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NASA NTRS2018

CALIPSO Lidar Calibration at 532 nm: Version 4 Nighttime Algorithm

Data products from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were recently updated following the implementation of new (version 4) calibration algorithms for all of the level 1 attenuated backscatter measurements. In this work we present the motivation for and the implementation of the version 4 nighttime 532 nm parallel channel calibration. The nighttime 532 nm calibration is the most fundamental calibration of CALIOP data, since all of CALIOP’s other radiometric calibration procedures – i.e., the 532 nm daytime calibration and the 1064 nm calibrations during both nighttime and daytime – depend either directly or indirectly on the 532 nm nighttime calibration. The accuracy of the 532 nm nighttime calibration has been significantly improved by raising the molecular normalization altitude from 30-34 km to 36-39 km to substantially reduce stratospheric aerosol contamination. Due to the greatly reduced molecular number density and consequently reduced signal-to-noise ratio (SNR) at these higher altitudes, the signal is now averaged over a larger number of samples using data from multiple adjacent granules. As well, an enhanced strategy for filtering the radiation-induced noise from high energy particles was adopted. Further, the meteorological model used in the earlier versions has been replaced by the improved MERRA-2 model. An aerosol scattering ratio of 1.01 ± 0.01 is now explicitly used for the calibration altitude. These modifications lead to globally revised calibration coefficients which are, on average, 2-3% lower than in previous data releases. Further, the new calibration procedure is shown to eliminate biases at high altitudes that were present in earlier versions and consequently leads to an improved representation of stratospheric aerosols. Validation results using airborne lidar measurements are also presented. Biases relative to collocated measurements acquired by the Langley Research Center (LaRC) airborne high spectral resolution lidar (HSRL) are reduced from 3.6% ± 2.2% in the version 3 data set to 1.6% ± 2.4 % in the version 4 release.

Jayanta Kar↗

NASA NTRS1987

Preliminary simultaneous L/C-band images from the JPL aircraft synthetic aperture radar

A squint mode processor for the processing of JPL aircraft SAR data collected in L-band and C-band is described which meets the criteria of optimum SNR, polarization isolation, and resolution. A steerable prefilter maximizes SNR while reducing the amount of data for processing efficiency. The resolution of images produced from data recorded at nonzero drift angle is improved by range migration compensation. The standard output products include high resolution images (with a range resolution of 7.5 m and an azimuth resolution of 2.74 m), four-look images (produced by averaging every four pixels in the azimuth direction for speckle reduction), and magnitude/phase-difference images (produced by correlating images of similar polarizations).

Lou, Yunling↗

NASA NTRS2022

Silicon Photonic Transceiver for Spacecraft Navigational Lidar

NASA is developing an entry, descent, and landing (EDL) lidar system, the Navigation Doppler Lidar (NDL), for high-precision landing on the Moon, Mars, and beyond. The current flight NDL systems use 1550 nm fiber-optic components for frequency-modulated continuous wave (FMCW) ranging beyond 5 km, but have reduced performance under vibrational and thermal stresses during EDL. Here we describe recent efforts to develop a breadboard silicon photonic optical transceiver for integration into NDL to reduce instrument size and improve robustness to environment and demonstrate the optical balanced receiver performance during testing with the breadboard NDL unit. Initial testing shows improved suppression of common mode noise by 25 dB over the current receiver, but a 10 dB reduction in signal to noise ratio (SNR) resulting from coupling losses from fiber to the on-chip waveguides. Future work will target reduced coupling loss, hermetic packaging, and co-integration of a single sideband suppressed carrier modulator into the same chip.

Photonic Integrated Circuits↗

NASA NTRS1986

Further studies with data collected by NASA's airborne Doppler lidar in Oklahoma in 1981

Continued study of the lidar data collected in 1981 has resulted in significant new improvements in the analysis techniques reported by Bluestein et al. (1985) and McCaul (1985). Through comparison of fore- and aft-derived scalar fields of intensity and spectral width, the self-consistency of the lidar moment estimates was assessed. Reflectivity estimates were found to be quite stable and reliable, while spectral widths were prone to become noisy if signal to noise ratio (SNR) fell below 12 dB. In addition, spectral widths contained a significant component due to radial velocity gradients in areas along gust fronts, and these components were different along the fore and aft lines of sight. Significant improvement in agreement between the fore and aft fields of spectral width was obtained by estimating the radial velocity gradient component and then removing it from the raw measured widths to yield only the turbulent portion of the contribution to width. Additional analyses showed that lidar-derived vorticity estimates were consistent with several approximate models of vorticity growth along gust front zones, and with the hypothesis that Helmholtz instability could have been responsible for vortices seen along part of the gust front of 30 June 1981. Computations of divergence transverse to axes through an isolated cumulus congestus indicated that the strongest convergence tended to lie along an axis parallel to the congestus. This and the results of other additional analyses seem to suggest that the lidar winds do indeed accurately reflected the basic features of the real wind field.

