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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

SPECIAL SESSION: (H21) on Global Precipitation Mission for Hydrology and Hydrometeorology. Sampling-Error Considerations for GPM-Era Rainfall Products

The proposed Global Precipitation Mission (GPM) builds on the success of the Tropical Rainfall Measuring Mission (TRMM), offering a constellation of microwave-sensor-equipped smaller satellites in addition to a larger, multiply-instrumented "mother" satellite that will include an improved precipitation radar system to which the precipitation estimates of the smaller satellites can be tuned. Coverage by the satellites will be nearly global rather than being confined as TRMM was to lower latitudes. It is hoped that the satellite constellation can provide observations at most places on the earth at least once every three hours, though practical considerations may force some compromises. The GPM system offers the possibility of providing precipitation maps with much better time resolution than the monthly averages around which TRMM was planned, and therefore opens up new possibilities for hydrology and data assimilation into models. In this talk, methods that were developed for estimating sampling error in the rainfall averages that TRMM is providing will be used to estimate sampling error levels for GPM-era configurations. Possible impacts on GPM products of compromises in the sampling frequency will be discussed.

Bell, Thomas L.↗
NASA NTRS2011

Toward a Framework for Systematic Error Modeling of NASA Spaceborne Radar with NOAA/NSSL Ground Radar-Based National Mosaic QPE

Characterization of the error associated to satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving space-born passive and active microwave measurement") for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. We focus here on the error structure of NASA's Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The problem is addressed by comparison of PR QPEs with reference values derived from ground-based measurements using NOAA/NSSL ground radar-based National Mosaic and QPE system (NMQ/Q2). A preliminary investigation of this subject has been carried out at the PR estimation scale (instantaneous and 5 km) using a three-month data sample in the southern part of US. The primary contribution of this study is the presentation of the detailed steps required to derive trustworthy reference rainfall dataset from Q2 at the PR pixel resolution. It relics on a bias correction and a radar quality index, both of which provide a basis to filter out the less trustworthy Q2 values. Several aspects of PR errors arc revealed and quantified including sensitivity to the processing steps with the reference rainfall, comparisons of rainfall detectability and rainfall rate distributions, spatial representativeness of error, and separation of systematic biases and random errors. The methodology and framework developed herein applies more generally to rainfall rate estimates from other sensors onboard low-earth orbiting satellites such as microwave imagers and dual-wavelength radars such as with the Global Precipitation Measurement (GPM) mission.

Kirstettier, Pierre-Emmanual↗
NASA NTRS2021

Evaluation of Sensor Uncertainty Mitigation Methods for Detect-and-Avoid Systems

The impact of sensor noise on the performance of Detect-And-Avoid (DAA) systems can be reduced by implementing various mitigation schemes. This paper evaluates two such methods. One of them is the Sensor Uncertainty Mitigation (SUM) method, implemented in the Detect and Avoid Alerting Logic for Unmanned Systems (DAIDALUS) algorithm, a reference implementation in the DAA minimum operational performance standards. The second method is the Virtual Intruder State Aggregation (VISA), which averages multiple subsequent intruder states extrapolated to the current (most recent) time into a single ``aggregated`` intruder state. The VISA method can be used either individually as a sensor noise mitigation method in its own right, or in combination with DAIDALUS SUM. The performance of these methods is evaluated using three safety and operational suitability metrics and compared with a baseline configuration using static safety buffers. A large number of encounters representative of low-speed unmanned aircraft against non-cooperative manned aircraft, not equipped with a broadcasting transponder or ADS-B out system, are simulated and evaluated. An air-to-air radar model produces representative sensor noise for the DAA system. Results show that increasing the DAIDALUS SUM parameters for horizontal and vertical uncertainty improves the safety metric at the cost of increasing the number of actionable alerts leading to increased workload. A range of SUM parameters is recommended as suitable values for the type of operations considered for this work. VISA was found to be almost as effective as other noise mitigation methods even when it was used alone. Combining VISA with DAIDALUS SUM achieved the best performance among all investigated methods used with DAIDALUS. General trends and optimal SUM configurations were found to be nearly the same for two large and very different encounter data sets.

