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2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)最新文献

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ICMIM 2019 Cover Page ICMIM 2019封面
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引用次数: 0
Estimation of the Influence of Incoherent Interference on the Detection of Small Obstacles with a DBF Radar 非相干干扰对DBF雷达探测小障碍物影响的估计
Konstantin Hahmann, Stefan Schneider, T. Zwick
As the technology of automated driving progresses, the market penetration and the functional importance of automotive radar systems are on the rise. Multiple access interference (crosstalk) between automotive radars will occur more often, reducing the detection capabilities of radars. The consequences are particularly critical regarding upcoming new requirements, such as the detection of small static targets in the road by radar. This Paper investigates the performance reduction of front mounted digital beamforming (DBF) radars due to the presence of an incoherent interferer on the neighboring track. A model for the estimation of signal-to-noise-ratio-loss due to crosstalk is introduced, focusing the impact of interference periods and quantities on chirp sequence radars. Further, the influence of digital beamforming is taken into account. A worst-case analysis regarding the relative position of the interferer is performed.
随着自动驾驶技术的进步,汽车雷达系统的市场渗透率和功能重要性不断提高。汽车雷达之间的多址干扰(串扰)将更加频繁地发生,从而降低了雷达的探测能力。对于即将到来的新要求,例如用雷达探测道路上的小型静态目标,其后果尤其重要。本文研究了前置数字波束形成(DBF)雷达由于相邻轨道上存在非相干干扰而导致的性能下降。介绍了一种估计串扰信噪比损失的模型,重点讨论了干扰周期和干扰量对啁啾序列雷达的影响。此外,还考虑了数字波束形成的影响。对干扰源的相对位置进行了最坏情况分析。
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引用次数: 2
Multi-Target Motion Detection Radar Sensor using 24GHz Metamaterial Leaky Wave Antennas 采用24GHz超材料漏波天线的多目标运动检测雷达传感器
Chun-Lin Lu, Yichao Yuan, C. Tseng, C. Wu
This paper presents a motion detection radar sensor using metamaterial (MTM) leaky wave antennas (LWAs) operating in the 24 GHz band. Utilizing continuous-wave Doppler radar integrated with MTM LWAs to perform frequency-space mapping over the azimuth angle, we can detect multiple human motion in the indoor environments. In addition, the moving distances of different people can be obtained by analyzing the baseband signals at different carrier frequencies.
本文提出了一种基于超材料漏波天线(LWAs)的运动探测雷达传感器,工作在24ghz频段。利用与MTM LWAs集成的连续波多普勒雷达在方位角上执行频率空间映射,我们可以检测室内环境中的多个人体运动。另外,通过分析不同载波频率下的基带信号,可以得到不同人的移动距离。
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引用次数: 4
Identification of Ghost Moving Detections in Automotive Scenarios with Deep Learning 基于深度学习的汽车场景幽灵运动检测识别
Javier Martínez García, Robert Prophet, Juan Carlos Fuentes Michel, R. Ebelt, M. Vossiek, Ingo Weber
We introduce a method to classify ghost moving detections in automotive radar sensors for advanced driver assistance systems. A fully connected network is used to distinguish between real and false moving detections in the occupancy gridmaps. By using this architecture, we combine the local Doppler information, along with the spatial context of the surrounding scenario to classify the moving detections. A proof of concept experiment shows promising results with data from a test drive in an urban scenario.
介绍了一种用于高级驾驶辅助系统的汽车雷达传感器中鬼魂运动检测的分类方法。利用全连通网络来区分占用网格图中运动检测的真假。通过使用该架构,我们结合局部多普勒信息以及周围场景的空间背景来对运动检测进行分类。一项概念验证实验显示,在城市场景中进行的试驾数据显示出了令人鼓舞的结果。
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引用次数: 15
Casting Powder Thickness Field-Measurement with Ultra Wideband Radar System 用超宽带雷达系统测量铸造粉末厚度
Alexander Kaineder, O. Lang, R. Feger, Paul Dollhäubl, A. Stelzer, Stefan Leitner
This paper describes a prototype sensor for the measurement of the casting powder thickness in a continuous cast system. The sensor is realized with an conventional vector network analyzer connected to a broadband horn antenna via a coaxial cable. The radiated power is diverted to the mold by a parabolic reflector. The system operates as a frequency-stepped continuous-wave radar, delivering the complex reflection coefficient at the calibration plane. The frequency is swept from 10 GHz to 40 GHz within 500 ms. The data transfer, evaluation and visualization is done in real-time.
