IET Signal Processing, 2023 It is difficult for a receiver to intercept the signals from a radar system that can emit low probability of intercept (LPI) polyphase coded signals. The traditional Wigner Hough transform (WHT) algorithm requires a large amount of computation and takes ...
Jincheng Yang +3 more
doaj +1 more source
Time-frequency represetation of radar signals using Doppler-Lag block searching Wigner-Ville distribution [PDF]
, 2018 Radar signals are time-varying signals where the signal parameters change over time. For these signals, Quadratic Time-Frequency Distribution (QTFD) offers advantages over classical spectrum estimation in terms of frequency and time resolution but it ...
Hamdi, Muhammad Noor Muhammad +1 more
core +3 more sources
Fuzzy Chance-constrained Programming Based Security Information Optimization for Low Probability of Identification Enhancement in Radar Network Systems [PDF]
, 2015 In this paper, the problem of low probability of identification (LPID) improvement for radar network systems is investigated. Firstly, the security information is derived to evaluate the LPID performance for radar network.
Chen, J. +3 more
core +2 more sources
LPI Optimization Framework for Radar Network Based on Minimum Mean-Square Error Estimation
Entropy, 2017 This paper presents a novel low probability of intercept (LPI) optimization framework in radar network by minimizing the Schleher intercept factor based on minimum mean-square error (MMSE) estimation.
Ji She +3 more
doaj +1 more source
Generation of pseudo-random sequences for noise radar applications [PDF]
, 2014 Noise Radar Technology (NRT) is nowadays a promising tool in radar systems. It is based on the transmission of waveforms composed of many noisy samples, which behave as LPI (Low Probability of Intercept) and antispoofing signals.
De Palo, F, Galati, G, Pavan, G
core +1 more source
Stellar Origins of Extremely $^{\text{13}}C$- and $^{15}N$-enriched Presolar SiC Grains: Novae or Supernovae? [PDF]
, 2016 Extreme excesses of $^{13}C$ ($^{12}C$/$^{13}C$
Alexander, Conel M. O'D. +6 more
core +6 more sources
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
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
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Information-Theoretic Optimal Radar Waveform Selection With Multi-Sensor Cooperation for LPI Purpose
IEEE Access, 2022 For the complex battlefield electromagnetic environment, low probability of interception (LPI) performance has become an indispensable ability for modern radars.
Jun Chen, Fei Wang, Jianjiang Zhou
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International Journal of Antennas and Propagation, 2014 Widely distributed radar network architectures can provide significant performance improvement for target detection and localization. For a fixed radar network, the achievable target detection performance may go beyond a predetermined threshold with full
Chenguang Shi +3 more
doaj +1 more source