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Radar active jamming recognition based on time-frequency image classification 21

Radar active jamming recognition based on time-frequency ima...

引用

5th International Conference on Electronic Information technology and Computer Engineering, EITCE 2021

作者： Wang, Jingyi Dong, Wenhao Song, Zhiyong National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense Technology Changsha China

ISBN: (纸本)9781450384322

Flexible active radar jamming has become one of the main threats in modern electronic warfare. Aiming at the problem of classifying and identifying active jamming patterns of towed decoy radar, this paper proposes a set of methods for classifying and identifying jamming time-frequency images based on deep learning. The content mainly includes: using short-time Fourier transform to obtain time-frequency images of six kinds of active interference under different interference signal ratios. Using ResNet network to realize the classification and recognition of different interferences. Through simulation analysis, the algorithm can still obtain better results under low interference-to-noise ratio. © 2021 ACM.

关键词： Jamming

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Design of radar waveform game platform based on PXI system 10

Design of radar waveform game platform based on PXI system

引用

10th International Conference on Control, Automation and Information sciences, ICCAIS 2021

作者： Wang, Min Jiang, Yanwen Fan, Hongqi National University of Defense Technology National Key Laboratory of Science and Technology on Automatic Target Recognition ChangSha China

ISBN: (纸本)9781665440295

In view of the lack of a test verification platform in the research of the game between radar and target, a test platform for radar waveform game is designed based on the PXI system. The platform includes a multi-channel radar and a simulator that can simulate targets and repeater jamming. The radar transmission waveform, signal processing, target and jamming parameters can be configured by the user, and it has good versatility. It provides a practical test and verification platform for radar waveform design and algorithm research under gaming conditions. © 2021 IEEE.

关键词： Radar

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Improved Sparse Representation of Open Set HRRP recognition Method 5

Improved Sparse Representation of Open Set HRRP Recognition ...

引用

5th International Conference on Electronics and Communication, Network and Computer technology, ECNCT 2023

作者： Zhang, Huiqiang Liu, Shengqi Qu, Shuang Ou, Jianping Zhang, Jun Deng, Jie National University of Defense Technology National Key Laboratory of Science and Technology on Automatic Target Recognition Changsha China

ISBN: (纸本)9798350328660

Traditional target recognition methods classify targets within a closed set, and the methods cannot effectively identify unknown categories outside the library. Research on open set recognition (OSR) has been developed in computer vision, yet rare research is conducted in radar target recognition. First the HRRP recognition performance of several state-of-The-Art OSR algorithms are compared in open set, including SROSR, WSVM, and 1-vs Set. Among them the SROSR algorithm performances better than the others. However, manual setting of tail and weight parameters is required in the algorithm, which may difficult to be obtained in practical applications. Focused on this issue, an modified SROSR method based on the mean ratio of reconstruction errors is presented. The mean ratio of reconstruction errors is used as a new metrics and its statistical distribution is modeled with extreme value theory (EVT). Compared with the classical SR-OSR, manual setting of the tail of reconstruction errors and weight parameters are avoided. Experiments were conducted on HRRP data generated from MSTAR SAR chips, and the results show that the recognition performance of the proposed method is better than the classical SROSR algorithm. © 2023 IEEE.

关键词： Radar target recognition

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Multi-level quantization method for suppressing interrupted-sampling repeater jamming

Multi-level quantization method for suppressing interrupted-...

引用

2021 International Conference on Signal Image Processing and Communication, ICSIPC 2021

作者： Wang, Min Jiang, Yanwen Fan, Hongqi National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense Technology Changsha China

ISBN: (数字)9781510645417

ISBN: (纸本)9781510645400

Interrupted-sampling repeater jamming, which is a new type of coherent jamming based on digital radio frequency memory can produce dense false target groups. According to the idea of 'reconstruction and cancellation', the paper uses multilevel quantization method to generate a large number of local templates to match the actual jamming, then the jamming can be suppressed and canceled after the parameter estimation. Since the template generation does not require real-time calculation, the algorithm proposed in this paper has a smaller amount of calculation than the original algorithm, when the performance of jamming suppression is the same. © 2021 SPIE.

关键词： Jamming

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Adaptive Sparse ISAR Imaging for Objects With Off-grid Scatterers 7

Adaptive Sparse ISAR Imaging for Objects With Off-grid Scatt...

引用

7th International Conference on Intelligent Computing and Signal Processing, ICSP 2022

作者： Yu, Xiang Wang, Zhuang Du, Xiaoyong Jiang, Libing National University of Defense Technology National Key Laboratory of Science and Technology on Automatic Target Recognition Changsha China

ISBN: (纸本)9781665478571

Due to the sparsity of inverse synthetic aperture radar (ISAR) images, compressive sensing (CS) has been introduced to ISAR imaging for resolution improvement. However, conventional CS ISAR algorithms assume that target scatterers are on the predefined range-Doppler grid, which will cause performance degradation in practical applications as scatterers are generally off-grid. In this paper, we investigate CS ISAR imaging technique for targets with off-grid scatterers. Based on adaptive grids, a two dimensional sparse ISAR imaging algorithm is presented. Simulation results validate the effectiveness of the proposed algorithm. © 2022 IEEE.

关键词： Compressed sensing

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A Compact Low-power ISM-band Harmonic Radar for RF Receiver Detection

A Compact Low-power ISM-band Harmonic Radar for RF Receiver ...

