A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing

Modern radar systems have high requirements in terms of accuracy, robustness and real-time capability when operating on increasingly complex electromagnetic environments. Traditional radar signal processing (RSP) methods have shown some limitations when meeting such requirements, particularly in matters of target classification. With the rapid development of machine learning (ML), especially deep learning, radar researchers have started integrating these new methods when solving RSP-related problems. This paper aims at helping researchers and practitioners to better understand the application of ML techniques to RSP-related problems by providing a comprehensive, structured and reasoned literature overview of ML-based RSP techniques. This work is amply introduced by providing general elements of ML-based RSP and by stating the motivations behind them. The main applications of ML-based RSP are then analysed and structured based on the application field. This paper then concludes with a series of open questions and proposed research directions, in order to indicate current gaps and potential future solutions and trends.

[1]  Yuting Zhai,et al.  Radar Emitter Recognition Based on Ambiguity Function Contour Plot , 2019, 2019 IEEE 7th International Conference on Computer Science and Network Technology (ICCSNT).

[2]  Ali Farhadi,et al.  YOLO9000: Better, Faster, Stronger , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[3]  Mihai Datcu,et al.  Classification of Large-Scale High-Resolution SAR Images With Deep Transfer Learning , 2020, IEEE Geoscience and Remote Sensing Letters.

[4]  Mark Sandler,et al.  MobileNetV2: Inverted Residuals and Linear Bottlenecks , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[5]  Fang Liu,et al.  SAR Image segmentation based on convolutional-wavelet neural network and markov random field , 2017, Pattern Recognit..

[6]  Wei Luo,et al.  SAR Image Retrieval Based on Unsupervised Domain Adaptation and Clustering , 2019, IEEE Geoscience and Remote Sensing Letters.

[7]  Fan Zhang,et al.  Synthetic aperture radar target recognition of incomplete training datasets via Siamese network , 2019 .

[8]  Giampaolo Ferraioli,et al.  Ten Years of Patch-Based Approaches for Sar Imaging: A Review , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[9]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[10]  Murray Shanahan,et al.  Reconciling deep learning with symbolic artificial intelligence: representing objects and relations , 2019, Current Opinion in Behavioral Sciences.

[11]  Min Li,et al.  Sparse Representation Denoising for Radar High Resolution Range Profiling , 2014 .

[12]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[13]  Quan Pan,et al.  Rotation Awareness Based Self-Supervised Learning for SAR Target Recognition , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[14]  Zongjie Cao,et al.  Image Data Augmentation for SAR Sensor via Generative Adversarial Nets , 2019, IEEE Access.

[15]  Fei Gao,et al.  Enhanced Feature Extraction for Ship Detection from Multi-Resolution and Multi-Scene Synthetic Aperture Radar (SAR) Images , 2019, Remote. Sens..

[16]  Xiongjun Fu,et al.  A semi-greedy neural network CAE-HL-CNN for SAR target recognition with limited training data , 2020 .

[17]  Jianwei Li,et al.  Ship detection in SAR images based on an improved faster R-CNN , 2017, 2017 SAR in Big Data Era: Models, Methods and Applications (BIGSARDATA).

[18]  Xueru Bai,et al.  Few-Shot SAR ATR Based on Conv-BiLSTM Prototypical Networks , 2019, 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR).

[19]  Okan K. Ersoy,et al.  Fast texture classification of denoised SAR image patches using GLCM on Spark , 2020 .

[20]  Geoffrey E. Hinton.  Deep belief networks , 2009, Scholarpedia.

[21]  Xiaorui Ma,et al.  Transfer Learning for SAR Image Classification Via Deep Joint Distribution Adaptation Networks , 2020, IEEE Transactions on Geoscience and Remote Sensing.

[22]  Jie Geng,et al.  High-Resolution SAR Image Classification via Deep Convolutional Autoencoders , 2015, IEEE Geoscience and Remote Sensing Letters.

[23]  Zhilu Wu,et al.  Hybrid Radar Emitter Recognition Based on Rough k-Means Classifier and Relevance Vector Machine , 2013, Sensors.

[24]  Youngwook Kim,et al.  Human Activity Classification Based on Micro-Doppler Signatures Using a Support Vector Machine , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[25]  José García Rodríguez,et al.  A Review on Deep Learning Techniques Applied to Semantic Segmentation , 2017, ArXiv.

[26]  A. Kawalec,et al.  Knowledge-based signal processing for radar identification , 2008, 2008 International Conference on "Modern Problems of Radio Engineering, Telecommunications and Computer Science" (TCSET).

[27]  Birsen Yazici,et al.  Deep Learning for Direct Automatic Target Recognition from SAR Data , 2019, 2019 IEEE Radar Conference (RadarConf).

[28]  S. N. Abdullah,et al.  Deinterleaving of radar signals and PRF identification algorithms , 2007 .

[29]  Bin Tang,et al.  Automatic modulation classification of radar signals using the Rihaczek distribution and hough transform , 2012 .

[30]  Ali Farhadi,et al.  You Only Look Once: Unified, Real-Time Object Detection , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[31]  Jun Wang,et al.  Deep learning based target detection method with multi-features in SAR imagery , 2019, 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR).

[32]  Gaoming Huang,et al.  Automatic Radar Waveform Recognition Based on Deep Convolutional Denoising Auto-encoders , 2018, Circuits Syst. Signal Process..

[33]  Yanping Bai,et al.  Deep convolutional neural network structural design for synthetic aperture radar image target recognition based on incomplete training data and displacement insensitivity , 2019, J. Electronic Imaging.

[34]  G. Anagnostopoulos.  SVM-based target recognition from synthetic aperture radar images using target region outline descriptors , 2009 .

[35]  Zhao Lin,et al.  Contextual Region-Based Convolutional Neural Network with Multilayer Fusion for SAR Ship Detection , 2017, Remote. Sens..

[36]  Chan Gook Park,et al.  Multiple Feature Aggregation Using Convolutional Neural Networks for SAR Image-Based Automatic Target Recognition , 2018, IEEE Geoscience and Remote Sensing Letters.

[37]  Bo Chen,et al.  MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications , 2017, ArXiv.

[38]  Hugo Larochelle,et al.  Optimization as a Model for Few-Shot Learning , 2016, ICLR.

[39]  Jing Xu,et al.  A Comprehensive Estimation Method for Kernel Function of Radar Signal Classifier , 2015 .

[40]  Moncef Gabbouj,et al.  Dual and Single Polarized SAR Image Classification Using Compact Convolutional Neural Networks , 2019, Remote. Sens..

[41]  Naoufel Werghi,et al.  Using transfer learning technique for SAR automatic target recognition , 2019, Other Conferences.

[42]  Max Welling,et al.  Semi-supervised Learning with Deep Generative Models , 2014, NIPS.

[43]  Gexiang Zhang,et al.  Radar emitter signal recognition based on support vector machines , 2004, ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004..

[44]  Fawwaz T. Ulaby,et al.  SAR speckle reduction using wavelet denoising and Markov random field modeling , 2002, IEEE Trans. Geosci. Remote. Sens..

[45]  Weisong Liu,et al.  Radar Emitter Classification With Attention-Based Multi-RNNs , 2020, IEEE Communications Letters.

[46]  Zhipeng Liu,et al.  Adaptive boosting for SAR automatic target recognition , 2007, IEEE Transactions on Aerospace and Electronic Systems.

[47]  Xiaojing Huang,et al.  Automatic Ship Detection in SAR Images Using Multi-Scale Heterogeneities and an A Contrario Decision , 2015, Remote. Sens..

[48]  Timothy A. Warner,et al.  Implementation of machine-learning classification in remote sensing: an applied review , 2018 .

[49]  Zhiyu Qu,et al.  Radar Signal Intra-Pulse Modulation Recognition Based on Convolutional Neural Network and Deep Q-Learning Network , 2020, IEEE Access.

[50]  Shannon D. Blunt,et al.  A machine learning approach to cognitive radar detection , 2015, 2015 IEEE Radar Conference (RadarCon).

[51]  Jian-Ping Mei,et al.  Radar emitter identification with bispectrum and hierarchical extreme learning machine , 2019, Multimedia Tools and Applications.

[52]  Lei Xue,et al.  A scale transfer convolution network for small ship detection in SAR images , 2019, 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC).

[53]  Wei Zhang,et al.  Adversarial Deep Domain Adaptation for Multi-Band SAR Images Classification , 2019, IEEE Access.

[54]  Saibun Tjuatja,et al.  ISAR Imaging in the Presence of Quasi-Random Multiplicative Noise Using Convolutional Deep Learning , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[55]  Bin Tang,et al.  An approach to the modulation recognition of MIMO radar signals , 2013, EURASIP J. Wirel. Commun. Netw..

[56]  Marek Vajgl,et al.  Poly-YOLO: higher speed, more precise detection and instance segmentation for YOLOv3 , 2020, Neural Comput. Appl..

[57]  Zewen Li,et al.  A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects , 2020, IEEE Transactions on Neural Networks and Learning Systems.

[58]  Zongben Xu,et al.  An Active Deep Learning Approach for Minimally-Supervised Polsar Image Classification , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[59]  Jiao Jiao,et al.  A Densely Connected End-to-End Neural Network for Multiscale and Multiscene SAR Ship Detection , 2018, IEEE Access.

[60]  Yang Li,et al.  Robust Automatic Target Recognition via HRRP Sequence Based on Scatterer Matching , 2018, Sensors.

[61]  Orhan Arikan,et al.  Classification of Intra-Pulse Modulation of Radar Signals by Feature Fusion Based Convolutional Neural Networks , 2018, 2018 26th European Signal Processing Conference (EUSIPCO).

[62]  Kai Liu,et al.  Multi-Stream Convolutional Neural Network for SAR Automatic Target Recognition , 2018, Remote. Sens..

[63]  Benjamin Schrauwen,et al.  Deep content-based music recommendation , 2013, NIPS.

[64]  Cai Yunze,et al.  Ship detection in SAR Image using YOLOv2 , 2018, 2018 37th Chinese Control Conference (CCC).

[65]  Chen Li,et al.  Point-wise discriminative auto-encoder with application on robust radar automatic target recognition , 2020, Signal Process..

[66]  Wei Jiang,et al.  End-to-end Learning of Waveform Generation and Detection for Radar Systems , 2019, 2019 53rd Asilomar Conference on Signals, Systems, and Computers.

[67]  Yuhui Zheng,et al.  Recent Progress on Generative Adversarial Networks (GANs): A Survey , 2019, IEEE Access.

