scholarly journals Detection and Localization of Terrestrial L Band RFI with GNSS Receivers

2021 ◽  
Author(s):  
Max Roberts ◽  
Thomas K. Meehan ◽  
Jeffery Y. Tien ◽  
Lawrence E. Young
Keyword(s):  
Signal To Noise Ratio ◽  
Precise Orbit Determination ◽  
Detection Algorithm ◽  
Measured Signal ◽  
Regional Conflicts ◽  
Wide Range ◽  
Initial Work ◽  
Gnss Receivers ◽  
Highly Sensitive Detection ◽  
Detection And Localization

GNSS signals are critically important for a wide range of commercial, military, and science applications. Recent studies have identified threats to the performance of GNSS from both intended and unintended sources of radio frequency interference (RFI). Understanding the distribution of the sources of RFI and the nature of the signals they are emitting is critical to determine and mitigate their effects on the measurements made by GNSS receivers. Terrestrial RFI can be substantially detrimental to the received GNSS signals, affecting the interpretation of related science measurements. NASA's Blackjack/TriG GNSS receivers are used for precise-orbit determination and radio occultation measurements, providing a data record spanning most of the Earth’s surface for nearly 20 years. We have developed a highly sensitive detection algorithm which uses variations in the measured signal to noise ratio (SNR), on the order of 10-50 seconds, common to all satellites to identify times and locations subject to RFI. Initial work has focused primarily on detection of the presence of RFI and using the receiver’s orbital solution to record the location of detection events. Our inter-mission analysis creates a unique record of global RFI with the potential for a) rigorous detection of the presence of interfering signals during science measurements, b) geolocation of RFI sources, and c) characterization of the nature of the transmitted signal to better identify intent. Preliminary analysis has shown the presence of RFI is well correlated with regional conflicts and other geopolitical activity.

scholarly journals Detection and Localization of Terrestrial L Band RFI with GNSS Receivers

2021 ◽  
Author(s):  
Max Roberts ◽  
Thomas K. Meehan ◽  
Paul R. Straus ◽  
Jeffery Y. Tien ◽  
Bonnie L. Valant-Weiss ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Precise Orbit Determination ◽  
Detection Algorithm ◽  
Measured Signal ◽  
Regional Conflicts ◽  
Wide Range ◽  
Initial Work ◽  
Gnss Receivers ◽  
Highly Sensitive Detection ◽  
Detection And Localization

GNSS signals are critically important for a wide range of commercial, military, and science applications. Recent studies have identified threats to the performance of GNSS from both intended and unintended sources of radio frequency interference (RFI). Understanding the distribution of the sources of RFI and the nature of the signals they are emitting is critical to determine and mitigate their effects on the measurements made by GNSS receivers. Terrestrial RFI can be substantially detrimental to the received GNSS signals, affecting the interpretation of related science measurements. NASA's Blackjack/TriG GNSS receivers are used for precise-orbit determination and radio occultation measurements, providing a data record spanning most of the Earth’s surface for nearly 20 years. We have developed a highly sensitive detection algorithm which uses variations in the measured signal to noise ratio (SNR), on the order of 10-50 seconds, common to all satellites to identify times and locations subject to RFI. Initial work has focused primarily on detection of the presence of RFI and using the receiver’s orbital solution to record the location of detection events. Our inter-mission analysis creates a unique record of global RFI with the potential for a) rigorous detection of the presence of interfering signals during science measurements, b) geolocation of RFI sources, and c) characterization of the nature of the transmitted signal to better identify intent. Preliminary analysis has shown the presence of RFI is well correlated with regional conflicts and other geopolitical activity.

scholarly journals Detection and Localization of Terrestrial L Band RFI with GNSS Receivers

2021 ◽  
Author(s):  
Max Roberts ◽  
Thomas K. Meehan ◽  
Paul R. Straus ◽  
Jeffery Y. Tien ◽  
Bonnie L. Valant-Weiss ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Precise Orbit Determination ◽  
Detection Algorithm ◽  
Measured Signal ◽  
Regional Conflicts ◽  
Wide Range ◽  
Initial Work ◽  
Gnss Receivers ◽  
Highly Sensitive Detection ◽  
Detection And Localization

GNSS signals are critically important for a wide range of commercial, military, and science applications. Recent studies have identified threats to the performance of GNSS from both intended and unintended sources of radio frequency interference (RFI). Understanding the distribution of the sources of RFI and the nature of the signals they are emitting is critical to determine and mitigate their effects on the measurements made by GNSS receivers. Terrestrial RFI can be substantially detrimental to the received GNSS signals, affecting the interpretation of related science measurements. NASA's Blackjack/TriG GNSS receivers are used for precise-orbit determination and radio occultation measurements, providing a data record spanning most of the Earth’s surface for nearly 20 years. We have developed a highly sensitive detection algorithm which uses variations in the measured signal to noise ratio (SNR), on the order of 10-50 seconds, common to all satellites to identify times and locations subject to RFI. Initial work has focused primarily on detection of the presence of RFI and using the receiver’s orbital solution to record the location of detection events. Our inter-mission analysis creates a unique record of global RFI with the potential for a) rigorous detection of the presence of interfering signals during science measurements, b) geolocation of RFI sources, and c) characterization of the nature of the transmitted signal to better identify intent. Preliminary analysis has shown the presence of RFI is well correlated with regional conflicts and other geopolitical activity.

