scholarly journals An Overall Assessment of JPSS-2 VIIRS Radiometric Performance Based on Pre-launch Testing

2018 ◽  
Author(s):  
Hassan Oudrari ◽  
Jeffrey McIntire ◽  
Xiaoxiong Xiong ◽  
James Butler ◽  
Qiang Ji ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Infrared Imaging ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Scattered Light ◽  
Light Response ◽  
Satellite System ◽  
Sensor Data ◽  
Polarization Sensitivity ◽  
Spectral Performance

The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the second Joint Polar Satellite System (JPSS) completed its sensor level testing in February 2018. The JPSS-2 (J2) mission is scheduled to launch in 2022, and will be very similar to its two predecessor missions, the Suomi National Polar-orbiting Partnership (SNPP) mission, launched on 28 October 2011, and JPSS-1 (renamed NOAA-20) launched on 18 November 2017. VIIRS instrument has 22 spectral bands covering the spectrum between 0.4 and 12.6 mircron: 14 reflective solar bands (RSB), 7 thermal emissive bands (TEB), and one day-night band (DNB). It is a cross-track scanning radiometer capable of providing global measurements through observations at two spatial resolutions, 375 m and 750 m at nadir for the imaging bands and moderate bands, respectively. This paper will provide an overview of J2 VIIRS characterization methodologies and calibration performance during the pre-launch testing phases performed by the National Aeronautics and Space Administration (NASA) VIIRS Characterization Support Team (VCST) to evaluate the at-launch baseline radiometric performance and generate the parameters needed to populate the sensor data record (SDR) Look-Up-Tables (LUTs). Key sensor performance metrics include the signal to noise ratio (SNR), radiance dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, spectral performance, response versus scan-angle (RVS), and scattered light response. A set of performance metrics generated during the pre-launch testing program will be compared to both the SNPP and JPSS-1 VIIRS sensors.

scholarly journals An Overall Assessment of JPSS-2 VIIRS Radiometric Performance Based on Pre-Launch Testing

2018 ◽  
Vol 10 (12) ◽  
pp. 1921 ◽  
Author(s):  
Hassan Oudrari ◽  
Jeff McIntire ◽  
Xiaoxiong Xiong ◽  
James Butler ◽  
Qiang Ji ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Infrared Imaging ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Scattered Light ◽  
Light Response ◽  
Satellite System ◽  
Sensor Data ◽  
Polarization Sensitivity ◽  
Spectral Performance

The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the second Joint Polar Satellite System (JPSS) completed its sensor level testing in February 2018. The JPSS-2 (J2) mission is scheduled to launch in 2022 and will be very similar to its two predecessor missions, the Suomi National Polar-orbiting Partnership (SNPP) mission, launched on 28 October 2011 and JPSS-1 (renamed NOAA-20) launched on 18 November 2017. VIIRS instrument has 22 spectral bands covering the spectrum between 0.4 and 12.6 μm: 14 reflective solar bands (RSB), 7 thermal emissive bands (TEB) and one day-night band (DNB). It is a cross-track scanning radiometer capable of providing global measurements through observations at two spatial resolutions, 375 m and 750 m at nadir for the imaging bands and moderate bands, respectively. This paper will provide an overview of J2 VIIRS characterization methodologies and calibration performance during the pre-launch testing phases performed by the National Aeronautics and Space Administration (NASA) VIIRS Characterization Support Team (VCST) to evaluate the at-launch baseline radiometric performance and generate the parameters needed to populate the sensor data record (SDR) Look-Up-Tables (LUTs). Our analysis results confirmed the good performance of J2 VIIRS, in general as good as previous VIIRS instruments and all non-compliances are expected to have low impact on data quality. Key sensor performance metrics include the signal to noise ratio (SNR), radiance dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, spectral performance, response versus scan-angle (RVS) and scattered light response. A set of performance metrics generated during the pre-launch testing program will be compared to both the SNPP and JPSS-1 VIIRS sensors.

scholarly journals Pre-launch Radiometric Characterization of JPSS-2 VIIRS Thermal Emissive Bands