Bluestein, H. B.↗

NASA NTRS2005

Sporadic E Morphology from GPS-CHAMP Radio Occultation

The scintillations of phase and amplitude in terms of signal-to-noise ratio (SNR) of the GPS radio occultation signal are caused by thin ionization layers. These thin irregular electron density layers in the E region ionosphere are often called sporadic E (Es). For a monthly retrieval of Es morphology we use the variances of the phase and SNR fluctuations of worldwide ~6000 GPS/CHAMP occultations in the E region. The Es climatology is studied globally with the SNR and phase variances in terms of monthly zonal means, seasonal maps, and diurnal and long-term variations. The zonal mean variances reveal strong, extended Es activities at summertime midlatitudes but weak, confined activities in wintertime high latitudes, peaking at ~105 km. Global maps at 105-km altitude show clear dependence of Es activities on the geomagnetic dip angle, where the summertime midlatitude Es occurs mostly at dip angles of 30 deg. - 60 deg. and the wintertime high-latitude enhancement occurs mostly at dip angles greater than 80 deg. The midlatitude Es variances exhibit a strong semidiurnal variation with peak hours near 0800 1000 and 2000 local solar time, respectively. The peak hours are delayed slightly with decreasing height, suggesting influences from the semidiurnal tide. To provide more insights on the observed SNR and phase variances, we model radio wave propagation for the CHAMP observing geometry under several perturbed cases in the E region ionosphere. The model simulations indicate that the SNR variance has the maximum response to Es perturbations at vertical wavelengths of 1.2 km, whereas the phase response maximizes at ~2 km (for the 1-s variance analysis). The characteristic scale depends little on the truncation time used in the SNR variance analysis, but it increases with the truncation time for the phase variances. Initial studies show that reasonable global Es morphology can be produced on a monthly and seasonal basis with the CHAMP one-antenna occultations. Better results from other existing and upcoming GPS occultation missions are anticipated in future studies, and they will significantly improve our understanding of this important phenomenon.

signal to noise ration (SNR)↗

NASA NTRS2000

Nonlinear Shock Acceleration and Photon Emission in Supernova Remnants

We have extended a simple model of nonlinear diffusive shock acceleration (Berezhko & Ellison 1999: Ellison &, Berezhko 1999a) to include the injection and acceleration of electrons and the production of photons from bremsstrahlung, synchrotron, inverse Compton, and pion-decay processes. We argue that, the results of this model, which is simpler to use than more elaborate ones, offer a significant improvement, over test-particle, power-law spectra which are often used in astrophysical applications of diffusive shock acceleration. With an evolutionary supernova remnant (SNR) model to obtain shock parameters as functions of ambient interstellar medium parameters and time, we predict broad-band continuum photon emission from supernova remnants in general, and SN1006 in particular, showing that our results compare well with the more complete time-dependent and spherically symmetric nonlinear model of Berezhko, Ksenofontov, & Petukhov (1999a). We discuss the implications nonlinear shock acceleration has for X-ray line emission, and use our model to describe how ambient conditions determine the TeV/radio flux ratio, an important parameter for gamma-ray observations of radio SNRs.

Ellison, Donald C.↗

NASA NTRS2006

The Novel Nonlinear Adaptive Doppler Shift Estimation Technique and the Coherent Doppler Lidar System Validation Lidar

The signal processing aspect of a 2-m wavelength coherent Doppler lidar system under development at NASA Langley Research Center in Virginia is investigated in this paper. The lidar system is named VALIDAR (validation lidar) and its signal processing program estimates and displays various wind parameters in real-time as data acquisition occurs. The goal is to improve the quality of the current estimates such as power, Doppler shift, wind speed, and wind direction, especially in low signal-to-noise-ratio (SNR) regime. A novel Nonlinear Adaptive Doppler Shift Estimation Technique (NADSET) is developed on such behalf and its performance is analyzed using the wind data acquired over a long period of time by VALIDAR. The quality of Doppler shift and power estimations by conventional Fourier-transform-based spectrum estimation methods deteriorates rapidly as SNR decreases. NADSET compensates such deterioration in the quality of wind parameter estimates by adaptively utilizing the statistics of Doppler shift estimate in a strong SNR range and identifying sporadic range bins where good Doppler shift estimates are found. The authenticity of NADSET is established by comparing the trend of wind parameters with and without NADSET applied to the long-period lidar return data.

