Swift Burst Alert Telescope (BAT) Instrument Response

2004 ◽  
Author(s):  
A. Parsons
Keyword(s):  
Instrument Response ◽  
Burst Alert Telescope

Burst Alert Telescope (BAT) instrument response generation

2004 ◽  
Author(s):  
Derek D. Hullinger ◽  
Ann M. Parsons ◽  
Goro Sato
Keyword(s):  
Instrument Response ◽  
Burst Alert Telescope

scholarly journals Self-quenching of uranin: Instrument response function for color sensitive photo-detectors

2010 ◽  
Vol 130 (12) ◽  
pp. 2446-2451 ◽  
Author(s):  
Rafal Luchowski ◽  
Sushant Sabnis ◽  
Mariusz Szabelski ◽  
Pabak Sarkar ◽  
Sangram Raut ◽  
...  
Keyword(s):  
Response Function ◽  
Instrument Response Function ◽  
Instrument Response ◽  
Photo Detectors

scholarly journals Increasing the accuracy and temporal resolution of two-filter radon–222 measurements by correcting for the instrument response

2016 ◽  
Vol 9 (6) ◽  
pp. 2689-2707 ◽  
Author(s):  
Alan D. Griffiths ◽  
Scott D. Chambers ◽  
Alastair G. Williams ◽  
Sylvester Werczynski
Keyword(s):  
Temporal Resolution ◽  
Radon Concentration ◽  
Time Response ◽  
Slow Time ◽  
Flow Loop ◽  
Detector Performance ◽  
Convective Boundary ◽  
Near Surface ◽  
Instrument Response

Abstract. Dual-flow-loop two-filter radon detectors have a slow time response, which can affect the interpretation of their output when making continuous observations of near-surface atmospheric radon concentrations. While concentrations are routinely reported hourly, a calibrated model of detector performance shows that ∼ 40 % of the signal arrives more than an hour after a radon pulse is delivered. After investigating several possible ways to correct for the detector's slow time response, we show that a Bayesian approach using a Markov chain Monte Carlo sampler is an effective method. After deconvolution, the detector's output is redistributed into the appropriate counting interval and a 10 min temporal resolution can be achieved under test conditions when the radon concentration is controlled. In the case of existing archived observations, collected under less ideal conditions, the data can be retrospectively reprocessed at 30 min resolution. In one case study, we demonstrate that a deconvolved radon time series was consistent with the following: measurements from a fast-response carbon dioxide monitor; grab samples from an aircraft; and a simple mixing height model. In another case study, during a period of stable nights and days with well-developed convective boundary layers, a bias of 18 % in the mean daily minimum radon concentration was eliminated by correcting for the instrument response.

The Konus-Wind and Konus-A instrument response functions and the spectral deconvolution procedure

1998 ◽  
Author(s):  
M. M. Terekhov ◽  
R. L. Aptekar ◽  
D. D. Frederiks ◽  
S. V. Golenetskii ◽  
V. N. Il’inskii ◽  
...  
Keyword(s):  
Response Functions ◽  
Spectral Deconvolution ◽  
Instrument Response

Empirical Investigations of the Instrument Response for Distributed Acoustic Sensing (DAS) across 17 Octaves

2020 ◽  
Author(s):  
Patrick Paitz ◽  
Pascal Edme ◽  
Dominik Gräff ◽  
Fabian Walter ◽  
Joseph Doetsch ◽  
...  
Keyword(s):  
Ground Motion ◽  
Urban Areas ◽  
Waveform Inversion ◽  
Acoustic Sensing ◽  
Full Waveform ◽  
Environmental Properties ◽  
Instrument Response ◽  
Distributed Acoustic Sensing ◽  
Reference Measurements ◽  
Seismic Networks

ABSTRACT With the potential of high temporal and spatial sampling and the capability of utilizing existing fiber-optic infrastructure, distributed acoustic sensing (DAS) is in the process of revolutionizing geophysical ground-motion measurements, especially in remote and urban areas, where conventional seismic networks may be difficult to deploy. Yet, for DAS to become an established method, we must ensure that accurate amplitude and phase information can be obtained. Furthermore, as DAS is spreading into many different application domains, we need to understand the extent to which the instrument response depends on the local environmental properties. Based on recent DAS response research, we present a general workflow to empirically quantify the quality of DAS measurements based on the transfer function between true ground motion and observed DAS waveforms. With a variety of DAS data and reference measurements, we adapt existing instrument-response workflows typically in the frequency band from 0.01 to 10 Hz to different experiments, with signal frequencies ranging from 1/3000 to 60 Hz. These experiments include earthquake recordings in an underground rock laboratory, hydraulic injection experiments in granite, active seismics in agricultural soil, and icequake recordings in snow on a glacier. The results show that the average standard deviations of both amplitude and phase responses within the analyzed frequency ranges are in the order of 4 dB and 0.167π radians, respectively, among all experiments. Possible explanations for variations in the instrument responses include the violation of the assumption of constant phase velocities within the workflow due to dispersion and incorrect ground-motion observations from reference measurements. The results encourage further integration of DAS-based strain measurements into methods that exploit complete waveforms and not merely travel times, such as full-waveform inversion. Ultimately, our developments are intended to provide a quantitative assessment of site- and frequency-dependent DAS data that may help establish best practices for upcoming DAS surveys.

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