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A novel multistage estimation of the signal parameters of a possibly data-modulated sinusoid under very high dynamics

A novel multistage estimation scheme is presented for estimating the parameters of a received carrier signal possibly phase-modulated by unknown data, and experiencing very high Doppler, Doppler rate, etc. Such a situation arises, for example, in the case of Global Positioning Systems (GPS) where the signal parameters are directly related to the position, velocity, acceleration and jerk of the GPS receiver. In the proposed multistage scheme, the first stage estimator operates as a coarse estimator resulting in higher rms estimation errors but with a relatively small probability of the frequency estimation error exceeding one-half of the sampling frequency (an event termed cycle slip). The second state of the estimator operates on the error signal available from the first stage, refining the overall estimates, and in the process also reduces the number of cycle slips. The first stage algorithm is selected to be a modified least squares algorithm operating upon the differential signal model and referred to as differential least squares. This estimation stage provides relatively coarse estimates of the frequency and its derivatives. The second algorithm is simply an extended Kalman filter which also yields the estimate of the phase along with a more refined estimate of frequency as well. A major advantage of the proposed algorithm is a reduction in the threshold on received carrier power-to-noise power spectral density ratio as compared to the threshold achievable by either of these algorithms alone. In fact, it appears from the simulations that for the case of an unmodulated carrier, the proposed scheme achieves the same threshold as for an almost exact and computationally intensive implementation of the maximum likelihood estimator.

Kumar, Rajendra↗

Reducing Multisensor Satellite Monthly Mean Aerosol Optical Depth Uncertainty: 1. Objective Assessment of Current AERONET Locations

Various space-based sensors have been designed and corresponding algorithms developed to retrieve aerosol optical depth (AOD), the very basic aerosol optical property, yet considerable disagreement still exists across these different satellite data sets. Surface-based observations aim to provide ground truth for validating satellite data; hence, their deployment locations should preferably contain as much spatial information as possible, i.e., high spatial representativeness. Using a novel Ensemble Kalman Filter (EnKF)- based approach, we objectively evaluate the spatial representativeness of current Aerosol Robotic Network (AERONET) sites. Multisensor monthly mean AOD data sets from Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, Sea-viewing Wide Field-of-view Sensor, Ozone Monitoring Instrument, and Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar are combined into a 605-member ensemble, and AERONET data are considered as the observations to be assimilated into this ensemble using the EnKF. The assessment is made by comparing the analysis error variance (that has been constrained by ground-based measurements), with the background error variance (based on satellite data alone). Results show that the total uncertainty is reduced by approximately 27% on average and could reach above 50% over certain places. The uncertainty reduction pattern also has distinct seasonal patterns, corresponding to the spatial distribution of seasonally varying aerosol types, such as dust in the spring for Northern Hemisphere and biomass burning in the fall for Southern Hemisphere. Dust and biomass burning sites have the highest spatial representativeness, rural and oceanic sites can also represent moderate spatial information, whereas the representativeness of urban sites is relatively localized. A spatial score ranging from 1 to 3 is assigned to each AERONET site based on the uncertainty reduction, indicating its representativeness level.

aerosol optical depth↗

Assessment of Biases in MODIS Surface Reflectance Due to Lambertian Approximation

Using MODIS data and the AERONET-based Surface Reflectance Validation Network (ASRVN), this work studies errors of MODIS atmospheric correction caused by the Lambertian approximation. On one hand, this approximation greatly simplifies the radiative transfer model, reduces the size of the look-up tables, and makes operational algorithm faster. On the other hand, uncompensated atmospheric scattering caused by Lambertian model systematically biases the results. For example, for a typical bowl-shaped bidirectional reflectance distribution function (BRDF), the derived reflectance is underestimated at high solar or view zenith angles, where BRDF is high, and is overestimated at low zenith angles where BRDF is low. The magnitude of biases grows with the amount of scattering in the atmosphere, i.e., at shorter wavelengths and at higher aerosol concentration. The slope of regression of Lambertian surface reflectance vs. ASRVN bidirectional reflectance factor (BRF) is about 0.85 in the red and 0.6 in the green bands. This error propagates into the MODIS BRDF/albedo algorithm, slightly reducing the magnitude of overall reflectance and anisotropy of BRDF. This results in a small negative bias of spectral surface albedo. An assessment for the GSFC (Greenbelt, USA) validation site shows the albedo reduction by 0.004 in the near infrared, 0.005 in the red, and 0.008 in the green MODIS bands.

