2019 IEEE Radar Conference (RadarConf)最新文献

Micro-Doppler Gesture Recognition using Doppler, Time and Range Based Features 基于多普勒、时间和距离特征的微多普勒手势识别

2019 IEEE Radar Conference (RadarConf) Pub Date : 2019-09-16 DOI: 10.1109/RADAR.2019.8835782

M. Ritchie, Aaron M. Jones

引用次数: 18

GNSS Based Passive Radar for UAV Monitoring 基于GNSS的无源雷达用于无人机监控

2019 IEEE Radar Conference (RadarConf) Pub Date : 2019-09-16 DOI: 10.1109/RADAR.2019.8835606

C. Ilioudis, Jianlin Cao, Ilias Theodorou, Pasquale Striano, William Coventry, C. Clemente, J. Soraghan

引用次数: 12

Assessment of Synthetic Aperture Radar Image Preprocessing Methods for Iceberg and Ship Recognition with Convolutional Neural Networks 基于卷积神经网络的冰山和船舶识别合成孔径雷达图像预处理方法评价

2019 IEEE Radar Conference (RadarConf) Pub Date : 2019-04-22 DOI: 10.1109/RADAR.2019.8835807

XingWen Li, Weimin Huang, D. Peters, D. Power

引用次数: 5

Robust Target Tracking with Discontinuous Signal for Passive Sensor Systems 无源传感器系统不连续信号鲁棒目标跟踪

2019 IEEE Radar Conference (RadarConf) Pub Date : 2019-04-22 DOI: 10.1109/RADAR.2019.8835659

Lingzhi Fu, Wei Yi, Suqi Li, L. Kong

引用次数: 1

Imaging radar for navigation and surveillance on an autonomous unmanned ground vehicle capable of detecting obstacles obscured by vegetation 用于导航和监视的自主无人地面车辆成像雷达，能够探测被植被遮挡的障碍物

2019 IEEE Radar Conference (RadarConf) Pub Date : 2019-04-22 DOI: 10.1109/RADAR.2019.8835514

Daniel Gusland, Borge Torvik, E. Finden, Fredrik Gulbrandsen, Ragnar Smestad

{"title":"Imaging radar for navigation and surveillance on an autonomous unmanned ground vehicle capable of detecting obstacles obscured by vegetation","authors":"Daniel Gusland, Borge Torvik, E. Finden, Fredrik Gulbrandsen, Ragnar Smestad","doi":"10.1109/RADAR.2019.8835514","DOIUrl":"https://doi.org/10.1109/RADAR.2019.8835514","url":null,"abstract":"The Norwegian Defence Research Establishment (FFI), has developed a multi purpose radar demonstrator for Intelligence, Surveillance and Reconnaissance (ISR) on the Off-road Light Autonomous Vehicle (OLAV) platform. The radar is designed to aid OLAV in navigation, detection and classification. Operating in off-road environments is a considerable challenge for autonomous vehicles, especially in the presence of vegetation. While existing perception sensors such as cameras and LIght Detection And Ranging (LiDAR) work well in clear weather and areas without vegetation, they are impaired by rain, fog, smoke and vegetation. This paper presents the development of the Multiple Usage Radar - S-band (MURA-S), developed to aid the autonomous platforms in challenging conditions. Initial considerations and frequency selection for the radar is presented in addition to a detailed explanation of the antenna configuration and the utilization of time-domain multiplexed Multiple-Input Multiple-Output (MIMO) techniques to increase the cross-range resolution of the radar. Preliminary experimental results for detecting obstacles obscured by vegetation are presented and compared with obstacle maps created by the LiDAR, showing that the radar enhances the capabilities of the perception system.","PeriodicalId":360366,"journal":{"name":"2019 IEEE Radar Conference (RadarConf)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132659404","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: 9

