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Lightweight CNN for Radar HRRP Recognition Using NAS-Based Pruning and Multi-Knowledge Distillation
2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)
Year: 2024 | Conference Paper |
Deep convolutional neural network (CNN) has been widely studied in radar target high resolution range profile (HRRP) recognition. However, the CNN with deep structure requires high storage and computational capabilities, thus restricting its applications with limited resources. In this paper, we propose a differentiable neural architecture search (NAS)-based channel pruning and multi-knowledge dis...Show More
Domain-Adaptive HRRP Generation Using Two-Stage Denoising Diffusion Probability Model
High-resolution range profile (HRRP) plays a crucial role in radar target recognition. In real-world applications, variations in operational conditions during testing, such as changes in depression angles, resulting in unsatisfactory performance for HRRP target recognition methods. One way to alleviate this issue is to augment training data with samples that embody the testing domain style. Theref...Show More
SDHC: Joint Semantic-Data Guided Hierarchical Classification for Fine-Grained HRRP Target Recognition
Yichen Liu;Teng Long;Liang Zhang;Yanhua Wang;Xin Zhang;Yang Li
High-resolution range profile (HRRP) is increasingly employed in radar target recognition under intricate ground scenarios. Such scenarios demand recognizing the specific type of a target from a wide range of categories, a task known as fine-grained target recognition (FGTR), which involves numerous and potentially unbalanced categories. To tackle this, we propose a joint semantic-data guided hier...Show More
In co-located multiple-input multiple-output (MIMO) radar, slow-time code division multiple access (ST-CDMA) is an essential option of orthogonal waveforms, because the transmit power and bandwidth are well exploited with a relatively low level of hardware complexity. However, the code produces high sidelobes in the Doppler spectrum, which poses a negative impact on weak target detection. To addre...Show More
Lightweight CNN for HRRP Recognition Based on Attention Mechanism Structured Pruning
Yanhua Wang;Zhilong Zhang;Mingchen Yuan;Jiandong Liao;Liang Zhang
2023 IEEE International Radar Conference (RADAR)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Deep convolutional neural network (CNN) has been widely investigated for radar target high resolution range profile (HRRP) recognition. However, the deep structures of CNN require high storage and computational capabilities, thus restricting its applications with limited resources. In this paper, we design a lightweight CNN model with structure pruning based on the channel-wise attention mechanism...Show More
Type-Aspect Disentanglement Network for HRRP Target Recognition With Missing Aspects
High-resolution range profile (HRRP) is essential for high-throughput radar automatic target recognition. Due to the aspect sensitivity of HRRP, the recognition performance degrades when the training dataset misses some aspects. Inspired by disentangled representation learning (DRL), this letter proposes a type-aspect disentanglement network (TADN) to alleviate the above aspects missing problem. T...Show More
Disentanglement Model for HRRP Target Recognition when Missing Aspects
Yanhua Wang;Yunchi Ma;Liang Zhang;Junfu Wang;Yi Zhang;Hongfen Lv
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
Year: 2023 | Conference Paper |
Cited by: Papers (2)
High resolution range profile (HRRP) is an important approach in radar automatic target recognition (RATR). Numerous deep learning methods have been proposed for HRRP recognition. However, HRRP is sensitive to aspects. When the training dataset misses aspects, the performance of the deep learning models is limited. Motivated by disentangled representation learning (DRL), this paper proposes a type...Show More
Doppler-Coded Joint Division Multiple Access Waveform for Automotive MIMO Radar
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Slow-time coded waveforms are commonly used in automotive multiple-input multiple-output (MIMO) radar to achieve inter-channel spatial diversity. Typical waveforms, such as Doppler division multiple access (DDMA) and code division multiple access (CDMA), are known to suffer from Doppler ambiguity and high side lobes, respectively. In this paper, we propose a Doppler-coded joint division multiple a...Show More
Multi-View HRRP Generation With Aspect-Directed Attention GAN
Yiheng Song;Qiang Zhou;Wei Yang;Yanhua Wang;Cheng Hu;Xueyao Hu
In radar automatic target recognition (RATR), high-resolution range profile (HRRP) has received intensive attention due to its low computational cost. As HRRP is sensitive to the aspect of the target, a training set covering sufficient aspects is essential to the success of an RATR model, which is however intractable in complex environment with noncooperative targets. In this article, an aspect-di...Show More
Online teaching system of Japanese translation course based on P2P network
2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)
Year: 2021 | Conference Paper |
in order to further improve the quality of Japanese teaching, this paper puts forward a design method of online teaching system of Japanese translation course based on P2P network, mainly for the detailed design of the system hardware structure framework and system function module, and optimizes the software module function and operation steps, on this basis, the system test is carried out. Throug...Show More
Polarimetric high resolution range profile (HRRP) holds great potential for radar automatic target recognition (RATR) owing to its capability of providing both polarimetric and spatial scattering information. Conventional polarimetric HRRP recognition methods generally extract a set of features and put them into a well-trained classifier, which heavily rely on expertise. On the contrary, deep lear...Show More
Range-Doppler Spectrum Estimation Based on Matrix Completion for Frequency Agile Radar
2020 IEEE Radar Conference (RadarConf20)
Year: 2020 | Conference Paper |
Coherent frequency agile (FA) radar has attracted considerable attention. Compared with the stepped frequency radar, FA radar not only has the high range-resolution characteristic obtained by synthesizing large bandwidth, but also has the ability of the range-Doppler decoupling and better electronic countermeasures performance. Typically, traditional matched filter (MF) is often used to estimate t...Show More