Detect-and-Avoid Systems↗
NASA NTRSDate not supplied

The Multiplatform Precipitation Feature (MPF) Database: Synthesizing Satellite and Ground-Based Precipitation and Lightning Datasets for Convective Studies

NASA’s Lightning Imaging Sensor (LIS) and the Global Precipitation Measurement (GPM) mission have contributed a wealth of data toward global lightning and precipitation studies, respectively. Combining lightning and precipitation datasets leverages their unique insights into deep convective processes that inform about characteristics of convection and its intensity. Recent efforts to synthesize the LIS and GPM datasets prepare the opportunity for unprecedented large-scale, value-added multiplatform analyses of convection. This data synthesis proof-of-concept study elaborates on the creation of a database of reflectivity-based multiplatform precipitation features (MPFs) that capture a combination of information extracted from spatiotemporally coincident lightning and precipitation data within individual storm features. The space-based GPM Dual-frequency Precipitation Radar (DPR) provides a record of precipitation data, while the GPM Validation Network (VN) additionally incorporates ground-based polarimetric Doppler radar data to provide microphysical and kinematic context to DPR data. The LIS instrument onboard the International Space Station has contributed lightning observations since 2017. MPFs encapsulating information from these datasets are created from isolated regions of filtered, smoothed DPR reflectivity data to which ellipses are fit. Each MPF includes feature location, size, and eccentricity information as well as summary reflectivity characteristics. They also include summaries of precipitation microphysics and derived three-dimensional wind available from ground-based radar data. LIS data provides standard lightning characteristics such as flash count and density to each MPF as well as other informative metrics such as flash area and radiance. Each MPF file includes information about the original data from which the MPF and its characteristics were determined, allowing end-user reconstruction of the ellipse and deeper “level I” analysis of captured data. This database of VN-LIS MPFs enables broad statistical analysis of the relationships between the microphysical, kinematic, and electrical properties of convection. Preliminary results from a demonstration of the database will be described as well as ongoing efforts and avenues for future work.

Lightning↗
NASA NTRS2011

NASA Tech Briefs, March 2011

Topics covered include: Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation; Airborne Radar Interferometric Repeat-Pass Processing; Plug-and-Play Environmental Monitoring Spacecraft Subsystem; Power-Combined GaN Amplifier with 2.28-W Output Power at 87 GHz; Wallops Ship Surveillance System; Source Lines Counter (SLiC) Version 4.0; Guidance, Navigation, and Control Program; Single-Frame Terrain Mapping Software for Robotic Vehicles; Auto Draw from Excel Input Files; Observation Scheduling System; CFDP for Interplanetary Overlay Network; X-Windows Widget for Image Display; Binary-Signal Recovery; Volumetric 3D Display System with Static Screen; MMIC Replacement for Gunn Diode Oscillators; Feature Acquisition with Imbalanced Training Data; Mount Protects Thin-Walled Glass or Ceramic Tubes from Large Thermal and Vibration Loads; Carbon Nanotube-Based Structural Health Monitoring Sensors; Wireless Inductive Power Device Suppresses Blade Vibrations; Safe, Advanced, Adaptable Isolation System Eliminates the Need for Critical Lifts; Anti-Rotation Device Releasable by Insertion of a Tool; A Magnetically Coupled Cryogenic Pump; Single Piezo-Actuator Rotary-Hammering Drill; Fire-Retardant Polymeric Additives; Catalytic Generation of Lift Gases for Balloons; Ionic Liquids to Replace Hydrazine; Variable Emittance Electrochromics Using Ionic Electrolytes and Low Solar Absorptance Coatings; Spacecraft Radiator Freeze Protection Using a Regenerative Heat Exchanger; Multi-Mission Power Analysis Tool; Correction for Self-Heating When Using Thermometers as Heaters in Precision Control Applications; Gravitational Wave Detection with Single-Laser Atom Interferometers; Titanium Alloy Strong Back for IXO Mirror Segments; Improved Ambient Pressure Pyroelectric Ion Source; Multi-Modal Image Registration and Matching for Localization of a Balloon on Titan; Entanglement in Quantum-Classical Hybrid; Algorithm for Autonomous Landing; Quantum-Classical Hybrid for Information Processing; Small-Scale Dissipation in Binary-Species Transitional Mixing Layers; Superpixel-Augmented Endmember Detection for Hyperspectral Images; Coding for Parallel Links to Maximize the Expected Value of Decodable Messages; and Microwave Tissue Soldering for Immediate Wound Closure.

