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Open-Set Radar Waveform Classification: Comparison of Different Features and Classifiers 开放集雷达波形分类:不同特征和分类器的比较
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114773
Rohit V. Chakravarthy, Haoran Liu, Anne Pavy
{"title":"Open-Set Radar Waveform Classification: Comparison of Different Features and Classifiers","authors":"Rohit V. Chakravarthy, Haoran Liu, Anne Pavy","doi":"10.1109/RADAR42522.2020.9114773","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114773","url":null,"abstract":"Performing open set classification of radar waveforms is a difficult problem due to issues including varying signal to noise ratio (SNR), complexity of the data, lack of separability between classes of interest, as well as the crowded nature of the spectrum. In addition, the evolving spectrum may lead to a situation where not every waveform is present in the training library. This paper addresses these challenges by the combination of obtaining machine learning features directly from the waveform, subsequently followed by a classification algorithm. The machine learning technique used in this paper is a discriminative network, specifically a convolutional neural network (CNN), for feature extraction. The classifier employed is SV-Means, a quantile one-class support vector machine-based algorithm (q-OCSVM), with the ability to reject unknown waveform classes while also providing an estimation of the likelihood of the class of interest being a member of the waveform library. A combination of these two methods results in a system of high credibility taking into account the challenges noted.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"23 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":"121479224","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: 6
Structure-Based Adaptive Radar Processing for Joint Clutter Cancellation and Moving Target Estimation 基于结构的自适应雷达杂波消除与运动目标估计
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114609
Christian C. Jones, Lumumba A. Harnett, Charles A. Mohr, S. Blunt, Chris Allen
{"title":"Structure-Based Adaptive Radar Processing for Joint Clutter Cancellation and Moving Target Estimation","authors":"Christian C. Jones, Lumumba A. Harnett, Charles A. Mohr, S. Blunt, Chris Allen","doi":"10.1109/RADAR42522.2020.9114609","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114609","url":null,"abstract":"During his many years with the Radar Division of the US Naval Research Laboratory (NRL), Dr. Karl Gerlach made significant contributions to adaptive interference cancellation for radar. For this memorial tribute special session, this paper leverages the reiterative minimum mean square error (RMMSE) estimator, which he also helped to develop, to formulate two techniques whereby interference cancellation is performed jointly with signal estimation as a way to enhance the subsequent range-Doppler response. Experimental results are demonstrated using free-space measurements from pulsed, nonrepeating waveforms at S-band and standard FMCW at W-band.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"44 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":"130196922","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: 6
Experimental Assessment of Joint Range-Doppler Processing to Address Clutter Modulation from Dynamic Radar Spectrum Sharing 联合距离-多普勒处理解决动态雷达频谱共享中杂波调制的实验评估
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114683
Brandon Ravenscroft, Jonathan Owen, B. Kirk, S. Blunt, A. Martone, K. Sherbondy, R. Narayanan
{"title":"Experimental Assessment of Joint Range-Doppler Processing to Address Clutter Modulation from Dynamic Radar Spectrum Sharing","authors":"Brandon Ravenscroft, Jonathan Owen, B. Kirk, S. Blunt, A. Martone, K. Sherbondy, R. Narayanan","doi":"10.1109/RADAR42522.2020.9114683","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114683","url":null,"abstract":"Cognitive sense-and-avoid (SAA) and sense-and-notch (SAN) emission strategies have recently been experimentally demonstrated as effective ways in which to reduce the interference a spectrum-sharing radar causes to other in-band users. In both cases, however, it has been observed that when the spectral content occupied by the radar changes during the coherent processing interval (CPI) in response to dynamic radio frequency interference (RFI), a nonstationarity in the form of clutter modulation is induced that degrades clutter cancellation. Here the efficacy of joint range/Doppler processing is experimentally assessed for this problem through use of the non-identical multiple pulse compression (NIMPC) method. The additional degrees of freedom provided by this type of approach are shown to compensate for this clutter modulation effect to a significant degree, thus implying a benefit to joint range/Doppler processing in general.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"2 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":"132943788","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: 12
Advanced Techniques for Robust SAR ATR: Mitigating Noise and Phase Errors 鲁棒SAR ATR的先进技术:降低噪声和相位误差
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114784
Nathan Inkawhich, Eric K. Davis, U. Majumder, C. Capraro, Yiran Chen
