KEYWORDS: Commercial off the shelf technology, Data processing, Field programmable gate arrays, Digital signal processing, Prototyping, Signal processing, Information technology, LIDAR, Earth sciences, Computing systems
The project called High-Speed On-Board Data Processing for Science Instruments (HOPS) has been funded by NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) program since April, 2012. The HOPS team recently completed two flight campaigns during the summer of 2014 on two different aircrafts with two different science instruments. The first flight campaign was in July, 2014 based at NASA Langley Research Center (LaRC) in Hampton, VA on the NASA’s HU-25 aircraft. The science instrument that flew with HOPS was Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) CarbonHawk Experiment Simulator (ACES) funded by NASA’s Instrument Incubator Program (IIP). The second campaign was in August, 2014 based at NASA Armstrong Flight Research Center (AFRC) in Palmdale, CA on the NASA’s DC-8 aircraft. HOPS flew with the Multifunctional Fiber Laser Lidar (MFLL) instrument developed by Excelis Inc. The goal of the campaigns was to perform an end-to-end demonstration of the capabilities of the HOPS prototype system (HOPS COTS) while running the most computationally intensive part of the ASCENDS algorithm real-time on-board. The comparison of the two flight campaigns and the results of the functionality tests of the HOPS COTS are presented in this paper.
Optimized designs of the Navigation Doppler Lidar (NDL) instrument for Autonomous Landing Hazard Avoidance Technology (ALHAT) were accomplished via Interdisciplinary Design Concept (IDEC) at NASA Langley Research Center during the summer of 2013. Three branches in the Engineering Directorate and three students were involved in this joint task through the NASA Langley Aerospace Research Summer Scholars (LARSS) Program. The Laser Remote Sensing Branch (LRSB), Mechanical Systems Branch (MSB), and Structural and Thermal Systems Branch (STSB) were engaged to achieve optimal designs through iterative and interactive collaborative design processes. A preliminary design iteration was able to reduce the power consumption, mass, and footprint by removing redundant components and replacing inefficient components with more efficient ones. A second design iteration reduced volume and mass by replacing bulky components with excessive performance with smaller components custom-designed for the power system. The existing power system was analyzed to rank components in terms of inefficiency, power dissipation, footprint and mass. Design considerations and priorities are compared along with the results of each design iteration. Overall power system improvements are summarized for design implementations.
Optimized designs of the Navigation Doppler Lidar (NDL) instrument for Autonomous Landing Hazard Avoidance Technology (ALHAT) were accomplished via Interdisciplinary Design Concept (IDEC) at NASA Langley Research Center during the summer of 2013. Three branches in the Engineering Directorate and three students were involved in this joint task through the NASA Langley Aerospace Research Summer Scholars (LARSS) Program. The Laser Remote Sensing Branch (LRSB), Mechanical Systems Branch (MSB), and Structural and Thermal Systems Branch (STSB) were engaged to achieve optimal designs through iterative and interactive collaborative design processes. A preliminary design iteration was able to reduce the power consumption, mass, and footprint by removing redundant components and replacing inefficient components with more efficient ones. A second design iteration reduced volume and mass by replacing bulky components with excessive performance with smaller components custom-designed for the power system. Thermal modeling software was used to run steady state thermal analyses, which were used to both validate the designs and recommend further changes. Analyses were run on each redesign, as well as the original system. Thermal Desktop was used to run trade studies to account for uncertainty and assumptions about fan performance and boundary conditions. The studies suggested that, even if the assumptions were significantly wrong, the redesigned systems would remain within operating temperature limits.