Wang, Yujie↗

Evaluation of Airborne Precision Spacing in a Human-in-the-Loop Experiment

A significant bottleneck in the current air traffic system occurs at the runway. Expanding airports and adding new runways will help solve this problem; however, this comes with significant costs: financially, politically and environmentally. A complementary solution is to safely increase the capacity of current runways. This can be achieved by precisely spacing aircraft at the runway threshold, with a resulting reduction in the spacing bu er required under today s operations. At NASA's Langley Research Center, the Airspace Systems program has been investigating airborne technologies and procedures that will assist the flight crew in achieving precise spacing behind another aircraft. A new spacing clearance allows the pilot to follow speed cues from a new on-board guidance system called Airborne Merging and Spacing for Terminal Arrivals (AMSTAR). AMSTAR receives Automatic Dependent Surveillance-Broadcast (ADS-B) reports from an assigned, leading aircraft and calculates the appropriate speed for the ownship to fly to achieve the desired spacing interval, time- or distance-based, at the runway threshold. Since the goal is overall system capacity, the speed guidance algorithm is designed to provide system-wide benefits and stability to a string of arriving aircraft. An experiment was recently performed at the NASA Langley Air Traffic Operations Laboratory (ATOL) to test the flexibility of Airborne Precision Spacing operations under a variety of operational conditions. These included several types of merge and approach geometries along with the complementary merging and in-trail operations. Twelve airline pilots and four controllers participated in this simulation. Performance and questionnaire data were collected from a total of eighty-four individual arrivals. The pilots were able to achieve precise spacing with a mean error of 0.5 seconds and a standard deviation of 4.7 seconds. No statistically significant di erences in spacing performance were found between in-trail and merging operations or among the three modeled airspaces. Questionnaire data showed general acceptance for both pilots and controllers. These results reinforce previous findings from full-mission simulation and flight evaluation of the in-trail operations. This paper reviews the results of this simulation in detail.

Barmore, Bryan E.↗

Enhanced Monitoring and Forecasting of South Asian Air Quality Episodes with Multi-Sensor Satellite Products and Dispersion Modeling

Air pollution and particulates represent a serious environmental, public health, and overarching societal concern in the Hindu Kush Himalaya (HKH) region of south-central Asia, especially during the boreal winter and spring months. Frequent contributors to poor air quality of the region include dust and particulate matter transport from the Middle East region and western India, persistent nocturnal fog and smog during the stable dry monsoon months, and biomass burning during the pre-monsoon months of boreal spring. Nocturnal and multi-day persistent stable fog and smog events can occur during the stable conditions of the dry monsoon months that lead to hazardous visibility reductions (e.g., at major airports such as Delhi, India)and poor air quality, particularly in urban corridors.Our project goal is therefore to design and implement a robust air quality and chemistry observation and modeling system using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and the Weather Research and Forecasting coupled with Chemistry (WRF-Chem) models. This system effectively assimilates aerosol and trace gas retrievals from geostationary and polar-orbiting satellites to advance the monitoring and prediction capabilities of air quality and visibility reductions throughout the HKH region. For this presentation, we highlight several[multi-spectral] geostationary satellite products and dispersion modeling capabilities being developed and implemented for improved situational awareness and forecasting of air quality episodes.Launched in December 2018, the Advanced Meteorological Imager (AMI) aboard the Geostationary-Korean Multi-Purpose Satellite-2A (GEO-KOMPSAT-2A, or GK2A) provides 16 channels of multi-spectral information similar to the U.S. GOES-16/17 satellites. Proven community recipes for generating multi-spectral Red-Green-Blue (RGB) composite products to detect specific meteorological phenomena are applied to the AMI data for the HKH region. We implemented four such RGB products consisting of truecolor with Rayleigh correction to aid in smoke detection; dust RGB for monitoring larger particulate matter; nighttime microphysics for fog/smog detection;and natural color fire RGB and the shortwave 3.8 micron channel for fire hot-spot detection.We additionally configured HYSPLIT for dust/sand dispersion and concentration forecasts over HKH. The HYSPLIT dispersion simulations are initially being conducted with two different methodologies: (1) dust/sand lofting based on initializing plume releases from visual inspection of the dust RGB imagery; and (2) dust/sand release and dispersion using the internal HYSPLIT algorithm that determines lofting from input wind speeds and prescribed land use. The goal is to develop a near real-time HYSPLIT modeling solution for routinely simulating the transport and dispersion of dust plumes across the HKH region. This presentation illustrates these products and capabilities for various use cases from the 2019 to 2021 period, highlighting a particularly unhealthy episode during late March 2021 across Nepal.