Source record↗
NASA NTRSDate not supplied

Using Optical Lightning Detection Data from the 2017 GOES-R Post Launch Test Field Campaign Flights as an Evaluation of Convective Processes

The primary mechanisms for thunderstorm electrification and lightning production are widely understood and allow connections between lightning intensity and occurrence to be used to derive storm strength and forecast the probability of related weather phenomena. However, these assumed relationships between lightning and convective properties were discovered primarily using ground-based lightning sensors and measurements, meaning the true depth of insight from space or air based detections is widely unexplored. In 2017, a field campaign was launched to validate the instrumentation aboard the GOES-16 satellite. It involved flying a NASA-ER2 aircraft over multiple storms across the continental US and it included the Fly’s Eye GLM Simulator (FEGS) as a proxy for the Geostationary Lightning Mapper (GLM). Utilizing the data from this field campaign, one of the main goals of this project is to investigate how attributes of convection impact optical lightning detection and the subsequent assumptions that can be made in relation to convective dynamics and precipitation microphysics. Hydrometeor identification, 3D winds retrieval, and additional radar and LiDAR data analysis will be utilized alongside FEGS and interferometer data in order to observe these relationships. This presentation will be to lay out the initial conclusions from our analysis and to explore any new insights or contradictions within our findings.

Kaitlyn Wheeler↗
NASA NTRS1993

Sea ice motions in the central arctic ice central arctic pack ice as inferred from AVHRR imagery

Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoy data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Merging the remotely-sensed ice motions with SAR, AVHRR, OLS, and SSM/I imagery permits studies of ice processes over a range of space and time scales. A medium-resolution passive microwave sensor might be ideal for this purpose, but no such satellite will be available in the near future. Combinations of existing data types are thus likely to be our best bet for generating motion fields with a coverage and resolution best suited to climate studies. Principal objectives of this project are to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions.

Emery, William↗
NASA NTRS2012

SweepSAR: Beam-forming on Receive Using a Reflector-Phased Array Feed Combination for Spaceborne SAR

In this paper, an alternative approach is described that is suited for longer wavelength SARs in particular, employing a large, deployable reflector antenna and a much simpler phased array feed. To illuminate a wide swath, a substantial fraction of the phased array feed is excited on transmit to sub-illuminate the reflector. Shorter transmit pulses are required than for conventional SAR. On receive, a much smaller portion of the phased array feed is used to collect the return echo, so that a greater portion of the reflector antenna area is used. The locus of the portion of the phased array used on receive is adjusted using an analog beam steering network, to 'sweep' the receive beam(s) across the illuminated swath, tracking the return echo. This is similar in some respects to the whiskbroom approach to optical sensors, hence the name: SweepSAR.SweepSAR has advantages over conventional SAR in that it requires less transmit power, and if the receive beam is narrow enough, it is relatively immune to range ambiguities. Compared to direct radiating arrays with digital beam- forming, it is much simpler to implement, uses currently available technologies, is better suited for longer wavelength systems, and does not require extremely high data rates or onboard processing.

synthetic aperture radars (SARs)↗
NASA NTRS1991

Rainfall estimation over oceans from scanning multichannel microwave radiometer and special sensor microwave/imager microwave data

The brightness temperature (T sub b) measured at 37 GHz shows fairly strong emission from rain, and only slight effects caused by scattering by ice above the rain clouds. At frequencies below 37 GHz, were the fov is larger and the volume extinction coefficient is weaker, it is found that the observations do not yield appreciable additional information about rain. At 85 GHz (fov = 15 km), where the volume extinction is considerably larger, direct information about rain below the clouds is usually masked. Based on the above ideas, 37 GHz observations with a 30 km fov from SMMR and SSM/I are selected to develop an empirical method for the estimation of rain rate. In this method, the statistics of the observed T sub b's at 37 GHz in a rain storm are related to the rain rate statistics in that storm. The underestimation of rain rate, arising from the inability of the radiometer to respond sensitively to rain rate above a given threshold, is rectified in this technique with the aid of two parameters that depend on the total water vapor content in the atmosphere. The retrieved rain rates compare favorably with radar observations and monthly mean global maps of rain derived from this technique over the oceans.