Beyon, Jeffrey Y.↗

NASA NTRS2021

Aerosol and Cloud Detection Using Machine Learning Algorithms and Space-Based Lidar Data

Clouds and aerosols play a significant role in determining the overall atmospheric radiation budget, yet remain a key uncertainty in understanding and predicting the future climate system. In addition to their impact on the Earth’s climate system, aerosols from volcanic eruptions, wildfires, man-made pollution events and dust storms are hazardous to aviation safety and human health. Space-based lidar systems provide critical information about the vertical distributions of clouds and aerosols that greatly improve our understanding of the climate system. However, daytime data from backscatter lidars, such as the Cloud-Aerosol Transport System (CATS) on the International Space Station (ISS), must be averaged during science processing at the expense of spatial resolution to obtain sufficient signal-to-noise ratio (SNR) for accurately detecting atmospheric features. For example, 50% of all atmospheric features reported in daytime operational CATS data products require averaging to 60 km for detection. Furthermore, the single-wavelength nature of the CATS primary operation mode makes accurately typing these features challenging in complex scenes. This paper presents machine learning (ML) techniques that, when applied to CATS data, (1) increased the 1064 nm SNR by 75%, (2) increased the number of layers detected (any resolution) by 30%, and (3) enabled detection of 40% more atmospheric features during daytime operations at a horizontal resolution of 5 km compared to the 60 km horizontal resolution often required for daytime CATS operational data products. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime.

lidar↗

NASA NTRS1995

Effects of correlated noise on the full-spectrum combining and complex-symbol combining arraying techniques

The process of combining telemetry signals received at multiple antennas, commonly referred to as arraying, can be used to improve communication link performance in the Deep Space Network (DSN). By coherently adding telemetry from multiple receiving sites, arraying produces an enhancement in signal-to-noise ratio (SNR) over that achievable with any single antenna in the array. A number of different techniques for arraying have been proposed and their performances analyzed in past literature. These analyses have compared different arraying schemes under the assumption that the signals contain additive white Gaussian noise (AWGN) and that the noise observed at distinct antennas is independent. In situations where an unwanted background body is visible to multiple antennas in the array, however, the assumption of independent noises is no longer applicable. A planet with significant radiation emissions in the frequency band of interest can be one such source of correlated noise. For example, during much of Galileo's tour of Jupiter, the planet will contribute significantly to the total system noise at various ground stations. This article analyzes the effects of correlated noise on two arraying schemes currently being considered for DSN applications: full-spectrum combining (FSC) and complex-symbol combining (CSC). A framework is presented for characterizing the correlated noise based on physical parameters, and the impact of the noise correlation on the array performance is assessed for each scheme.

Vazirani, P.↗

NASA NTRS1992

The IRAS Minor Planet Survey

This report documents the program and data used to identify known asteroids observed by the Infrared Astronomical Satellite (IRAS) and to compute albedos and diameters from their IRAS fluxes. It also presents listings of the results obtained. These results supplant those in the IRAS Asteroid and Comet Survey, 1986. The present version used new and improved asteroid orbital elements for 4679 numbered asteroids and 2632 additional asteroids for which at least two-opposition elements were available as of mid-1991. It employed asteroid absolute magnitudes on the International Astronomical Union system adopted in 1991. In addition, the code was modified to increase the reliability of associating asteroids with IRAS sources and rectify several shortcomings in the final data products released in 1986. Association reliability was improved by decreasing the position difference between an IRAS source and a predicted asteroid position required for an association. The shortcomings addressed included the problem of flux overestimation for low SNR sources and the systematic difference in albedos and diameters among the three wavelength bands (12, 25, and 60 micrometers). Several minor bugs in the original code were also corrected.