Remote Sensing↗

NASA Tech Briefs, December 2005

Topics covered include: Video Mosaicking for Inspection of Gas Pipelines; Shuttle-Data-Tape XML Translator; Highly Reliable, High-Speed, Unidirectional Serial Data Links; Data-Analysis System for Entry, Descent, and Landing; Hybrid UV Imager Containing Face-Up AlGaN/GaN Photodiodes; Multiple Embedded Processors for Fault-Tolerant Computing; Hybrid Power Management; Magnetometer Based on Optoelectronic Microwave Oscillator; Program Predicts Time Courses of Human/ Computer Interactions; Chimera Grid Tools; Astronomer's Proposal Tool; Conservative Patch Algorithm and Mesh Sequencing for PAB3D; Fitting Nonlinear Curves by Use of Optimization Techniques; Tool for Viewing Faults Under Terrain; Automated Synthesis of Long Communication Delays for Testing; Solving Nonlinear Euler Equations With Arbitrary Accuracy; Self-Organizing-Map Program for Analyzing Multivariate Data; Tool for Sizing Analysis of the Advanced Life Support System; Control Software for a High-Performance Telerobot; Java Radar Analysis Tool; Architecture for Verifiable Software; Tool for Ranking Research Options; Enhanced, Partially Redundant Emergency Notification System; Close-Call Action Log Form; Task Description Language; Improved Small-Particle Powders for Plasma Spraying; Bonding-Compatible Corrosion Inhibitor for Rinsing Metals; Wipes, Coatings, and Patches for Detecting Hydrazines; Rotating Vessels for Growing Protein Crystals; Oscillating-Linear-Drive Vacuum Compressor for CO2; Mechanically Biased, Hinged Pairs of Piezoelectric Benders; Apparatus for Precise Indium-Bump Bonding of Microchips; Radiation Dosimetry via Automated Fluorescence Microscopy; Multistage Magnetic Separator of Cells and Proteins; Elastic-Tether Suits for Artificial Gravity and Exercise; Multichannel Brain-Signal-Amplifying and Digitizing System; Ester-Based Electrolytes for Low-Temperature Li-Ion Cells; Hygrometer for Detecting Water in Partially Enclosed Volumes; Radio-Frequency Plasma Cleaning of a Penning Malmberg Trap; Reduction of Flap Side Edge Noise - the Blowing Flap; and Preventing Accidental Ignition of Upper-Stage Rocket Motors.