Optimized designs of the Navigation Doppler Lidar (NDL) instrument for Autonomous Landing Hazard Avoidance Technology (ALHAT) were accomplished via Interdisciplinary Design Concept (IDEC) at NASA Langley Research Center during the summer of 2013. Three branches in the Engineering Directorate and three students were involved in this joint task through the NASA Langley Aerospace Research Summer Scholars (LARSS) Program. The Laser Remote Sensing Branch (LRSB), Mechanical Systems Branch (MSB), and Structural and Thermal Systems Branch (STSB) were engaged to achieve optimal designs through iterative and interactive collaborative design processes. A preliminary design iteration was able to reduce the power consumption, mass, and footprint by removing redundant components and replacing inefficient components with more efficient ones. A second design iteration reduced volume and mass by replacing bulky components with excessive performance with smaller components custom-designed for the power system. Mechanical placement collaboration reduced potential electromagnetic interference (EMI). Through application of newly selected electrical components and thermal analysis data, a total electronic chassis redesign was accomplished. Use of an innovative forced convection tunnel heat sink was employed to meet and exceed project requirements for cooling, mass reduction, and volume reduction. Functionality was a key concern to make efficient use of airflow, and accessibility was also imperative to allow for servicing of chassis internals. The collaborative process provided for accelerated design maturation with substantiated function.
The latest flight demonstration of Doppler Aerosol Wind Lidar (DAWN) at NASA Langley Research Center (LaRC) is presented. The goal of the campaign was to demonstrate the improvement of DAWN system since the previous flight campaign in 2012 and the capabilities of DAWN and the latest airborne wind profiling algorithm APOLO (Airborne Wind Profiling Algorithm for Doppler Wind Lidar) developed at LaRC. The comparisons of APOLO and another algorithm are discussed utilizing two and five line-of-sights (LOSs), respectively. Wind parameters from DAWN were compared with ground-based radar measurements for validation purposes. The campaign period was June – July in 2013 and the flight altitude was 8 km in inland toward Charlotte, NC, and offshores in Virginia Beach, VA and Ocean City, MD. The DAWN system was integrated into a UC12B with two operators onboard during the campaign.
KEYWORDS: Data processing, Commercial off the shelf technology, Field programmable gate arrays, Data archive systems, Digital signal processing, Algorithm development, Signal processing, Carbon dioxide, Aerosols, LIDAR
A new development of on-board data processing platform has been in progress at NASA Langley Research Center since April, 2012, and the overall review of such work is presented in this paper. The project is called High-Speed On-Board Data Processing for Science Instruments (HOPS) and focuses on a high-speed scalable data processing platform for three particular National Research Council’s Decadal Survey missions such as Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS), Aerosol-Cloud-Ecosystems (ACE), and Doppler Aerosol Wind Lidar (DAWN) 3-D Winds. HOPS utilizes advanced general purpose computing with Field Programmable Gate Array (FPGA) based algorithm implementation techniques. The significance of HOPS is to enable high speed on-board data processing for current and future science missions with its reconfigurable and scalable data processing platform. A single HOPS processing board is expected to provide approximately 66 times faster data processing speed for ASCENDS, more than 70% reduction in both power and weight, and about two orders of cost reduction compared to the state-of-the-art (SOA) on-board data processing system. Such benchmark predictions are based on the data when HOPS was originally proposed in August, 2011. The details of these improvement measures are also presented. The two facets of HOPS development are identifying the most computationally intensive algorithm segments of each mission and implementing them in a FPGA-based data processing board. A general introduction of such facets is also the purpose of this paper.
A technique has been developed for imaging the wind field over offshore areas being considered for wind farming. This is accomplished with an eye-safe 2-μm wavelength coherent Doppler lidar installed in an aircraft. By raster scanning the aircraft over the wind energy area (WEA), a three-dimensional map of the wind vector can be made. This technique was evaluated in 11 flights over the Virginia and Maryland offshore WEAs. Heights above the ocean surface planned for wind turbines are shown to be within the marine boundary layer, and the wind vector is seen to show variation across the geographical area of interest at turbine heights.
Two versions of airborne wind profiling algorithms for the pulsed 2-micron coherent Doppler lidar system at NASA Langley Research Center in Virginia are presented. Each algorithm utilizes different number of line-of-sight (LOS) lidar returns while compensating the adverse effects of different coordinate systems between the aircraft and the Earth. One of the two algorithms APOLO (Airborne Wind Profiling Algorithm for Doppler Wind Lidar) estimates wind products using two LOSs. The other algorithm utilizes five LOSs. The airborne lidar data were acquired during the NASA’s Genesis and Rapid Intensification Processes (GRIP) campaign in 2010. The wind profile products from the two algorithms are compared with the dropsonde data to validate their results.