[68]  Hao Ling,et al.  Human activity classification based on micro-Doppler signatures using an artificial neural network , 2008, 2008 IEEE Antennas and Propagation Society International Symposium.

[69]  Erfu Yang,et al.  Dual-Branch Deep Convolution Neural Network for Polarimetric SAR Image Classification , 2017 .

[70]  Lanqing Huang,et al.  OpenSARShip: A Dataset Dedicated to Sentinel-1 Ship Interpretation , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[71]  Tao Xie,et al.  Inshore Ship Detection Based on Level Set Method and Visual Saliency for SAR Images , 2018, Sensors.

[72]  Chen Wang,et al.  Automated Geophysical Classification of Sentinel-L Wave Mode Sar Images Through Deep-Learning , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[73]  J. Friedman.  Greedy function approximation: A gradient boosting machine. , 2001 .

[74]  Eric P. Xing,et al.  Contextual Explanation Networks , 2017, J. Mach. Learn. Res..

[75]  Zhitao Huang,et al.  Denoising of Radar Pulse Streams With Autoencoders , 2020, IEEE Communications Letters.

[76]  Yongfeng Zhu,et al.  Semi-Supervised Deep Transfer Learning-Based on Adversarial Feature Learning for Label Limited SAR Target Recognition , 2019, IEEE Access.

[77]  Xiang Li,et al.  An Adaptive Feature Learning Model for Sequential Radar High Resolution Range Profile Recognition , 2017, Sensors.

[78]  Francesco Fioranelli,et al.  Review of radar classification and RCS characterisation techniques for small UAVs or drones , 2018, IET Radar, Sonar & Navigation.

[79]  Shunjun Wei,et al.  ACSE Networks and Autocorrelation Features for PRI Modulation Recognition , 2020, IEEE Communications Letters.

[80]  Xiangyu Zhang,et al.  ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[81]  Tushar Gadhiya,et al.  Optimized Wishart Network for an Efficient Classification of Multifrequency PolSAR Data , 2018, IEEE Geoscience and Remote Sensing Letters.

[82]  Jin Xing,et al.  Automatic Extraction of Water and Shadow from SAR Images Based on a Multi-Resolution Dense Encoder and Decoder Network , 2019, Sensors.

[83]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[84]  Hong Zhang,et al.  A Two-Component Deep Learning Network for SAR Image Denoising , 2020, IEEE Access.

[85]  Cong Peng,et al.  Recognition Algorithm of Emitter Signals Based on PCA+CNN , 2018, 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC).

[86]  Andrea Lodi,et al.  On learning and branching: a survey , 2017 .

[87]  Ximing Wang,et al.  Jamming Pattern Recognition Using Spectrum Waterfall: A Deep Learning Method , 2019, 2019 IEEE 5th International Conference on Computer and Communications (ICCC).

[88]  Nuno Vasconcelos,et al.  Cascade R-CNN: Delving Into High Quality Object Detection , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[89]  Jugal K. Kalita,et al.  Deep Learning applied to NLP , 2017, ArXiv.

[90]  Wang Qi,et al.  SAR Target Classification Method Based on Convolutional Neural Network , 2018, 2018 IEEE 9th International Conference on Software Engineering and Service Science (ICSESS).

[91]  Seong-Ook Park,et al.  Drone Classification Using Convolutional Neural Networks With Merged Doppler Images , 2017, IEEE Geoscience and Remote Sensing Letters.

[92]  David A. Castanon,et al.  Markov random field segmentation methods for SAR target chips , 1999, Defense, Security, and Sensing.

[93]  Janusz Dudczyk,et al.  Radar Emission Sources Identification Based on Hierarchical Agglomerative Clustering for Large Data Sets , 2016, J. Sensors.

[94]  J. Dudczyk,et al.  Identification of emitter sources in the aspect of their fractal features , 2013 .

[95]  Wei Chen,et al.  Recognition method of dense false targets jamming based on time-frequency atomic decomposition , 2019 .

[96]  Jianyu Yang,et al.  SAR Automatic Target Recognition Based on Multiview Deep Learning Framework , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[97]  Henry Leung,et al.  Synthetic Aperture Radar Image Generation With Deep Generative Models , 2019, IEEE Geoscience and Remote Sensing Letters.

[98]  Fu Ruo-Ran.  Compound Jamming Signal Recognition Based on Neural Networks , 2016, 2016 Sixth International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC).

[99]  Haipeng Wang,et al.  SAR target recognition based on deep learning , 2014, 2014 International Conference on Data Science and Advanced Analytics (DSAA).

[100]  Siyang Cao,et al.  Support vector machines for classification of automotive radar interference , 2018, 2018 IEEE Radar Conference (RadarConf18).

[101]  Feng Wang,et al.  Automatic modulation classification based on joint feature map and convolutional neural network , 2019, IET Radar, Sonar & Navigation.

[102]  Joshua B. Tenenbaum,et al.  Deep Convolutional Inverse Graphics Network , 2015, NIPS.

[103]  Sergey Ioffe,et al.  Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.

[104]  Gaoming Huang,et al.  Radar Waveform Recognition Based on Multiple Autocorrelation Images , 2019, IEEE Access.

[105]  Roberto Marcondes Cesar Junior,et al.  A hierarchical Markov random field for road network extraction and its application with optical and SAR data , 2011, 2011 IEEE International Geoscience and Remote Sensing Symposium.

[106]  Fabrizio Argenti,et al.  Speckle removal from SAR images in the undecimated wavelet domain , 2002, IEEE Trans. Geosci. Remote. Sens..

[107]  Zhipeng Ge,et al.  Improved Algorithm of Radar Pulse Repetition Interval Deinterleaving Based on Pulse Correlation , 2019, IEEE Access.

[108]  Joshua B. Tenenbaum,et al.  Human-level concept learning through probabilistic program induction , 2015, Science.

[109]  Ningning Tong,et al.  DIOD: Fast and Efficient Weakly Semi-Supervised Deep Complex ISAR Object Detection , 2019, IEEE Transactions on Cybernetics.

[110]  Ya Shi,et al.  Kernel canonical correlation analysis for specific radar emitter identification , 2014 .

[111]  Bin Xue,et al.  Real-World ISAR Object Recognition and Relation Discovery Using Deep Relation Graph Learning , 2019, IEEE Access.

[112]  H. Zhang,et al.  Hierarchical feature exttratction for object recogition in complex SAR image using modified convolutional auto-encoder , 2017, 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[113]  Wen Nie,et al.  Fully Polarized SAR imagery Classification Based on Deep Reinforcement Learning Method Using Multiple Polarimetric Features , 2019, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[114]  Nan Lin,et al.  Target Classification From SAR Imagery Based on the Pixel Grayscale Decline by Graph Convolutional Neural Network , 2020, IEEE Sensors Letters.

[115]  L. Cifola,et al.  Multi-target human gait classification using LSTM recurrent neural networks applied to micro-Doppler , 2017, 2017 European Radar Conference (EURAD).

[116]  Eric R. Keydel,et al.  MSTAR extended operating conditions: a tutorial , 1996, Defense, Security, and Sensing.

[117]  Shuai Wang,et al.  Deep learning for sentiment analysis: A survey , 2018, WIREs Data Mining Knowl. Discov..

[118]  Yunhao Tang,et al.  Reinforcement Learning for Integer Programming: Learning to Cut , 2019, ICML.

[119]  Fabrizio Argenti,et al.  Automatic ship detection in SAR images , 1992 .

[120]  Samiur Rahman,et al.  Radar micro-Doppler signatures of drones and birds at K-band and W-band , 2018, Scientific Reports.

[121]  Xin Xu,et al.  DIOD: Fast, Semi-Supervised Deep ISAR Object Detection , 2019, IEEE Sensors Journal.

[122]  Carlos Guestrin,et al.  "Why Should I Trust You?": Explaining the Predictions of Any Classifier , 2016, ArXiv.

[123]  Jeffrey H. Reed,et al.  Specific Emitter Identification for Cognitive Radio with Application to IEEE 802.11 , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[124]  Vincenzo Piuri,et al.  Robust SAR Automatic Target Recognition Based on Transferred MS-CNN with L2-Regularization , 2019, Comput. Intell. Neurosci..

[125]  Jan Zak,et al.  The identification of radar signals by histogram description leads to cluster analysis processing , 2014, 2014 15th International Radar Symposium (IRS).

[126]  S. Quegan,et al.  Understanding Synthetic Aperture Radar Images , 1998 .

[127]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[128]  Xiaowei Hu,et al.  High-resolution ISAR imaging of fast rotating targets based on pattern-coupled Bayesian strategy for multiple measurement vectors , 2019, Digit. Signal Process..

[129]  Cristian Coman,et al.  A Deep Learning SAR Target Classification Experiment on MSTAR Dataset , 2018, 2018 19th International Radar Symposium (IRS).

[130]  Yanan Xu,et al.  High-dimensional feature extraction of sea clutter and target signal for intelligent maritime monitoring network , 2019, Comput. Commun..

[131]  Yue Yan,et al.  Convolutional neural networks based on augmented training samples for synthetic aperture radar target recognition , 2018 .

[132]  Tushar Gadhiya,et al.  Superpixel-Driven Optimized Wishart Network for Fast PolSAR Image Classification Using Global ${k}$ -Means Algorithm , 2020, IEEE Transactions on Geoscience and Remote Sensing.

[133]  Yu Guo,et al.  Least square support vector data description for HRRP-based radar target recognition , 2016, Applied Intelligence.

[134]  Leif E. Peterson.  K-nearest neighbor , 2009, Scholarpedia.

[135]  Hong Sun,et al.  Automatic modulation classification using stacked sparse auto-encoders , 2016, 2016 IEEE 13th International Conference on Signal Processing (ICSP).

[136]  Xiaowei Hu,et al.  Automatic recognition of ISAR images based on deep learning , 2016, 2016 CIE International Conference on Radar (RADAR).

[137]  Francesco Fioranelli,et al.  Feature Diversity for Optimized Human Micro-Doppler Classification Using Multistatic Radar , 2017, IEEE Transactions on Aerospace and Electronic Systems.

[138]  Matti Pietikäinen,et al.  Deep Learning for Generic Object Detection: A Survey , 2018, International Journal of Computer Vision.

[139]  Jiang Jie,et al.  Radar HRRP recognition based on discriminant deep autoencoders with small training data size , 2016 .

[140]  Shuiping Gou,et al.  Classification of interferometric synthetic aperture radar image with deep learning approach , 2016, 2016 CIE International Conference on Radar (RADAR).

