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2020 IEEE International Radar Conference (RADAR)最新文献

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Optimizing Transmitter Amplifier Load Impedance for Tuning Performance in a Metacognition-Guided, Spectrum Sharing Radar 元认知制导频谱共享雷达中发射机放大器负载阻抗优化调谐性能
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114669
Adam Goad, Austin Egbert, Angelique Dockendorf, C. Baylis, A. Martone, R. Marks
{"title":"Optimizing Transmitter Amplifier Load Impedance for Tuning Performance in a Metacognition-Guided, Spectrum Sharing Radar","authors":"Adam Goad, Austin Egbert, Angelique Dockendorf, C. Baylis, A. Martone, R. Marks","doi":"10.1109/RADAR42522.2020.9114669","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114669","url":null,"abstract":"Transmitter power amplifier load impedance impacts the transmitted power of the radar, which affects the maximum detection range. In spectrum sharing radars, the operating frequency is expected to change on the order of a few milliseconds coherent processing interval (CPI), which can be in the low milliseconds. While a high-power impedance tuner has been developed for radar applications, its reconfiguration time requires at least several hundreds of milliseconds, thus significantly exceeding the CPI time scale and preventing configuration adjustments within the CPI. We demonstrate an algorithm that assesses and improves the amplifier impedance tuning during a spectrum sharing metacognition process in a cognitive radar. Measurement results show success in achieving maximum average power over test intervals using the control of an adaptive software-defined radio platform.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129881929","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: 5
Robust Drone Classification Using Two-Stage Decision Trees and Results from SESAR SAFIR Trials 基于两阶段决策树和SESAR SAFIR试验结果的鲁棒无人机分类
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114870
M. Jahangir, B. I. Ahmad, C. Baker
{"title":"Robust Drone Classification Using Two-Stage Decision Trees and Results from SESAR SAFIR Trials","authors":"M. Jahangir, B. I. Ahmad, C. Baker","doi":"10.1109/RADAR42522.2020.9114870","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114870","url":null,"abstract":"Non-cooperative surveillance of drones is an important consideration in the EU SESAR vision for the provision of U-space services. The Aveillant Gamekeeper multiple beam staring radar utilises extended dwells to be able to detect small drones at ranges of several kilometres. However, target discrimination is necessary with such non-cooperative surveillance system as the increased detection sensitivity against low RCS targets, such as birds and surface objects (e.g., pedestrians and vehicles), extenuates the problem of false target reports. A simple two-stage supervised learning approach is proposed in order to discriminate drones from other confuser targets. This approach is based on a decision tree classifier and is shown to be effective at filtering out non-drone, targets. Field trials from the SESAR SAFIR trials to test initial U-space services in realistic urban environments shows that the two-stage decision tree classifier provides robust discrimination with minimal false positives.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129625993","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: 18
Measurement of Opaque Container Contents by an M-Sequence UWB Radar 用m序列超宽带雷达测量不透明容器内容物
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114749
M. Pecovský, P. Galajda, M. Sokol, M. Kmec
{"title":"Measurement of Opaque Container Contents by an M-Sequence UWB Radar","authors":"M. Pecovský, P. Galajda, M. Sokol, M. Kmec","doi":"10.1109/RADAR42522.2020.9114749","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114749","url":null,"abstract":"This paper deals with the method for liquid or powder level measurement inside closed non-metallic opaque containers. The proposed method uses the progressive M-sequence short-range radar technology which achieves high measurement precision and according to previous publications, allows not only the localization of the desired material interface, but is capable to estimate material properties as well. In the first part of the article, the M-sequence radar system is described. Later, the measurement technique is proposed using a low-cost microstrip transmission line as a probe. In the final parts, simulations and measurement results are presented to confirm the viability of the proposed method. The measurements show that the proposed method is able to distinguish the liquid level changes of less than 1 mm in a simple measurement setup.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128018804","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: 5
Attention-Augmented Convolutional Autoencoder for Radar-Based Human Activity Recognition 基于雷达的人体活动识别的注意增强卷积自编码器
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114787
Christopher Campbell, F. Ahmad