Prabhakara, C.↗
NASA NTRS2019

LEAVES: Lofted Environmental and Atmospheric Venus Sensors

LEAVES (Lofted Environmental Atmospheric Venus Sensors) is a design exercise with the goal of dramatically decreasing the cost of obtaining prioritized chemical and physical data in planetary atmospheres. Through the application of a swarm approach this concept parallelizes atmospheric exploration, with geographic coverage far exceeding what is possible with conventional monolithic platforms or sondes. Each unit in the swarm is exceptionally compact, with a powered payload mass of only a few tens of grams and a high-drag, semi-rigid structure that acts to slow each probe as it descends through the atmosphere. This structural design can collapse into a planar form to allow for efficient stowage prior to arrival at the target body. With a total per-unit mass of only 120 g, a fleet of 100 (or more) units can be very reasonably accommodated on a carrier spacecraft.Science operations, which begin when the LEAVES probes reach an altitude of 100 km, are targeted for the cloud-bearing region of Venus' atmosphere. During the roughly 9 hour, terminal velocity descent through the atmosphere, LEAVES collects data of the state and composition of the atmosphere in parallel across multiple units. These data would represent an unprecedented constraint on the distribution and concentration of targeted chemical species, and the detection of local and regional variations in both chemistry and physical properties.A novel and compelling result of this exercise was that the same optimization that produced a structure with an exceptionally low areal mass density (0.126 kg/m2) also resulted in a probe that can be deployed directly from an aerobraking orbit (~140 km at 5 km/s) without the need for aeroshell protection. This translates to a tremendous mass savings and gives LEAVES the flexibility to be carried as a secondary payload aboard either a descending surface probe or an orbital radar mapper. Because such missions are under active development or have already been proposed (but not flown), we infer that LEAVES is well positioned as a technology

Swarm↗
NASA NTRS1981

Using radar image simulation to assess relative geometric distortions inherent in radar imagery

A unique method for observing the relative contributions of backscatter and propagation effects is afforded by radar image simulation. Digital terrain data are used in modeling radar image formation. Backscatter and propagation effects are modeled separately. These are incorporated serially and the image expression of each is noted. Sequences of images are presented illustrating these effects over a range of slopes and angles of incidence. The conclusions reached are that at angles of incidence that are smaller than the average slope of the terrain in a region, propagation phenomena predominate. As the angle of incidence increases beyond this, the radar image portrays an increasingly faithful representation of the backscatter from the ground. It is also demonstrated that digital simulation affords an important tool for evaluating complex interactions between the ground and radar, for training users in radar image interpretation, and for selecting optimum sensor parameters for particular applications.

Kaupp, V. H.↗
NASA NTRSDate not supplied

Sensing Small Uncrewed Aerial Vehicles with Distributed Radars for Advanced Air Mobility Surveillance

In the context of Advanced and Urban Air Mobility major attention is being reserved to the development of sensing strategies for small Uncrewed Aerial Vehicles (sUAVs) to enable their safe operations in and around urban areas. Such strategies should rely on non-cooperative distributed sensors to strengthen the surveillance solution towards the unreliability of Global Navigation Satellite System (GNSS) positioning information, which is typical for low-altitude-flying platforms in urban regions, and increase the monitored airspace volume. To this aim, this paper proposes a fusion solution for a network of distributed ground-based radars, which can be exploited to not only increase the coverage over large airspace volumes but also improve the overall detectability and traceability of sUAVs by leveraging on multiple views over the same area. The solution exploits a centralized fusion scheme in which measurements collected by each radar are shared with a Fusion Center where Kalman Filtering is exploited to build a unique, fused track. Tests conducted on experimental data collected using two sUAVs as flying targets and three distributed radars showed that the proposed solution can produce an increase in coverage from about 20 % (single radar configuration) to about 80 % of the targets’ flight path, as well as a finer accuracy yielding meter and meter-per-second root mean square error values on position and velocity components.

Federica Vitiello↗
DOE OSTI2019

Arctic Sea Ice Classification Using Microwave Scatterometer and Radiometer Data During 2002-2017