2019 ◽  
Vol 11 (6) ◽  
pp. 732
Author(s):  
Jeff McIntire ◽  
David Moyer ◽  
Hassan Oudrari ◽  
Xiaoxiong Xiong
Keyword(s):  
Performance Metrics ◽  
Infrared Imaging ◽  
Dynamic Range ◽  
Satellite System ◽  
Quality Data ◽  
Climate Data ◽  
Environmental Testing ◽  
Improved Performance ◽  
Estimation Of Uncertainties ◽  
Thermal Band

The Joint Polar Satellite System 2 (JPSS-2) Visible Infrared Imaging Radiometer Suite (VIIRS) is the third in its series of sensors designed to produce high quality data products for environmental and climate data records once launched. To meet this goal, the VIIRS instrument must be calibrated and characterized prior to launch. A comprehensive test program was conducted at the Raytheon Space and Airborne Systems facility in 2016–2017, including extensive environmental testing. The pre-launch thermal band radiometric performance and stability is the focus of this work including: the evaluation of a number of sensor performance metrics, comparison to the design requirements, and the estimation of uncertainties. Comparisons of the thermal band performance to the earlier Suomi National Polar-orbiting Partnership (SNPP) and JPSS-1 VIIRS instruments as well as the design specifications have shown that JPSS-2 VIIRS exhibits similar performance to its predecessors. The differences of note (decreased blackbody uniformity, reduced dynamic range for bands M15 and M16, and improved performance with respect to striping) are small and not expected to have a significant impact on the science products.

scholarly journals Estimation and Correction of Sampling Time Offsets in Tiadcs using Optimization Algorithm

2020 ◽  
Vol 9 (4) ◽  
pp. 1217-1222
Keyword(s):  
Optimization Algorithm ◽  
High Frequency ◽  
Performance Metrics ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Sampling Time ◽  
Signal To Noise ◽  
High Sampling ◽  
Noise Ratio ◽  
Estimation And Correction

In recent communication technologies, very high sampling rates are required for rf signals particularly for signals coming under ultra high frequency (UHF), super high frequency (SHF) and extremely high frequency (EHF) ranges. The applications include global positioning system (GPS), satellite communication, radar, radio astronomy, 5G mobile phones etc. Such high sampling rates can be accomplished with time-interleaved analog to digital converters (TIADCs). However, sampling time offsets existing in TIADCs produce non-uniform samples. This poses a drawback in the reconstruction of the signal. The current paper addresses this drawback and offers a solution for improved signal reconstruction by estimation and correction of the offsets. A modified differential evolution (MDE) algorithm, which is an optimization algorithm, is used for estimating the sampling time offsets and the estimated offsets are used for correction. The estimation algorithm is implemented on an FPGA board and correction is implemented using MATLAB. The power consumption of FPGA for implementation is 57mW. IO utilization is 27% for 4-channel TIADCs and 13% for 2-channel TIADCs. The algorithm estimated the sampling time offsets precisely. For estimation the algorithm uses a sinusoidal signal as a test signal. Correction is performed with sinusoidal and speech signals as inputs for TIADCs. Performance metrics used for evaluating the algorithm are SNR (signal to noise ratio), SNDR (signal to noise and distortion ratio), SFDR (spurious-free dynamic range) and PSNR (peak signal to noise ratio). A noteworthy improvement is observed in the above mentioned parameters. Results are compared with the existing state of the art algorithms and superiority of the proposed algorithm is verified.

scholarly journals Enhanced Partial Discharge Signal Denoising Using Dispersion Entropy Optimized Variational Mode Decomposition

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1567
Author(s):  
Ragavesh Dhandapani ◽  
Imene Mitiche ◽  
Scott McMeekin ◽  
Venkateswara Sarma Mallela ◽  
Gordon Morison
Keyword(s):  
Performance Metrics ◽  
Regularization Parameter ◽  
Signal To Noise Ratio ◽  
Partial Discharge ◽  
Sensor Data ◽  
Variational Mode Decomposition ◽  
Intrinsic Mode Functions ◽  
Denoising Method ◽  
Mode Decomposition ◽  
Band Limited

