Results 51 to 60 of about 350 (145)

Multiple receiver specific emitter identification

IET Radar, Sonar & Navigation
Specific emitter identification (SEI) is a technique for identifying emitters based on the principle that the hardware chain is not ideal, causing the emitted signal to contain emitter‐specific information.
Liting Sun, Zheng Liu, Zhitao Huang
doaj   +1 more source

Radar emitter structure identification based on stacked frequency sparse auto‐encoder network

IET Radar, Sonar & Navigation
In the current complex situations of electronic intelligence (ELINT), the authors present a radar emitter structure (RES) identification method based on deep learning at a new level to address the issue of incomplete cognitive information.
Lutao Liu, Wei Zhang, Yu Song, Yilin Jiang, Xiangzhen Yu   +4 more
doaj   +1 more source

Open space radar specific emitter identification using MSAK‐CNN‐LSTM network

IET Radar, Sonar & Navigation
To enhance the capability of identifying unknown emitters in open spaces, an open‐multiscale attention kernel (MSAK)‐convolutional neural network‐long short‐term memory (CNN‐LSTM) structure is proposed.
Yuanhao Zheng, Jiantao Wang, Jie Huang
doaj   +1 more source

Investigating the effects of destructive factors on pulse repetition interval modulation type recognition using deep convolutional neural networks based on transfer learning

IET Radar, Sonar & Navigation
Automation and self‐sufficiency in the complex environment of modern electronic warfare (EW) are critical and necessary issues in electronic intelligence and support systems to detect real‐time and accurate threat radars.
Mahshid Khodabandeh, Azar Mahmoodzadeh, Hamed Agahi   +2 more
doaj   +1 more source

Weak Labeling-specific Emitter Identification Algorithm Based on the Weakly Supervised Wav-KAN Network

Leida xuebao
Most existing specific emitter identification technologies rely on supervised learning, making them unsuitable for scenarios with label loss due to factors such as the acquisition environment (e.g., weather conditions, terrain, obstacles, and ...
Kangsheng LIU, Qing LING, Wenjun YAN, Limin ZHANG, Keyuan YU, Hengyan LIU   +5 more
doaj   +1 more source

Dual‐labelled multi‐Bernoulli filter based on specific emitter identification

IET Radar, Sonar & Navigation
In complex electromagnetic environments, airborne passive bistatic radar encounters the challenge of associating emitters with measurements for multi‐target tracking.
Xin Guan, Yu Lu
doaj   +1 more source

Multi‐function radar work mode recognition based on residual shrinkage reconstruction recurrent neural network

IET Radar, Sonar & Navigation
In modern electronic warfare, multi‐function radar work mode recognition is increasingly crucial. However, the challenges posed by complex electromagnetic environments, such as lost pulses, spurious pulses, and measurement errors, along with the reliance
Lihong Wang, Kai Xie
doaj   +1 more source

Semi-Global Attention and Inter-Class Multi-constraint Enforced Open-Set Radar Emitter Individual Identification [PDF]

Radioengineering
This paper proposes an open-set radar emitter individual identification algorithm based on semi-global attention and inter-class multi-constraint to address the problem of inadequately adaptive feature representation and discrimination difficulty with ...
J. Xu, J. Hu, W. Jiang, Z. Zhang, M. Yang, Z. Zou   +5 more
doaj  

Boundary‐Aware Learning for Robust Automatic Modulation Recognition Based on Adaptive Pyramid Network

IET Radar, Sonar & Navigation
Automatic modulation recognition (AMR) of radar signals plays a pivotal role in intelligent spectrum management for modern electronic warfare systems.
Yuanhang Li, Mengyi Qi, Xiaofeng Tao, Wenbin Shao   +3 more
doaj   +1 more source

Radar signal deinterleaving in open‐set environments based variational autoencoder with probabilistic ladder structure

IET Radar, Sonar & Navigation
In the field of electronic reconnaissance, deinterleaving techniques for radar signals are crucial. Although a large number of studies have been devoted to the classification of known radar signals by recurrent neural networks under closed set conditions,
Huibo Sun, Kai Xie
doaj   +1 more source