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A Rapid Radar Signal Sorting Method Based on Density and Gaussian Mixture Model Data Stream Clustering
Weibo Huo;Haoyang Yu;Yujie Zhang;Gengchen Xu;Jifang Pei;Yin Zhang;Yulin Huang
IEEE Transactions on Aerospace and Electronic Systems
Year: 2025 | Early Access Article |
Radar signal sorting is one of the crucial techniques in radar reconnaissance. However, as the electromagnetic environment increasingly complex and the density of radar pulses surges, the efficiency of clustering-based sorting algorithms is severely degraded. To better align with the streaming data characteristics of radar pulses and avoid the storage and computation of large amounts of pulse data...Show More
KiRV: Robust Human Identification Via Multi-Modal Learning Based on Kinetic Gait Features of Radar and Vision
Lang Deng;Jifang Pei;Yuansen Song;Weibo Huo;Yin Zhang;Yulin Huang
IEEE Internet of Things Journal
Year: 2025 | Early Access Article |
Gait is an appealing biometric pattern that aims to identify individuals based on the way they walk. Gait recognition, a passive human identification technology utilized from a distance without subject cooperation, plays a considerable role in life monitoring, crime prevention, security guarantee, and other identity recognition applications. Although vision-based methods dominate the state-of-the-...Show More
FlexiRL: An Integrated Jamming Strategy Framework for Hybrid Mode and Parameter Decision-Making
Yujie Zhang;Cui Zhang;Weibo Huo;Yulin Huang;Rundong Jiang;Jifang Pei;Yin Zhang
IEEE Transactions on Aerospace and Electronic Systems
Year: 2025 | Early Access Article |
Electronic warfare holds increasing importance in modern military operations. Effective jamming decision-making is capable of supplying timely electronic protection for high-value targets. Developing a powerful jamming strategy requires selecting appropriate jamming modes and optimizing jamming parameters. To achieve simultaneous optimization of jamming modes and multidomain parameters, a jamming ...Show More
SAR-PAA: A Physically Adversarial Attack Approach Against SAR Intelligent Target Recognition
Yanjing Ma;Jifang Pei;Weibo Huo;Yin Zhang;Yulin Huang;Keyang Chen;Jianyu Yang
Synthetic aperture radar (SAR) target recognition has entered a new era of intelligence due to the rapid development of deep learning. Naturally, an accompanying challenge arises in countering SAR intelligent target recognition technology and protecting the targets of interest from exposure risks. In this article, a novel adversarial attack approach against SAR intelligent target recognition is pr...Show More
Airborne Radar Operating State Recognition Based on Multi-Parameter Fusion RCS-Conv Method
Xu Zhou;Hao Mu;Yujie Zhang;Xinjie Shi;Weibo Huo;Jianyu Yang;Jianqi Wu
2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)
Year: 2024 | Conference Paper |
Airborne radar operating state directly reflects the combat intention of the target platform, playing a crucial role in electronic warfare. However, the challenge of parameter overlap among different operating states poses a new obstacle to radar state recognition. To enhance the capability of recognizing radar operating states with overlapping parameters, a multi-parameter fusion residual coordin...Show More
Deceptive Jamming Mitigation Based on Proximal Policy Optimization
2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)
Year: 2024 | Conference Paper |
With the increasing reliance on radar technology in modern warfare, the operational capability of radar in countermeasure environments has become increasingly important. For waveform agile radars, randomly choosing transmit waveforms from a large set of orthogonal waveforms is not the optimal approach to mitigate the interference signal. Aiming at deception jamming mitigation, an anti-interference...Show More
SAR Image Reconstruction Method for Target Detection Using Self-Attention CNN-Based Deep Prior Learning
Due to its all-day and all-weather capability, synthetic aperture radar (SAR) plays an important role in many remote sensing and monitoring applications. However, conventional SAR image reconstruction methods generally perform undifferentiated imaging, complicating target detection. To address this challenge, we propose a SAR image reconstruction method based on self-attention deep prior learning ...Show More
A Novel SAR Target Recognition Approach under Imbalanced Categories: Constraint and Optimization
Yanjing Ma;Xing Zhang;Jifang Pei;Weibo Huo;Yin Zhang;Yuling Huang;Jianyu Yang
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Year: 2024 | Conference Paper |
Target recognition is one of the most significant tasks in synthetic aperture radar (SAR) image interpretation. However, due to the varying difficulty in acquiring SAR images for different categories, SAR target recognition often encounters the issue of categories imbalance. This make majority categories contribute more to the loss than minority categories, yielding a decline in classification per...Show More
Cascaded Feature Fusion Pyramid Network for Ship Detection in Dualpolarization SAR Images
Xue Tang;Yuanzhe Shang;Honglin Xu;Jifang Pei;Yin Zhang;Weibo Huo;Yulin Huang
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Year: 2024 | Conference Paper |
Cited by: Papers (1)
