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Compound Jamming Signal Recognition Based on Neural Networks
2016 Sixth International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC), 2016An algorithm of recognizing radar compound jamming signals including additive, multiplicative and convolution signals of typical blanket jamming and deception jamming based on neural networks is proposed in this article. Firstly, all signals of echo, jamming and noise received in one pulse repetition interval are acquired as signal sources.
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Chaff Jamming Recognition for Anti-Vessel End-Guidance Radars
2009 2nd International Congress on Image and Signal Processing, 2009In order to solve the problem of chaff jamming recognition for end-guidance radar, average gray correlation degree (AGCD) is introduced here to analyze the difference of time-domain correlation characteristic between vessels' echo and clutter. A novel recognition method called position matching is presented making use of the difference of spatial ...
Xiongjun Fu +3 more
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A novel algorithm for jamming recognition in wireless communication
2013 6th International Congress on Image and Signal Processing (CISP), 2013The jamming is one of the most important factors in modern wireless communication. More and more attention has been paid to the analysis of jamming signals. In this paper, a novel algorithm for the recognition of jamming signals in wireless communication is proposed.
Lei Kong +3 more
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Enhanced Transformers for Radar Jamming Recognition
2023 IEEE International Radar Conference (RADAR), 2023Menglu Zhang +3 more
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Multiresolution Jamming Recognition with Few-shot Learning
2021 CIE International Conference on Radar (Radar), 2021Xinyi Tian, Baixiao Chen, Zhaoming Zhang
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Open world recognition of communication jamming signals
China Communications, 2023Yan Tang +6 more
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Radar Jamming Recognition via a New Siamese Network
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023Zixuan Wang, Ganggang Dong, Yinghua Wang
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Machine Learning Image Recognition for GNSS Jamming Signals Categorization
Neural Network WorldGlobal Navigation Satellite Systems are a critical positioning, navigation, and timing source for various industries. However, their weak signal on Earth’s surface makes them vulnerable to jamming. This paper explores the use of machine learning image recognition for categorizing GNSS jamming signals.
Jakub Steiner, Jiří Pešík
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A feature fusion-based communication jamming recognition method
Wireless Networks, 2023Mingrui Xin, Zhuoran Cai
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RA-Net: An Effective Radar Jamming Recognition Method
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023Siyao Wang +3 more
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