LPI Radar Waveform Recognition Based on CNN and TPOT [PDF]
Symmetry, 2019 The electronic reconnaissance system is the operational guarantee and premise of electronic warfare. It is an important tool for intercepting radar signals and providing intelligence support for sensing the battlefield situation. In this paper, a radar waveform automatic identification system for detecting, tracking and locating low probability ...
Jian Wan, Xin Yu, Qiang Guo
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LPI Optimization Framework for Target Tracking in Radar Network Architectures Using Information-Theoretic Criteria [PDF]
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
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LPI waveforms for AESA radar [PDF]
, 2020 The purpose of low probability of intercept (LPI) radar is, on top of the standard requirements on a radar, to remain undetected by hostile electronic warfare (EW) systems. This can be achieved primarily by reducing the amount of radiated power in any given direction at all times and is done by transmitting longer modulated pulses that can then be ...
Sjöberg, Andreas
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LPI Optimization Framework for Radar Network Based on Minimum Mean-Square Error Estimation [PDF]
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
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Dwell Time Allocation Algorithm for Multiple Target Tracking in LPI Radar Network Based on Cooperative Game [PDF]
Sensors, 2020 To solve the problem of dwell time management for multiple target tracking in Low Probability of Intercept (LPI) radar network, a Nash bargaining solution (NBS) dwell time allocation algorithm based on cooperative game theory is proposed.
Chenyan Xue, Ling Wang, Daiyin Zhu
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Cognitive MIMO Frequency Diverse Array Radar with High LPI Performance [PDF]
International Journal of Antennas and Propagation, 2016 Frequency diverse array (FDA) has its unique advantage in realizing low probability of intercept (LPI) technology for its dependent beam pattern. In this paper, we proposed a cognitive radar based on the frequency diverse array multiple-input multiple ...
Ling Huang +3 more
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1D Convolutional Neural Networks Versus Automatic Classifiers for Known LPI Radar Signals Under White Gaussian Noise [PDF]
IEEE Access, 2020 In this study we analyze the signal classification performances of various classifiers for deterministic signals under the additive White Gaussian Noise (WGN) in a wide range of signal to noise ratio (SNR) levels (-40dB to +20dB).
Alper Yildirim, Serkan Kiranyaz
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Densely-Accumulated Convolutional Network for Accurate LPI Radar Waveform Recognition [PDF]
2021 IEEE Global Communications Conference (GLOBECOM), 2021 Abstract This paper presents a deep learning-based method to automatically recognize low probability of intercept (LPI) radar waveforms against diversified jamming attacks. Concretely, an efficient convolutional neural network (CNN) architecture, namely Densely-Accumulated Network (DANet), is introduced to learn the time-frequency representation ...
Thien Huynh-The +6 more
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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
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Automatic Recognition of General LPI Radar Waveform Using SSD and Supplementary Classifier [PDF]
, 2020 © 1991-2012 IEEE. For low probability of intercept (LPI) radars, frequency-modulated and phase-modulated continuous waveforms are widely used because of their low peak power compared to that of pulse waves (PW).
Kong SH, Hoang LM, Kim M
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