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At least 1,369 records · Page 76
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NASA NTRS2014

Design Principles and Algorithms for Air Traffic Arrival Scheduling

This report presents design principles and algorithms for building a real-time scheduler of arrival aircraft based on a first-come-first-served (FCFS) scheduling protocol. The algorithms provide the conceptual and computational foundation for the Traffic Management Advisor (TMA) of the Center/terminal radar approach control facilities (TRACON) automation system, which comprises a set of decision support tools for managing arrival traffic at major airports in the United States. The primary objective of the scheduler is to assign arrival aircraft to a favorable landing runway and schedule them to land at times that minimize delays. A further objective of the scheduler is to allocate delays between high-altitude airspace far away from the airport and low-altitude airspace near the airport. A method of delay allocation is described that minimizes the average operating cost in the presence of errors in controlling aircraft to a specified landing time. This report is a revision of an earlier paper first presented as part of an Advisory Group for Aerospace Research and Development (AGARD) lecture series in September 1995. The authors, during vigorous discussions over the details of this paper, felt it was important to the air-trafficmanagement (ATM) community to revise and extend the original 1995 paper, providing more detail and clarity and thereby allowing future researchers to understand this foundational work as the basis for the TMA's scheduling algorithms.

Center TRACON↗
NASA NTRS2014

The 183-WSL Fast Rain Rate Retrieval Algorithm. Part II: Validation Using Ground Radar Measurements

The Water vapour Strong Lines at 183 GHz (183-WSL) algorithm is a method for the retrieval of rain rates and precipitation type classification (convectivestratiform), that makes use of the water vapor absorption lines centered at 183.31 GHz of the Advanced Microwave Sounding Unit module B (AMSU-B) and of the Microwave Humidity Sounder (MHS) flying on NOAA-15-18 and NOAA-19Metop-A satellite series, respectively. The characteristics of this algorithm were described in Part I of this paper together with comparisons against analogous precipitation products. The focus of Part II is the analysis of the performance of the 183-WSL technique based on surface radar measurements. The ground truth dataset consists of 2.5 years of rainfall intensity fields from the NIMROD European radar network which covers North-Western Europe. The investigation of the 183-WSL retrieval performance is based on a twofold approach: 1) the dichotomous statistic is used to evaluate the capabilities of the method to identify rain and no-rain clouds; 2) the accuracy statistic is applied to quantify the errors in the estimation of rain rates.The results reveal that the 183-WSL technique shows good skills in the detection of rainno-rain areas and in the quantification of rain rate intensities. The categorical analysis shows annual values of the POD, FAR and HK indices varying in the range 0.80-0.82, 0.330.36 and 0.39-0.46, respectively. The RMSE value is 2.8 millimeters per hour for the whole period despite an overestimation in the retrieved rain rates. Of note is the distribution of the 183-WSL monthly mean rain rate with respect to radar: the seasonal fluctuations of the average rainfalls measured by radar are reproduced by the 183-WSL. However, the retrieval method appears to suffer for the winter seasonal conditions especially when the soil is partially frozen and the surface emissivity drastically changes. This fact is verified observing the discrepancy distribution diagrams where2the 183-WSL performs better during the warm months, while during the winter time the discrepancies with radar measurements tends to maximum values. A stable behavior of the 183-WSL algorithm is demonstrated over the whole study period with an overall overestimation for rain rates intensities lower than 1 millimeter per hour. This threshold is crucial especially in wintertime where the low precipitation regime is difficult to be classified.

validationradar↗
NASA NTRS2014

Preliminary Structural Design Using Topology Optimization with a Comparison of Results from Gradient and Genetic Algorithm Methods

In this paper, genetic algorithm based and gradient-based topology optimization is presented in application to a real hardware design problem. Preliminary design of a planetary lander mockup structure is accomplished using these methods that prove to provide major weight savings by addressing the structural efficiency during the design cycle. This paper presents two alternative formulations of the topology optimization problem. The first is the widely-used gradient-based implementation using commercially available algorithms. The second is formulated using genetic algorithms and internally developed capabilities. These two approaches are applied to a practical design problem for hardware that has been built, tested and proven to be functional. Both formulations converged on similar solutions and therefore were proven to be equally valid implementations of the process. This paper discusses both of these formulations at a high level.

Burt, Adam O.↗
NASA NTRS2014

Optimization of a Lunar Pallet Lander Reinforcement Structure Using a Genetic Algorithm

In this paper, a unique system level spacecraft design optimization will be presented. A Genetic Algorithm is used to design the global pattern of the reinforcing structure, while a gradient routine is used to adequately stiffen the sub-structure. The system level structural design includes determining the optimal physical location (and number) of reinforcing beams of a lunar pallet lander deck structure. Design of the substructure includes determining placement of secondary stiffeners and the number of rivets required for assembly.. In this optimization, several considerations are taken into account. The primary objective was to raise the primary natural frequencies of the structure such that the Pallet Lander primary structure does not significantly couple with the launch vehicle. A secondary objective is to determine how to properly stiffen the reinforcing beams so that the beam web resists the shear buckling load imparted by the spacecraft components mounted to the pallet lander deck during launch and landing. A third objective is that the calculated stress does not exceed the allowable strength of the material. These design requirements must be met while, minimizing the overall mass of the spacecraft. The final paper will discuss how the optimization was implemented as well as the results. While driven by optimization algorithms, the primary purpose of this effort was to demonstrate the capability of genetic algorithms to enable design automation in the preliminary design cycle. By developing a routine that can automatically generate designs through the use of Finite Element Analysis, considerable design efficiencies, both in time and overall product, can be obtained over more traditional brute force design methods.