A field demonstration was done from Virginia Beach, Virginia, to show the use of high-energy (250-mJ) eyesafe Doppler lidar for measurements of offshore wind. The lidar is located onshore and pointed near-horizontally to reach a target area many kilometers away. In sample measurements, the lidar scan's hypothetical turbine is located 6 km away. For one beam elevation of interest, the horizontal wind vector is measured by scanning the beam in azimuth. The elevation can then be changed to profile the wind at many altitudes. An example measurement is shown in which wind vector is determined at six altitudes covering the height of a supposed turbine and above. In addition to the wind vector, wind shear is measured across a turbine blade span width. Over a two-week period in October 2011, range capability was found to vary from 4.5 to 17 km depending on weather and aerosol backscatter conditions. A comparison was made with an anemometer to validate the lidar's measurements.
A pulsed 2-micron coherent Doppler lidar system at NASA Langley Research Center in Virginia flew on the NASA's
DC-8 aircraft during the NASA Genesis and Rapid Intensification Processes (GRIP) during the summer of 2010. The
participation was part of the project Doppler Aerosol Wind Lidar (DAWN) Air. Selected results of airborne wind
profiling are presented and compared with the dropsonde data for verification purposes. Panoramic presentations of
different wind parameters over a nominal observation time span are also presented for selected GRIP data sets. The real-time
data acquisition and analysis software that was employed during the GRIP campaign is introduced with its unique
features.
KEYWORDS: LIDAR, Profiling, Signal to noise ratio, Data acquisition, Doppler effect, Control systems, Data processing, Digital signal processing, Data transmission, Fourier transforms
Two different noise whitening methods in airborne wind profiling with a pulsed 2-micron coherent Doppler lidar system
at NASA Langley Research Center in Virginia are presented. In order to provide accurate wind parameter estimates
from the airborne lidar data acquired during the NASA Genesis and Rapid Intensification Processes (GRIP) campaign in
2010, the adverse effects of background instrument noise must be compensated properly in the early stage of data
processing. The results of the two methods are presented using selected GRIP data and compared with the dropsonde
data for verification purposes.
Sustained research efforts at NASA Langley Research Center (LaRC) during last fifteen years have resulted in a
significant advancement in 2-micron diode-pumped, solid-state laser transmitter for wind and carbon dioxide
measurement from ground, air and space-borne platform. Solid-state 2-micron laser is a key subsystem for a
coherent Doppler lidar that measures the horizontal and vertical wind velocities with high precision and resolution.
The same laser, after a few modifications, can also be used in a Differential Absorption Lidar (DIAL) system for
measuring atmospheric CO2 concentration profiles. Researchers at NASA Langley Research Center have
developed a compact, flight capable, high energy, injection seeded, 2-micron laser transmitter for ground and
airborne wind and carbon dioxide measurements. It is capable of producing 250 mJ at 10 Hz by an oscillator and
one amplifier. This compact laser transmitter was integrated into a mobile trailer based coherent Doppler wind and
CO2 DIAL system and was deployed during field measurement campaigns. This paper will give an overview of 2-
micron solid-state laser technology development and discuss results from recent ground-based field measurements.
KEYWORDS: Data acquisition, Digital signal processing, LIDAR, Control systems, Doppler effect, Electronics, Laser optics, Scanners, Laser systems engineering, Laser processing
A general overview of the development of a data acquisition and processing system is presented for a pulsed, 2-micron
coherent Doppler Lidar system located in NASA Langley Research Center in Hampton, Virginia, USA. It is a
comprehensive system that performs high-speed data acquisition, analysis, and data display both in real time and offline.
The first flight missions are scheduled for the summer of 2010 as part of the NASA Genesis and Rapid Intensification
Processes (GRIP) campaign for the study of hurricanes. The system as well as the control software is reviewed and its
requirements and unique features are discussed.