Read, Understand, Learn, & Excel: Development and Testing of an Automated Reading Strategy Detection Algorithm for Postsecondary Students

2019 ◽  
Vol 28 (3) ◽  
pp. 1257-1267 ◽  
Author(s):  
Priya Kucheria ◽  
McKay Moore Sohlberg ◽  
Jason Prideaux ◽  
Stephen Fickas
Keyword(s):  
Academic Success ◽  
Undergraduate Students ◽  
Expository Text ◽  
Reading Strategy ◽  
Detection Algorithm ◽  
Expository Texts ◽  
Human Observer ◽  
Behavioral Strategies ◽  
Periodic Review ◽  
Wide Range

PurposeAn important predictor of postsecondary academic success is an individual's reading comprehension skills. Postsecondary readers apply a wide range of behavioral strategies to process text for learning purposes. Currently, no tools exist to detect a reader's use of strategies. The primary aim of this study was to develop Read, Understand, Learn, & Excel, an automated tool designed to detect reading strategy use and explore its accuracy in detecting strategies when students read digital, expository text.MethodAn iterative design was used to develop the computer algorithm for detecting 9 reading strategies. Twelve undergraduate students read 2 expository texts that were equated for length and complexity. A human observer documented the strategies employed by each reader, whereas the computer used digital sequences to detect the same strategies. Data were then coded and analyzed to determine agreement between the 2 sources of strategy detection (i.e., the computer and the observer).ResultsAgreement between the computer- and human-coded strategies was 75% or higher for 6 out of the 9 strategies. Only 3 out of the 9 strategies–previewing content, evaluating amount of remaining text, and periodic review and/or iterative summarizing–had less than 60% agreement.ConclusionRead, Understand, Learn, & Excel provides proof of concept that a reader's approach to engaging with academic text can be objectively and automatically captured. Clinical implications and suggestions to improve the sensitivity of the code are discussed.Supplemental Materialhttps://doi.org/10.23641/asha.8204786

scholarly journals Line-of-Sight Winds and Doppler Effect Smearing in ACE-FTS Solar Occultation Measurements

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 680
Author(s):  
Chris D. Boone ◽  
Johnathan Steffen ◽  
Jeff Crouse ◽  
Peter F. Bernath
Keyword(s):  
Atmospheric Chemistry ◽  
Doppler Effect ◽  
Line Of Sight ◽  
Measured Signal ◽  
Mixing Ratio ◽  
Model Calculations ◽  
Doppler Shifts ◽  
Solar Occultation ◽  
Wide Range ◽  
Wind Profiles

Line-of-sight wind profiles are derived from Doppler shifts in infrared solar occultation measurements from the Atmospheric Chemistry Experiment Fourier transform spectrometers (ACE-FTS), the primary instrument on SCISAT, a satellite-based mission for monitoring the Earth’s atmosphere. Comparisons suggest a possible eastward bias from 20 m/s to 30 m/s in ACE-FTS results above 80 km relative to some datasets but no persistent bias relative to other datasets. For instruments operating in a limb geometry, looking through a wide range of altitudes, smearing of the Doppler effect along the line of sight can impact the measured signal, particularly for saturated absorption lines. Implications of Doppler effect smearing are investigated for forward model calculations and volume mixing ratio retrievals. Effects are generally small enough to be safely ignored, except for molecules having a large overhang in their volume mixing ratio profile, such as carbon monoxide.

scholarly journals Detectivity optimization to detect of ultraweak light fluxes with an EM-CCD as binary photon counter array

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ibtissame Khaoua ◽  
Guillaume Graciani ◽  
Andrey Kim ◽  
François Amblard
Keyword(s):  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Photon Counting ◽  
Detection Methods ◽  
Strong Nonlinearity ◽  
Wide Range ◽  
Depth Analysis ◽  
Spatially Extended ◽  
Extended Sources ◽  
Photon Counting Mode