{"title":"Advanced Techniques for Robust SAR ATR: Mitigating Noise and Phase Errors","authors":"Nathan Inkawhich, Eric K. Davis, U. Majumder, C. Capraro, Yiran Chen","doi":"10.1109/RADAR42522.2020.9114784","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114784","url":null,"abstract":"We present advanced Deep Learning (DL) techniques for robust Synthetic Aperture Radar (SAR) automatic target recognition (ATR) in the presence of noise and signal phase errors. Our research focuses on ensuring robust performance of SAR ATR algorithms under noise and adversarial attacks. Robust DL-based SAR ATR is paramount in operational scenarios such as disaster relief, search and rescue, and highly accurate object classification for autonomous vehicles. Our contributions, as described in this paper, include algorithm development and implementation of an advanced deep learning technique known as adversarial training (AT) to mitigate the detrimental effects of sophisticated noise and phase errors. Our research demonstrated that 1) AT improves performance under extended operating conditions, in some cases improving up to 10% over models without AT. 2) The use of AT improves performance when sinusoidal or wideband phase noise is present, in some cases gaining 40% in accuracy that would be lost in the presence of noise. 3) We find the model architecture has significant impact on robustness, with more complex networks showing a greater improvement from AT. 4) The availability of multi-polarization data is always advantageous. To our knowledge no one has provided an extensive analysis of the impact of adversarial machine learning (ML) on SAR image classification. Thus, this paper serves as a comprehensive research revealing the impact of adversarial attack and how to mitigate it.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"61 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":"131250313","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: 12
Improved Covariance Matrix Estimation using Riemannian Geometry for Beamforming Applications 波束形成应用中改进的黎曼几何协方差矩阵估计
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114700
Hossein Chahrour, R. Dansereau, S. Rajan, B. Balaji
{"title":"Improved Covariance Matrix Estimation using Riemannian Geometry for Beamforming Applications","authors":"Hossein Chahrour, R. Dansereau, S. Rajan, B. Balaji","doi":"10.1109/RADAR42522.2020.9114700","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114700","url":null,"abstract":"The estimation of interference plus noise covariance (INC) matrix for beamforming applications is considered from a Riemannian space perspective. A new INC estimation technique based on regularized Burg algorithm (RBA), Riemannian mean and Riemannian distance is proposed to maintain a stable performance in presence of angle of arrival mismatch and small sample size with high and low signal to interference plus noise ratio (SINR). The RBA is exploited to generate Toeplitz Hermitian positive definite (THPD) covariance matrices from the estimates of the reflection coefficients for each radar snapshot. The estimated INC is formulated as a linear combination of THPD covariance matrices of the interference plus noise excluding potential target snapshots. The weights of the linear combination operation are based on the Riemannian distance between the Riemannian mean and each THPD covariance matrix. The largest distance (potential target) will have zero weight and the smallest distance will have maximum weight. Simulation results demonstrate the performance of the proposed technique in comparison with sample covariance and Riemannian mean covariance under steering vector mismatch and small sample size in presence of high and low SINR.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"9 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":"132710997","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
Welcome 欢迎
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/radar42522.2020.9114701
Jayeann Harr
{"title":"Welcome","authors":"Jayeann Harr","doi":"10.1109/radar42522.2020.9114701","DOIUrl":"https://doi.org/10.1109/radar42522.2020.9114701","url":null,"abstract":"","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"71 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":"127388578","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
Circularly Polarized Fabry Perot Cavity Antennas with Peripheral Roughness in Superstrate Unit Cells 层上单元格中具有外围粗糙度的圆极化法布里珀罗腔天线
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114543
Sagar Jain, S. S. Ram
{"title":"Circularly Polarized Fabry Perot Cavity Antennas with Peripheral Roughness in Superstrate Unit Cells","authors":"Sagar Jain, S. S. Ram","doi":"10.1109/RADAR42522.2020.9114543","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114543","url":null,"abstract":"Fabry Perot cavity (FPC) antennas have been extensively researched and developed for their reduced fabrication complexity and cost as compared to other high gain planar antennas. Recently, the partially reflecting surfaces (PRS) of the FPC antennas have been engineered with metasurfaces with desirable electromagnetic properties in order to reduce their profile dimensions. These surfaces usually consist of an array of unit cells that are skillfully designed in order to obtain high bandwidth or desired polarization. In this paper, we have considered a unit cell design of a rectangular loop with a diagonal - with an objective of achieving circular polarization. Then we introduced a new design parameter in the form of peripheral roughness in the edge of each of the unit cells. We demonstrate that the incorporation of the new design feature in the unit cell results in an enhancement of the return loss bandwidth to 202.8 MHz (8.9%) and gain to 9.5 dBi along with a reduced axial ratio of 4.8dB.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"24 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":"115335628","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