Temporal and spatial variation of sea ice type in the Arctic is an indicator of regional and global change. Arctic sea ice can be classified into two major categories: multiyear ice (MYI) and first-year ice. In this paper, classification method based on machine learning is established and applied to produce daily sea ice classification data set during the winter (November–April) from 2002 to 2017 using active microwave data from QuikSCAT and Advanced Scatterometer as well as passive microwave data from Advanced Microwave Scanning Radiometer for EOS, Special Sensor Microwave Imager/Sounder, and Advanced Microwave Scanning Radiometer 2 radiometer. First, the open water area is flagged out using brightness temperature (Tb) from the passive microwave sensor. Then, K-means algorithm is applied to identify the clusters of the two ice types in the Tb/backscatter parameter space and finally assign pixels to each class. Two optimization methods based on the movement of MYI and marginal ice zone are used to correct the misclassification of MYI. The results have shown a decrease of MYI in winter from 2002 to 2017, especially in 2008 and 2013 with a remarkable recovery in 2014. The classifications are consistent with results by visual interpretation from synthetic aperture radar images in the Canadian Arctic Archipelago with overall classification accuracy over 93%. Comparison with classifications from previous studies and products shows that our method could reflect more differences in MYI declining trend interannually and less anomalous fluctuations in certain years.

58 GEOSCIENCES↗
NASA NTRS1999

An Overview of Future NASA Missions, Concepts, and Technologies Related to Imaging of the World's Land Areas

In the near term NASA is entering into the peak activity period of the Earth Observing System (EOS). The EOS AM-1 /"Terra" spacecraft is nearing launch and operation to be followed soon by the New Millennium Program (NMP) Earth Observing (EO-1) mission. Other missions related to land imaging and studies include EOS PM-1 mission, the Earth System Sciences Program (ESSP) Vegetation Canopy Lidar (VCL) mission, the EOS/IceSat mission. These missions involve clear advances in technologies and observational capability including improvements in multispectral imaging and other observing strategies, for example, "formation flying". Plans are underway to define the next era of EOS missions, commonly called "EOS Follow-on" or EOS II. The programmatic planning includes concepts that represent advances over the present Landsat-7 mission that concomitantly recognize the advances being made in land imaging within the private sector. The National Polar Orbiting Environmental Satellite Series (NPOESS) Preparatory Project (NPP) is an effort that will help to transition EOS medium resolution (herein meaning spatial resolutions near 500 meters), multispectral measurement capabilities such as represented by the EOS Moderate Resolution Imaging Spectroradiometer (MODIS) into the NPOESS operational series of satellites. Developments in Synthetic Aperture Radar (SAR) and passive microwave land observing capabilities are also proceeding. Beyond these efforts the Earth Science Enterprise Technology Strategy is embarking efforts to advance technologies in several basic areas: instruments, flight systems and operational capability, and information systems. In the case of instruments architectures will be examined that offer significant reductions in mass, volume, power and observational flexibility. For flight systems and operational capability, formation flying including calibration and data fusion, systems operation autonomy, and mechanical and electronic innovations that can reduce spacecraft and subsystem resource requirements. The efforts in information systems will include better approaches for linking multiple data sets, extracting and visualizing information, and improvements in collecting, compressing, transmitting, processing, distributing and archiving data from multiple platforms. Overall concepts such as sensor webs, constellations of observing systems, and rapid and tailored data availability and delivery to multiple users comprise and notions Earth Science Vision for the future.

Salomonson, Vincent V.↗
NASA NTRS2014

The New NASA Orbital Debris Engineering Model ORDEM 3.0

The NASA Orbital Debris Program Office (ODPO) has released its latest Orbital Debris Engineering Model, ORDEM 3.0. It supersedes ORDEM 2.0. This newer model encompasses the Earth satellite and debris flux environment from altitudes of low Earth orbit (LEO) through geosynchronous orbit (GEO). Debris sizes of 10 microns through 1 m in non-GEO and 10 cm through 1 m in GEO are modeled. The inclusive years are 2010 through 2035. The ORDEM model series has always been data driven. ORDEM 3.0 has the benefit of many more hours from existing data sources and from new sources that weren't available to past versions. Returned surfaces, ground tests, and remote sensors all contribute data. The returned surface and ground test data reveal material characteristics of small particles. Densities of fragmentation debris particles smaller than 10 cm are grouped in ORDEM 3.0 in terms of high-, medium-, and lowdensities, along with RORSAT sodium-potassium droplets. Supporting models have advanced significantly. The LEO-to-GEO ENvironment Debris model (LEGEND) includes an historical and a future projection component with yearly populations that include launched and maneuvered intacts, mission related debris (MRD), and explosion and collision fragments. LEGEND propagates objects with ephemerides and physical characteristics down to 1 mm in size. The full LEGEND yearly population acts as an a priori condition for a Bayesian statistical model. Specific, well defined populations are added like the Radar Ocean Reconnaissance Satellite (RORSAT) sodium-potassium (NaK) droplets, recent major accidental and deliberate collision fragments, and known anomalous debris event fragments. For microdebris of sizes 10 microns to 1 mm the ODPO uses an in-house Degradation/Ejecta model in which a MLE technique is used with returned surface data to estimate populations. This paper elaborates on the upgrades of this model over previous versions highlighting the material density splits and consequences of that to the penetration risk to spacecraft.

