scholarly journals Performance Improvement of Spaceborne Carbon Dioxide Detection IPDA LIDAR Using Optimization of Optical Detector and Amplifier Linearity

2021 ◽  
Vol 13 (10) ◽  
pp. 2007
Author(s):  
Yadan Zhu ◽  
Juxin Yang ◽  
Xiaoxi Zhang ◽  
Jiqiao Liu ◽  
Xiaopeng Zhu ◽  
...  
Keyword(s):  
Circuit Board ◽  
Transfer Model ◽  
Circuit Optimization ◽  
Inversion Algorithm ◽  
Lidar System ◽  
Amplifier Circuit ◽  
Detector Module ◽  
Data Inversion ◽  
Air Mixing ◽  
Carbon Dioxide Detection

The spaceborne double-pulse integrated-path differential absorption (IPDA) light detection and ranging (LIDAR) system was found to be helpful in observing atmospheric CO2 and understanding the carbon cycle. The airborne experiments of a scale prototype of China’s planned spaceborne IPDA LIDAR was implemented in 2019. A problem with data inversion caused by the detector module nonlinearity was found. Through many experiments, the amplifier circuit board (ACB) of the detector module was proved to be the main factor causing the nonlinearity. Through amplifier circuit optimization, the original bandwidth of the ACB was changed to 1 MHz by using a fifth-order active filter. Compared with the original version, the linearity of optimized ACB is improved from 42.6% to 0.0747%. The optimized ACB was produced and its linearity was verified by experiments. In addition, the output waveform of the optimized ACB changes significantly, which will affect the random error (RE) of the optimized IPDA LIDAR system. Through the performance simulation, the RE of more than 90% of the global area is less than 0.728 ppm. Finally, the transfer model of the detector module was given, which will be helpful for the further optimization of the CO2 column-averaged dry-air mixing ratio (XCO2) inversion algorithm.

Calibration and data reduction for X-hotwires using cross validation

2021 ◽  
pp. 095441002110403
Author(s):  
Mohan Vijaya Anoop ◽  
Budda Thiagarajan Kannan
Keyword(s):  
Cross Validation ◽  
Low Flow ◽  
Calibration Data ◽  
Inversion Algorithm ◽  
Present Scheme ◽  
Wire Probe ◽  
Data Inversion ◽  
Turbulent Jet Flow ◽  
High Reynolds ◽  
Yaw Angle

A strategy for calibration of X-wire probes and data inversion is described in this article. The approach used has elements of full velocity vs yaw-angle calibration with robust curve fitting. The responses of an X-wire probe placed in a calibration jet are recorded for a set of velocity and yaw inputs followed by fitting cross-validated splines. These spline functions trained from calibration data are evaluated for the probe responses during measurement. X-wire probes are calibrated for low to moderate velocities (0.65 m/s to 32 m/s) and yaw angles in the range −40° to 40° and comparisons with conventional interpolation schemes are made. The proposed algorithm can be extended to calibration of other multiple wire probes and for higher velocities. Some measurements in a single round turbulent jet flow at high Reynolds number using the proposed inversion algorithm are also presented. The present scheme is found to perform better particularly at low flow magnitudes and/or extreme flow angles than the schemes used previously.

A new data inversion algorithm for DMPS and TDMA measurements

1999 ◽  
Vol 30 ◽  
pp. S775-S776 ◽  
Author(s):  
A. Voutilainen ◽  
F. Stratmann ◽  
J.P. Kaipio
Keyword(s):  
Inversion Algorithm ◽  
Data Inversion

Statistical considerations on the Raman inversion algorithm: data inversion and error assessment

2004 ◽  
Author(s):  
Francesc Rocadenbosch ◽  
Michael Sicard ◽  
Albert Ansmann ◽  
Ulla Wandinger ◽  
Volker Matthias ◽  
...  
Keyword(s):  
Error Assessment ◽  
Inversion Algorithm ◽  
Data Inversion