{"title":"Attention-Augmented Convolutional Autoencoder for Radar-Based Human Activity Recognition","authors":"Christopher Campbell, F. Ahmad","doi":"10.1109/RADAR42522.2020.9114787","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114787","url":null,"abstract":"We propose an attention-augmented convolutional autoencoder for human activity recognition using radar micro-Doppler signatures. We use attention to overcome the limited receptive field of convolutional autoencoders (CAE), thereby enabling them to learn global information in addition to spatially localized features, while preserving their unsupervised pretraining characteristic. The augmentation is accomplished by concatenating convolutional local-feature maps with a set of attention feature maps that capture global dependencies. Using real data measurements of falls and activities of daily living, we demonstrate that the incorporation of the attention mechanism yields superior classification accuracy with respect to training sample size, compared to the conventional CAE.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121647012","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: 13
Performance Analysis of Pulse-Agile SDRadar with Hardware Accelerated Processing 基于硬件加速处理的脉冲敏捷雷达性能分析
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114561
B. Kirk, A. Martone, K. Sherbondy, R. Narayanan
{"title":"Performance Analysis of Pulse-Agile SDRadar with Hardware Accelerated Processing","authors":"B. Kirk, A. Martone, K. Sherbondy, R. Narayanan","doi":"10.1109/RADAR42522.2020.9114561","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114561","url":null,"abstract":"With the increasing demand for access to the radio frequency spectrum, there has been an emergence of spectrum sharing radar systems. Along with this comes the need for rapid pulse-agility to avoid other time varying signals in the spectrum effectively. A software-defined radar (SDRadar) system that has been previously explored is further developed in this work to improve its spectrum sharing performance. To take advantage of the rapid reaction time of the improved system, pulse adaption occurs within a radar coherent processing interval, which causes significant distortion in the Doppler dimension. A simulation was formulated to show how the distortion becomes more significant as the magnitude of the adaptation increases. The distortion is also shown to significantly impact the number of false alarms detected, reducing the ability to verify true targets.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125920647","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: 13
Assessing Block-Sparsity-Based Spectrum Sensing Approaches for Cognitive Radar on Measured Data 基于块稀疏度的认知雷达频谱感知方法在测量数据上的评估
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114600
A. Aubry, V. Carotenuto, A. De Maio, M. Govoni, A. Farina
{"title":"Assessing Block-Sparsity-Based Spectrum Sensing Approaches for Cognitive Radar on Measured Data","authors":"A. Aubry, V. Carotenuto, A. De Maio, M. Govoni, A. Farina","doi":"10.1109/RADAR42522.2020.9114600","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114600","url":null,"abstract":"Due to increasing demands for spectral resources in both communication and radar systems, the Radio Frequency (RF) electromagnetic spectrum is becoming more and more crowded with interfering nuisances. In order to tackle the scarcity of available spectral intervals, in recent years a multitude of spectrum sensing algorithms have been developed for improving spectrum sharing. Among these, two-dimensional (2-D) spectrum sensing can be used to obtain real time space-frequency electromagnetic spectrum awareness. Specifically, this approach makes it possible to optimize the spectrum usage of certain spectrum portions whose occupancy varies both temporally and spatially. In this paper, we evaluate the effectiveness of certain space-frequency map recovery algorithms relying on the use of commercially-available hardware. To this end, we employ an inexpensive four channel coherent receiver using Software Defined Radio (SDR) components for emitter localization. Hence, after proper calibration of the receiving system, the acquired samples are used to evaluate the effectiveness of different signal processing strategies which exploit the inherent block-sparsity of the overall profile. At the analysis stage, results reveal the effectiveness of such algorithms.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126477018","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: 2
Computationally Efficient Narrowband RFI Mitigation for Pulse Compression Radar 基于计算效率的脉冲压缩雷达窄带射频干扰抑制
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114639
Neal W. Smith, M. Frankford, R. M. Thompson