This paper presents a new approach for denoising Partial Discharge (PD) signals using a hybrid algorithm combining the adaptive decomposition technique with Entropy measures and Group-Sparse Total Variation (GSTV). Initially, the Empirical Mode Decomposition (EMD) technique is applied to decompose a noisy sensor data into the Intrinsic Mode Functions (IMFs), Mutual Information (MI) analysis between IMFs is carried out to set the mode length K. Then, the Variational Mode Decomposition (VMD) technique decomposes a noisy sensor data into K number of Band Limited IMFs (BLIMFs). The BLIMFs are separated as noise, noise-dominant, and signal-dominant BLIMFs by calculating the MI between BLIMFs. Eventually, the noise BLIMFs are discarded from further processing, noise-dominant BLIMFs are denoised using GSTV, and the signal BLIMFs are added to reconstruct the output signal. The regularization parameter λ for GSTV is automatically selected based on the values of Dispersion Entropy of the noise-dominant BLIMFs. The effectiveness of the proposed denoising method is evaluated in terms of performance metrics such as Signal-to-Noise Ratio, Root Mean Square Error, and Correlation Coefficient, which are are compared to EMD variants, and the results demonstrated that the proposed approach is able to effectively denoise the synthetic Blocks, Bumps, Doppler, Heavy Sine, PD pulses and real PD signals.

scholarly journals Cross-Sensor Nighttime Lights Image Calibration for DMSP/OLS and SNPP/VIIRS with Residual U-Net

2021 ◽  
Vol 13 (24) ◽  
pp. 5026
Author(s):  
Dmitry Nechaev ◽  
Mikhail Zhizhin ◽  
Alexey Poyda ◽  
Tilottama Ghosh ◽  
Feng-Chi Hsu ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Dynamic Range ◽  
Satellite System ◽  
Sensor Calibration ◽  
Environmental Light ◽  
Nighttime Lights ◽  
Military Conflicts ◽  
Highly Correlated ◽  
Polar Satellite

Remote sensing of nighttime lights (NTL) is widely used in socio-economic studies of economic growth, urbanization, stability of power grid, environmental light pollution, pandemics and military conflicts. Currently, NTL data are collected with two sensors: (1) Operational Line-scan System (OLS) onboard the satellites from the Defense Meteorology Satellite Program (DMSP) and (2) Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi NPP (SNPP) and NOAA-20 satellites from the Joint Polar Satellite System (JPSS). However, the nighttime images acquired by these two sensors are incompatible in spatial resolution and dynamic range. To address this problem, we propose a method for the cross-sensor calibration with residual U-net convolutional neural network (CNN). The CNN produces DMSP-like NTL composites from the VIIRS annual NTL composites. The pixel radiances predicted from VIIRS are highly correlated with NTL observed with OLS (0.96 < R2 < 0.99). The method can be used to extend long-term series of annual NTL after the end of DMSP mission or to cross-calibrate same year NTL from different satellites to study diurnal variations.

An Over 120dB Dynamic Range Linear Response Single Exposure CMOS Image Sensor with Two-stage Lateral Overflow Integration Trench Capacitors

2020 ◽  
Vol 2020 (7) ◽  
pp. 143-1-143-6 ◽  
Author(s):  
Yasuyuki Fujihara ◽  
Maasa Murata ◽  
Shota Nakayama ◽  
Rihito Kuroda ◽  
Shigetoshi Sugawa
Keyword(s):  
Linear Response ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Signal To Noise ◽  
Single Exposure ◽  
Two Stage ◽  
Noise Ratio ◽  
Maximum Signal

This paper presents a prototype linear response single exposure CMOS image sensor with two-stage lateral overflow integration trench capacitors (LOFITreCs) exhibiting over 120dB dynamic range with 11.4Me- full well capacity (FWC) and maximum signal-to-noise ratio (SNR) of 70dB. The measured SNR at all switching points were over 35dB thanks to the proposed two-stage LOFITreCs.