Synthetic aperture radar (SAR) has been widely applied in maritime target detection. However, most existing SAR ship detection algorithms based on convolutional neural network (CNN) only use single polarization SAR images for detection, neglecting to further improve the detection performance by utilizing the rich polarization information of the SAR images. To deal with this issue, this paper propo...Show More
Mixed Attention SAR Ship Recognition Network with Robust Background Interference
Yanyu Lyu;Yuanzhe Shang;Chongsong Wang;Yulin Huang;Jifang Pei;Wei Pu;Weibo Huo;Junjie Wu;Yin Zhang
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Year: 2024 | Conference Paper |
Ship recognition in synthetic aperture radar (SAR) images is a significant and fundamental step in the maritime surveillance. However, recognition of ships inevitably faces background interference in the maritime environment. The interference guides the network focusing on useless even harmful regions. To deal with issue, a mixed attention mechanism consists of coordinate and Squeeze-and-Excitatio...Show More
A SAR Open-Set Recognition Method Aided by Hierarchically Reconstructive Latent Representation Learning
Yuchun Lu;Jifang Pei;Yin Zhang;Weibo Huo;Yulin Huang;Wenjing Wang;Jianyu Yang
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Year: 2024 | Conference Paper |
Cited by: Papers (1)
Automatic target recognition (ATR) based on synthetic aperture radar (SAR) images has already obtained remarkable achievements on closed-set task. However, the recognition in a real-world scenario should not only identify the known classes but also appropriately deal with the unknown ones. To this end, we propose a SAR open-set recognition method aided by hierarchically reconstructive latent repre...Show More
Beta Mixture Model and Boundary Amplification Guided Label Noise Mitigation for Polsar Image Classification
Xiaowei Lin;Yanjing Ma;Jifang Pei;Weibo Huo;Junjie Wu;Yin Zhang;Yulin Huang;Jianyu Yang
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Year: 2024 | Conference Paper |
In the field of polarimetric synthetic aperture radar (PolSAR) automatic target classification (ATR), convolutional neural network (CNN) based methods have excelled owing to their adept feature extraction capabilities. However, these methods heavily rely on a sufficiently labeled training dataset for superior classification performance. Limited PolSAR training samples and inevitable noisy labels o...Show More
A DCT-Based Local Contrast Enhancement SAR Imaging Detection Algorithm*
Ran An;Weibo Huo;Yujie Zhang;Jifang Pei;Yin Zhang;Yulin Huang
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Year: 2024 | Conference Paper |
Synthetic aperture radar (SAR) is commonly used for ship imaging on the sea. By using small target detection algorithms, ship targets can be highlighted under different SAR backgrounds for detection and observation. Local contrast measurement (LCM) has poor detection performance in situations with strong background noise or uneven distribution, and its results cannot preserve the shape features of...Show More
Angular Superresolution for Forward-Looking Scanning Radar With Pulse Interference Using Cross-Domain Low-Rank and Sparse Optimization
Deqing Mao;Jianyu Yang;Xingyu Tuo;Yongchao Zhang;Weibo Huo;Yin Zhang;Yulin Huang
Frequency modulation continuous wave (FMCW) radar has been paid much attention in forward-looking navigation applications because of its no-blind-range capability. However, after dechirp processing, pulse interference signals may appear in the range time domain, which seriously pollutes the whole radiation direction. In this article, a cross-domain low-rank and sparse (CD-LRS) optimization framewo...Show More
Deinterleaving Pulse Trains via RPMA-TConv for Parameter-Agile Radar
Caiyu Liang;Han Tang;Weibo Huo;Yin Zhang;Jifang Pei;Yulin Huang
2024 IEEE Radar Conference (RadarConf24)
Year: 2024 | Conference Paper |
Radar pulse trains deinterleaving is a challenging task in modern electronic reconnaissance. The RPMA-TConv model based on multi-branch atrous convolution and feature reconstruction is proposed to solve the problem of deinterleaving parameter-agile emitters. The time of arrival (TOA), center frequency (CF) and pulse width (PW) are used to characterize the relative position and variation pattern of...Show More
A Split SPICE-TV Super-Resolution Method for Scanning Radar
Jiawei Luo;Yongchao Zhang;Tianzhi Sun;Yin Zhang;Weibo Huo;Yulin Huang;Jianyu Yang
2024 IEEE Radar Conference (RadarConf24)
Year: 2024 | Conference Paper |
Recently, the sparse iterative covariance fitting estimation (SPICE) method has garnered attention for scanning radar super-resolution imaging. While it offers improved azimuth resolution, a notable drawback is its limited efficacy in reconstructing target contours. In this paper, a Split SPICE total variation (Split SPICE-TV) super-resolution method is proposed to address this problem. First, the...Show More
Intra-Pulse Modulation Recognition Method of Radar Signals Based on GFSE-InRes2Net Under Multipath Effects
Yang Luo;Yujie Zhang;Weibo Huo;Jifang Pei;Yin Zhang;Yulin Huang;Caiyu Liang
In modern complex electromagnetic environments, the received radar signals are often affected by multipath effects. The distortion and noise of the multipath signals make it difficult to recognize the intra-pulse modulation of radar signals. To address this issue, a gram angular field-fusion Inception-Res2Net with squeeze-and-excitation (GFSE-InRes2Net) is proposed. Firstly, in addition to the con...Show More