[141]  Bo Zhang,et al.  Residual encoder-decoder network introduced for multisource SAR image despeckling , 2017, 2017 SAR in Big Data Era: Models, Methods and Applications (BIGSARDATA).

[142]  Derek Anderson,et al.  Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community , 2017 .

[143]  Xiao Bai,et al.  Ground Target Classification in Noisy SAR Images Using Convolutional Neural Networks , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[144]  Shanzeng Guo,et al.  A comparison study of radar emitter identification based on signal transients , 2018, 2018 IEEE Radar Conference (RadarConf18).

[145]  Wei Liu,et al.  SSD: Single Shot MultiBox Detector , 2015, ECCV.

[146]  Yuan Zeng,et al.  Radar Emitter Signal Detection with Convolutional Neural Network , 2019, 2019 IEEE 11th International Conference on Advanced Infocomm Technology (ICAIT).

[147]  Philippe Vincke,et al.  Analysis of multicriteria decision aid in Europe , 1986 .

[148]  Wang Manxi,et al.  Identification of Jamming Factors in Electronic Information System Based on Deep Learning , 2018, 2018 IEEE 18th International Conference on Communication Technology (ICCT).

[149]  Naftali Tishby,et al.  Opening the Black Box of Deep Neural Networks via Information , 2017, ArXiv.

[150]  Kaiming He,et al.  Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[151]  Harry A. Pierson,et al.  Deep learning in robotics: a review of recent research , 2017, Adv. Robotics.

[152]  Kevin W. Sowerby,et al.  RF fingerprint extraction from the energy envelope of an instantaneous transient signal , 2012, 2012 Australian Communications Theory Workshop (AusCTW).

[153]  Quoc V. Le,et al.  EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks , 2019, ICML.

[154]  George Kesidis,et al.  Adversarial Learning Targeting Deep Neural Network Classification: A Comprehensive Review of Defenses Against Attacks , 2020, Proceedings of the IEEE.

[155]  Chao Wang,et al.  SAR Object Classification with a Multi-Scale Convolutional Auto-Encoder , 2019, 2019 SAR in Big Data Era (BIGSARDATA).

[156]  Eric Eaton,et al.  SAR Image Classification Using Few-Shot Cross-Domain Transfer Learning , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[157]  Fan Zhang,et al.  Slim and Efficient Neural Network Design for Resource-Constrained SAR Target Recognition , 2018, Remote. Sens..

[158]  Edmund Y. Lam,et al.  Nonlocal Means Filtering Based Speckle Removal Utilizing the Maximum a Posteriori Estimation and the Total Variation Image Prior , 2019, IEEE Access.

[159]  Xiaoxin Liu,et al.  Incremental Wishart Broad Learning System for Fast PolSAR Image Classification , 2019, IEEE Geoscience and Remote Sensing Letters.

[160]  M. Barkat,et al.  Automatic censoring CFAR detector based on ordered data variability for nonhomogeneous environments , 2005 .

[161]  Krištof Oštir,et al.  Vessel detection and classification from spaceborne optical images: A literature survey , 2018, Remote sensing of environment.

[162]  G. Poggi,et al.  Nonlocal Sar Image Despeckling by Convolutional Neural Networks , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[163]  Ran Zhang,et al.  Multi‐feature radar signal modulation recognition based on improved PSO algorithm , 2019, The Journal of Engineering.

[164]  Tao Li,et al.  Radar high-resolution range profile feature extraction method based on multiple kernel projection subspace fusion , 2018 .

[165]  Marc'Aurelio Ranzato,et al.  Efficient Learning of Sparse Representations with an Energy-Based Model , 2006, NIPS.

[166]  Brian D. Rigling,et al.  ACF-based classification of phase modulated waveforms , 2010, 2010 IEEE Radar Conference.

[167]  Honglak Lee,et al.  Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations , 2009, ICML '09.

[168]  Andrea Baraldi,et al.  A refined gamma MAP SAR speckle filter with improved geometrical adaptivity , 1995, IEEE Trans. Geosci. Remote. Sens..

[169]  J. Roe.  A review of applications of artificial intelligence techniques to naval ESM signal processing , 1989 .

[170]  Zhiyu Qu,et al.  Radar Signal Intra-Pulse Modulation Recognition Based on Convolutional Neural Network , 2018, IEEE Access.

[171]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[172]  Hidetoshi Furukawa,et al.  Deep Learning for Target Classification from SAR Imagery: Data Augmentation and Translation Invariance , 2017, ArXiv.

[173]  Xiaoshuang Ma,et al.  Learning a Dilated Residual Network for SAR Image Despeckling , 2017, Remote. Sens..

[174]  Jianwei Li,et al.  A Lightweight Convolutional Neural Network Based on Visual Attention for SAR Image Target Classification , 2018, Sensors.

[175]  Yee Whye Teh,et al.  A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.

[176]  Haipeng Wang,et al.  A Lightweight Feature Optimizing Network for Ship Detection in SAR Image , 2019, IEEE Access.

[177]  Chao Wang,et al.  Combining a single shot multibox detector with transfer learning for ship detection using sentinel-1 SAR images , 2018, Remote Sensing Letters.

[178]  Daan Wierstra,et al.  Stochastic Backpropagation and Approximate Inference in Deep Generative Models , 2014, ICML.

[179]  Cengiz Öztireli,et al.  Towards better understanding of gradient-based attribution methods for Deep Neural Networks , 2017, ICLR.

[180]  Zhiyu Qu,et al.  Radar Signal Intra-Pulse Modulation Recognition Based on Convolutional Denoising Autoencoder and Deep Convolutional Neural Network , 2019, IEEE Access.

[181]  Wei Zhang,et al.  Deep learning and recognition of radar jamming based on CNN , 2019, 2019 12th International Symposium on Computational Intelligence and Design (ISCID).

[182]  Zheru Chi,et al.  A scale-invariant framework for image classification with deep learning , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[183]  Xuegang Wang,et al.  Joint Supervised Dictionary and Classifier Learning for Multi-View SAR Image Classification , 2019, IEEE Access.

[184]  Hongwei Liu,et al.  Convolutional Neural Network With Data Augmentation for SAR Target Recognition , 2016, IEEE Geoscience and Remote Sensing Letters.

[185]  Zhiyuan Yan,et al.  Radar emitter classification based on unidimensional convolutional neural network , 2018, IET Radar, Sonar & Navigation.

[186]  S. Z. Gürbüz,et al.  Deep Neural Network Initialization Methods for Micro-Doppler Classification With Low Training Sample Support , 2017, IEEE Geoscience and Remote Sensing Letters.

[187]  Xudong Zhang,et al.  Radar signal classification based on auto-correlation function and directed graphical model , 2016, 2016 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC).

[188]  Xiang Li,et al.  Joint Sparse Aperture ISAR Autofocusing and Scaling via Modified Newton Method-Based Variational Bayesian Inference , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[189]  Jesús Grajal,et al.  Real-time low-complexity automatic modulation classifier for pulsed radar signals , 2015, IEEE Transactions on Aerospace and Electronic Systems.

[190]  Jie Jiang,et al.  Radar HRRP Target Recognition Based on t-SNE Segmentation and Discriminant Deep Belief Network , 2017, IEEE Geoscience and Remote Sensing Letters.

[191]  Pascal Vincent,et al.  Contractive Auto-Encoders: Explicit Invariance During Feature Extraction , 2011, ICML.

[192]  Xiuwu Liao,et al.  An interpretable machine learning framework for modelling human decision behavior , 2019, ArXiv.

[193]  Fan Zhang,et al.  SAR Target Small Sample Recognition Based on CNN Cascaded Features and AdaBoost Rotation Forest , 2020, IEEE Geoscience and Remote Sensing Letters.

[194]  Vibha Patel,et al.  Analysis of Denoising Techniques for Speckle Noise Removal in Synthetic Aperture Radar Images , 2018, 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[195]  Yang Liu,et al.  Research on electronic jamming identification based on CNN , 2019, 2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP).

[196]  Zongjie Cao,et al.  PolSAR image classification based on deep polarimetric feature and contextual information , 2019 .

[197]  Max Welling,et al.  Visualizing Deep Neural Network Decisions: Prediction Difference Analysis , 2017, ICLR.

[198]  Pieter Abbeel,et al.  InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets , 2016, NIPS.

[199]  Jan Matuszewski.  Applying the decision trees to radar targets recognition , 2010, 11-th INTERNATIONAL RADAR SYMPOSIUM.

[200]  Yanfei Wang,et al.  Classification of PolSAR Image Using Neural Nonlocal Stacked Sparse Autoencoders with Virtual Adversarial Regularization , 2019, Remote. Sens..

[201]  Bo Li,et al.  Towards Interpretable R-CNN by Unfolding Latent Structures , 2017, 1711.05226.

[202]  Yulin Huang,et al.  Multi-View Bistatic Synthetic Aperture Radar Target Recognition Based on Multi-Input Deep Convolutional Neural Network , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[203]  Dumitru Erhan,et al.  Deep Neural Networks for Object Detection , 2013, NIPS.

[204]  Junya Lv,et al.  Exploiting multi-level deep features via joint sparse representation with application to SAR target recognition , 2019, International Journal of Remote Sensing.

[205]  Klaus-Robert Müller,et al.  Learning how to explain neural networks: PatternNet and PatternAttribution , 2017, ICLR.

[206]  Chao Yang,et al.  A Survey on Deep Transfer Learning , 2018, ICANN.

[207]  Daiying Zhou,et al.  Radar target HRRP recognition based on reconstructive and discriminative dictionary learning , 2016, Signal Process..

[208]  Yue Liu,et al.  Data Augmentation Based on Attributed Scattering Centers to Train Robust CNN for SAR ATR , 2019, IEEE Access.

[209]  Yu Guo,et al.  Learning using privileged information for HRRP-based radar target recognition , 2018, IET Signal Process..

[210]  Han Bin Bae,et al.  Classification of the trained and untrained emitter types based on class probability output networks , 2017, Neurocomputing.

[211]  Hong Zhang,et al.  Fine-grained ship classification based on deep residual learning for high-resolution SAR images , 2019, Remote Sensing Letters.

[212]  Baiyuan Ding,et al.  Data Augmentation by Multilevel Reconstruction Using Attributed Scattering Center for SAR Target Recognition , 2017, IEEE Geoscience and Remote Sensing Letters.

[213]  Navdeep Jaitly,et al.  Pointer Networks , 2015, NIPS.

[214]  Simon Osindero,et al.  Conditional Generative Adversarial Nets , 2014, ArXiv.