Source record↗

Colloid Microthruster Flight Performance Results from Space Technology 7 Disturbance Reduction System

Space Technology 7 Disturbance Reduction System (ST7-DRS) is a NASA technology demonstration payload as part of the ESA LISA Pathfinder (LPF) mission, which launched on December 3, 2015. The ST7-DRS payload includes colloid microthrusters as part of a drag-free dynamic control system (DCS) hosted on an integrated avionics unit (IAU) with spacecraft attitude and test mass position provided by the LPF spacecraft computer and the highly sensitive gravitational reference sensor (GRS) as part of the LISA Technology Package (LTP). The objective of the DRS was to validate two technologies: colloid micro-Newton thrusters (CMNT) to provide low-noise control capability of the spacecraft, and drag-free flight control. The CMNT were developed by Busek Co., Inc., in a partnership with NASA Jet Propulsion Laboratory (JPL), and the DCS algorithms and flight software were developed at NASA Goddard Space Flight Center (GSFC). ST7-DRS demonstrated drag-free operation with 10nmHz level precision spacecraft position control along the primary axis of the LTP using eight CMNTs that provided 5-30 N each with 0.1 N precision. The DCS and CMNTs performed as required and as expected from ground test results, meeting all Level 1 requirements based on on-orbit data and analysis. DRS microthrusters operated for 2400 hours in flight during commissioning activities, a 90-day experiment and the extended mission. This mission represents the first validated demonstration of electrospray thrusters in space, providing precision spacecraft control and drag-free operation in a flight environment with applications to future gravitational wave observatories like LISA.

Ziemer, John↗

Spectral Re-Growth Reduction for CCSDS 8-D 8-PSK TCM

This report presents a study on the CCSDS recommended 8-dimensional 8 PSK Trellis Coded Modulation (TCM) scheme. The important steps of the CCSDS scheme include: conversion of serial data into parallel form, differential encoding, convolutional encoding, constellation mapping, and filtering the 8-PSK symbols using the square root raised cosine (SRRC) pulses. The last step, namely the filtering of the 8 PSK symbols using SRRC pulses, significantly affects the bandwidth of the signal. If a nonlinear power amplifier is used, the SRRC filtered signal creates spectral regrowth. The purpose of this report is to investigate a technique, called the smooth phase interpolated keying (SPIK), that can provide an alternative to SRRC filtering so that good spectral as well as power efficiencies can be obtained with the CCSDS encoder. The results of this study show that the CCSDS encoder does not affect the spectral shape of the SRRC filtered signal or the SPIK signal. When a nonlinear traveling wave tube amplifier (TWTA) is used, the spectral performance of the SRRC signal degrades significantly while the spectral performance of SPIK remains unaffected. The degrading effect of a nonlinear solid state power amplifier (SSPA) on SRRC is found to be less than that due to a nonlinear TWTA. However, in both cases, the spectral performance of the SRRC modulated signal is worse than that of the SPIK signal. The bit error rate (BER) performance of the SRRC signal in a linear amplifier environment is about 2.5 dB better than that of the SPIK signal when both the receivers use algorithms of similar complexity. In a nonlinear TWTA environment, the SRRC signal requires accurate phase tracking since the TWTA introduces additional phase distortion. This problem does not arise with SPIK signal due to its constant envelope property. When a nonlinear amplifier is used, the SRRC method loses nearly 1 dB in the bit error rate performance. The SPIK signal does not lose any performance. Thus the performance gap between SRRC and SPIK reduces. The BER performance of SPIK can be improved even further by using a more optimal receiver. A similar optimal receiver for SRRC is quite complex since the amplifier distorts the pulse shape. However, this requires further investigation and is not covered in this report.

Borah, Deva K.↗

Parameterizing Spectral Surface Reflectance Relationships for the Dark Target Aerosol Algorithm Applied to A Geostationary Imager