引用

2021 CIE International Conference on Radar, Radar 2021

作者： Li, Yuanzhe Hu, Weidong Fan, Hongqi Du, Xiaoyong National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense Technology Changsha China

ISBN: (纸本)9781665498142

Harmonic radars have received sustained attention in recent years for unique capability on clutter suppression, which demonstrates huge potential in detecting and locating RF receivers in harsh environment. We implemented a laboratory-level harmonic detection system with a compact single-antenna setup by using standard general instruments and commercial RF modules. The system successfully detected the simulated RF receiver with 0 dBm transmitting power at about 8 m. Furthermore, we revised classical harmonic radar equation by introducing the receiver modules' nonlinear characteristics and updated the relations between the receiving harmonic power, transmitting power and range, which were validated by the observed data by the system. The system could be the test bench for related indoor and outdoor experiments in the future. © 2021 IEEE.

关键词： harmonic detection harmonic radar equation low-powered receiver detection

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Radar jamming classification and recognition technology based on deep learning

Radar jamming classification and recognition technology base...

引用

2021 International Conference on Signal Image Processing and Communication, ICSIPC 2021

作者： Wang, Jingyi Dong, Wenhao Fu, Qiang Song, Zhiyong National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense Technology Changsha China

ISBN: (数字)9781510645417

ISBN: (纸本)9781510645400

Towed radar active jamming has attracted much attention in the military struggle of air-to-air combat because of its simple structure and remarkable efficiency. The radar jamming patterns are becoming more and more complicated. In order to realize the identification of towed decoys, it is necessary to classify and identify the jamming patterns. The difference between time-frequency images of different interference patterns is the key to classification and recognition. Deep learning provides classifiers for classification algorithms with its powerful image data processing capabilities. Therefore, in this paper, aiming at towed decoy interference, the convolutional neural network, which is good at image analysis in deep learning, is applied to the radar active interference pattern time-frequency image classification and recognition technology. The simulation experiment part uses convolutional neural network (ResNeXt residual network) to classify and verify two different interference patterns of dense false target interference and noise convolutional interference. © 2021 SPIE.

关键词： Convolution

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A Deep Learning Method with Wavelet Packet Transform for Infrared target recognition

A Deep Learning Method with Wavelet Packet Transform for Inf...

引用

2021 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2021

作者： Yu, Bingzhi Lu, Huanzhang Tao, Huamin National University of Defense Technology National Key Laboratory of Science and Technology on Automatic Target Recognition Changsha China

ISBN: (纸本)9781665429184

Space object recognition is an important process in infrared (IR) monitoring system. The gray value time series of the IR detector is the only data available for recognition due to long observation distance. Besides, the non-uniformity of the detector pixels and imaging noise make it difficult to extract features for recognition. In this paper, a wavelet packet transform convolution neural network (WPCN) is proposed for feature learning and classification. Different from other deep learning and handcrafted feature based methods, our method use the wavelet packet transform (WPT) to extract time-frequency domain information as the preprocessing of signal. Then the convolution neural network (CNN) extracts high-level features of decomposition data to predict label. WPCN introduces residual learning block to build the network making the learning performance improved. Training data are generated from IR gray value simulation model combined with micro-motion dynamics, geometry characteristics of space targets and imaging effect of IR detector. We evaluate WPCN on three datasets obtained by 20, 40 and 60 Hz sampling frequency. The results indicate that our method promotes the performance. The classification accuracy can reach 95% at 60Hz. © 2021 IEEE.

关键词： Frequency domain analysis

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Cross-domain infrared target recognition based on simulation

Cross-domain infrared target recognition based on simulation

引用

2021 International Conference on Signal Image Processing and Communication, ICSIPC 2021

作者： Zhang, Ning Wang, Weihua Chen, Gao National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense Technology Changsha China

ISBN: (数字)9781510645417

ISBN: (纸本)9781510645400

In recent years, automatic target recognition (ATR) based on deep learning has achieved great success in RGB field, which has huge data support. However, due to the confidentiality of military targets, weather constraints, and high shooting costs, it is difficult to obtain a large number of real IR images which leads to the performance degradation of deep learning algorithms in IR field. This paper discusses the method of using simulation IR images as training set to get rid of dependence on the real image. However, there are still great differences between the original simulated image and the real image, which leads to many defects when using the original simulated image for training. Therefore, in this paper, we use cycleGAN to convert the original simulation image into the intermediate image closer to the real image based on generative adversarial networks (GAN). Finally, the effectiveness of this method is proved by experiments. © 2021 SPIE.

关键词： automatic target recognition

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Pose estimation for monocular image object using convolution neural network 2

Pose estimation for monocular image object using convolution...

引用

2nd International Symposium on Computer Engineering and Intelligent Communications, ISCEIC 2021

作者： Li, Hangyu Wu, Han Zhang, Zhilong Li, Chuwei National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense Technology Changsha China

ISBN: (纸本)9781665441605

Obtaining the accurate position and attitude of the object is the key to realize rendezvous and docking, on-orbit maintenance and other related tasks of space spacecraft. However, for non-cooperative objects, they lack prearranged cooperation sign, which would make it much more difficult to estimate their pose. Therefore, this paper attempts to use the powerful feature learning ability of neural network to establish the mapping relationship between the object in image and its current pose, then regresses the pose parameters of the object from a monocular image. Finally, we tested and verified the network on the public satellite dataset called Speed. The results showed that the translation error was 0.1237 and the rotation error was 0.1335. © 2021 IEEE.

关键词： Orbits

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