A pulsed, 2-μm coherent Differential Absorption Lidar (DIAL) / Integrated Path Differential Absorption (IPDA)
transceiver, developed under the Laser Risk Reduction Program (LRRP) at NASA, is integrated into a fully functional
lidar instrument. This instrument measures atmospheric CO2 profiles (by DIAL) from a ground platform. It allows the
investigators to pursue subsequent in science-driven deployments, and provides a unique tool for Active Sensing of CO2
Emissions over Night, Days, and Seasons (ASCENDS) validation that was strongly advocated in the recent ASCENDS
Workshop.
The design of the software for a 2-micron coherent high-speed Doppler lidar system for CO2 measurement at NASA
Langley Research Center is discussed in this paper. The specific strategy and design topology to meet the requirements
of the system are reviewed. In order to attain the high-speed digitization of the different types of signals to be sampled
on multiple channels, a carefully planned design of the control software is imperative. Samples of digitized data from
each channel and their roles in data analysis post processing are also presented. Several challenges of extremely-fast,
high volume data acquisition are discussed. The software must check the validity of each lidar return as well as other
monitoring channel data in real-time. For such high-speed data acquisition systems, the software is a key component that
enables the entire scope of CO2 measurement studies using commercially available system components.
The accurate measurement of energy in the application of lidar system for CO2 measurement is critical. Different
techniques of energy estimation in the online and offline pulses are investigated for post processing of lidar returns. The
cornerstone of the technique is the accurate estimation of the spectrum of lidar signal and background noise. Since the
background noise is not the ideal white Gaussian noise, simple average level estimation of noise level is not well fit in
the energy estimation of lidar signal and noise. A brief review of the methods is presented in this paper.
A 2-µm wavelength coherent Doppler lidar for wind measurement has been developed of an unprecedented laser pulse energy of 250-mJ in a rugged package. This high pulse energy is produced by a Ho:Tm:LuLiF laser with an optical amplifier. While the lidar is meant for use as an airborne instrument, ground-based tests were carried out to characterize performance of the lidar. Atmospheric measurements are presented, showing the lidar's capability for wind measurement in the atmospheric boundary layer and free troposphere. Lidar wind measurements are compared to a balloon sonde, showing good agreement between the two sensors.
KEYWORDS: Doppler effect, Signal to noise ratio, LIDAR, Data processing, Statistical analysis, Data analysis, Data acquisition, Digital signal processing, Algorithm development, Profiling
The new development of a one-sided nonlinear adaptive shift estimation technique (NADSET) is introduced. The
background of the algorithm and a brief overview of NADSET are presented. The new technique is applied to the wind
parameter estimates from a 2-μm wavelength coherent Doppler lidar system called VALIDAR located in NASA Langley
Research Center in Virginia. The new technique enhances wind parameters such as Doppler shift and power estimates in
low Signal-To-Noise-Ratio (SNR) regimes using the estimates in high SNR regimes as the algorithm scans the range
bins from low to high altitude. The original NADSET utilizes the statistics in both the lower and the higher range bins to
refine the wind parameter estimates in between. The results of the two different approaches of NADSET are compared.
This paper presents the comparison study of the theoretical and the empirical Cramer-Rao lower bounds (CRLBs) of
wind parameter estimates from a 2-μm wavelength coherent Doppler lidar system called VALIDAR located in NASA
Langley Research Center in Virginia. The statistical behavior of Doppler shift (DS) estimates in particular is of interest.
The estimates are commonly modeled as single-modal Gaussian random variables and this study is based on such
convention. The empirical statistics of DS estimates are estimated from a large amount of sample data in order to obtain
meaningful statistical moments. The impact of the new nonlinear adaptive Doppler-shift estimation technique known as
NADSET is also briefly presented in terms of the statistics of wind parameter estimates.
A coherent Doppler lidar at 2 µm wavelength has been built with higher output energy (100 mJ) than previously available. The laser transmitter is based on diode-pumped Ho:Tm:LuLiF, a recently developed laser material that allows more efficient energy extraction. Single-frequency operation is achieved by a ramp-and-fire injection seeding technique. An advanced photodetector architecture is used incorporating photodiodes in a dual-balanced configuration. A digital signal processing system has been built, allowing real-time display of wind and aerosol backscatter data products. The high pulse energy and receiver efficiency provides for measurement of wind fields to ranges not seen before with 2 µm lidars, and example wind measurements were made to show this capability.