Tedesco, Edward F.↗

NASA NTRS2011

The Celestial Reference Frame at X/Ka-band (8.4/32 GHz)

A celestial reference frame at X/Ka-band (8.4/32 GHz) has been constructed using fifty-one 24-hour sessions with the Deep Space Network. We report on observations which have detected 436 sources covering the full 24 hours of right ascension and declinations down to -45 deg. Comparison of this X/Ka-band frame to the S/X-band (2.3/8.4 GHz) ICRF2 shows wRMS agreement of 200 micro-arcsec in a cos delta and 290 micro-arcsec in delta. There is evidence for zonal errors at the 100 micro-arcsec level. Known errors include limited SNR, lack of phase calibration, troposphere mismodelling, and limited southern geometry. The motivations for extending the ICRF to frequencies above 8 GHz are to access more compact source morphology for improved frame stability, to provide calibrators for phase referencing, and to support spacecraft navigation at Ka-band.

reference systems catalog↗

NASA NTRS2010

The Celestial Reference Frame at X/Ka-band (8.4/32 GHz)

A celestial reference frame at X/Kaband (8.4/32 GHz) has been constructed using fiftyone 24-hour sessions with the Deep Space Network. We report on observations which have detected 436 sources covering the full 24 hours of right ascension and declinations down to -45 deg. Comparison of this X/Ka-band frame to the S/X-band (2.3/8.4 GHz) ICRF2 shows wRMS agreement of 200 micro-arcsec ( mu as) in alpha cos delta and 290 mu as in delta. There is evidence for zonal errors at the 100 mu as level. Known errors include limited SNR, lack of phase calibration, troposphere mismodelling, and limited southern geometry. The motivations for extending the ICRF to frequencies above 8 GHz are to access more compact source morphology for improved frame stability, to provide calibrators for phase referencing, and to support spacecraft navigation at Ka-band.

interferometry↗

NASA NTRS2021

Aerosol and Cloud Detection Using Machine Learning Algorithms and Space-Based Lidar Data

Clouds and aerosols play a significant role in determining the overall atmospheric radiation budget, yet remain a key uncertainty in understanding and predicting the future climate system. In addition to their impact on the Earth’s climate system, aerosols from volcanic eruptions, wildfires, man-made pollution events, and dust storms are hazardous to aviation safety and human health. Space-based lidar systems provide critical information about the vertical distributions of clouds and aerosols that greatly improve our understanding of the climate system. However, daytime data from backscatter lidars, such as the Cloud-Aerosol Transport System (CATS) on the International Space Station (ISS), must be averaged during science processing at the expense of spatial resolution to obtain sufficient signal-to-noise ratio (SNR) for accurately detecting atmospheric features. For example, 50% of all atmospheric features reported in daytime operational CATS data products require averaging to 60 km for detection. Furthermore, the single-wavelength nature of the CATS primary operation mode makes accurately typing these features challenging in complex scenes. This paper presents machine learning (ML) techniques that, when applied to CATS data, enable detection of atmospheric features during daytime operations with a horizontal resolution of 5 km compared to the 60 km horizontal resolution often required for daytime CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime.

lidar↗

NASA NTRS2016

On the Performance of Adaptive Data Rate over Deep Space Ka-Bank Link: Case Study Using Kepler Data

Future missions envisioned for both human and robotic exploration demand increasing communication capacity through the use of Ka-band communications. The Ka-band channel, being more sensitive to weather impairments, presents a unique trade-offs between data storage, latency, data volume and reliability. While there are many possible techniques for optimizing Ka-band operations such as adaptive modulation and coding and site-diversity, this study focus exclusively on the use of adaptive data rate (ADR) to achieve significant improvement in the data volume-availability tradeoff over a wide range of link distances for near Earth and Mars exploration. Four years of Kepler Ka-band downlink symbol signal-to-noise (SNR) data reported by the Deep Space Network were utilized to characterize the Ka-band channel statistics at each site and conduct various what-if performance analysis for different link distances. We model a notional closed-loop adaptive data rate system in which an algorithm predicts the channel condition two-way light time (TWLT) into the future using symbol SNR reported in near-real time by the ground receiver and determines the best data rate to use. Fixed and adaptive margins were used to mitigate errors in channel prediction. The performance of this closed-loop adaptive data rate approach is quantified in terms of data volume and availability and compared to the actual mission configuration and a hypothetical, optimized single rate configuration assuming full a priori channel knowledge.