A compressed implicit Jacobian scheme for 3D electromagnetic data inversion

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. F173-F183 ◽  
Author(s):  
Maokun Li ◽  
Aria Abubakar ◽  
Jianguo Liu ◽  
Guangdong Pan ◽  
Tarek M. Habashy
Keyword(s):  
Electric Fields ◽  
Jacobian Matrix ◽  
Iterative Solvers ◽  
Computational Time ◽  
Memory Usage ◽  
Inversion Algorithm ◽  
Linear System Of Equations ◽  
Electromagnetic Data ◽  
Data Inversion ◽  
Computational Overhead

We developed a compressed implicit Jacobian scheme for the regularized Gauss-Newton inversion algorithm for reconstructing 3D conductivity distributions from electromagnetic data. In this algorithm, the Jacobian matrix, whose storage usually requires a large amount of memory, is decomposed in terms of electric fields excited by sources located and oriented identically to the physical sources and receivers. As a result, the memory usage for the Jacobian matrix reduces from O(NFNSNRNP) to O[NF(NS + NR)NP], where NF is the number of frequencies, NS is the number of sources, NR is the number of receivers, and NP is the number of conductivity cells to be inverted. When solving the Gauss-Newton linear system of equations using iterative solvers, the multiplication of the Jacobian matrix with a vector is converted to matrix-vector operations between the matrices of the electric fields and the vector. In order to mitigate the additional computational overhead of this scheme, these fields are further compressed using the adaptive cross approximation (ACA) method. The compressed implicit Jacobian scheme provides a good balance between memory usage and computational time and renders the Gauss-Newton algorithm more efficient. We demonstrated the benefits of this scheme using numerical examples including both synthetic and field data for both crosswell and controlled-source electromagnetic (CSEM) applications.

scholarly journals Airborne multiwavelength High Spectral Resolution Lidar (HSRL-2) observations during TCAP 2012: vertical profiles of optical and microphysical properties of a smoke/urban haze plume over the northeastern coast of the US

2014 ◽  
Vol 7 (2) ◽  
pp. 1059-1073 ◽  
Author(s):  
D. Müller ◽  
C. A. Hostetler ◽  
R. A. Ferrare ◽  
S. P. Burton ◽  
E. Chemyakin ◽  
...  
Keyword(s):  
Spectral Resolution ◽  
Phase 1 ◽  
Department Of Energy ◽  
High Spectral Resolution ◽  
Inversion Algorithm ◽  
Data Inversion ◽  
Microphysical Properties ◽  
The Us ◽  
Langley Research Center ◽  
High Spectral Resolution Lidar

Abstract. We present measurements acquired by the world's first airborne multiwavelength High Spectral Resolution Lidar (HSRL-2), developed by NASA Langley Research Center. The instrument was operated during Phase 1 of the Department of Energy (DOE) Two-Column Aerosol Project (TCAP)in July 2012. We observed pollution outflow from the northeast coast of the US out over the West Atlantic Ocean. Lidar ratios were 50–60 sr at 355 nm and 60–70 sr at 532 nm. Extinction-related Ångström exponents were on average 1.2–1.7 indicating comparably small particles. Our novel automated, unsupervised data inversion algorithm retrieves particle effective radii of approximately 0.2 μm, which is in agreement with the large Ångström exponents. We find good agreement with particle size parameters obtained from coincident in situ measurements carried out with the DOE Gulfstream-1 aircraft.

scholarly journals First Three Years of the Microwave Radiometer aboard Envisat: In-Flight Calibration, Processing, and Validation of the Geophysical Products

2006 ◽  
Vol 23 (6) ◽  
pp. 802-814 ◽  
Author(s):  
E. Obligis ◽  
L. Eymard ◽  
N. Tran ◽  
S. Labroue ◽  
P. Femenias
Keyword(s):  
Microwave Radiometer ◽  
Radiative Transfer Model ◽  
Altimeter Data ◽  
Transfer Model ◽  
Path Delay ◽  
Inversion Algorithm ◽  
Weather Forecasts ◽  
Brightness Temperatures ◽  
Medium Range ◽  
Satellite Altimeter Data

Abstract The Envisat microwave radiometer is designed to correct the satellite altimeter data for the excess path delay resulting from tropospheric humidity. Neural networks have been used to formulate the inversion algorithm to retrieve this quantity from the measured brightness temperatures. The learning database has been built with European Centre for Medium-Range Weather Forecasts (ECMWF) analyses and simulated brightness temperatures by a radiative transfer model. The in-flight calibration has been performed in a consistent way by adjusting measurements on simulated brightness temperatures. Finally, coincident radiosonde measurements are used to validate the Envisat wet-tropospheric correction, and this comparison shows the good performances of the method.

