Results 11 to 20 of about 356 (136)

LPI Optimization Framework for Radar Network Based on Minimum Mean-Square Error Estimation

open access: yesEntropy, 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, Jianjiang Zhou, Fei Wang
exaly   +4 more sources

Spatial Information-Theoretic Optimal LPI Radar Waveform Design

open access: yesEntropy, 2022
In this paper, the design of low probability of intercept (LPI) radar waveforms considers not only the performance of passive interception systems (PISs), but also radar detection and resolution performance. Waveform design is an important considerations
Jun Chen   +4 more
doaj   +2 more sources

Low Probability of Intercept Formation Communication Method Based on Chaotic Particle Swam Optimization [PDF]

open access: yesJisuanji gongcheng, 2017
In order to improve the low interception performance of aircraft formation,a new method of Low Probability of Intercept(LPI) formation communication is proposed.The communication of aircraft formation is considered as an adaptive optimization problem,and
JIANG Bo,DU Xinjun,YANG Yuxiao
doaj   +2 more sources

Low-PAPR Waveforms with Shaped Spectrum for Enhanced Low Probability of Intercept Noise Radars

open access: yesRemote Sensing, 2021
Noise radars employ random waveforms in their transmission as compared to traditional radars. Considered as enhanced Low Probability of Intercept (LPI) radars, they are resilient to interference and jamming and less vulnerable to adversarial exploitation
Kubilay Savci   +2 more
doaj   +2 more sources

Efficient Radar-Target Assignment in Low Probability of Intercept Radar Networks: A Machine-Learning Approach

open access: yesIEEE Open Journal of the Communications Society, 2023
To achieve low probability of intercept (LPI) in radar networks for multiple target detection, it is necessary to find the optimal assignment of distributed radars to targets.
Hamid Amiriara   +2 more
doaj   +2 more sources

A Deep Reinforcement Learning Method with a Low Intercept Probability in a Netted Synthetic Aperture Radar

open access: yesRemote Sensing
A deep reinforcement learning (DRL)-based power allocation method is proposed to achieve a low probability of intercept (LPI) in a netted synthetic aperture radar (SAR).
Longhao Xie   +3 more
doaj   +2 more sources

A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

open access: yesSensors, 2016
Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI) performance for target ...
Ji She, Fei Wang, Jianjiang Zhou
exaly   +3 more sources

Automatic LPI Radar Waveform Recognition Using CNN

open access: yesIEEE Access, 2018
Detecting and classifying the modulation scheme of the intercepted noisy low probability of intercept (LPI) radar signals in real time is a necessary survival technique required in the electronic warfare systems. Therefore, LPI radar waveform recognition
Seung-Hyun Kong   +2 more
exaly   +3 more sources

RLC3-LPI: A Reinforcement Learning-Based Multi-UAV Cooperative Communication Coverage Algorithm With Low Interception Probability

open access: yesIEEE Open Journal of Vehicular Technology
In low-altitude applications, Unmanned Aerial Vehicles (UAVs) have gained widespread adoption, expanding their roles across diverse domains such as search and rescue, communication coverage, and security surveillance.
Shihong Zhao   +4 more
doaj   +2 more sources

Low Probability of Intercept/Detect (LPI/LPD) Secure Communications Using Antenna Arrays Employing Rapid Sidelobe Time Modulation

open access: yesIEEE Transactions on Antennas and Propagation
We present an electronically-reconfigurable antenna array offering low probability of intercept/detect (LPI/LPD) and secure communications capabilities simultaneously at the physical layer. This antenna array is designed to provide rapidly time-varying sidelobes and a stationary main lobe. By performing rapid sidelobe time modulation (SLTM), the signal
Jiahao Zhao   +2 more
exaly   +3 more sources

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