[215]  Ran Duan,et al.  Deep kernel learning method for SAR image target recognition. , 2017, The Review of scientific instruments.

[216]  Chen Wang,et al.  A Deep Unsupervised Learning Method for SAR Object Classification , 2019, 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR).

[217]  Ivan Poupyrev,et al.  Interacting with Soli: Exploring Fine-Grained Dynamic Gesture Recognition in the Radio-Frequency Spectrum , 2016, UIST.

[218]  Qian Song,et al.  SAR Image Representation Learning With Adversarial Autoencoder Networks , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[219]  Liu Hongwei,et al.  Reinforcement Learning based Anti-jamming Frequency Hopping Strategies Design for Cognitive Radar , 2018, 2018 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC).

[220]  Tao Xie,et al.  A Novel Marine Oil Spillage Identification Scheme Based on Convolution Neural Network Feature Extraction From Fully Polarimetric SAR Imagery , 2020, IEEE Access.

[221]  Jonathan Li,et al.  Ship Detection Using a Fully Convolutional Network with Compact Polarimetric SAR Images , 2019, Remote. Sens..

[222]  Christopher J. C. Burges,et al.  A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.

[223]  Nedyalko Petrov,et al.  Radar Emitter Signals Recognition and Classification with Feedforward Networks , 2013, KES.

[224]  Maria-Florina Balcan,et al.  Learning to Branch , 2018, ICML.

[225]  Long Tang,et al.  Nonparallel support vector regression model and its SMO-type solver , 2018, Neural Networks.

[226]  Nadav Levanon,et al.  Ambiguity Function Based Radar Waveform Classification and Unsupervised Adaptation Using Deep CNN Models , 2019, 2019 IEEE International Conference on Microwaves, Antennas, Communications and Electronic Systems (COMCAS).

[227]  Zhitao Huang,et al.  Attention-Based Radar PRI Modulation Recognition With Recurrent Neural Networks , 2020, IEEE Access.

[228]  Frank Hutter,et al.  Neural Architecture Search: A Survey , 2018, J. Mach. Learn. Res..

[229]  Xin Wang,et al.  Synthetic Aperture Radar Target Recognition Using Weighted Multi-Task Kernel Sparse Representation , 2019, IEEE Access.

[230]  Lisandro Zambenedetti Granville,et al.  Improving reinforcement learning algorithms for dynamic spectrum allocation in cognitive sensor networks , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[231]  Tao Zhang,et al.  A Survey of Model Compression and Acceleration for Deep Neural Networks , 2017, ArXiv.

[232]  Marc Peter Deisenroth,et al.  Deep Reinforcement Learning: A Brief Survey , 2017, IEEE Signal Processing Magazine.

[233]  S. Z. Gürbüz,et al.  Deep convolutional autoencoder for radar-based classification of similar aided and unaided human activities , 2018, IEEE Transactions on Aerospace and Electronic Systems.

[234]  Yiyu Zhou,et al.  Approach based on combination of vector neural networks for emitter identification , 2010 .

[235]  Jin Zhao,et al.  Multilayer Projective Dictionary Pair Learning and Sparse Autoencoder for PolSAR Image Classification , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[236]  Trevor Darrell,et al.  Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[237]  Xiaoling Zhang,et al.  SAR deception jamming target recognition based on the shadow feature , 2017, 2017 25th European Signal Processing Conference (EUSIPCO).

[238]  Giampaolo Ferraioli,et al.  A New Ratio Image Based CNN Algorithm for SAR Despeckling , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[239]  Tom White,et al.  Generative Adversarial Networks: An Overview , 2017, IEEE Signal Processing Magazine.

[240]  Luisa Verdoliva,et al.  Benchmarking Framework for SAR Despeckling , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[241]  Zelong Wang,et al.  Efficient deep convolutional neural networks using CReLU for ATR with limited SAR images , 2019, The Journal of Engineering.

[242]  Ning Fang,et al.  Scale-space theory-based multi-scale features for aircraft classification using HRRP , 2016 .

[243]  Davide Castelvecchi,et al.  Can we open the black box of AI? , 2016, Nature.

[244]  Qing Wang,et al.  Transferred deep learning based waveform recognition for cognitive passive radar , 2019, Signal Process..

[245]  Saeid Homayouni,et al.  Hybrid SAR Speckle Reduction Using Complex Wavelet Shrinkage and Non-Local PCA-Based Filtering , 2019, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[246]  Mihai Datcu,et al.  Deep SAR-Net: Learning objects from signals , 2020 .

[247]  Xin Xu,et al.  Exploring Convolutional Lstm for Polsar Image Classification , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[248]  Hongjun Song,et al.  SAR Target Classification Based on Deep Forest Model , 2020, Remote. Sens..

[249]  Vivienne Sze,et al.  Efficient Processing of Deep Neural Networks: A Tutorial and Survey , 2017, Proceedings of the IEEE.

[250]  Victor C. Chen,et al.  Doppler signatures of radar backscattering from objects with micro-motions , 2008 .

[251]  Rui Min,et al.  A Gradually Distilled CNN for SAR Target Recognition , 2019, IEEE Access.

[252]  Giles M. Foody,et al.  An evaluation of some factors affecting the accuracy of classification by an artificial neural network , 1997 .

[253]  Naftali Tishby,et al.  Deep learning and the information bottleneck principle , 2015, 2015 IEEE Information Theory Workshop (ITW).

[254]  Peter F. McGuire,et al.  Automatic Target Recognition in Synthetic Aperture Radar Imagery: A State-of-the-Art Review , 2016, IEEE Access.

[255]  V. Koivunen,et al.  Automatic Radar Waveform Recognition , 2007, IEEE Journal of Selected Topics in Signal Processing.

[256]  Alper Yildirim,et al.  Deinterleaving of radar signals with stagger PRI and dwell-switch PRI types , 2017, 2017 25th Signal Processing and Communications Applications Conference (SIU).

[257]  Wei Yu,et al.  A Survey of Deep Learning: Platforms, Applications and Emerging Research Trends , 2018, IEEE Access.

[258]  Sergei A. Vakin,et al.  Fundamentals of Electronic Warfare , 2000 .

[259]  Zongxu Pan,et al.  Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network , 2018, Sensors.

[260]  Qiang Guo,et al.  LPI Radar Waveform Recognition Based on CNN and TPOT , 2019, Symmetry.

[261]  Benjamin C. Flores,et al.  Classification of radar jammer FM signals using a neural network , 2017, Defense + Security.

[262]  Vishal M. Patel,et al.  SAR Image Despeckling Using a Convolutional Neural Network , 2017, IEEE Signal Processing Letters.

[263]  Yunpu Wu,et al.  Automatic Modulation Recognition of Radar Signals Based on Manhattan Distance-Based Features , 2019, IEEE Access.

[264]  Simon A. Wagner,et al.  SAR ATR by a combination of convolutional neural network and support vector machines , 2016, IEEE Transactions on Aerospace and Electronic Systems.

[265]  Francesco Fioranelli,et al.  Classification of Unarmed/Armed Personnel Using the NetRAD Multistatic Radar for Micro-Doppler and Singular Value Decomposition Features , 2015, IEEE Geoscience and Remote Sensing Letters.

[266]  Cuntai Guan,et al.  A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI , 2019, IEEE Transactions on Neural Networks and Learning Systems.

[267]  Albert Gordo,et al.  Learning Global Additive Explanations for Neural Nets Using Model Distillation , 2018 .

[268]  Erfu Yang,et al.  Semi-Supervised Generative Adversarial Nets with Multiple Generators for SAR Image Recognition , 2018, Sensors.

[269]  James A. Anderson,et al.  Advanced signal waveform classifier , 1997, Optics & Photonics.

[270]  Bir Bhanu,et al.  SAR object classification using the DAE with a modified triplet restriction , 2019 .

[271]  Nitish Srivastava,et al.  Multimodal learning with deep Boltzmann machines , 2012, J. Mach. Learn. Res..

[272]  Daniel S. Katz,et al.  High Performance Computing Systems for Autonomous Spaceborne Missions , 2001, Int. J. High Perform. Comput. Appl..

[273]  Jie Geng,et al.  Semisupervised Classification of Polarimetric SAR Image via Superpixel Restrained Deep Neural Network , 2018, IEEE Geoscience and Remote Sensing Letters.

[274]  Jin Xing,et al.  A New Deep Learning Algorithm for SAR Scene Classification Based on Spatial Statistical Modeling and Features Re-Calibration , 2019, Sensors.

[275]  Haipeng Wang,et al.  Complex-Valued Convolutional Neural Network and Its Application in Polarimetric SAR Image Classification , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[276]  Yuejin Zhao,et al.  SAR target recognition and posture estimation using spatial pyramid pooling within CNN , 2018, International Conference on Optical Instruments and Technology.

[277]  Zhi-Quan Luo,et al.  Online clustering algorithms for radar emitter classification , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[278]  Yasheng Zhang,et al.  Multiple Heterogeneous P-DCNNs Ensemble With Stacking Algorithm: A Novel Recognition Method of Space Target ISAR Images Under the Condition of Small Sample Set , 2020, IEEE Access.

[279]  Nicolas Brodu.  Low-rankness transfer for denoising Sentinel-1 SAR images , 2018, 2018 9th International Symposium on Signal, Image, Video and Communications (ISIVC).

[280]  Xiaoqing Xu,et al.  Moving Target Indication Using Deep Convolutional Neural Network , 2018, IEEE Access.

[281]  Geoffrey Zweig,et al.  Recent advances in deep learning for speech research at Microsoft , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[282]  Simon Wagner,et al.  A deep learning SAR ATR system using regularization and prioritized classes , 2017, 2017 IEEE Radar Conference (RadarConf).

[283]  Alberto de la Fuente,et al.  Jammer Classification in GNSS Bands Via Machine Learning Algorithms , 2019, Sensors.

[284]  Shuiping Gou,et al.  Fast Classification for Large Polarimetric SAR Data Based on Refined Spatial-Anchor Graph , 2017, IEEE Geoscience and Remote Sensing Letters.

[285]  Sameer Singh,et al.  A Framework of Rapid Regional Tsunami Damage Recognition From Post-event TerraSAR-X Imagery Using Deep Neural Networks , 2018, IEEE Geoscience and Remote Sensing Letters.

[286]  Hao Su,et al.  Radar Signal Recognition Based on Squeeze-and-Excitation Networks , 2019, 2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP).

[287]  Yuan Xie,et al.  Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey , 2020, Proceedings of the IEEE.

[288]  Sergey Ioffe,et al.  Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning , 2016, AAAI.