In radar high-resolution range profile (HRRP) recognition, the recognition accuracy will decline when the training samples in some classes (majority classes) greatly outnumbers other classes (minority classes). To alleviate the above imbalanced problem, an HRRP data augmentation framework is proposed. A one-dimensional (1-D) deep convolutional generative adversarial network (DCGAN) is developed to...Show More
Dual Polarimetric HRRP Sequence Recognition Based on H/\alpha Features
2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)
Year: 2019 | Conference Paper |
Dual polarimetric high resolution range prole (HRRP) is able to provide polarimetric and high resolution scattering characteristics information of radar target, which are very useful for automatic target recognition (ATR). In this paper, a novel feature extraction method, which combines both polarimetric and high resolution information, is proposed for dual polarimetric HRRP sequence based on H/α ...Show More
Polarimetric SAR Image Scattering Center Estimation via Atomic Norm Minimization
2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)
Year: 2019 | Conference Paper |
Polarization is one of the most important characteristics of electromagnetic wave, which offers another dimension of information to radar automatic target recognition (RATR). The combination of polarization and SAR technology is a vital research direction for RATR. Fusing the polarization information into the scattering center model is able to refine the scattering structural information. This pap...Show More
SAR Image Scattering Center Estimation via Atomic Norm Minimization
2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)
Year: 2019 | Conference Paper |
Cited by: Papers (3)
Scatter center matching is one of the choke points of radar automatic target recognition (RATR) based on Synthetic Aperture Radar (SAR). Accuracy of scattering center extraction is an important factor affecting target recognition performance. This paper proposes a SAR images scattering center estimation method based on atomic norm minimization (ANM) model. This method models the scattering center ...Show More
Polarimetric HRRP Target Recognition Based on Convlstm
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
Year: 2019 | Conference Paper |
Cited by: Papers (4)
The high resolution range profiles (HRRPs) of different polarimetric channels can enhance the recognition performance. Few existing methods focus on combining the structure information with correlation between different polarimetric channels. In this paper, we applied ConvLSTM to polarimetric HRRP target recognition. ConvLSTM can be used to combine the structure information with correlation due to...Show More
Polarimetric high resolution range profile (HRRP) contains the geometrical structural information along radar line-of-sight and has shown great potentials in target recognition. In existing researches, H/α decomposition has been applied to exploit global polarimetric features of a single HRRP from its spatially averaged coherent matrix, which loses target local scattering information. In this pape...Show More
In this paper, the slant 45° dual polarization mode, where the transmitter polarization is orientated at 45° and the receivers are at 45° and 135° polarizations, is applied to radar high resolution range profile (HRRP) ground target recognition. The H/α decomposition is performed on the HRRP data as the feature extractor, and a modified H-α plane is subsequently applied for scattering mechanism cl...Show More
High resolution radar real-time signal and information processing
Teng Long;Tao Zeng;Cheng Hu;Xichao Dong;Liang Chen;Quanhua Liu;Yizhuang Xie;Zegang Ding;Yang Li;Yanhua Wang;Yan Wang
Radar is an electronic device that uses radio waves to determine the range, angle, or velocity of objects. Real-time signal and information processor is an important module for real-time positioning, imaging, detection and recognition of targets. With the development of ultra-wideband technology, synthetic aperture technology, signal and information processing technology, the radar coverage, detec...Show More
A Multi-Carrier-Frequency Random-Transmission Chirp Sequence for TDM MIMO Automotive Radar
The collocated time-division multiplexing (TDM) multiple-input multiple-output (MIMO) technique and frequency-modulated continuous-wave (FMCW) chirp sequence are widely used in automotive radar because of the low hardware complexity and the high-accurate range and velocity measurements. In conventional TDM chirp sequences, the transmitters are switched according to their natural spatial order (ref...Show More
Most of the progresses achieved in radar high range resolution profile (HRRP) recognition rely on the closed set condition, where the test sample is from a known class. In realistic scenario, however, the test sample may be drawn from unknown classes, which is regarded as an open set recognition task. In such cases, conventional recognition algorithms will inevitably make a wrong prediction. In th...Show More
A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold Recovery in Highly Accelerated Dynamic MRI
Ukash Nakarmi;Yanhua Wang;Jingyuan Lyu;Dong Liang;Leslie Ying
While many low rank and sparsity-based approaches have been developed for accelerated dynamic magnetic resonance imaging (dMRI), they all use low rankness or sparsity in input space, overlooking the intrinsic nonlinear correlation in most dMRI data. In this paper, we propose a kernel-based framework to allow nonlinear manifold models in reconstruction from sub-Nyquist data. Within this framework, ...Show More
As the one-dimensional projection of the echoes from scattering centers on a target along the radar line-of-sight, high range resolution profile (HRRP) has drawn great attention to automatic target recognition (ATR). Normally, features are extracted based on the strong scattering centers of HRRP. In recent years, several scattering center estimation methods have been proposed, such as Prony and or...Show More
Robust adaptive beamforming using interference covariance matrix reconstruction
Xueyao Hu;Teng Yu;Xinyu Zhang;Yanhua Wang;Hongyu Wang;Yang Li
2016 CIE International Conference on Radar (RADAR)
Year: 2016 | Conference Paper |
The performance of adaptive beamforming degrades severely when the strong desired signal is present in training snapshots with model mismatch. A robust adaptive beamforming is proposed using interference covariance matrix reconstruction in this paper. In the proposed method, the eigenvalue and eigenvector of desired signal is determined by calculating the correlation coefficients between eigenvect...Show More
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