Originally developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) in polar, sun-synchronous low-earth orbit (LEO), the Dark Target (DT) aerosol retrieval algorithm relies on the assumption of a Surface Reflectance Parameterization (SRP) over land surfaces. Specifically for vegetated and dark-soiled surfaces, values of surface reflectance in blue and red visible-wavelength bands are assumed to be nearly linearly related to each other and to the value in a shortwave infrared (SWIR) wavelength band. This SRP also includes dependencies on scattering angle and a normalized difference vegetation index computed from two SWIR bands (NDVISWIR). As the DT retrieval algorithm is being ported to new sensors to continue and expand the aerosol data record, we assess whether the MODIS-assumed SRP can be used for these sensors. Here, we specifically assess SRP for the Advanced Baseline Imager (ABI) aboard, the Geostationary Operational Environmental Satellite (GOES)-16/East (ABIE). First, we find that using MODIS-based SRP leads to higher biases and artificial diurnal signatures in aerosol optical depth (AOD)retrievals from ABIE. The primary reason appears to be that geostationary orbit (GEO) encounters an entirely different set of observation geometry than does LEO, primarily with regards to solar angles coupled with fixed view angles. Therefore, we have developed a new SRP for GEO that draws the angular shape of the surface bidirectional reflectance. We also introduce modifications to the parametrization of both red-SWIR and blue-red spectral relationships to include additional information.The revised Red-SWIR SRP includes solar zenith angle, NDVISWIR, and land-type percentage from an ancillary database. The blue-red SRP adds dependencies on the scattering angle and NDVISWIR. The new SRPs improve the AOD retrieval of ABIE in terms of overall less bias and mitigation of the overestimation around local noon. The average bias of DT AOD compared to AERONET AOD shows a reduction from 0.08 to 0.03, while the bias of local solar noon decreases from 0.12 to 0.03.The agreement between DT and AERONET AOD is established through regression slope of 1.06 and y-intercept of 0.01with correlation coefficient is0.74. By using the new SRP, the percentage of data falling within the expected error range (±0.05 + 15%) is notably risen from 54% to 78%.

Mijin Kim↗

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-ofthe-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Hesham ElAbd↗

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Deep-learning↗

RUSHMAPS: Real-Time Uploadable Spherical Harmonic Moment Analysis for Particle Spectrometers

RUSHMAPS is a new onboard data reduction scheme that gives real-time access to key science parameters (e.g. moments) of a class of heliophysics science and/or solar system exploration investigation that includes plasma particle spectrometers (PPS), but requires moments reporting (density, bulk-velocity, temperature, pressure, etc.) of higher-level quality, and tolerates a lowpass (variable quality) spectral representation of the corresponding particle velocity distributions, such that telemetry use is minimized. The proposed methodology trades access to the full-resolution velocity distribution data, saving on telemetry, for real-time access to both the moments and an adjustable-quality (increasing quality increases volume) spectral representation of distribution functions. Traditional onboard data storage and downlink bandwidth constraints severely limit PPS system functionality and drive cost, which, as a consequence, drives a limited data collection and lower angular energy and time resolution. This prototypical system exploit, using high-performance processing technology at GSFC (Goddard Space Flight Center), uses a SpaceCube and/or Maestro-type platform for processing. These processing platforms are currently being used on the International Space Station as a technology demonstration, and work is currently ongoing in a new onboard computation system for the Earth Science missions, but they have never been implemented in heliospheric science or solar system exploration missions. Preliminary analysis confirms that the targeted processor platforms possess the processing resources required for realtime application of these algorithms to the spectrometer data. SpaceCube platforms demonstrate that the target architecture possesses the sort of compact, low-mass/power, radiation-tolerant characteristics needed for flight. These high-performing hybrid systems embed unprecedented amounts of onboard processing power in the CPU (central processing unit), FPGAs (field programmable gate arrays), and DSP (digital signal processing) elements. The fundamental computational algorithm de constructs 3D velocity distributions in terms of spherical harmonic spectral coefficients (which are analogous to a Fourier sine-cosine decomposition), but uses instead spherical harmonics Legendre polynomial orthogonal functions as a basis for the expansion, portraying each 2D angular distribution at every energy or, geometrically, spherical speed-shell swept by the particle spectrometer. Optionally, these spherical harmonic spectral coefficients may be telemetered to the ground. These will provide a smoothed description of the velocity distribution function whose quality will depend on the number of coefficients determined. Successfully implemented on the GSFC-developed processor, the capability to integrate the proposed methodology with both heritage and anticipated future plasma particle spectrometer designs is demonstrated (with sufficiently detailed design analysis to advance TRL) to show specific science relevancy with future HSD (Heliophysics Science Division) solar-interplanetary, planetary missions, sounding rockets and/or CubeSat missions.