An Efficient Waveform Design Method with Spectral Coexistence and Pulse-like Autocorrelation Function
Cui Zhang;Jifang Pei;Yujie Zhang;Yin Zhang;Weibo Huo;Yulin Huang;Jianyu Yang
2024 IEEE Radar Conference (RadarConf24)
Year: 2024 | Conference Paper |
Spectrum coexistence capability is particularly important for radar systems in complex electromagnetic environments, since it can suppress interference arising from signals in the common frequency band. In this paper, a unimodular waveform design method based on the Karush-Kuhn-Tucker (KKT) conditions is proposed to design transmit waveforms with spectral coexistence and pulse-like autocorrelation...Show More
Anti-Jamming Strategy Design Based on Deep Q-Network for Slope-Varying LFM Signal
Shubo Chen;Weibo Huo;Cui Zhang;Jifang Pei;Yin Zhang;Yulin Huang;Jiahao Shen
2024 IEEE Radar Conference (RadarConf24)
Year: 2024 | Conference Paper |
Radar systems with anti-jamming capability have become extremely important in the complex electromagnetic environment. In this paper, an anti-jamming strategy generation method based on deep Q-network (DQN) is proposed for slope-varying linear frequency modulation (SV-LFM) signals. First, the radar-jammer confrontation scenario is modeled as a Markov decision process. Subsequently, a reward functi...Show More
Class Ambiguity Regularized Adversarial Domain Adaptation for Cross-resolution SAR ATR
Yuchun Lu;Jifang Pei;Yi Liu;Yin Zhang;Weibo Huo;Yulin Huang;Jianyu Yang;Jianqi Wu
2024 IEEE Radar Conference (RadarConf24)
Year: 2024 | Conference Paper |
Automatic target recognition (ATR) plays a critical role in synthetic aperture radar (SAR) applications. However, existing SAR ATR methods usually assume that the training and test SAR samples have the same imaging resolution but it is hard to satisfy in practice due to the complexity of the SAR imaging process, which results in the discrepancy between different resolution domains and degrades the...Show More
A Dual-Mode Radar Signal Sorting Method Based on Adaptive Density Peak Clustering
Aijiong Yang;Weibo Huo;Gengchen Xu;Yujie Zhang;Yulin Huang;Jifang Pei;Yin Zhang;Yi Liu
2024 IEEE Radar Conference (RadarConf24)
Year: 2024 | Conference Paper |
Radar signal sorting is a key component in electronic support measures (ESM). Adaptive sorting algorithms are a type of method that does not require prior understanding of radar information in the sorting scenario. However, these methods have consistently faced the issue of high runtime costs. To address this problem, in this paper, a dual-mode radar signal sorting method based on density clusteri...Show More
Dynamically Weighted Prototypical Learning Method for Few-Shot SAR ATR
Congwen Wu;Jianyu Yang;Yuanzhe Shang;Jifang Pei;Deqing Mao;Weibo Huo;Yulin Huang;Yin Zhang
Automatic target recognition (ATR) holds a crucial position in synthetic aperture radar (SAR) image interpretation. Despite deep-learning advancements having significantly propelled SAR ATR, addressing the challenge of target recognition with a few training data remains a vital concern in SAR applications. Two main issues still exist: 1) in few-shot SAR ATR, the depth and width of convolutional ne...Show More
Parameter Extraction Method of Overlapping Radar Signals Using Modulation Recognition-Guided Semantic Segmentation
Weibo Huo;Yang Luo;Hao Wang;Jifang Pei;Yin Zhang;Yulin Huang;Jianyu Yang
Parameter extraction of radar signals is an important but challenging task in electronic warfare. In the modern electromagnetic environment, the radiation sources greatly increase, causing different radar signals to overlap, making the parameter extraction of radar signals difficult. Meanwhile, using radar signal parameter extraction methods that are not suitable for dealing with overlapping signa...Show More
Transmit Beampattern Design with Similarity and Variable Modulus Constraints for MIMO Radar
Cui Zhang;Jifang Pei;Yujie Zhang;Qingying Yi;Weibo Huo;Yin Zhang;Yulin Huang
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
Year: 2023 | Conference Paper |
In this paper, the constrained waveform design of multiple-input multiple-output (MIMO) radar is considered to achieve transmit beampattern assignment. Firstly, we construct a framework that minimizes the spatial integrated sidelobe level ratio (ISLR) as the objective function and constrains the transmit waveforms in terms of amplitude fluctuations and similarity. To solve the resulting non-convex...Show More
Transfer Learning on Self-Supervised Model for SAR Target Recognition with Limited Labeled Data
Xiaoyu Liu;Lin Liu;Chenwei Wang;Jifang Pei;Weibo Huo;Yin Zhang;Yulin Huang
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
Year: 2023 | Conference Paper |
Deep learning contributes to significant improvements in synthetic aperture radar (SAR) target recognition performance. Most SAR target recognition methods are based on supervised learning and require labeled SAR data. There only exists limited labeled data due to the time-consuming and laborious work of labeling, and there is still a large amount of available unlabeled radar data. Therefore, we a...Show More
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