[289]  Visa Koivunen,et al.  Radar Waveform Recognition Using Fourier-Based Synchrosqueezing Transform and CNN , 2019, 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

[290]  Karen O. Egiazarian,et al.  Image denoising with block-matching and 3D filtering , 2006, Electronic Imaging.

[291]  Lan Du,et al.  SAR Target Detection Based on SSD With Data Augmentation and Transfer Learning , 2019, IEEE Geoscience and Remote Sensing Letters.

[292]  Ross B. Girshick,et al.  Fast R-CNN , 2015, 1504.08083.

[293]  Jun Zhang,et al.  Classification via weighted kernel CNN: application to SAR target recognition , 2018, International Journal of Remote Sensing.

[294]  Santanu Chaudhury,et al.  Despeckling CNN with Ensembles of Classical Outputs , 2018, 2018 24th International Conference on Pattern Recognition (ICPR).

[295]  Dhireesha Kudithipudi,et al.  Semi-random deep neural networks for near real-time target classification , 2019, Defense + Commercial Sensing.

[296]  Jianyu Yang,et al.  Target recognition for SAR images based on heterogeneous CNN ensemble , 2018, 2018 IEEE Radar Conference (RadarConf18).

[297]  David Mascharka,et al.  Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[298]  Chin-Teng Lin,et al.  A vector neural network for emitter identification , 2002 .

[299]  Hongliang Zhu,et al.  SAR Target Classification Based on Radar Image Luminance Analysis by Deep Learning , 2020, IEEE Sensors Letters.

[300]  Jiachun An,et al.  High-Performance SAR Automatic Target Recognition Under Limited Data Condition Based on a Deep Feature Fusion Network , 2019, IEEE Access.

[301]  Xunzhang Gao,et al.  Resolution enhancement for inverse synthetic aperture radar images using a deep residual network , 2019, Microwave and Optical Technology Letters.

[302]  Zhutian Yang,et al.  A study on radar emitter recognition based on spds neural network , 2011 .

[303]  Zongxu Pan,et al.  Transfer Learning with Deep Convolutional Neural Network for SAR Target Classification with Limited Labeled Data , 2017, Remote. Sens..

[304]  Victor S. Frost,et al.  A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[305]  Rama Chellappa,et al.  Separated Component-Based Restoration of Speckled SAR Images , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[306]  Zhiwen Zhou,et al.  A Novel Algorithm of Radar Emitter Identification Based Convolutional Neural Network and Random Vector Functional-Link , 2019, ICNC-FSKD.

[307]  Fang Liu,et al.  Complex Contourlet-CNN for polarimetric SAR image classification , 2020, Pattern Recognit..

[308]  Quanming Yao,et al.  Few-shot Learning: A Survey , 2019, ArXiv.

[309]  Yafeng Wang,et al.  Recognition of radar active‐jamming through convolutional neural networks , 2019, The Journal of Engineering.

[310]  Jie Gu,et al.  A Deinterleaving Method for Mixed Pulse Signals in Complex Electromagnetic Environment , 2019, 2019 International Conference on Control, Automation and Information Sciences (ICCAIS).

[311]  Jian Wang,et al.  A Maritime Target Detector Based on CNN and Embedded Device for GF-3 Images , 2019, 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR).

[312]  拓海 杉山,et al.  “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告 , 2017 .

[313]  Dong Yu,et al.  Deep Learning and Its Applications to Signal and Information Processing [Exploratory DSP] , 2011, IEEE Signal Processing Magazine.

[314]  Yu Zhou,et al.  Polarimetric SAR Image Classification Using Deep Convolutional Neural Networks , 2016, IEEE Geoscience and Remote Sensing Letters.

[315]  Wang Gongming,et al.  Radar Emitter Sorting and Recognition Based on Time-frequency Image Union Feature , 2019, 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP).

[316]  Jin Zhao,et al.  Discriminant deep belief network for high-resolution SAR image classification , 2017, Pattern Recognit..

[317]  Woo-Jin Song,et al.  Speckle-Noise-Invariant Convolutional Neural Network for SAR Target Recognition , 2019, IEEE Geoscience and Remote Sensing Letters.

[318]  Jie Chen,et al.  Explainable Neural Networks based on Additive Index Models , 2018, ArXiv.

[319]  Yi Zhang,et al.  Spectrum Monitoring for Radar Bands Using Deep Convolutional Neural Networks , 2017, GLOBECOM 2017 - 2017 IEEE Global Communications Conference.

[320]  Chao Wang,et al.  A SAR Dataset of Ship Detection for Deep Learning under Complex Backgrounds , 2019, Remote. Sens..

[321]  G Nagendra Rao,et al.  Trends in Electronic Warfare , 2003 .

[322]  Davide Cozzolino,et al.  Guided Patchwise Nonlocal SAR Despeckling , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[323]  Xiangdong Chen,et al.  A Robust Polarmetric SAR Terrain Classification Based on Sparse Deep Autoencoder Model Combined With Wavelet Kernel-Based Classifier , 2020, IEEE Access.

[324]  Lawrence V. Snyder,et al.  Reinforcement Learning for Solving the Vehicle Routing Problem , 2018, NeurIPS.

[325]  Baiyuan Ding,et al.  An Efficient and Robust Framework for SAR Target Recognition by Hierarchically Fusing Global and Local Features , 2018, IEEE Transactions on Image Processing.

[326]  Emile Ndikumana,et al.  Deep Recurrent Neural Network for Agricultural Classification using multitemporal SAR Sentinel-1 for Camargue, France , 2018, Remote. Sens..

[327]  Jie Geng,et al.  Classification of fusing SAR and multispectral image via deep bimodal autoencoders , 2017, 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[328]  Le Song,et al.  2 Common Formulation for Greedy Algorithms on Graphs , 2018 .

[329]  Bin Yang,et al.  A Study of Human Body Characteristics Effect on Micro-Doppler-Based Person Identification using Deep Learning , 2018, ArXiv.

[330]  Zheng Liu,et al.  Noise-robust HRRP target recognition method via sparse-low-rank representation , 2017 .

[331]  Majid Altamimi,et al.  An Investigation of LPI Radar Waveforms Classification in RoF Channels , 2019, IEEE Access.

[332]  Tong Liu,et al.  Convolutional Neural Network and Guided Filtering for SAR Image Denoising , 2019, Remote. Sens..

[333]  Zhuo Yue,et al.  Target recognition in synthetic aperture radar image based on PCANet , 2019 .

[334]  Ievgen M. Gorovyi,et al.  Comparative analysis of convolutional neural networks and support vector machines for automatic target recognition , 2017, 2017 IEEE Microwaves, Radar and Remote Sensing Symposium (MRRS).

[335]  Cynthia Rudin,et al.  Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model , 2015, ArXiv.

[337]  Asoke K. Nandi,et al.  Automatic digital modulation recognition using artificial neural network and genetic algorithm , 2004, Signal Process..

[338]  J. R. Guerci,et al.  Cognitive radar: A knowledge-aided fully adaptive approach , 2010, 2010 IEEE Radar Conference.

[339]  Jie Geng,et al.  Deep Supervised and Contractive Neural Network for SAR Image Classification , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[340]  Amina Adadi,et al.  Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI) , 2018, IEEE Access.

[341]  Jun Liu,et al.  SAR ATR by Decision Fusion of Multiple Random Convolution Features , 2019, 2019 22th International Conference on Information Fusion (FUSION).

[342]  Alin Achim,et al.  SAR image denoising via Bayesian wavelet shrinkage based on heavy-tailed modeling , 2003, IEEE Trans. Geosci. Remote. Sens..

[343]  Shuiping Gou,et al.  Polarimetric SAR Feature Extraction With Neighborhood Preservation-Based Deep Learning , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[344]  Shuanghui Zhang,et al.  Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine , 2018, Sensors.

[345]  Tianyao Huang,et al.  Decentralized Automotive Radar Spectrum Allocation to Avoid Mutual Interference Using Reinforcement Learning , 2020 .

[346]  Weidong Jin,et al.  Radar Signal Recognition Based on TPOT and LIME , 2018, 2018 37th Chinese Control Conference (CCC).

[347]  Jian Yang,et al.  Automatic modulation recognition of compound signals using a deep multi-label classifier: A case study with radar jamming signals , 2020, Signal Process..

[348]  Yan Liang,et al.  SAR Target Recognition Based on Transfer Learning and Data Augmentation with LSGANs , 2019, 2019 Chinese Automation Congress (CAC).

[349]  Xiaoling Zhang,et al.  High-Speed Ship Detection in SAR Images Based on a Grid Convolutional Neural Network , 2019, Remote. Sens..

[350]  Tianqi Chen,et al.  XGBoost: A Scalable Tree Boosting System , 2016, KDD.

[351]  Erfu Yang,et al.  Combining Deep Convolutional Neural Network and SVM to SAR Image Target Recognition , 2017, 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData).

[352]  Hai-Tan Tran,et al.  Signal Separation of Helicopter Radar Returns Using Wavelet-Based Sparse Signal Optimisation , 2016 .

[353]  Rob Fergus,et al.  Visualizing and Understanding Convolutional Networks , 2013, ECCV.

[354]  Erik Cambria,et al.  Recent Trends in Deep Learning Based Natural Language Processing , 2017, IEEE Comput. Intell. Mag..

[355]  Stephen Grossberg,et al.  A What-and-Where fusion neural network for recognition and tracking of multiple radar emitters , 2001, Neural Networks.

[356]  David A. Clausi,et al.  Improved texture recognition of SAR sea ice imagery by data fusion of MRF features with traditional methods , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[357]  Carmine Clemente,et al.  Micro-Doppler based target classification using multi-feature integration , 2013 .

[358]  Alfred Stein,et al.  PolSARNet: A Deep Fully Convolutional Network for Polarimetric SAR Image Classification , 2019, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[359]  Xindong Wu,et al.  Object Detection With Deep Learning: A Review , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[360]  Xinwei Zheng,et al.  Radar emitter classification for large data set based on weighted-xgboost , 2017 .

[361]  Andrew Y. Ng,et al.  Zero-Shot Learning Through Cross-Modal Transfer , 2013, NIPS.

[362]  Chuan He,et al.  A Deep Neural Network Based on an Attention Mechanism for SAR Ship Detection in Multiscale and Complex Scenarios , 2019, IEEE Access.

[363]  Zongjie Cao,et al.  Scale-Transferrable Pyramid Network for Multi-Scale Ship Detection in Sar Images , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[364]  Gong Zhang,et al.  Multiscale kernel sparse coding-based classifier for HRRP radar target recognition , 2016 .