Krisko, P. H.↗
NASA NTRS2009

Vibro-Acoustic Analysis of NASA's Space Shuttle Launch Pad 39A Flame Trench Wall

A vital element to NASA's manned space flight launch operations is the Kennedy Space Center Launch Complex 39's launch pads A and B. Originally designed and constructed In the 1960s for the Saturn V rockets used for the Apollo missions, these pads were modified above grade to support Space Shuttle missions. But below grade, each of the pad's original walls (including a 42 feet deep, 58 feet wide, and 450 feet long tunnel designed to deflect flames and exhaust gases, the flame trench) remained unchanged. On May 31, 2008 during the launch of STS-124, over 3500 of the. 22000 interlocking refractory bricks that lined east wall of the flame trench, protecting the pad structure were liberated from pad 39A. The STS-124 launch anomaly spawned an agency-wide initiative to determine the failure root cause, to assess the impact of debris on vehicle and ground support equipment safety, and to prescribe corrective action. The investigation encompassed radar imaging, infrared video review, debris transport mechanism analysis using computational fluid dynamics, destructive testing, and non-destructive evaluation, including vibroacoustic analysis, in order to validate the corrective action. The primary focus of this paper is on the analytic approach, including static, modal, and vibro-acoustic analysis, required to certify the corrective action, and ensure Integrity and operational reliability for future launches. Due to the absence of instrumentation (including pressure transducers, acoustic pressure sensors, and accelerometers) in the flame trench, defining an accurate acoustic signature of the launch environment during shuttle main engine/solid rocket booster Ignition and vehicle ascent posed a significant challenge. Details of the analysis, including the derivation of launch environments, the finite element approach taken, and analysistest/ launch data correlation are discussed. Data obtained from the recent launch of STS-126 from Pad 39A was instrumental in validating the design analysis philosophies outlined in this paper.

Margasahayam, Ravi N.↗
DOE OSTI2020

Online Parameter Estimation Methods for Adaptive Cruise Control Systems

Modeling Adaptive Cruise Control (ACC) vehicles enables the understanding of the impact of these vehicles on traffic flow. In this work, two online methods are used to provide real time system identification of ACC enabled vehicles. The first technique is a recursive least squares (RLS) approach, while the second method solves a nonlinear joint state and parameter estimation problem via particle filtering (PF). We provide a parameter identifiability analysis for both methods to analytically show that the model parameters are not identifiable using equilibrium driving. The accuracy and computational runtime of the online methods are compared to a commonly used offline simulation-based optimization (i.e., batch optimization) approach. The methods are tested on synthetic data as well as on empirical data collected directly from a 2019 model year ACC vehicle using data from sensors that are part of the stock ACC system. The online methods are scalable and provide comparable accuracy to the batch method. RLS runs in real time and is two orders of magnitude faster than the batch method for modest sized (e.g., 15 min) datasets. The particle filter also runs in real- time, and is also suitable in streaming applications in which the datasets can grow arbitrarily large.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1984

Comparison of winds, waves, and turbulence as observed by airborne lidar, ground-based radars, and instrumented tower

On June 29, 1981, two ground-based Doppler radars, an airborne Doppler optical radar (lidar), an instrumented tower, and a rawinsonde were employed to collect wind data in the planetary boundary layer (PBL) in central Oklahoma. The main objectives of this experiment were related to a comparison of wind estimates and the visualization of the three-dimensional eddy structure in the convective atmospheric boundary layer. Discrepancies in the mean wind and wind profile detected by the different sensing systems were explained as being caused by a Schuler resonance of the aircraft's inertial navigation system, which caused an erroneous component of the aircraft's ground-relative velocity vector to be subtracted from the lidar-measured radial velocities. It is concluded that NASA's airborne Doppler optical radar system is capable of measuring wind fields in clear air on a smaller scale than was previously available with fixed remote sensors.

Eilts, M. D.↗