Figueroa-Vinas, Adolfo↗

NASA's Robotic Lunar Lander Development Project

Since early 2005, NASA's Robotic Lunar Lander Development (RLLD) office at NASA MSFC, in partnership with the Applied Physics Laboratory (APL), has developed mission concepts and preformed risk-reduction activities to address planetary science and exploration objectives uniquely met with landed missions. The RLLD team developed several concepts for lunar human-exploration precursor missions to demonstrate precision landing and in-situ resource utilization, a multi-node lunar geophysical network mission, either as a stand-alone mission, or as part of the International Lunar Network (ILN), a Lunar Polar Volatiles Explorer and a Mercury lander mission for the Planetary Science decadal survey, and an asteroid rendezvous and landing mission for the Exploration Precursor Robotics Mission (xPRM) office. The RLLD team has conducted an extensive number of risk-reduction activities in areas common to all lander concepts, including thruster testing, propulsion thermal control demonstration, composite deck design and fabrication, and landing leg stability and vibration. In parallel, the team has developed two robotic lander testbeds providing closed-loop, autonomous hover and descent activities for integration and testing of flight-like components and algorithms. A compressed-air test article had its first flight in September 2009 and completed over 150 successful flights. This small test article (107 kg dry/146 kg wet) uses a central throttleable thruster to offset gravity, plus 3 descent thrusters (~37lbf ea) and 6 attitude-control thrusters (~12lbf ea) to emulate the flight system with pulsed operation over approximately 10s of flight time. The test article uses carbon composite honeycomb decks, custom avionics (COTS components assembled in-house), and custom flight and ground software. A larger (206 kg dry/322 kg wet), hydrogen peroxide-propelled vehicle began flight tests in spring 2011 and fly over 30 successful flights to a maximum altitude of 30m. The monoprop testbed also uses a central gravity-canceling thruster and 3 descent thrusters, but has 12 attitude-control thrusters and a maximum flight time of over a minute. The testbed uses aluminum ortho-grid decks, an LN200-1 IMU, Roke Manor Radar Altimeter, Illunis optical cameras, Novatel Pro-Pak GPS truth data system, Pressure transducers & thermocouples for housekeeping, "In-Control" ground system software, and the core Flight Executive (cFE) modular software environment. The peroxide lander testbed is able to accept other sensors and algorithms for testing, both from within NASA and from other customers. Through these activities, the RLLD team has significantly reduced technical risks for all small and medium class robotic landers for the Moon and other airless planetary bodies.

Cohen, Barbara A.↗

Model-Based Fatigue Prognosis of Fiber-Reinforced Laminates Exhibiting Concurrent Damage Mechanisms

Prognostics of large composite structures is a topic of increasing interest in the field of structural health monitoring for aerospace, civil, and mechanical systems. Along with recent advancements in real-time structural health data acquisition and processing for damage detection and characterization, model-based stochastic methods for life prediction are showing promising results in the literature. Among various model-based approaches, particle-filtering algorithms are particularly capable in coping with uncertainties associated with the process. These include uncertainties about information on the damage extent and the inherent uncertainties of the damage propagation process. Some efforts have shown successful applications of particle filtering-based frameworks for predicting the matrix crack evolution and structural stiffness degradation caused by repetitive fatigue loads. Effects of other damage modes such as delamination, however, are not incorporated in these works. It is well established that delamination and matrix cracks not only co-exist in most laminate structures during the fatigue degradation process but also affect each other's progression. Furthermore, delamination significantly alters the stress-state in the laminates and accelerates the material degradation leading to catastrophic failure. Therefore, the work presented herein proposes a particle filtering-based framework for predicting a structure's remaining useful life with consideration of multiple co-existing damage-mechanisms. The framework uses an energy-based model from the composite modeling literature. The multiple damage-mode model has been shown to suitably estimate the energy release rate of cross-ply laminates as affected by matrix cracks and delamination modes. The model is also able to estimate the reduction in stiffness of the damaged laminate. This information is then used in the algorithms for life prediction capabilities. First, a brief summary of the energy-based damage model is provided. Then, the paper describes how the model is embedded within the prognostic framework and how the prognostics performance is assessed using observations from run-to-failure experiments