A Time-Resolved Low-Angle Light Scattering Apparatus. Application to Phase Separation Problems in Polymer Systems

2001 ◽  
Vol 66 (6) ◽  
pp. 973-982 ◽  
Author(s):  
Čestmír Koňák ◽  
Jaroslav Holoubek ◽  
Petr Štěpánek
Keyword(s):  
Phase Separation ◽  
Light Scattering ◽  
Signal To Noise Ratio ◽  
Scattered Light ◽  
Ccd Camera ◽  
Time Resolved ◽  
Polymer Systems ◽  
Software Analysis ◽  
Phase Separation Kinetics ◽  
Small Angle Light Scattering

A time-resolved small-angle light scattering apparatus equipped with azimuthal integration by means of a conical lens or software analysis of scattering patterns detected with a CCD camera was developed. Averaging allows a significant reduction of the signal-to-noise ratio of scattered light and makes this technique suitable for investigation of phase separation kinetics. Examples of applications to time evolution of phase separation in concentrated statistical copolymer solutions and dissolution of phase-separated domains in polymer blends are given.

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.

scholarly journals A Comparative Study of 3D UE Positioning in 5G New Radio with a Single Station

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1178
Author(s):  
Bo Sun ◽  
Bo Tan ◽  
Wenbo Wang ◽  
Elena Simona Lohan
Keyword(s):  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Time Estimation ◽  
Satellite System ◽  
Base Station ◽  
Rectangular Array ◽  
Single Station ◽  
5G Network ◽  
Autonomous Machines ◽  
3D Positioning

The 5G network is considered as the essential underpinning infrastructure of manned and unmanned autonomous machines, such as drones and vehicles. Besides aiming to achieve reliable and low-latency wireless connectivity, positioning is another function provided by the 5G network to support the autonomous machines as the coexistence with the Global Navigation Satellite System (GNSS) is typically supported on smart 5G devices. This paper is a pilot study of using 5G uplink physical layer channel sounding reference signals (SRSs) for 3D user equipment (UE) positioning. The 3D positioning capability is backed by the uniform rectangular array (URA) on the base station and by the multiple subcarrier nature of the SRS. In this work, the subspace-based joint angle-time estimation and statistics-based expectation-maximization (EM) algorithms are investigated with the 3D signal manifold to prove the feasibility of using SRSs for 3D positioning. The positioning performance of both algorithms is evaluated by estimation of the root mean squared error (RMSE) versus the varying signal-to-noise-ratio (SNR), the bandwidth, the antenna array configuration, and multipath scenarios. The simulation results show that the uplink SRS works well for 3D UE positioning with a single base station, by providing a flexible resolution and accuracy for diverse application scenarios with the support of the phased array and signal estimation algorithms at the base station.

scholarly journals In-Process Diameter Measurement Technique for Micro-Optical Fiber with Standing Wave Illumination

2021 ◽  
Author(s):  
Masaki Michihata ◽  
Zhao Zheng ◽  
Daiki Funaiwa ◽  
Sojiro Murakami ◽  
Shotaro Kadoya ◽  
...  
Keyword(s):  
Optical Fiber ◽  
Standing Wave ◽  
Dynamic Range ◽  
Scattered Light ◽  
High Dynamic Range ◽  
Measurement Range ◽  
Diameter Distribution ◽  
Process Measurement ◽  
Air Turbulence ◽  
Tapered Optical Fiber

AbstractIn this paper, we propose an in-process measurement method of the diameter of micro-optical fiber such as a tapered optical fiber. The proposed technique is based on analyzing optically scattered light generated by standing wave illumination. The proposed method is significant in that it requires an only limited measurement range and does not require a high dynamic range sensor. These properties are suitable for in-process measurement. This experiment verified that the proposed method could measure a fiber diameter as stable as ± 0.01 μm under an air turbulence environment. As a result of comparing the measured diameter distribution with those by scanning electron microscopy, it was confirmed that the proposed method has a measurement accuracy better than several hundred nanometers.

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