Different methods of energy estimation for a differential absorption lidar (DIAL) system at NASA Langley Research
Center in Virginia are investigated in this paper. The system is a 2- &mgr;m wavelength coherent Doppler lidar called
VALIDAR that has been traditionally used for measuring wind. Recent advances in laser wavelength control have
allowed the new use of this lidar for measuring atmospheric CO2 concentration by a DIAL technique. In order to realize
accurate DIAL measurements, optimal signal processing techniques are required to represent the energy of the
heterodyned backscatter signals. The noise energy was estimated by minimizing the mean square error in its estimate
and was used to normalize its adverse influence on accurate estimation of the concentration of CO2 in the atmosphere.
The impact of different methods on the statistics of CO2 concentration measurements is compared.
KEYWORDS: Doppler effect, LIDAR, Signal to noise ratio, Wind measurement, Nonlinear optics, Data acquisition, Digital signal processing, Optical engineering, Statistical analysis, Signal processing
The signal-processing aspect of a 2-µm wavelength-coherent Doppler lidar system under development at NASA Langley Research Center in Virginia is investigated in this paper. The 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 of power, Doppler shift, wind speed, and wind direction, especially in the low signal-to-noise-ratio (SNR) regime. A novel nonlinear adaptive Doppler-shift estimation technique (NADSET) is developed for this purpose, 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 the SNR decreases. NADSET compensates this deterioration by adaptively utilizing the statistics of Doppler-shift estimates 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.
KEYWORDS: LIDAR, Doppler effect, Signal processing, Data processing, Solids, Digital signal processing, Stochastic processes, Interference (communication), Statistical analysis, Signal to noise ratio
A 2-μm wavelength coherent Doppler lidar system under development at NASA Langley Research Center in Virginia is
discussed from the perspective of signal processing. The current data processing algorithm returns a variety of wind
parameters such as power spectra, Doppler shift, wind speed, and wind direction. This paper compares the quality of
selected wind parameter estimates by computing the power spectral density of stochastic lidar return data via the
periodogram and the maximum likelihood power estimation method. The improvement in resolution of power spectra
and Doppler shift estimates is witnessed by means of zero padding before the power spectral density was estimated in
each range bin.
KEYWORDS: LIDAR, Signal to noise ratio, Doppler effect, Interference (communication), Data processing, Profiling, Stochastic processes, Signal processing, Backscatter, Aerosols
The current nonlinear algorithm of the coherent Doppler lidar system VALIDAR at NASA Langley Research Center
estimates wind parameters such as Doppler shift, power, wind velocity and direction by locating the maximum power
and its frequency from the periodogram of the stochastic lidar returns. Due to the nonlinear nature of the algorithm,
mathematically tractable parametric approaches to improve the quality of wind parameter estimates may pose a very
little influence on the estimates especially in low signal-to-noise-ratio (SNR) regime. This paper discusses an alternate
approach to accurately estimate the nonlinear wind parameters while preventing ambiguity in decision-making process
via the subspace decomposition of wind data. By exploring the orthogonality between noise and signal subspaces
expanded by the eigenvectors corresponding to the eigenvalues representing each subspace, a single maximum power
frequency is estimated while suppressing erroneous peaks that are always present with conventional Fourier-transformbased
frequency spectra. The subspace decomposition approach is integrated into the data processing program of
VALIDAR in order to study the impact of such an approach on wind profiling with VALIDAR.
KEYWORDS: LIDAR, Statistical analysis, Statistical modeling, Data modeling, Signal to noise ratio, Solids, Doppler effect, Data processing, Profiling, Data acquisition
The wind parameter estimates from a state-of-the-art 2-μm coherent lidar system located at NASA Langley, Virginia,
named VALIDAR (validation lidar), were compared after normalizing the noise by its estimated power spectra via the
periodogram and the linear predictive coding (LPC) scheme. The power spectra and the Doppler shift estimates were the
main parameter estimates for comparison. Different types of windowing functions were implemented in VALIDAR data
processing algorithm and their impact on the wind parameter estimates was observed. Time and frequency independent
windowing functions such as Rectangular, Hanning, and Kaiser-Bessel and time and frequency dependent apodized
windowing function were compared. The briefing of current nonlinear algorithm development for Doppler shift
correction subsequently follows.