Characterizing the Impact of IQ Imbalance and DC Bias on Pulse-Agile Radar Processing IQ不平衡和DC偏置对脉冲捷变雷达处理的影响
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114629
J. Metcalf, Shane Flandermeyer, Charles A. Mohr, Andrew M. Kordik, Patrick M. McCormick, Cenk Sahin
{"title":"Characterizing the Impact of IQ Imbalance and DC Bias on Pulse-Agile Radar Processing","authors":"J. Metcalf, Shane Flandermeyer, Charles A. Mohr, Andrew M. Kordik, Patrick M. McCormick, Cenk Sahin","doi":"10.1109/RADAR42522.2020.9114629","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114629","url":null,"abstract":"The advent of commercial-off-the-shelf (COTS) software-defined radars (SDRs) has enabled low-cost, flexible experimentation with emerging pulse-agile waveform designs to mitigate spectral congestion, improve radar performance, embed communications, and other applications. We examine the impact of direct digital downconversion sampling imperfections in the form of IQ imbalance and DC bias on pulse-agile waveforms. A general framework is developed and examples given for a particular radar-embedded communication waveform. It is shown that the clutter response due to IQ imbalance is significantly increased in a pulse agile framework.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"19 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":"115439878","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
Interference Suppression and Signal Restoration Using Kalman Filter in Automotive Radar Systems 基于卡尔曼滤波的汽车雷达干扰抑制与信号恢复
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114723
Jaehoon Jung, Sohee Lim, Jinwook Kim, Seong-Cheol Kim, Seongwook Lee
{"title":"Interference Suppression and Signal Restoration Using Kalman Filter in Automotive Radar Systems","authors":"Jaehoon Jung, Sohee Lim, Jinwook Kim, Seong-Cheol Kim, Seongwook Lee","doi":"10.1109/RADAR42522.2020.9114723","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114723","url":null,"abstract":"When a radar equipped on an approaching vehicle transmits a signal whose frequency band overlaps with our own radar system, mutual interference problems arise. When mutual interference occurs, the target detection performance is degraded because the target signals are masked by the high power of direct interference signals. Therefore, we propose a signal processing technique to restore signals distorted by mutual interference in an automotive radar system to increase the reliability of target detection. First, since it is necessary to recognize the period where the interference occurred, a method to find the period of interference based on peak detection is presented. Then, the Kalman filter is employed to recover the distorted signal in the interference region by using the undistorted portion of the signal as its input. In simulations using two frequency modulated continuous wave radar systems, the influence of interference was effectively mitigated with our proposed method and target information was correctly estimated.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"103 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":"124063156","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: 8
Multichannel Coprime SAR/GMTI (CopGMTI) 多通道Coprime SAR/GMTI (CopGMTI)
2020 IEEE International Radar Conference (RADAR) Pub Date : 2020-04-01 DOI: 10.1109/RADAR42522.2020.9114845
Abdulmalik Aldharrab, Mike E. Davies
{"title":"Multichannel Coprime SAR/GMTI (CopGMTI)","authors":"Abdulmalik Aldharrab, Mike E. Davies","doi":"10.1109/RADAR42522.2020.9114845","DOIUrl":"https://doi.org/10.1109/RADAR42522.2020.9114845","url":null,"abstract":"CopSAR and OrthoCopSAR have been recently proposed in the literature to reduce the amount of data to be stored and processed and to extend the maximum swath width that can be imaged without introducing any degradation to the azimuth resolution. Such a High-Resolution Wide-Swath (HRWS) imaging capability is achieved by sampling the synthetic aperture using multiple interlaced sub-Nyquist PRFs. However, a limitation in such imaging modalities is in the assumption that the scene contains only stationary targets. Consequently, moving targets will appear shifted from their true location mostly in the azimuth direction. In this paper, CopGMTI is proposed to detect ground moving targets and estimate their radial velocities when the synthetic aperture is sampled at a sub-Nyquist rate according to CopSAR or OrthoCopSAR. This allows identifying the true azimuth location of such moving targets. Theoretical results provided in this paper are validated using the publicly available Air Force Research Laboratories (AFRL) multichannel SAR GMTI Gotcha data set.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"2 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":"129499039","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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