detector output
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Author(s):  
David Kulla ◽  
Samuel A Lazerson ◽  
Sibylle Günter ◽  
Matthias Hirsch ◽  
Dirk Hartmann ◽  
...  

Abstract In light of measuring the fast ionized particle confinement in the stellarator Wendelstein 7-X, particles generated by the neutral beam injection system are simulated to determine the placement of an array of faraday-cup fast ion loss detectors. This array is important due to the localization of the loss pattern, which changes drastically with experimental parameters. The Monte Carlo codes BEAMS3D and ASCOT5 are used for the simulations, following the particles from injection to wall collision. Different magnetic configurations and plasma pressures are investigated in this manner, and a configuration suitable for measuring the loss fraction is found. It qualitatively reproduces the global losses, is installable in locations of current carbon wall-tiles and the individual detector output appears well-suited for experimental purposes.


2021 ◽  
Author(s):  
Donatella Darsena ◽  
Giacinto Gelli ◽  
Ivan Iudice ◽  
Francesco Verde

Unmanned aerial vehicles (UAVs) can be integrated into wireless sensor networks (WSNs) for smart city applications in several ways. Among them, a UAV can be employed as a relay in a “store-carry and forward” fashion by uploading data from ground sensors and metering devices and, then, downloading it to a central unit. However, both the uploading and downloading phases can be prone to potential threats and attacks. As a legacy from traditional wireless networks, the jamming attack is still one of the major and serious threats to UAV-aided communications, especially when also the jammer is mobile, e.g., it is mounted on a UAV or inside a terrestrial vehicle. In this paper, we investigate anti-jamming communications for UAV-aided WSNs operating over doubly-selective channels in the downloading phase. In such a scenario, the signals transmitted by the UAV and the malicious mobile jammer undergo both time dispersion due to multipath propagation effects and frequency dispersion caused by their mobility. To suppress high-power jamming signals, we propose a blind physical-layer technique that jointly detects the UAV and jammer symbols through serial disturbance cancellation based on symbol-level post-sorting of the detector output. Amplitudes, phases, time delays, and Doppler shifts – required to implement the proposed detection strategy – are blindly estimated from data through the use of algorithms that exploit the almost-cyclostationarity properties of the received signal and the detailed structure of multicarrier modulation format. Simulation results corroborate the anti-jamming capabilities of the proposed method, for different mobility scenarios of the jammer.


2021 ◽  
Author(s):  
Donatella Darsena ◽  
Giacinto Gelli ◽  
Ivan Iudice ◽  
Francesco Verde

Unmanned aerial vehicles (UAVs) can be integrated into wireless sensor networks (WSNs) for smart city applications in several ways. Among them, a UAV can be employed as a relay in a “store-carry and forward” fashion by uploading data from ground sensors and metering devices and, then, downloading it to a central unit. However, both the uploading and downloading phases can be prone to potential threats and attacks. As a legacy from traditional wireless networks, the jamming attack is still one of the major and serious threats to UAV-aided communications, especially when also the jammer is mobile, e.g., it is mounted on a UAV or inside a terrestrial vehicle. In this paper, we investigate anti-jamming communications for UAV-aided WSNs operating over doubly-selective channels in the downloading phase. In such a scenario, the signals transmitted by the UAV and the malicious mobile jammer undergo both time dispersion due to multipath propagation effects and frequency dispersion caused by their mobility. To suppress high-power jamming signals, we propose a blind physical-layer technique that jointly detects the UAV and jammer symbols through serial disturbance cancellation based on symbol-level post-sorting of the detector output. Amplitudes, phases, time delays, and Doppler shifts – required to implement the proposed detection strategy – are blindly estimated from data through the use of algorithms that exploit the almost-cyclostationarity properties of the received signal and the detailed structure of multicarrier modulation format. Simulation results corroborate the anti-jamming capabilities of the proposed method, for different mobility scenarios of the jammer.


