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A Rapid Accurate Recognition System for Radar Emitter Signals

https://doi.org/10.3390/electronics8040463

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Low probability of intercept radar strategies

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Automatic LPI Radar Waveform Recognition Using CNN

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Going deeper with convolutions

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Deep Residual Learning for Image Recognition

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Automatic Radar Waveform Recognition

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From the STFT to the Wigner Distribution [Lecture Notes]

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Radar Emitter Recognition Based on SIFT Position and Scale Features

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Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks

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Neural Networks for Radar Waveform Recognition

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Towards an accurate radar waveform recognition algorithm based on dense CNN

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Electronic radar signal recognition based on wavelet transform and convolution neural network

inferred← citeshttps://doi.org/10.1016/j.measurement.2020.107777openalex-snapshot

Mutation grey wolf elite PSO balanced XGBoost for radar emitter individual identification based on measured signals

inferred← citeshttps://doi.org/10.1049/rsn2.12201openalex-snapshot

Unsupervised radar signal recognition based on multi‐block – Multi‐view Low‐Rank Sparse Subspace Clustering

inferred← citeshttps://doi.org/10.1088/1361-6501/abb0c0openalex-snapshot

Squeeze excitation densely connected residual convolutional networks for specific emitter identification based on measured signals

inferred← citeshttps://doi.org/10.1088/1742-6596/1971/1/012099openalex-snapshot

Radar signals modulation recognition based on bispectrum feature processing

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MATLAB simulation of performance evaluation model of time-frequency analysis method based on SVM

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Radar Signal Intra-Pulse Modulation Recognition Based on Convolutional Neural Network and Deep Q-Learning Network

inferred← citeshttps://doi.org/10.1109/icemi46757.2019.9101630openalex-snapshot

Modulation recognition algorithm using innovative CNN and cyclic-spectrum graph

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Next-Generation Multiple Access for Integrated Sensing and Communications

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Automatic Modulation Recognition of Dual-Component Radar Signals Using ResSwinT-SwinT Network

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Self-Attention Bi-LSTM Networks for Radar Signal Modulation Recognition

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Multidomain Separation for Human Vital Signs Detection With FMCW Radar in Interference Environment

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Deep Learning Techniques in Radar Emitter Identification

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Specific Emitter Identification Using IMF-DNA with a Joint Feature Selection Algorithm

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