[365]  Samuel Foucher,et al.  Deep speckle noise filtering , 2017, 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[366]  Di He,et al.  Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View , 2019, ArXiv.

[367]  Moeness Amin,et al.  Fall Detection Using Deep Learning in Range-Doppler Radars , 2018, IEEE Transactions on Aerospace and Electronic Systems.

[368]  Geoffrey E. Hinton,et al.  Dynamic Routing Between Capsules , 2017, NIPS.

[369]  Xinwu Li,et al.  Unsupervised classification of polarimetric SAR images using deep embedding network , 2017, 2017 SAR in Big Data Era: Models, Methods and Applications (BIGSARDATA).

[370]  Ronghua Shang,et al.  Complex-Valued Convolutional Autoencoder and Spatial Pixel-Squares Refinement for Polarimetric SAR Image Classification , 2019, Remote. Sens..

[371]  Murray Shanahan,et al.  An Explicitly Relational Neural Network Architecture , 2019, ICML.

[372]  Van Long Do,et al.  A Parallel Neural Network-based Scheme for Radar Emitter Recognition , 2020, 2020 14th International Conference on Ubiquitous Information Management and Communication (IMCOM).

[373]  Guigang Zhang,et al.  Deep Learning , 2016, Int. J. Semantic Comput..

[374]  Biao Hou,et al.  Patch-Sorted Deep Feature Learning for High Resolution SAR Image Classification , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[375]  Jungwoo Lee,et al.  A Deep Learning Approach for Automotive Radar Interference Mitigation , 2018, 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall).

[376]  Xinwu Li,et al.  High-Resolution PolSAR Scene Classification With Pretrained Deep Convnets and Manifold Polarimetric Parameters , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[377]  Luc Van Gool,et al.  The Pascal Visual Object Classes Challenge: A Retrospective , 2014, International Journal of Computer Vision.

[378]  Dong Yu,et al.  Deep Learning and Its Applications to Signal and Information Processing , 2011 .

[379]  Dave Tahmoush,et al.  Review of micro-Doppler signatures , 2015 .

[380]  Fangqi Zhu,et al.  Radar HRRP Target Recognition Based on Concatenated Deep Neural Networks , 2018, IEEE Access.

[381]  Ming Zhang,et al.  Convolutional Neural Networks for Automatic Cognitive Radio Waveform Recognition , 2017, IEEE Access.

[382]  Soumith Chintala,et al.  Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , 2015, ICLR.

[383]  Ya Li,et al.  Adversarial attacks on deep-learning-based SAR image target recognition , 2020, J. Netw. Comput. Appl..

[384]  Quanshi Zhang,et al.  Interpretable Convolutional Neural Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[385]  Bassem Mahafza,et al.  Radar Systems Analysis and Design Using MATLAB , 2000 .

[386]  Wenqiang Zhang,et al.  Radar Signal Recognition Based on FCBF and AdaBoost Algorithm , 2018, 2018 37th Chinese Control Conference (CCC).

[387]  Qiang Huang,et al.  Underwater target classification using wavelet packets and neural networks , 2000, IEEE Trans. Neural Networks Learn. Syst..

[388]  N. V. S. N. Sarma,et al.  Identification of LPI Radar signals by higher order spectra and neural network techniques , 2008, 2008 International Conference on Electronic Design.

[389]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[390]  Francesco Fioranelli,et al.  Multistatic micro-Doppler radar feature extraction for classification of unloaded/loaded micro-drones , 2017 .

[391]  Ross B. Girshick,et al.  Focal Loss for Dense Object Detection , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[392]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[393]  Shuang Wang,et al.  Dual-Channel Convolutional Neural Network for Polarimetric SAR Images Classification , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[394]  Aaron C. Courville,et al.  Improved Training of Wasserstein GANs , 2017, NIPS.

[395]  Yoshua Bengio,et al.  Gradient-based learning applied to document recognition , 1998, Proc. IEEE.

[396]  Moeness G. Amin,et al.  DNN Transfer Learning From Diversified Micro-Doppler for Motion Classification , 2018, IEEE Transactions on Aerospace and Electronic Systems.

[397]  You He,et al.  Study on radar emitter recognition signal based on rough sets and RBF neural network , 2009, International Conference on Machine Learning and Computing.

[398]  Yoshua Bengio,et al.  Deep Learning of Representations: Looking Forward , 2013, SLSP.

[399]  Xiaoli Ding,et al.  SAR image despeckling with a multilayer perceptron neural network , 2019, Int. J. Digit. Earth.

[400]  Xi Chen,et al.  A modified method for the estimation of SAR target aspect angle based on MRF segmentation , 2009, International Symposium on Multispectral Image Processing and Pattern Recognition.

[401]  Gangyao Kuang,et al.  An Adaptive and Fast CFAR Algorithm Based on Automatic Censoring for Target Detection in High-Resolution SAR Images , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[402]  Maoguo Gong,et al.  Sparse Manifold-Regularized Neural Networks for Polarimetric SAR Terrain Classification , 2020, IEEE Transactions on Neural Networks and Learning Systems.

[403]  Wenhui,et al.  AIR-SARShip-1.0: High-resolution SAR Ship Detection Dataset , 2020 .

[404]  Xueru Bai,et al.  Spatial–Temporal Ensemble Convolution for Sequence SAR Target Classification , 2021, IEEE Transactions on Geoscience and Remote Sensing.

[405]  Wei Tian,et al.  Radar Emitter Recognition Based on the Energy Cumulant of Short Time Fourier Transform and Reinforced Deep Belief Network , 2018, Sensors.

[406]  Nedyalko Petrov,et al.  Supervised radar signal classification , 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

[407]  Erfu Yang,et al.  A New Algorithm for SAR Image Target Recognition Based on an Improved Deep Convolutional Neural Network , 2018, Cognitive Computation.

[408]  Yoshua Bengio,et al.  Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon , 2018, Eur. J. Oper. Res..

[409]  Ali Farhadi,et al.  YOLOv3: An Incremental Improvement , 2018, ArXiv.

[410]  Wen Yang,et al.  SAR Image Despeckling Using Pre-trained Convolutional Neural Network Models , 2019, 2019 Joint Urban Remote Sensing Event (JURSE).

[411]  Wei Jing,et al.  Radar emitter recognition based on deep learning architecture , 2016, 2016 CIE International Conference on Radar (RADAR).

[412]  Youngwook Kim,et al.  Human Detection and Activity Classification Based on Micro-Doppler Signatures Using Deep Convolutional Neural Networks , 2016, IEEE Geoscience and Remote Sensing Letters.

[413]  Lei Zhao,et al.  Convolutional Highway Unit Network for Large-Scale Classification with GF-3 Dual-Pol Sar Data , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[414]  Fei Gao,et al.  A novel biologically-inspired target detection method based on saliency analysis for synthetic aperture radar (SAR) imagery , 2020, Neurocomputing.

[415]  Ali Mohammad-Djafari,et al.  Radar emitters classification and clustering with a scale mixture of normal distributions , 2018, 2018 IEEE Radar Conference (RadarConf18).

[416]  Gaoming Huang,et al.  Radar emitter recognition based on the short time fourier transform and convolutional neural networks , 2017, 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI).

[417]  Wei-Yin Loh,et al.  Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..

[418]  Chang Min Jeong,et al.  Deep belief networks based radar signal classification system , 2018 .

[419]  Huanxin Zou,et al.  Ship Classification in TerraSAR-X Images With Feature Space Based Sparse Representation , 2013, IEEE Geoscience and Remote Sensing Letters.

[420]  Ross B. Girshick,et al.  Mask R-CNN , 2017, 1703.06870.

[421]  Le Zhao,et al.  Noise Robust Radar HRRP Target Recognition Based on Scatterer Matching Algorithm , 2016, IEEE Sensors Journal.

[422]  Meng Li,et al.  Research on Online Learning of Radar Emitter Recognition Based on Hull Vector , 2017, 2017 IEEE Second International Conference on Data Science in Cyberspace (DSC).

[423]  Thomas Brox,et al.  U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.

[424]  Adnan Orduyilmaz,et al.  A Complete Framework of Radar Pulse Detection and Modulation Classification for Cognitive EW , 2019, 2019 27th European Signal Processing Conference (EUSIPCO).

[425]  S. Haykin,et al.  Cognitive radar: a way of the future , 2006, IEEE Signal Processing Magazine.

[426]  Ting Jiang,et al.  Data Augmentation with Gabor Filter in Deep Convolutional Neural Networks for Sar Target Recognition , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[427]  Khilan Ravani,et al.  A Practical Approach for SAR Image Despeckling Using Deep Learning , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[428]  Geoffrey E. Hinton,et al.  Acoustic Modeling Using Deep Belief Networks , 2012, IEEE Transactions on Audio, Speech, and Language Processing.

[429]  Chuang Gan,et al.  The Neuro-Symbolic Concept Learner: Interpreting Scenes Words and Sentences from Natural Supervision , 2019, ICLR.

[430]  Yanlong Zhao,et al.  Jamming signals classification using convolutional neural network , 2017, 2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT).

[431]  Tommi S. Jaakkola,et al.  Towards Robust Interpretability with Self-Explaining Neural Networks , 2018, NeurIPS.

[432]  Bo Chen,et al.  SAR image target recognition via deep Bayesian generative network , 2017, 2017 International Workshop on Remote Sensing with Intelligent Processing (RSIP).

[433]  Sebastian Ruder,et al.  An Overview of Multi-Task Learning in Deep Neural Networks , 2017, ArXiv.

[434]  Xueru Bai,et al.  Sequence SAR Image Classification Based on Bidirectional Convolution-Recurrent Network , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[435]  Francisco López-Ferreras,et al.  Study of Two Error Functions to Approximate the Neyman–Pearson Detector Using Supervised Learning Machines , 2009, IEEE Transactions on Signal Processing.

[436]  Tomas E. Ward,et al.  Generative Adversarial Networks: A Survey and Taxonomy , 2019, ArXiv.

[437]  Jing Liu,et al.  Radio ground-to-air interference signals recognition based on support vector machine , 2015, 2015 IEEE International Conference on Digital Signal Processing (DSP).

[438]  Irene Cheng,et al.  CNN-Based InSAR Denoising and Coherence Metric , 2018, 2018 IEEE SENSORS.

[439]  Dan Zhang,et al.  Stacked Sparse Autoencoder in PolSAR Data Classification Using Local Spatial Information , 2016, IEEE Geoscience and Remote Sensing Letters.