scholarly journals Validation of brightness and physical temperature from two scanning microwave radiometers in the 60 GHz O<sub>2</sub>-band using radiosonde measurements

2016 ◽  
Author(s):  
Francisco Navas-Guzmán ◽  
Niklaus Kämpfer ◽  
Alexander Haefele
Keyword(s):  
Brightness Temperature ◽  
Microwave Radiometer ◽  
Estimation Method ◽  
Weather Conditions ◽  
Radiative Transfer Model ◽  
Inversion Method ◽  
Transfer Model ◽  
Tropospheric Temperature ◽  
60 Ghz ◽  
Inversion Algorithm

Abstract. In this paper, we address the assessment of the tropospheric performance of a new temperature radiometer (TEMPERA) at 60 GHz.With this goal, an intercomparison campaign was carried out at the aerological station of MeteoSwiss in Payerne (Swizerland). The brightness temperature and the tropospheric temperature were assessed by means of a comparison with simultaneous and collocated radiosondes which are launched twice a day at this station. In addition, the TEMPERA performances are compared with the ones from a commercial microwave radiometer (HATPRO) which has some different instrumental characteristics and uses a different inversion algorithm. Brightness temperatures from both radiometers were compared with the ones simulated using a radiative transfer model and atmospheric profiles from radiosondes. A total of 532 cases were analyzed under all weather conditions and evidenced larger brightness temperature deviations between the two radiometers and the radiosondes for the most transparent channels. Two different retrievals for the TEMPERA radiometer were implemented in order to evaluate the effect of the different channels on the temperature retrievals. The comparison with radiosondes evidenced better results and very similar to the ones from HATPRO when the 8 more opaques channels were used. The study shows the good performance of TEMPERA to retrieve temperature profiles in the troposphere. The inversion method of TEMPERA is based on the Optimal Estimation Method. The main advantage of this algorithm is that there is no necessity for radiosonde information to achieve good results in contrast to conventional methods as neuronal networks or lineal regression. Finally, an assessment of the effect of instrumental characteristics as the filter response and the antenna pattern on the brightness temperature showed that they can have an important impact on the most transparent channels.

scholarly journals 3D induced-polarization data inversion for complex resistivity

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. F157-F171 ◽  
Author(s):  
Michael Commer ◽  
Gregory A. Newman ◽  
Kenneth H. Williams ◽  
Susan S. Hubbard
Keyword(s):  
Environmental Remediation ◽  
Large Scale ◽  
Forward Modeling ◽  
Induced Polarization ◽  
Inversion Method ◽  
Data Sets ◽  
Inversion Algorithm ◽  
Data Set ◽  
Complex Resistivity ◽  
Data Inversion

The conductive and capacitive material properties of the subsurface can be quantified through the frequency-dependent complex resistivity. However, the routine three-dimensional (3D) interpretation of voluminous induced polarization (IP) data sets still poses a challenge due to large computational demands and solution nonuniqueness. We have developed a flexible methodology for 3D (spectral) IP data inversion. Our inversion algorithm is adapted from a frequency-domain electromagnetic (EM) inversion method primarily developed for large-scale hydrocarbon and geothermal energy exploration purposes. The method has proven to be efficient by implementing the nonlinear conjugate gradient method with hierarchical parallelism and by using an optimal finite-difference forward modeling mesh design scheme. The method allows for a large range of survey scales, providing a tool for both exploration and environmental applications. We experimented with an image focusing technique to improve the poor depth resolution of surface data sets with small survey spreads. The algorithm’s underlying forward modeling operator properly accounts for EM coupling effects; thus, traditionally used EM coupling correction procedures are not needed. The methodology was applied to both synthetic and field data. We tested the benefit of directly inverting EM coupling contaminated data using a synthetic large-scale exploration data set. Afterward, we further tested the monitoring capability of our method by inverting time-lapse data from an environmental remediation experiment near Rifle, Colorado. Similar trends observed in both our solution and another 2D inversion were in accordance with previous findings about the IP effects due to subsurface microbial activity.

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