Prognostics↗

An efficient system for reliably transmitting image and video data over low bit rate noisy channels

This research project is intended to develop an efficient system for reliably transmitting image and video data over low bit rate noisy channels. The basic ideas behind the proposed approach are the following: employ statistical-based image modeling to facilitate pre- and post-processing and error detection, use spare redundancy that the source compression did not remove to add robustness, and implement coded modulation to improve bandwidth efficiency and noise rejection. Over the last six months, progress has been made on various aspects of the project. Through our studies of the integrated system, a list-based iterative Trellis decoder has been developed. The decoder accepts feedback from a post-processor which can detect channel errors in the reconstructed image. The error detection is based on the Huber Markov random field image model for the compressed image. The compression scheme used here is that of JPEG (Joint Photographic Experts Group). Experiments were performed and the results are quite encouraging. The principal ideas here are extendable to other compression techniques. In addition, research was also performed on unequal error protection channel coding, subband vector quantization as a means of source coding, and post processing for reducing coding artifacts. Our studies on unequal error protection (UEP) coding for image transmission focused on examining the properties of the UEP capabilities of convolutional codes. The investigation of subband vector quantization employed a wavelet transform with special emphasis on exploiting interband redundancy. The outcome of this investigation included the development of three algorithms for subband vector quantization. The reduction of transform coding artifacts was studied with the aid of a non-Gaussian Markov random field model. This results in improved image decompression. These studies are summarized and the technical papers included in the appendices.

Costello, Daniel J., Jr.↗

Phase Shift Interferometer and Growth Set Up to Step Pattern Formation During Growth From Solutions. Influence of the Oscillatory solution Flow on Stability

We have assembled an experimental setup based on Michelson interferometry with the growing crystal surface as one of the reflective surfaces. The crystallization part of the device allows optical monitoring of a face of a crystal growing at temperature stable within 0.05 C in a flow of solution of controlled direction and speed. The reference arm of the interferometer contains a liquid crystal element that allows controlled shifts of the phase of the interferograms. We employ an image-processing algorithm, which combines five images with a pi/2 phase difference between each pair of images. The images are transferred to a computer by a camera capable of capturing 60 frames per second. The device allows data collection on surface morphology and kinetics during the face layers growth over a relatively large area (approximately 4 sq. mm) in situ and in real time during growth. The estimated depth resolution of the phase shifting interferometry is approximately 50 Angstroms. The data will be analyzed in order to reveal and monitor step bunching during the growth process. The crystal chosen as a model for study in this work is KH2PO4 (KDP). This optically non-linear material is widely used in frequency doubling applications. There have been a number of studies of the kinetics of KDP crystallization that can serve as a benchmark for our investigations. However, so far, systematic quantitative characteristics of step interaction and bunching are missing. We intend to present our first quantitative results on the onset, initial stages and development of instabilities in moving step trains on vicinal crystal surfaces at varying supersaturation, flow rate, and flow direction. Behavior of a vicinal face growing from solution flowing normal to the steps and periodically changing its direction in time was considered theoretically. It was found that this oscillating flow reduces both stabilization and destabilization effects resulted from the unidirectional solution flow directed up the step stream and down the step stream. This reduction of stabilization and destabilization comes from effective mixing which entangles the phase shifts between the spatially periodic interface perturbation and the concentration wave induced by this perturbation. Numerical results and simplified mixing criterion will be discussed.