[440]  Bram van Ginneken,et al.  A survey on deep learning in medical image analysis , 2017, Medical Image Anal..

[441]  Zhuo Sun,et al.  Interference Detection and Recognition Based on Signal Reconstruction Using Recurrent Neural Network , 2019, 2019 IEEE Globecom Workshops (GC Wkshps).

[442]  Qaisar Abbas,et al.  Video scene analysis: an overview and challenges on deep learning algorithms , 2017, Multimedia Tools and Applications.

[443]  Ming Diao,et al.  Deep Reinforcement Learning for Target Searching in Cognitive Electronic Warfare , 2019, IEEE Access.

[444]  Jiangtao Huangfu,et al.  Doppler-Radar Based Hand Gesture Recognition System Using Convolutional Neural Networks , 2017, CSPS.

[445]  Guoquan Huang,et al.  A novel group squeeze excitation sparsely connected convolutional networks for SAR target classification , 2019, International Journal of Remote Sensing.

[446]  Hong-Yuan Mark Liao,et al.  YOLOv4: Optimal Speed and Accuracy of Object Detection , 2020, ArXiv.

[447]  Ming Yang,et al.  A Survey of Multi-View Representation Learning , 2019, IEEE Transactions on Knowledge and Data Engineering.

[448]  Weifeng Liu,et al.  Radar Emitter Identification Based on Deep Convolutional Neural Network , 2018, 2018 International Conference on Control, Automation and Information Sciences (ICCAIS).

[449]  Zhaolei Liu,et al.  Radar Signal Waveform Recognition Based on Convolutional Denoising Autoencoder , 2018, CSPS.

[450]  이상헌,et al.  Deep Belief Networks , 2010, Encyclopedia of Machine Learning.

[451]  Li Wang,et al.  Deep Learning Algorithms with Applications to Video Analytics for A Smart City: A Survey , 2015, ArXiv.

[452]  Yiran Li,et al.  Potential Active Shooter Detection Based on Radar Micro-Doppler and Range-Doppler Analysis Using Artificial Neural Network , 2019, IEEE Sensors Journal.

[453]  Huanxin Zou,et al.  Deep Convolutional Highway Unit Network for SAR Target Classification With Limited Labeled Training Data , 2017, IEEE Geoscience and Remote Sensing Letters.

[454]  Sergey Ioffe,et al.  Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[455]  Huan Wang,et al.  Low Probability of Intercept Radar Waveform Recognition Based on Dictionary Leaming , 2018, 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP).

[456]  Bohdan M. Pavlyshenko,et al.  Linear, machine learning and probabilistic approaches for time series analysis , 2016, 2016 IEEE First International Conference on Data Stream Mining & Processing (DSMP).

[457]  Xiang Wang,et al.  Specific Emitter Identification Based on Nonlinear Dynamical Characteristics , 2016, Canadian Journal of Electrical and Computer Engineering.

[458]  Xiangyu Zhang,et al.  ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design , 2018, ECCV.

[459]  Thomas G. Dietterich.  Multiple Classifier Systems , 2000, Lecture Notes in Computer Science.

[460]  Yun Fu,et al.  Zero-Shot Learning , 2019 .

[461]  Léon Bottou,et al.  Wasserstein GAN , 2017, ArXiv.

[462]  Kiran George,et al.  Deinterleaving Radar Pulse Train Using Neural Networks , 2019, 2019 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC).

[463]  Xiang Wang,et al.  Toward Convolutional Neural Networks on Pulse Repetition Interval Modulation Recognition , 2018, IEEE Communications Letters.

[464]  You He,et al.  Radar Target Recognition Based on Feature Pyramid Fusion Lightweight CNN , 2019, IEEE Access.

[465]  Radford M. Neal.  Pattern Recognition and Machine Learning , 2007, Technometrics.

[466]  Yurong Liu,et al.  A survey of deep neural network architectures and their applications , 2017, Neurocomputing.

[467]  Wilfried Philips,et al.  A Deep-Neural-Network-Based Hybrid Method for Semi-Supervised Classification of Polarimetric SAR Data , 2019, 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR).

[468]  Mou Wang,et al.  Intra‐pulse modulation radar signal recognition based on CLDN network , 2020, IET Radar, Sonar & Navigation.

[469]  Qi Li,et al.  Multiscale Ship Detection Based On Dense Attention Pyramid Network in Sar Images , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[470]  Xueru Bai,et al.  2D-Temporal Convolution for Target Recognition of SAR Sequence Image , 2019, 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR).

[471]  S. Z. Gürbüz,et al.  Deep learning of micro-Doppler features for aided and unaided gait recognition , 2017, 2017 IEEE Radar Conference (RadarConf).

[472]  Jürgen Schmidhuber,et al.  Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction , 2011, ICANN.

[473]  Kobi Cohen,et al.  Deep Multi-User Reinforcement Learning for Distributed Dynamic Spectrum Access , 2017, IEEE Transactions on Wireless Communications.

[474]  Li Wang,et al.  Reinforcement learning-based waveform optimization for MIMO multi-target detection , 2018, 2018 52nd Asilomar Conference on Signals, Systems, and Computers.

[475]  Lidong Zhu,et al.  An Efficient Way for Satellite Interference Signal Recognition Via Incremental Learning , 2019, 2019 International Symposium on Networks, Computers and Communications (ISNCC).

[476]  Jan Matuszewski.  The Specific Radar Signature in Electronic Recognition System , 2013 .

[477]  Mihai Datcu,et al.  Contrastive-Regulated CNN in the Complex Domain: A Method to Learn Physical Scattering Signatures From Flexible PolSAR Images , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[478]  Chuan He,et al.  MSARN: A Deep Neural Network Based on an Adaptive Recalibration Mechanism for Multiscale and Arbitrary-Oriented SAR Ship Detection , 2019, IEEE Access.

[479]  Quoc V. Le,et al.  Searching for MobileNetV3 , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[480]  Mingsheng Liao,et al.  Nonlinear Manifold Learning Integrated with Fully Convolutional Networks for PolSAR Image Classification , 2020, Remote. Sens..

[481]  Wei Li,et al.  Multi-Aspect-Aware Bidirectional LSTM Networks for Synthetic Aperture Radar Target Recognition , 2017, IEEE Access.

[482]  Dumitru Erhan,et al.  Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[483]  Haichao Wang,et al.  Spatial Anti-Jamming Scheme for Internet of Satellites Based on the Deep Reinforcement Learning and Stackelberg Game , 2020, IEEE Transactions on Vehicular Technology.

[484]  Li Hui,et al.  Modified PPCA Methods for Radar HRRP Robust Recognition , 2016 .

[485]  Luisa Verdoliva,et al.  A Nonlocal SAR Image Denoising Algorithm Based on LLMMSE Wavelet Shrinkage , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[486]  Yuri P. Grishin,et al.  Radar signal recognition based on time-frequency representations and multidimensional probability density function estimator , 2015, 2015 Signal Processing Symposium (SPSympo).

[487]  Yue Zhang,et al.  High Resolution SAR Image Classification with Deeper Convolutional Neural Network , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[488]  Jianyu Yang,et al.  Multi-view SAR ATR based on networks ensemble and graph search , 2018, 2018 IEEE Radar Conference (RadarConf18).

[489]  Jianyuan Guo,et al.  GhostNet: More Features From Cheap Operations , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[490]  Bin Tang,et al.  Automatic modulation classification of radar signals using the generalised time-frequency representation of Zhao, Atlas and Marks , 2011 .

[491]  Haipeng Wang,et al.  Application of deep-learning algorithms to MSTAR data , 2015, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[492]  Tao Wang,et al.  Two-Stage Multi-Task Representation Learning for Synthetic Aperture Radar (SAR) Target Images Classification , 2017, Sensors.

[493]  Giampaolo Ferraioli,et al.  A Novel Cost Function for Despeckling using Convolutional Neural Networks , 2019, 2019 Joint Urban Remote Sensing Event (JURSE).

[494]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[495]  Li Liu,et al.  Online Non-Cooperative Radar Emitter Classification From Evolving and Imbalanced Pulse Streams , 2020, IEEE Sensors Journal.

[496]  Bingliang Hu,et al.  Attention Mask R-CNN for Ship Detection and Segmentation From Remote Sensing Images , 2020, IEEE Access.

[497]  Orhan Arikan,et al.  Deep learning in electronic warfare systems: Automatic intra-pulse modulation recognition , 2018, 2018 26th Signal Processing and Communications Applications Conference (SIU).

[498]  Chi-Keung Tang,et al.  Attribute-Guided Face Generation Using Conditional CycleGAN , 2017, ECCV.

[499]  Qi Li,et al.  Dense Attention Pyramid Networks for Multi-Scale Ship Detection in SAR Images , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[500]  Huanxin Zou,et al.  Synthetic Aperture Radar Target Recognition with Feature Fusion Based on a Stacked Autoencoder , 2017, Sensors.

[501]  Shuanghui Zhang,et al.  Fast Sparse Aperture ISAR Autofocusing and Imaging via ADMM Based Sparse Bayesian Learning , 2019, IEEE Transactions on Image Processing.

[502]  Yangyang Li,et al.  SAR Targets Classification Based on Deep Memory Convolution Neural Networks and Transfer Parameters , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[503]  Yonina C. Eldar,et al.  Cognitive radar antenna selection via deep learning , 2018, IET Radar, Sonar & Navigation.

[504]  Ashutosh Vyas,et al.  Deep Learning for Natural Language Processing , 2016 .

[505]  Bolei Zhou,et al.  Places: A 10 Million Image Database for Scene Recognition , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[506]  Jason M. Daida,et al.  Genetic Programming for Automatic Target Classification and Recognition , 1998, Evolutionary Programming.

[507]  Behrooz Kamgar-Parsi,et al.  Automatic Data Sorting Using Neural Network Techniques. , 1996 .

[508]  Luciano Alparone,et al.  A Tutorial on Speckle Reduction in Synthetic Aperture Radar Images , 2013, IEEE Geoscience and Remote Sensing Magazine.

[509]  Hongwei Liu,et al.  A Review of the Autoencoder and Its Variants: A Comparative Perspective from Target Recognition in Synthetic-Aperture Radar Images , 2018, IEEE Geoscience and Remote Sensing Magazine.

[510]  Yang Ruliang,et al.  SAR Target Recognition Based on MRF and Gabor Wavelet Feature Extraction , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.

[511]  Woo-Jin Song,et al.  Multistage Fusion With Dissimilarity Regularization for SAR/IR Target Recognition , 2019, IEEE Access.

