景中随距离的增加有上升趋势,而均方根时延扩展值在两场景中变化趋势相反。     

基于动态异构冗余架构的车载网络内生安全机制

针对车载网络通信报文容易被捕获重放的问题,该文提出一种基于动态异构冗余(DHR)架构的车载网络内生安全机制(ESM-VN)。首先,对车载网络重放攻击进行建模分析,总结重放攻击依赖的车载网络特征;然后结合网络空间内生安全理论,设计车载网络通信报文动态异构冗余的实现机制,通过拟态裁决和负反馈机制实现攻击感知与主动防御的协调统一。实验结果表明,相比于传统车载网络防御方法,该文所提机制能够在至少降低50%报文响应时延的同时,有效提高车载网络对重放攻击的防御能力。     

VehLoc: an in-vehicle high-precision location method based on BLE multi-channel RSSI values

High precision in-vehicle positioning is the basis of providing smart in-vehicle service, passengers' behavior analysis and other issues, and has important practical value. The RSSI (received signal strength indicator) values of BLE (bluetooth low energy) can be used to do analysis and computation in location system. To deal with the problem that RSSI is vulnerable to environmental issues, an in-vehicle location method called VehLoc based on BLE multi-channel multi-RSSI values was proposed. By using a plurality of Bluetooth transmitters, the location of the receiving terminals in the vehicle was analyzed by combining the coarse, fine classifier and distribution fitting of the user's RSSI values in different channels. The experimental results show that the average accuracy of VehLoc in the five main positions in-vehicle classification can reach 90%.     

IMAPCAR: A 100 GOPS In-Vehicle Vision Processor Based on 128 Ring Connected Four-Way VLIW Processing Elements

This paper presents IMAPCAR, a 100GOPS programmable highly parallel vision processor LSI consuming less than 2 W of power for in-vehicle vision tasks of driver assistance systems. First, requirements of vision processors for driver assistance systems as well as the characteristics of vision tasks for safety are summarized. Next, features in the design of IMAPCAR are described in detail, which comparing with a previous design, improved the performance for major vision tasks by a factor of 2.5 while reduced 50% of power. Design choices taken by other in-vehicle vision processors are also compared and analyzed. Finally, technology perspectives of future in-vehicle vision processors are discussed.     

A novel intrusion detection model for the CAN bus packet of in-vehicle network based on attention mechanism and autoencoder

The attacks on in-vehicle Controller Area Network (CAN) bus messages severely disrupt normal communication between vehicles. Therefore, researches on intrusion detection models for CAN have positive business value for vehicle security, and the intrusion detection technology for CAN bus messages can effectively protect the in-vehicle network from unlawful attacks. Previous machine learning-based models are unable to effectively identify intrusive abnormal messages due to their inherent shortcomings. Hence, to address the shortcomings of the previous machine learning-based intrusion detection technique, we propose a novel method using Attention Mechanism and AutoEncoder for Intrusion Detection (AMAEID). The AMAEID model first converts the raw hexadecimal message data into binary format to obtain better input. Then the AMAEID model encodes and decodes the binary message data using a multi-layer denoising autoencoder model to obtain a hidden feature representation that can represent the potential features behind the message data at a deeper level. Finally, the AMAEID model uses the attention mechanism and the fully connected layer network to infer whether the message is an abnormal message or not. The experimental results with three evaluation metrics on a real in-vehicle CAN bus message dataset outperform some traditional machine learning algorithms, demonstrating the effectiveness of the AMAEID model.     

Evaluation of Vehicle Penetration Loss at Wireless Communication Frequencies

Measurements and simulations of the vehicle penetration loss (VPL) at 600, 900, 1800, and 2400 MHz are presented. The measured average penetration loss varies from 3.2 to 23.8 dB, depending on frequency, illuminated vehicle side, and in-vehicle antenna orientation. VPL tends to follow a lognormal distribution. Reported penetration loss values are compared to previous measurements from the literature.     

Traffic Shaping for Resource-Efficient In-Vehicle Communication

In-vehicle communication has become complex and costly due to the growing number of automotive network systems applied for different data types. In this work, our previously proposed in-vehicle network architecture that is based on Internet Protocol (IP) and full-duplex switched Ethernet (IP/Ethernet) is further investigated for real-time audio and video streaming. Quality-of-service (QoS) and resource usage are analyzed for selected IP/Ethernet-based network topologies. Traffic shaping is used to reduce the required network resources and consequently the cost. A novel traffic shaping algorithm is presented that outperforms other traffic shapers in terms of resource usage when applied to variable bit rate video sources in the proposed double star topology. In addition, a new architecture design is introduced for traffic shaper implementation in switches which operates on a per stream basis. Analytical and simulation results confirm that the proposed network architecture with traffic shaping is well-adapted for in-vehicle communication.      

基于CGI Studio的汽车液晶仪表显示系统的设计与实现

CGI Studio是富士通公司为车用混合2D与3D图形接口(HMI/GUI)所建立的软件开发平台,对OpenGL ES进行的封装。可进行2D/3D建构与编辑、效率测量与改善、状态机器整合与测试,以及完善的2D/3D渲染引擎,可实现先进车载人机界面(HMI)应用程序。将开发者从繁琐、复杂的开发流程中解放了出来,极大地提升了开发效率。本文设计了一种基于CGI Studio的纯电客车液晶仪表底板和核心板相结合的显示系统。提出了合理运用CGI Studio对图片导入、属性的赋予、变量的绑定与生成来搭建液晶仪表显示系统的方法。提高了仪表的开发效率和人机交互性能,缩短了二次开发周期,减少了跨平台移植的复杂程度。     

智能网联汽车网络系统的研究

随着汽车的电动化、智能化和网联化,智能网联汽车已经成为汽车转型的重要发展方向之一。智能网联汽车上的电控系统、传感器等电子元件和系统的数量更多,这要求各系统之间的通信更加安全、迅速、准确,因此智能网联汽车必定是一个庞大的网络系统。文中从智能网联汽车网络的类型和特点、车载自组织网络以及车载移动互联网等方面,介绍了智能网联汽车的网络系统。     

基于AT89S52的车载压实度检测仪设计

随着现代化高等级公路建设规模的不断扩大,对路基压实质量的要求也越来越高.传统的压实质量检测方法是用人工抽样检测来推测所有的压实区域,其结果误差较大,易造成漏检,因此研制开发一种快速、无损、定量的压实度检测仪器迫在眉睫.利用Atmel公司的AT89S52完成了基于单片机的车载振动压路机压实度仪的硬件和软件设计,并根据RS-232协议实现与上位PC机的串行通信.     

基于车载视频图像的道路消失点检测算法

道路消失点检测是高级驾驶辅助系统中盲区监测的重要组成部分。针对现有消失点检测方法所存在的准确度低、运算量大等问题,提出一种基于车载视频图像的道路消失点检测算法。该算法在Harris角点检测基础上优化得分函数检测出图像特征点,减少在跟踪阶段的运算量;通过金字塔光流法和帧差距离对运动特征点进行跟踪,在结束帧上准确获得各特征点的位置;对特征点去除离值点后,通过优化初始聚类中心的K-Means聚类算法,得到车载视频图像的道路消失点。最后将算法应用于各种车辆行驶场景进行测试,在较短运行时间内,能准确检测出车载视频图像中道路消失点,证明算法鲁棒性好、运算简单易实现。