Chernov, Alex A.↗

Data Assimilation Experiments using Quality Controlled AIRS Version 5 Temperature Soundings

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AlRS data. Version 5 contains accurate case-by-case error estimates for most derived products, which are also used for quality control. We have conducted forecast impact experiments assimilating AlRS quality controlled temperature profiles using the NASA GEOS-5 data assimilation system, consisting of the NCEP GSI analysis coupled with the NASA FVGCM. Assimilation of quality controlled temperature profiles resulted in significantly improved forecast skill in both the Northern Hemisphere and Southern Hemisphere Extra-Tropics, compared to that obtained from analyses obtained when all data used operationally by NCEP except for AlRS data is assimilated. Experiments using different Quality Control thresholds for assimilation of AlRS temperature retrievals showed that a medium quality control threshold performed better than a tighter threshold, which provided better overall sounding accuracy; or a looser threshold, which provided better spatial coverage of accepted soundings. We are conducting more experiments to further optimize this balance of spatial coverage and sounding accuracy from the data assimilation perspective. In all cases, temperature soundings were assimilated well below cloud level in partially cloudy cases. The positive impact of assimilating AlRS derived atmospheric temperatures all but vanished when only AIRS stratospheric temperatures were assimilated. Forecast skill resulting from assimilation of AlRS radiances uncontaminated by clouds, instead of AlRS temperature soundings, was only slightly better than that resulting from assimilation of only stratospheric AlRS temperatures. This reduction in forecast skill is most likely the result of significant loss of tropospheric information when only AIRS radiances unaffected by clouds are used in the data assimilation process.

Susskind, Joel↗

Orion MPCV GN and C End-to-End Phasing Tests

End-to-end integration tests are critical risk reduction efforts for any complex vehicle. Phasing tests are an end-to-end integrated test that validates system directional phasing (polarity) from sensor measurement through software algorithms to end effector response. Phasing tests are typically performed on a fully integrated and assembled flight vehicle where sensors are stimulated by moving the vehicle and the effectors are observed for proper polarity. Orion Multi-Purpose Crew Vehicle (MPCV) Pad Abort 1 (PA-1) Phasing Test was conducted from inertial measurement to Launch Abort System (LAS). Orion Exploration Flight Test 1 (EFT-1) has two end-to-end phasing tests planned. The first test from inertial measurement to Crew Module (CM) reaction control system thrusters uses navigation and flight control system software algorithms to process commands. The second test from inertial measurement to CM S-Band Phased Array Antenna (PAA) uses navigation and communication system software algorithms to process commands. Future Orion flights include Ascent Abort Flight Test 2 (AA-2) and Exploration Mission 1 (EM-1). These flights will include additional or updated sensors, software algorithms and effectors. This paper will explore the implementation of end-to-end phasing tests on a flight vehicle which has many constraints, trade-offs and compromises. Orion PA-1 Phasing Test was conducted at White Sands Missile Range (WSMR) from March 4-6, 2010. This test decreased the risk of mission failure by demonstrating proper flight control system polarity. Demonstration was achieved by stimulating the primary navigation sensor, processing sensor data to commands and viewing propulsion response. PA-1 primary navigation sensor was a Space Integrated Inertial Navigation System (INS) and Global Positioning System (GPS) (SIGI) which has onboard processing, INS (3 accelerometers and 3 rate gyros) and no GPS receiver. SIGI data was processed by GN&C software into thrust magnitude and direction commands. The processing changes through three phases of powered flight: pitchover, downrange and reorientation. The primary inputs to GN&C are attitude position, attitude rates, angle of attack (AOA) and angle of sideslip (AOS). Pitch and yaw attitude and attitude rate responses were verified by using a flight spare SIGI mounted to a 2-axis rate table. AOA and AOS responses were verified by using a data recorded from SIGI movements on a robotic arm located at NASA Johnson Space Center. The data was consolidated and used in an open-loop data input to the SIGI. Propulsion was the Launch Abort System (LAS) Attitude Control Motor (ACM) which consisted of a solid motor with 8 nozzles. Each nozzle has active thrust control by varying throat area with a pintle. LAS ACM pintles are observable through optically transparent nozzle covers. SIGI movements on robot arm, SIGI rate table movements and LAS ACM pintle responses were video recorded as test artifacts for analysis and evaluation. The PA-1 Phasing Test design was determined based on test performance requirements, operational restrictions and EGSE capabilities. This development progressed during different stages. For convenience these development stages are initial, working group, tiger team, Engineering Review Team (ERT) and final.

Neumann, Brian C.↗