[512]  Wasim Huleihel,et al.  Optimal Adaptive Waveform Design for Cognitive MIMO Radar , 2013, IEEE Transactions on Signal Processing.

[513]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[514]  Hongwei Liu,et al.  SAR Automatic Target Recognition Based on Euclidean Distance Restricted Autoencoder , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[515]  Xueru Bai,et al.  Deceptive jamming for tracked vehicles based on micro-Doppler signatures , 2018 .

[516]  Andriy Mnih,et al.  Disentangling by Factorising , 2018, ICML.

[517]  Jun Shi,et al.  Automatic Modulation Recognition for Radar Signals via Multi-Branch ACSE Networks , 2020, IEEE Access.

[518]  Andreas Kamilaris,et al.  Deep learning in agriculture: A survey , 2018, Comput. Electron. Agric..

[519]  Chen Wang,et al.  Precise and Robust Ship Detection for High-Resolution SAR Imagery Based on HR-SDNet , 2020, Remote. Sens..

[520]  André Bourdoux,et al.  Micro-Doppler feature extraction using convolutional auto-encoders for low latency target classification , 2017, 2017 IEEE Radar Conference (RadarConf).

[521]  Marie̅tte Conning,et al.  Analysis of measured radar data for Specific Emitter Identification , 2010, 2010 IEEE Radar Conference.

[522]  Weidong Jin,et al.  Radar Signal Automatic Classification Based on PCA , 2009, 2009 WRI Global Congress on Intelligent Systems.

[523]  Qun Zhao,et al.  Support vector machines for SAR automatic target recognition , 2001 .

[524]  Erfu Yang,et al.  A Deep Convolutional Generative Adversarial Networks (DCGANs)-Based Semi-Supervised Method for Object Recognition in Synthetic Aperture Radar (SAR) Images , 2018, Remote. Sens..

[525]  Yiran Chen,et al.  Advanced Techniques for Robust SAR ATR: Mitigating Noise and Phase Errors , 2020, 2020 IEEE International Radar Conference (RADAR).

[526]  Munchurl Kim,et al.  SPAM-Net: A CNN-Based SAR Target Recognition Network With Pose Angle Marginalization Learning , 2021, IEEE Transactions on Circuits and Systems for Video Technology.

[527]  Qiang Yang,et al.  A Concurrent and Hierarchy Target Learning Architecture for Classification in SAR Application , 2018, Sensors.

[528]  Yoshua Bengio,et al.  The Consciousness Prior , 2017, ArXiv.

[529]  Hao Su,et al.  HRSID: A High-Resolution SAR Images Dataset for Ship Detection and Instance Segmentation , 2020, IEEE Access.

[530]  Ming Zhang,et al.  Neural Networks for Radar Waveform Recognition , 2017, Symmetry.

[531]  Jingchao Li,et al.  Radar signal recognition algorithm based on entropy theory , 2014, The 2014 2nd International Conference on Systems and Informatics (ICSAI 2014).

[532]  Jinsheng Xie.  Robust intra-pulse modulation recognition via sparse representation , 2016, 2016 CIE International Conference on Radar (RADAR).

[533]  Cai Jinyan,et al.  Classification of radar signals using time-frequency transforms and fuzzy clustering , 2010, 2010 International Conference on Microwave and Millimeter Wave Technology.

[534]  Davide Cozzolino,et al.  SAR image despeckling through convolutional neural networks , 2017, 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[535]  Xiaoqiang Lu,et al.  Remote Sensing Image Scene Classification: Benchmark and State of the Art , 2017, Proceedings of the IEEE.

[536]  Yoshua Bengio,et al.  Light Gated Recurrent Units for Speech Recognition , 2018, IEEE Transactions on Emerging Topics in Computational Intelligence.

[537]  Qian Song,et al.  Zero-Shot Learning of SAR Target Feature Space With Deep Generative Neural Networks , 2017, IEEE Geoscience and Remote Sensing Letters.

[538]  Si-Wei Chen,et al.  Polarimetric SAR Targets Detection and Classification with Deep Convolutional Neural Network , 2018, 2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama).

[539]  Hui Ma,et al.  MF-SarNet: Effective CNN with data augmentation for SAR automatic target recognition , 2019 .

[540]  Abdelmalek Toumi,et al.  Target classification using convolutional deep learning and auto-encoder models , 2018, 2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP).

[541]  Mou Wang,et al.  PRI Modulation Recognition Based on Squeeze-and-Excitation Networks , 2020, IEEE Communications Letters.

[542]  Odysseas Kechagias-Stamatis,et al.  Fusing Deep Learning and Sparse Coding for SAR ATR , 2019, IEEE Transactions on Aerospace and Electronic Systems.

[543]  Scott Evans,et al.  Causal Inference via Conditional Kolmogorov Complexity using MDL Binning , 2019, ArXiv.

[544]  Cheong Hee Park,et al.  Jamming Prediction for Radar Signals Using Machine Learning Methods , 2020, Secur. Commun. Networks.

[545]  Lingjia Gu,et al.  Crop Classification based on Deep Learning in Northeast China using SAR and Optical Imagery , 2019, 2019 SAR in Big Data Era (BIGSARDATA).

[546]  Shuiping Gou,et al.  Full polarization SAR image classification using deep learning with shallow feature , 2017, 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[547]  Bo Du,et al.  Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art , 2016, IEEE Geoscience and Remote Sensing Magazine.

[548]  Lam H. Nguyen,et al.  RFI-radar signal separation via simultaneous low-rank and sparse recovery , 2016, 2016 IEEE Radar Conference (RadarConf).

[549]  Kristin L. Sainani,et al.  Logistic Regression , 2014, PM & R : the journal of injury, function, and rehabilitation.

[550]  Lamei Zhang,et al.  Densely Connected Convolutional Neural Network Based Polarimetric SAR Image Classification , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[551]  Yonina C. Eldar,et al.  Deep Learning in Ultrasound Imaging , 2019, Proceedings of the IEEE.

[552]  Lei Guo,et al.  The Generalized Gamma-DBN for High-Resolution SAR Image Classification , 2018, Remote. Sens..

[553]  Xudong Jiang,et al.  Regularized 2-D complex-log spectral analysis and subspace reliability analysis of micro-Doppler signature for UAV detection , 2017, Pattern Recognit..

[554]  Simon Haykin,et al.  Cognitive Radar: Step Toward Bridging the Gap Between Neuroscience and Engineering , 2012, Proceedings of the IEEE.

[555]  Babafemi O. Odelowo,et al.  Identifying Agile Waveforms with Neural Networks , 2018, 2018 21st International Conference on Information Fusion (FUSION).

[556]  Vincenzo Piuri,et al.  TAI-SARNET: Deep Transferred Atrous-Inception CNN for Small Samples SAR ATR , 2020, Sensors.

[557]  Bin Xu,et al.  Target-Aware Recurrent Attentional Network for Radar HRRP Target Recognition , 2019, Signal Process..

[558]  Xingzhao Liu,et al.  Semi-Supervised SAR ATR via Multi-Discriminator Generative Adversarial Network , 2019, IEEE Sensors Journal.

[559]  Haipeng Wang,et al.  Target Classification Using the Deep Convolutional Networks for SAR Images , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[560]  Chengyan Zhang,et al.  Spotlight SAR Image Recognition Based on Dual-Channel Feature Map Convolutional Neural Network , 2019, 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP).

[561]  Marian Wnuk,et al.  Applying the relational modelling and knowledge based techniques to the emitter database design , 2002, 14th International Conference on Microwaves, Radar and Wireless Communications. MIKON - 2002. Conference Proceedings (IEEE Cat.No.02EX562).

[562]  Ryan J. Soldin,et al.  HySARNet: a hybrid machine learning approach to synthetic aperture radar automatic target recognition , 2019 .

[563]  Jason C. Dickinson,et al.  A comparison of machine learning methods for target recognition using ISAR imagery , 2011, Defense + Commercial Sensing.

[564]  Arumugam Nallanathan,et al.  Robust Radar Emitter Recognition Based on the Three-Dimensional Distribution Feature and Transfer Learning , 2016, Sensors.

[565]  Shengkun Zhu,et al.  Radar Signal Modulation Recognition Based on Deep Joint Learning , 2020, IEEE Access.

[566]  Wei Feng,et al.  Modeling Attention Flow on Graphs , 2018, ArXiv.

[567]  Philip S. Yu,et al.  Classification, Denoising, and Deinterleaving of Pulse Streams With Recurrent Neural Networks , 2019, IEEE Transactions on Aerospace and Electronic Systems.

[568]  Kaiming He,et al.  Feature Pyramid Networks for Object Detection , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[569]  Xin Yu,et al.  LPI Radar Waveform Recognition Based on Deep Convolutional Neural Network Transfer Learning , 2019, Symmetry.

[570]  Jie Huang,et al.  Radar Waveform Recognition based on Deep Residual Network , 2019, 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC).

[571]  Yoshua Bengio,et al.  Generative Adversarial Nets , 2014, NIPS.

[572]  Xiao Xiang Zhu,et al.  Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources , 2017, IEEE Geoscience and Remote Sensing Magazine.

[573]  Hong Zhang,et al.  Automatic Ship Detection Based on RetinaNet Using Multi-Resolution Gaofen-3 Imagery , 2019, Remote. Sens..

[574]  Xueliang Zhang,et al.  Deep learning in remote sensing applications: A meta-analysis and review , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.

[575]  Hongwei Liu,et al.  Radar HRRP target recognition with deep networks , 2017, Pattern Recognit..

[576]  Jan Matuszewski,et al.  The knowledge based approach for emitter identification , 1998, 12th International Conference on Microwaves and Radar. MIKON-98. Conference Proceedings (IEEE Cat. No.98EX195).

[577]  Hod Lipson,et al.  Understanding Neural Networks Through Deep Visualization , 2015, ArXiv.

[578]  Chen Wang,et al.  Complex Background SAR Target Recognition Based on Convolution Neural Network , 2019, 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR).

[579]  Yang Zhang,et al.  HRRP classification based on multi-scale fusion sparsity preserving projections , 2017 .

[580]  Ke Wang,et al.  Radar Emitter Recognition Based on SIFT Position and Scale Features , 2018, IEEE Transactions on Circuits and Systems II: Express Briefs.

[581]  Ljubisa Stankovic,et al.  Analysis of radar micro-Doppler signatures from experimental helicopter and human data , 2007 .

[582]  Augusto Aubry,et al.  Cumulants-based Radar Specific Emitter Identification , 2011, 2011 IEEE International Workshop on Information Forensics and Security.