Gao, Jay L.↗

NASA NTRS2010

The Wide-Field Infrared Survey Explorer (WISE): Mission Description and Initial On-Orbit Performance

The all sky surveys done by the Palomar Observatory Schmidt, the European Southern Observatory Schmidt, and the United Kingdom Schmidt, the InfraRed Astronomical Satellite and the 2 Micron All Sky Survey have proven to be extremely useful tools for astronomy with value that lasts for decades. The Wide-field Infrared Survey Explorer is mapping the whole sky following its launch on 14 December 2009. WISE began surveying the sky on 14 Jan 2010 and completed its first full coverage of the sky on July 17. The survey will continue to cover the sky a second time until the cryogen is exhausted (anticipated in November 2010). WISE is achieving 5 sigma point source sensitivities better than 0.08, 0.11, 1 and 6 mJy in unconfused regions on the ecliptic in bands centered at wavelengths of 3.4, 4.6, 12 and 22 micrometers. Sensitivity improves toward the ecliptic poles due to denser coverage and lower zodiacal background. The angular resolution is 6.1", 6.4", 6.5" and 12.0" at 3.4, 4.6, 12 and 22 micrometers, and the astrometric precision for high SNR sources is better than 0.15".

Wright, Edward L.↗

NASA NTRS2011

A Ka-Band Celestial Reference Frame with Applications to Deep Space Navigation

The Ka-band radio spectrum is now being used for a wide variety of applications. This paper highlights the use of Ka-band as a frequency for precise deep space navigation based on a set of reference beacons provided by extragalactic quasars which emit broadband noise at Ka-band. This quasar-based celestial reference frame is constructed using X/Ka-band (8.4/32 GHz) from fifty-five 24-hour sessions with the Deep Space Network antennas in California, Australia, and Spain. We report on observations which have detected 464 sources covering the full 24 hours of Right Ascension and declinations down to -45 deg. Comparison of this X/Ka-band frame to the international standard S/X-band (2.3/8.4 GHz) ICRF2 shows wRMS agreement of approximately 200 micro-arcsec in alpha cos(delta) and approximately 300 micro-arcsec in delta. There is evidence for systematic errors at the 100 micro-arcsec level. Known errors include limited SNR, lack of instrumental phase calibration, tropospheric refraction mis-modeling, and limited southern geometry. The motivation for extending the celestial reference frame to frequencies above 8 GHz is to access more compact source morphology for improved frame stability and to support spacecraft navigation for Ka-band based NASA missions.

k-band↗

NASA NTRS1990

Performance analysis of a noncoherently combined large aperture optical heterodyne receiver

The performance of a noncoherently combined (NC) multiple-mirror heterodyne receiver is analyzed. With no atmospheric turbulence (AT), the performance of the NC receiver is shown to the inferior to that of a monolithic diffraction-limited receiver with equivalent aperture area. When AT is taken into consideration, however, the efficiency of a monolithic receiver is limited by the phase coherence length of the atmosphere, and generally does not improve with increasing aperture size. In contrast, the performance of an NC system improves with an increasing number of receivers. Consequently, given a fixed collecting area, the NC system can offer superior performance. The performance of the NC heterodyne receiver is studied by analyzing the combining loss of the receiver SNR. It is shown that, given a constant collecting area, the performance of the NC receiver is optimized when the diameter of each of the individual receivers is on the order of the phase coherence length of the AT.

Chen, Chien-Chung↗

NASA NTRS2003

InGaAsSb Detectors' Characterization for 2-Micron CO2 Lidar/DIAL Applications

Recent interest in monitoring atmospheric CO2 focuses attention on infrared remote sensing using the 2-micron lidar/differential absorption lidar (DIAL) technique. Quantum detectors are critical components in this technique, and many research efforts concentrate on developing such devices for the 2-micron wavelength. Characterization results of InGaAsSb quantum detectors for the 2-micron wavelength range are presented, including experimental setup and procedure. Detectors are prototype devices manufactured by using separate absorption and multiplication (SAM) structures. Characterization experiments include V-I measurements, spectral response and its variation with bias voltage and temperature, noise measurements, noise-equivalent-power (NEP) and detectivity calculations, and signal-to-noise ratio (SNR) estimation. A slight increase in the output signal occurred with increased bias voltage and was associated with a noise level increase. Cooling down the detectors reduces noise and shifts the cutoff wavelength to shorter values. Further improvement in the design and manufacturing process, by increasing the device gain and lowering its noise level, is necessary to meet the required CO2 lidar/DIAL specifications.

Refaat, Tamer F.↗