2021 ◽  
Author(s):  
Donatella Darsena ◽  
Giacinto Gelli ◽  
Ivan Iudice ◽  
Francesco Verde

Unmanned aerial vehicles (UAVs) can be integrated into wireless sensor networks (WSNs) for smart city applications in several ways. Among them, a UAV can be employed as a relay in a “store-carry and forward” fashion by uploading data from ground sensors and metering devices and, then, downloading it to a central unit. However, both the uploading and downloading phases can be prone to potential threats and attacks. As a legacy from traditional wireless networks, the jamming attack is still one of the major and serious threats to UAV-aided communications, especially when also the jammer is mobile, e.g., it is mounted on a UAV or inside a terrestrial vehicle. In this paper, we investigate anti-jamming communications for UAV-aided WSNs operating over doubly-selective channels in the downloading phase. In such a scenario, the signals transmitted by the UAV and the malicious mobile jammer undergo both time dispersion due to multipath propagation effects and frequency dispersion caused by their mobility. To suppress high-power jamming signals, we propose a blind physical-layer technique that jointly detects the UAV and jammer symbols through serial disturbance cancellation based on symbol-level post-sorting of the detector output. Amplitudes, phases, time delays, and Doppler shifts – required to implement the proposed detection strategy – are blindly estimated from data through the use of algorithms that exploit the almost-cyclostationarity properties of the received signal and the detailed structure of multicarrier modulation format. Simulation results corroborate the anti-jamming capabilities of the proposed method, for different mobility scenarios of the jammer.


Author(s):  
T Akutsu ◽  
M Ando ◽  
K Arai ◽  
Y Arai ◽  
S Araki ◽  
...  

Abstract KAGRA is a newly built gravitational wave observatory, a laser interferometer with a 3 km arm length, located in Kamioka, Gifu, Japan. In this series of articles, we present an overview of the baseline KAGRA, for which we finished installing the designed configuration in 2019. This article describes the method of calibration (CAL) used for reconstructing gravitational wave signals from the detector outputs, as well as the characterization of the detector (DET). We also review the physical environmental monitors (PEM) system and the geophysics interferometer (GIF). Both are used for characterizing and evaluating the data quality of the gravitational wave channel. They play important roles in utilizing the detector output for gravitational wave searches. These characterization investigations will be even more important in the near future, once gravitational wave detection has been achieved, and in using KAGRA in the gravitational wave astronomy era.


Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2525
Author(s):  
Robert Krupiński ◽  
Eugeniusz Kornatowski

Vibroacoustic diagnostics (VM—Vibroacoustic Method) is one of the methods for diagnosing the active part of power transformers. Measurement technologies have been refined over the past several years, but the methods of analyzing data obtained in VM diagnostics are still in development. In most cases, they are based on a simple frequency spectrum analysis, and the diagnostic conclusions are subjective and depend on the expert’s professional experience. The article presents an objective method for the detection of transformer unit core damage, based on the analysis of the statistical properties of the vibration signal registered on the surface of the tank of an unloaded transformer in the steady state of vibrations (VM). The algorithm for proceeding further is: FFT analysis of the vibroacoustic signal, with the determination of the relative changes in vibration power as a function of frequency P r ( f ) and, finally, the determination of the statistic properties of the dataset P r ( f ) . The Generalized Gaussian Distribution (GGD) is used to describe the P r ( f ) set. The detector output values are the λ and p parameters of the GGD distribution. These two numerical values form the basis for the classification of the technical condition of the transformer unit core. The correctness of the described solution was verified on the example of ten pieces of 16 MVA power transformers with different operating times and degrees of wear.


Physics ◽  
2019 ◽  
Vol 1 (3) ◽  
pp. 360-374
Author(s):  
Riccardo Maria Liberati ◽  
Alessio Del Paggio ◽  
Massimiliano Rossi

We propose a method for the estimation of the spectral response of a photodetector, using only the variation of the temperature of a black body source without the need of an expensive monochromator or a circular filter. The proposed method is suitable especially for infrared detectors in which the cut-off wavelength and the responsivity vs. wavelength is not exactly known. The method provides a rough estimation of the spectral response solving a Fredholm integral equation of the first kind. The precision of this technique depends on the temperatures at which the detector output is measured. Some examples are given for illustration.


2019 ◽  
Vol 6 (6) ◽  
Author(s):  
Gregor Kasieczka ◽  
Nicholas Kiefer ◽  
Tilman Plehn ◽  
Jennifer Thompson

Distinguishing quarks from gluons based on low-level detector output is one of the most challenging applications of multi-variate and machine learning techniques at the LHC. We first show the performance of our 4-vector-based LoLa tagger without and after considering detector effects. We then discuss two benchmark applications, mono-jet searches with a gluon-rich signal and di-jet resonances with a quark-rich signal. In both cases an immediate benefit compared to the standard event-level analysis exists.


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