Results 21 to 30 of about 619,289 (184)
LPI Radar Waveform Recognition Based on Neural Architecture Search. [PDF]
Comput Intell Neurosci, 2022 In order to reach the intelligent recognition, the deep learning classifiers adopted by radar waveform are normally trained with transfer learning, where the pretrained convolutional neural network on an external large-scale classification dataset (e.g., ImageNet) is used as the backbone.
Ma Z +5 more
europepmc +5 more sources
The dependence of radar target detectability on array weighting function [PDF]
, 2009 Presented at the IET-Radar 2007 Conference Edinburgh 15-18 October 2007This paper describes simulation work to assess the detectability of targets by an airborne fire control radar (FCR) operating in a medium pulse repetition frequency (PRF) mode in ...
Alabaster, Clive M., Hughes, Evan J.
core +7 more sources
Optimal Time-Frequency Distribution Selection for LPI Radar Pulse Classification [PDF]
, 2020 The work presented in this paper shows the performance of various time-frequency distributions when gathering ELectronic INTelligence (ELINT) from an electromagnetic environment that contains transmissions from radars operating in a Low Probability of ...
Ben Willetts +5 more
core +2 more sources
Defence Technology, 2023 Nyquist Folding Receiver (NYFR) is a perceptron structure that realizes a low probability of intercept (LPI) signal analog to information. Aiming at the problem of LPI radar signal receiving, the time domain, frequency domain, and time-frequency domain ...
Tao Wan, Kai-li Jiang, Hao Ji, Bin Tang
doaj +1 more source
Developments in target micro-Doppler signatures analysis : radar imaging, ultrasound and through-the-wall radar [PDF]
, 2013 Target motions, other than the main bulk translation of the target, induce Doppler modulations around the main Doppler shift that form what is commonly called a target micro-Doppler signature.
Woodbridge, K. +3 more
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Radar signal recognition exploiting information geometry and support vector machine
IET Signal Processing, 2023 Aiming at the recognition of low‐probability‐of‐intercept (LPI) radar signals, a support vector machine (SVM)‐based algorithm is proposed, where the information geometry theory is utilised to optimise the kernel function of the SVM.
Yuqing Cheng, Muran Guo, Limin Guo
doaj +1 more source
Radar signal recognition based on triplet convolutional neural network
EURASIP Journal on Advances in Signal Processing, 2021 Recently, due to the wide application of low probability of intercept (LPI) radar, lots of recognition approaches about LPI radar signal modulations have been proposed.
Lutao Liu, Xinyu Li
doaj +1 more source
LPI Radar Waveform Recognition Based on Multi-Resolution Deep Feature Fusion
IEEE Access, 2021 Deep neural networks are used as effective methods for the Low Probability of Intercept (LPI) radar waveform recognition. However, existing models' performance degrades seriously at low Signal-to-Noise Ratios (SNRs) because the effective features ...
Xue Ni +4 more
doaj +1 more source
Digital LPI Radar Detector [PDF]
, 2001 The function of a Low Probability ofIntercept (LPI) radar is to prevent its interception by an Electronic Support (ES) receiver. This objective is generally achieved through the use of a radar waveform that is mismatched to those waveforms for which an ...
Ong, Peng Ghee, Teng, Haw Kiad
core +2 more sources
Sensors, 2020 Radar network systems have been demonstrated to offer numerous advantages for target tracking. In this paper, a low probability of intercept (LPI)-based joint dwell time and bandwidth optimization strategy is proposed for multi-target tracking in a radar
Lintao Ding +3 more
doaj +1 more source