KEYWORDS: Doppler effect, LIDAR, Signal to noise ratio, Statistical analysis, Wind measurement, Data acquisition, Autoregressive models, Data processing, Control systems, Aerosols
A novel Nonlinear Adaptive Doppler Shift Estimation Technique (NADSET) is introduced in this paper. The quality of
Doppler shift and power estimations by conventional Fourier-transform-based spectrum estimation methods deteriorates
rapidly in low signal-to-noise-ratio (SNR) environment. The new NADSET algorithm compensates such deterioration in
the quality of wind parameter estimates by adaptively utilizing the statistics of Doppler shift estimate in strong SNR
ranges and identifying sporadic range bins where good Doppler shift estimates are found. NADSET is based on the
nature of continuous wind profile and significantly improves the accuracy and the quality of Doppler shift estimates in
low SNR ranges. The authenticity of NADSET is established by comparing the trend of wind parameters with and
without NADSET applied to the lidar returns acquired over a long period of time by the coherent Doppler lidar system
VALIDAR at NASA Langley Research Center in Virginia.
State of the art 2-micron lasers and other lidar components under development by NASA are being demonstrated and validated in a mobile test bed Doppler wind lidar. A lidar intercomparison facility has been developed to ensure parallel alignment of up to 4 Doppler lidar systems while measuring wind. Investigations of the new components; their operation in a complete system; systematic and random errors; the hybrid (joint coherent and direct detection) approach to global wind measurement; and atmospheric wind behavior are planned. Future uses of the VALIDAR (VALIDation LIDAR) mobile lidar may include comparison with the data from an airborne Doppler wind lidar in preparation for validation by the airborne system of an earth orbiting Doppler wind lidar sensor.
High-energy 2-micron lasers have been incorporated in a breadboard coherent Doppler lidar to test component technologies and explore applications for remote sensing of the atmosphere. Design of the lidar is presented including aspects in the laser transmitter, receiver, photodetector, and signal processing. Sample data is presented on wind profiling and CO2 concentration measurements.
The majority of Direction-of-Arrival (DOA) estimation methods studied in the literature work effectively in relatively strong signal power environment [positive dB of Array- Signal-to-Noise-Ratio (ASNR)]. In weak power signal environments, conventional beamformer-based and subspace-based methods fail to estimate the DOA correctly. The MaxMax method allows to maintain accurate estimates of the DOA even in extremely noisy environments (-10 dB of ASNR). The method is reviewed and its performance is compared with that of the Conventional Beamformer, Capon's Beamformer, MUSIC, ESPRIT, and Min-Norm methods. In contrast with the subspace-based methods which entirely depend on the full rank signal covariance matrix, the MaxMax method does not. Hence, the performance of the method remains superior to that of the others without adjusting the algorithm to the characteristics of source signals such as multipath or singlepath. If the signal power is so weak that its presence is almost negligible, Akaike's Information Criterion (AIC) or Minimum Description Length (MDL) do not yield correct estimates the number of signal paths. A new 'spatial sampling' technique and its performance are presented for estimating the number of signals in case of strongly suppressed signal power.
Estimation of the direction-of-arrival (DOA), also known as direction-finding (DF) problem, has been an active research area for some time. While one DOA estimation method may be better than another depending on the application, these methods can be categorized into either subspace decomposition methods or beamforming methods. Subspace decomposition methods are usually known to provide higher resolution but most of them assume relatively high signal to noise ratio. For low array-signal-to-noise-ratio (ASNR), however, their performance degenerates in a similar way as conventional beam forming methods do. In this paper, we introduce a new method which we refer to as 'MaxMax' method for ASNR below zero. The new method does not depend entirely on either the subspace decomposition technique or the conventional beamforming technique and is attractive for extremely low ASNR environment with small number of sensors at the price of higher computational complexity. Its performance is superior to the others for multipath signals for the same number of sensors. The number of signals need not be known and more than M-1 signals can be resolved where M is the number of sensors. The increased computational complexity can be reduced through parallel processing implemented on massively parallel computers.
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