AbstractFor a wide range of purposes, one faces the challenge to detect light from extremely faint and spatially extended sources. In such cases, detector noises dominate over the photon noise of the source, and quantum detectors in photon counting mode are generally the best option. Here, we combine a statistical model with an in-depth analysis of detector noises and calibration experiments, and we show that visible light can be detected with an electron-multiplying charge-coupled devices (EM-CCD) with a signal-to-noise ratio (SNR) of 3 for fluxes less than $$30\,{\text{photon}}\,{\text{s}}^{ - 1} \,{\text{cm}}^{ - 2}$$ 30 photon s - 1 cm - 2 . For green photons, this corresponds to 12 aW $${\text{cm}}^{ - 2}$$ cm - 2 ≈ $$9{ } \times 10^{ - 11}$$ 9 × 10 - 11 lux, i.e. 15 orders of magnitude less than typical daylight. The strong nonlinearity of the SNR with the sampling time leads to a dynamic range of detection of 4 orders of magnitude. To detect possibly varying light fluxes, we operate in conditions of maximal detectivity $${\mathcal{D}}$$ D rather than maximal SNR. Given the quantum efficiency $$QE\left( \lambda \right)$$ Q E λ of the detector, we find $${ \mathcal{D}} = 0.015\,{\text{photon}}^{ - 1} \,{\text{s}}^{1/2} \,{\text{cm}}$$ D = 0.015 photon - 1 s 1 / 2 cm , and a non-negligible sensitivity to blackbody radiation for T > 50 °C. This work should help design highly sensitive luminescence detection methods and develop experiments to explore dynamic phenomena involving ultra-weak luminescence in biology, chemistry, and material sciences.

Modal frequencies of bridges from GNSS (GPS) monitoring data: Experimental, statistical evidence

2021 ◽  
Vol 17 (1-2) ◽  
pp. 3-14
Author(s):  
Stathis C. Stiros ◽  
F. Moschas ◽  
P. Triantafyllidis
Keyword(s):  
Signal To Noise Ratio ◽  
Vertical Axis ◽  
Bridge Monitoring ◽  
Low Snr ◽  
True Value ◽  
Gps Satellites ◽  
Wide Range ◽  
Spectral Peaks ◽  
Monitoring Survey ◽  
True Frequency

GNSS technology (known especially for GPS satellites) for measurement of deflections has proved very efficient and useful in bridge structural monitoring, even for short stiff bridges, especially after the advent of 100 Hz GNSS sensors. Mode computation from dynamic deflections has been proposed as one of the applications of this technology. Apart from formal modal analyses with GNSS input, and from spectral analysis of controlled free attenuating oscillations, it has been argued that simple spectra of deflections can define more than one modal frequencies. To test this scenario, we analyzed 21 controlled excitation events from a certain bridge monitoring survey, focusing on lateral and vertical deflections, recorded both by GNSS and an accelerometer. These events contain a transient and a following oscillation, and they are preceded and followed by intervals of quiescence and ambient vibrations. Spectra for each event, for the lateral and the vertical axis of the bridge, and for and each instrument (GNSS, accelerometer) were computed, normalized to their maximum value, and printed one over the other, in order to produce a single composite spectrum for each of the four sets. In these four sets, there was also marked the true value of modal frequency, derived from free attenuating oscillations. It was found that for high SNR (signal-to-noise ratio) deflections, spectral peaks in both acceleration and displacement spectra differ by up to 0.3 Hz from the true value. For low SNR, defections spectra do not match the true frequency, but acceleration spectra provide a low-precision estimate of the true frequency. This is because various excitation effects (traffic, wind etc.) contribute with numerous peaks in a wide range of frequencies. Reliable estimates of modal frequencies can hence be derived from deflections spectra only if excitation frequencies (mostly traffic and wind) can be filtered along with most measurement noise, on the basis of additional data.

Joseph Edkins and the “Discovery” of Early Chinese: the linguistic ideas behind the first (partial) reconstruction of the sound system of Early Chinese

2019 ◽  
Vol 29 (3) ◽  
pp. 519-541
Author(s):  
GIORGIO ORLANDI
Keyword(s):  
Chinese Language ◽  
Sound System ◽  
Partial Reconstruction ◽  
Wide Range ◽  
Initial Work ◽  
Sinitic Languages

AbstractThe ‘discovery’ of early Chinese, and its subsequent reconstruction, have allowed the modern linguist to reach a wide range of firm conclusions about the Chinese language and its position within the Tibeto-Burman family. Reverend Joseph Edkins (1823–1905) should be credited with initial work on early Chinese as the ancestor language of the various Sinitic languages, and with its first partial reconstruction. This article is an attempt to supply at least a first historical guide for those interested in obtaining a better understanding of the implicit discovery of Sinitic and the first reconstructions of early Chinese.

scholarly journals A Nanoplasmonic-Based Biosensing Approach for Wide-Range and Highly Sensitive Detection of Chemicals