本文介绍了一种用于连铸系统中铸造粉末厚度测量的传感器样机。该传感器是通过同轴电缆与宽带喇叭天线连接的传统矢量网络分析仪实现的。辐射功率通过抛物面反射器转移到模具上。该系统作为频率阶跃连续波雷达工作,在校准平面上提供复反射系数。频率在500毫秒内从10ghz扫至40ghz。数据传输、评估和可视化是实时完成的。
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引用次数: 0
ICMIM 2019 Organizing Committee ICMIM 2019组委会
{"title":"ICMIM 2019 Organizing Committee","authors":"","doi":"10.1109/icmim.2019.8726850","DOIUrl":"https://doi.org/10.1109/icmim.2019.8726850","url":null,"abstract":"","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115199126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
ICMIM 2019 Sponsoring Societies ICMIM 2019赞助协会
{"title":"ICMIM 2019 Sponsoring Societies","authors":"","doi":"10.1109/icmim.2019.8726729","DOIUrl":"https://doi.org/10.1109/icmim.2019.8726729","url":null,"abstract":"","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127302582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
ICMIM 2019 Technical Program Committee ICMIM 2019技术计划委员会
{"title":"ICMIM 2019 Technical Program Committee","authors":"","doi":"10.1109/icmim.2019.8726638","DOIUrl":"https://doi.org/10.1109/icmim.2019.8726638","url":null,"abstract":"","PeriodicalId":225972,"journal":{"name":"2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126750841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Automated Ground Truth Estimation of Vulnerable Road Users in Automotive Radar Data Using GNSS 基于GNSS的汽车雷达数据中脆弱道路使用者地面真值自动估计
Nicolas Scheiner, N. Appenrodt, J. Dickmann, B. Sick
Annotating automotive radar data is a difficult task. This article presents an automated way of acquiring data labels which uses a highly accurate and portable global navigation satellite system (GNSS). The proposed system is discussed besides a revision of other label acquisitions techniques and a problem description of manual data annotation. The article concludes with a systematic comparison of conventional hand labeling and automatic data acquisition. The results show clear advantages of the proposed method without a relevant loss in labeling accuracy. Minor changes can be observed in the measured radar data, but the so introduced bias of the GNSS reference is clearly outweighed by the indisputable time savings. Beside data annotation, the proposed system can also provide a ground truth for validating object tracking or other automated driving system applications.
对汽车雷达数据进行标注是一项艰巨的任务。本文介绍了一种利用高精度便携式全球导航卫星系统(GNSS)自动获取数据标签的方法。除了对其他标签获取技术的修订和手动数据注释的问题描述外,还讨论了所提出的系统。文章最后对传统手工标注和自动数据采集进行了系统的比较。结果表明,所提出的方法具有明显的优势,并且在标注精度上没有相应的损失。在测量到的雷达数据中可以观察到微小的变化,但GNSS参考的如此引入的偏差显然被无可争议的节省时间所抵消。除了数据注释,所提出的系统还可以为验证对象跟踪或其他自动驾驶系统应用提供基础事实。
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引用次数: 6
Fast DOA Estimation Method based on MUSIC algorithm combined Newton Method for FMCW Radar 基于MUSIC算法结合牛顿法的FMCW雷达快速DOA估计方法
So-Hee Jeong, You-Sun Won, Dongseung Shin
This paper proposes a fast DOA estimation method for FMCW radar systems. In order to achieve the fast processing speed, the proposed method utilizes the MUSIC algorithm combined the Newton method. It also utilizes the phase-comparison monopulse method to obtain the initial angle which is used in Newton method. In addition, a cost function is defined to find the maximum value of the MUSIC spectrum. By the analysis of the measured data using our developed 77GHz FMCW radar, measurements show that the processing speed of the proposed method is improved by 54 percent than that of the conventional MUSIC algorithm.
提出了一种FMCW雷达系统的快速DOA估计方法。为了实现快速的处理速度,该方法将MUSIC算法与牛顿法相结合。采用牛顿法中常用的单脉冲比相法来获得初始角。另外,定义了一个代价函数来求MUSIC谱的最大值。通过对研制的77GHz FMCW雷达实测数据的分析,测量结果表明,该方法的处理速度比传统MUSIC算法提高了54%。
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引用次数: 10
期刊
2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)
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