{"title":"Computationally Efficient Narrowband RFI Mitigation for Pulse Compression Radar","authors":"Neal W. Smith, M. Frankford, R. M. Thompson","doi":"10.1109/RADAR42522.2020.9114639","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114639","url":null,"abstract":"Mitigating in-band, continuous-wave (CW) radio frequency interference (RFI) is a common problem for radar systems which themselves may employ continuous-wave waveforms. The source of this RFI can be intentional or unintentional spectral artifacts of near-by narrowband communications systems. Radar signal modulations of just a few megahertz are frequently quite broad compared to the modulation bandwidths of the interferers. So, characterization of RFI by a simple tone can be sufficient to assess its impact. When the RFI sources are unanticipated or of uncertain characteristics, there is motivation to mitigate them in a responsive manner in receive processing. A computationally efficient RFI cancellation method for receive is described here. Salient properties of this method are the recovery of radar sensitivity in the presence of narrowband RFI and the preservation of pulse compression time sidelobe levels. In fact, the technique described here overcomes the disadvantages of isolating and removing an RFI source that is completely immersed in the radar waveform in both time and frequency. While removing each of possibly multiple RFI sources with surgical IIR filters, little secondary influences on pulse compression responses arise because the IIR filter is suitably designed with finite word influences and impulse-response time sidelobes in mind.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133732532","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
Accurate Time Synchronization for Automotive Cooperative Radar (CoRD) Applications 用于汽车协同雷达(CoRD)应用的精确时间同步
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114861
O. Bar-Shalom, Nir Dvorecki, L. Banin, Y. Amizur
{"title":"Accurate Time Synchronization for Automotive Cooperative Radar (CoRD) Applications","authors":"O. Bar-Shalom, Nir Dvorecki, L. Banin, Y. Amizur","doi":"10.1109/RADAR42522.2020.9114861","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114861","url":null,"abstract":"The increasing amount of automotive radars makes mutual radar interference a prominent problem. Cooperation between the radars could not only minimize their mutual level of interference but would also enable remote radar nodes to operate synchronously for jointly improving their performance. The concept of Collaborative Time of Arrival (CToA) has recently been proposed for enabling distributed wireless network synchronization. In this paper, we explore the application of CToA to automotive radar systems for achieving sub-nanosecond level synchronization between radar nodes. The proposed scheme, dubbed “cooperative radar” (CoRD), opens a wide range of applications including bistatic automotive radars.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127174295","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: 1
Covariance-Free TDOA/FDOA-Based Moving Target Localization for Multi-Static Radar 基于无协方差TDOA/ fdoa的多静态雷达运动目标定位
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114799
Xudong Zhang, Fangzhou Wang, Hongbin Li, B. Himed
{"title":"Covariance-Free TDOA/FDOA-Based Moving Target Localization for Multi-Static Radar","authors":"Xudong Zhang, Fangzhou Wang, Hongbin Li, B. Himed","doi":"10.1109/RADAR42522.2020.9114799","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114799","url":null,"abstract":"In this paper, we consider the problem of estimating the location and velocity of a non-cooperative moving target using a multi-static radar, which consists of a set of spatially distributed sensors in listening mode. The moving target may be transmitting, or reflecting, a source signal that is assumed to be unknown and modeled as a deterministic process. We develop a computationally efficient two-step approach to solve the localization problem. The first step finds the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) estimates for each sensor with respect to a reference sensor by using a 2-dimensional Fast Fourier transform, and the second step employs an iterative reweighted least square (IRLS) approach with a varying weighting matrix to determine the target location and velocity. While most existing TDOA/FDOA-based methods require knowledge of the covariance matrix of the TDOA and FDOA estimates, which is usually unknown in practice, our proposed IRLS approach is covariance matrix-free. Numerical results show that the IRLS approach has a lower signal-to-noise ratio (SNR) threshold compared with a recent TDOA/FDOA-based method, especially when the target is considerably farther away from some sensors than others.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128161054","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: 3
An Optimal Multistatic Synthetic Aperture Radar Reconstruction Filter 一种最优多静态合成孔径雷达重构滤波器
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114768
John Summerfield
{"title":"An Optimal Multistatic Synthetic Aperture Radar Reconstruction Filter","authors":"John Summerfield","doi":"10.1109/RADAR42522.2020.9114768","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114768","url":null,"abstract":"Approximations are used to overcome spatial and time variations in the multistatic synthetic aperture radar (MSAR) image formation process in order to define an optimal reconstruction filter that maximizes signal to noise ratio (SNR), clutter to noise ratio (CNR), and target to clutter ratio (TCR). The objective is to geolocate a known target with unknown position. The target is surrounded by homogeneous clutter while return signals are corrupted by thermal noise in each receiver.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"7 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113968706","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: 1
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