A Quantum-Enhanced Radar Prototype 量子增强雷达原型

2019 IEEE Radar Conference (RadarConf) Pub Date : 2019-04-22 DOI: 10.1109/RADAR.2019.8835632

David Luong, A. Damini, B. Balaji, Sandbo Chang, A. Vadiraj, C. Wilson

{"title":"A Quantum-Enhanced Radar Prototype","authors":"David Luong, A. Damini, B. Balaji, Sandbo Chang, A. Vadiraj, C. Wilson","doi":"10.1109/RADAR.2019.8835632","DOIUrl":"https://doi.org/10.1109/RADAR.2019.8835632","url":null,"abstract":"We have built and evaluated a prototype quantum radar in the laboratory which operates at microwave frequencies. Because the signal generation process relies on quantum mechanical principles, the system is considered to contain a quantum-enhanced radar transmitter. This transmitter generates a pair of entangled microwave signals and transmits one of them through free space, where the one-way signal is measured using a simple and rudimentary receiver. The type of entanglement used is called two-mode squeezed vacuum (TMSV), so we may call our radar a quantum two-mode squeezing radar (QTMS radar). At the heart of the transmitter is a device called a Josephson parametric amplifier (JPA), which generates the entangled microwave beams; these are then sent through a chain of amplifiers. One beam passes through 0.5 m of free space; the other is measured directly. The two measurement results are correlated in order to distinguish noise from signal. We compare this quantum-enhanced transmitter to a similar one using only conventional components, and find that there is a significant gain when the two systems broadcast signals at approximately the same power.","PeriodicalId":360366,"journal":{"name":"2019 IEEE Radar Conference (RadarConf)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132295912","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: 17

Mission Planning Tool for Space Debris Detection and Tracking with the MeerKAT Radar MeerKAT雷达空间碎片探测与跟踪任务规划工具

2019 IEEE Radar Conference (RadarConf) Pub Date : 2019-04-22 DOI: 10.1109/RADAR.2019.8835735

Ashiv Dhondea, M. Inggs

引用次数: 2

Through-Wall Human Motion Representation via Autoencoder-Self Organized Mapping Network 基于自编码器-自组织映射网络的穿墙人体运动表征

2019 IEEE Radar Conference (RadarConf) Pub Date : 2019-04-22 DOI: 10.1109/RADAR.2019.8835845

Mingyang Wang, G. Cui, Huabin Huang, Xuyu Gao, Pengyun Chen, Huquan Li, Haining Yang, L. Kong

{"title":"Through-Wall Human Motion Representation via Autoencoder-Self Organized Mapping Network","authors":"Mingyang Wang, G. Cui, Huabin Huang, Xuyu Gao, Pengyun Chen, Huquan Li, Haining Yang, L. Kong","doi":"10.1109/RADAR.2019.8835845","DOIUrl":"https://doi.org/10.1109/RADAR.2019.8835845","url":null,"abstract":"This paper addresses a problem of human motion representation for through wall radar exploiting an autoencoder-self organized mapping network. Motivated by the natural language processing, we interpret the echoes of the through-wall human motions into a simple integer sequence with motion “semantics” by regarding each range profile as a “word” and treating the multi-temporal-frame hidden human motion range profile data as a “sentence”, simplifying and maintaining the effectiveness of the through-wall human motion representations. Specifically, we firstly use an auto encoder network (AEN) with three dense layers to reduce the dimension and extract the features of each range profile. Then, a self organized mapping (SOM) network is employed to concatenate the trained AEN to establish the word-to-index mapping, transferring the temporal sequential range-profile data of through-wall human motions into an integer sequence which implies the “semantic” information of the motion. Finally, experimental data including four through-wall human motion types validate the proposed framework.","PeriodicalId":360366,"journal":{"name":"2019 IEEE Radar Conference (RadarConf)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130796892","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: 4

SISAR Imaging - Radio Holography Signal Reconstruction Based on Receiver-Transmitter Motion 基于接收-发射运动的无线电全息成像信号重建

2019 IEEE Radar Conference (RadarConf) Pub Date : 2019-04-22 DOI: 10.1109/RADAR.2019.8835596

Ilias Theodorou, C. Ilioudis, C. Clemente, M. Vasile

引用次数: 5

Millimeter wave V2I beam-training using base-station mounted radar 毫米波V2I波束训练使用基站安装雷达

2019 IEEE Radar Conference (RadarConf) Pub Date : 2019-04-22 DOI: 10.1109/radar.2019.8835615

Anum Ali, N. González-Prelcic, Amitava Ghosh

引用次数: 19