Nanomaterials ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1961
Author(s):  
Francesco Arcadio ◽  
Luigi Zeni ◽  
Aldo Minardo ◽  
Caterina Eramo ◽  
Stefania Di Di Ronza ◽  
...  
Keyword(s):  
Optical Fibers ◽  
Limit Of Detection ◽  
Slab Waveguide ◽  
Grating Pattern ◽  
Transparent Substrate ◽  
Synthetic Receptor ◽  
Sensing Applications ◽  
Wide Range ◽  
Plastic Optical Fibers ◽  
Highly Sensitive Detection

In a specific biosensing application, a nanoplasmonic sensor chip has been tested by an experimental setup based on an aluminum holder and two plastic optical fibers used to illuminate and collect the transmitted light. The studied plasmonic probe is based on gold nanograting, realized on the top of a Poly(methyl methacrylate) (PMMA) chip. The PMMA substrate could be considered as a transparent substrate and, in such a way, it has been already used in previous work. Alternatively, here it is regarded as a slab waveguide. In particular, we have deposited upon the slab surface, covered with a nanograting, a synthetic receptor specific for bovine serum albumin (BSA), to test the proposed biosensing approach. Exploiting this different experimental configuration, we have determined how the orientation of the nanostripes forming the grating pattern, with respect to the direction of the input light (longitudinal or orthogonal), influences the biosensing performances. For example, the best limit of detection (LOD) in the BSA detection that has been obtained is equal to 23 pM. Specifically, the longitudinal configuration is characterized by two observable plasmonic phenomena, each sensitive to a different BSA concentration range, ranging from pM to µM. This aspect plays a key role in several biochemical sensing applications, where a wide working range is required.

Head Instability Detection for Testing Process in Perpendicular Magnetic Recording System

2013 ◽  
Vol 770 ◽  
pp. 319-322 ◽  
Author(s):  
Piya Kovintavewat ◽  
Santi Koonkarnkhai ◽  
Aimamorn Suvichakorn
Keyword(s):  
Magnetic Recording ◽  
Signal To Noise Ratio ◽  
Disk Drive ◽  
Detection Algorithm ◽  
Recording System ◽  
High Signal ◽  
Signal To Noise ◽  
Perpendicular Magnetic Recording ◽  
Read Head ◽  
Pass Through

During hard disk drive (HDD) testing process, the magneto-resistive read (MR) head is analyzed and checked if the head is defective or not. Baseline popping (BLP) is one of the crucial problems caused by head instability, whose effect can distort the readback signal to the extent of causing possible sector read failure. Without BLP detection algorithm, the defective read head might pass through HDD assembling process, thus producing an unreliable HDD. This situation must be prevented so as to retain customer satisfaction. This paper proposes a simple (but efficient) BLP detection algorithm for perpendicular magnetic recording systems. Results show that the proposed algorithm outperforms the conventional one in terms of both the percentage of detection and the percentage of false alarm, when operating at high signal-to-noise ratio.

Localized Acoustic-Event Measurement Probe: Connector Confirmation Utilizing Acoustic Signatures

2020 ◽  
Author(s):  
Brian Skoglind ◽  
Travis Roberts ◽  
Sourabh Karmakar ◽  
Cameron Turner ◽  
Laine Mears
Keyword(s):  
Background Noise ◽  
Signal To Noise Ratio ◽  
Detection Algorithm ◽  
Consumer Products ◽  
Noise Mitigation ◽  
Acoustic Event ◽  
Electrical Connection ◽  
Acoustic Signatures ◽  
Electrical Connector ◽  
Electrical Connections

Abstract Electrical connections in consumer products are typically made manually rather than through automated assembly systems due to the high variety of connector types and connector positions, and the soft flexible nature of their structures. Manual connections are prone to failure through missed or improper connections in the assembly process and can lead to unexpected downtime and expensive rework. Past approaches for registering connection success such as vision verification or Augmented Reality have shown limited ability to verify correct connection state. However, the feasibility of an acoustic-based verification system for electrical connector confirmation has not been extensively researched. One of the major problems preventing acoustic based verification in a manufacturing or assembly environment is the typically low signal to noise ratio (SNR) between the sound of an electrical connection and the diverse soundscape of the plant. In this study, a physical means of background noise mitigation and signature amplification are investigated in order to increase the SNR between the electrical connection and the plant soundscape in order to improve detection. The concept is that an increase in the SNR will lead to an improvement in the accuracy and robustness of an acoustic event detection and classification system. Digital filtering has been used in the past to deal with low SNRs, however, it runs the risk of filtering out potential important features for classification. A sensor platform is designed to filter out and reduce background noise from the plant without effecting the raw acoustic signal of the electrical connection, and an automated detection algorithm is presented. The solution is over 75% effective at detecting and classifying connections.

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