Burt, Adam↗
NASA NTRS2015

Development of a Near-Real Time Hail Damage Swath Identification Algorithm for Vegetation

The Midwest is home to one of the world's largest agricultural growing regions. Between the time period of late May through early September, and with irrigation and seasonal rainfall these crops are able to reach their full maturity. Using moderate to high resolution remote sensors, the monitoring of the vegetation can be achieved using the red and near-infrared wavelengths. These wavelengths allow for the calculation of vegetation indices, such as Normalized Difference Vegetation Index (NDVI). The vegetation growth and greenness, in this region, grows and evolves uniformly as the growing season progresses. However one of the biggest threats to Midwest vegetation during the time period is thunderstorms that bring large hail and damaging winds. Hail and wind damage to crops can be very expensive to crop growers and, damage can be spread over long swaths associated with the tracks of the damaging storms. Damage to the vegetation can be apparent in remotely sensed imagery and is visible from space after storms slightly damage the crops, allowing for changes to occur slowly over time as the crops wilt or more readily apparent if the storms strip material from the crops or destroy them completely. Previous work on identifying these hail damage swaths used manual interpretation by the way of moderate and higher resolution satellite imagery. With the development of an automated and near-real time hail swath damage identification algorithm, detection can be improved, and more damage indicators be created in a faster and more efficient way. The automated detection of hail damage swaths will examine short-term, large changes in the vegetation by differencing near-real time eight day NDVI composites and comparing them to post storm imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua and Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi NPP. In addition land surface temperatures from these instruments will be examined as for hail damage swath identification. Initial validation of the automated algorithm is based upon Storm Prediction Center storm reports but also the National Severe Storm Laboratory (NSSL) Maximum Estimated Size Hail (MESH) product. Opportunities for future work are also shown, with focus on expansion of this algorithm with pixel-based image classification techniques for tracking surface changes as a result of severe weather.

Bell, Jordan R.↗
NASA NTRS2016

A Mathematical Model and Algorithm for Routing Air Traffic Under Weather Uncertainty

A central challenge in managing today's commercial en route air traffic is the task of routing the aircraft in the presence of adverse weather. Such weather can make regions of the airspace unusable, so all affected flights must be re-routed. Today this task is carried out by conference and negotiation between human air traffic controllers (ATC) responsible for the involved sectors of the airspace. One can argue that, in so doing, ATC try to solve an optimization problem without giving it a precise quantitative formulation. Such a formulation gives the mathematical machinery for constructing and verifying algorithms that are aimed at solving the problem. This paper contributes one such formulation and a corresponding algorithm. The algorithm addresses weather uncertainty and has closed form, which allows transparent analysis of correctness, realism, and computational costs.

uncertainty↗
NASA NTRS2014

Object-Oriented/Data-Oriented Design of a Direct Simulation Monte Carlo Algorithm

Over the past decade, there has been much progress towards improved phenomenological modeling and algorithmic updates for the direct simulation Monte Carlo (DSMC) method, which provides a probabilistic physical simulation of gas Rows. These improvements have largely been based on the work of the originator of the DSMC method, Graeme Bird. Of primary importance are improved chemistry, internal energy, and physics modeling and a reduction in time to solution. These allow for an expanded range of possible solutions In altitude and velocity space. NASA's current production code, the DSMC Analysis Code (DAC), is well-established and based on Bird's 1994 algorithms written in Fortran 77 and has proven difficult to upgrade. A new DSMC code is being developed in the C++ programming language using object-oriented and data-oriented design paradigms to facilitate the inclusion of the recent improvements and future development activities. The development efforts on the new code, the Multiphysics Algorithm with Particles (MAP), are described, and performance comparisons are made with DAC.

Liechty, Derek S.↗
NASA NTRS2016

Moderate Resolution Imaging Spectroradiometer (MODIS) MOD21 Land Surface Temperature and Emissivity Algorithm Theoretical Basis Document

This document outlines the theory and methodology for generating the Moderate Resolution Imaging Spectroradiometer (MODIS) Level-2 daily daytime and nighttime 1-km land surface temperature (LST) and emissivity product using the Temperature Emissivity Separation (TES) algorithm. The MODIS-TES (MOD21_L2) product, will include the LST and emissivity for three MODIS thermal infrared (TIR) bands 29, 31, and 32, and will be generated for data from the NASA-EOS AM and PM platforms. This is version 1.0 of the ATBD and the goal is maintain a 'living' version of this document with changes made when necessary. The current standard baseline MODIS LST products (MOD11*) are derived from the generalized split-window (SW) algorithm (Wan and Dozier 1996), which produces a 1-km LST product and two classification-based emissivities for bands 31 and 32; and a physics-based day/night algorithm (Wan and Li 1997), which produces a 5-km (C4) and 6-km (C5) LST product and emissivity for seven MODIS bands: 20, 22, 23, 29, 31-33.

Hulley, G.↗
NASA NTRS2016

Automated Storm Tracking and the Lightning Jump Algorithm Using GOES-R Geostationary Lightning Mapper (GLM) Proxy Data

This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning jump algorithm (LJA), which are important elements in the transition of the LJA concept from a research to an operational based algorithm. Storm cluster tracking is based on a product created from the combination of a radar parameter (vertically integrated liquid, VIL), and lightning information (flash rate density). Evaluations showed that the spatial scale of tracked features or storm clusters had a large impact on the lightning jump system performance, where increasing spatial scale size resulted in decreased dynamic range of the system's performance. This framework will also serve as a means to refine the LJA itself to enhance its operational applicability. Parameters within the system are isolated and the system's performance is evaluated with adjustments to parameter sensitivity. The system's performance is evaluated using the probability of detection (POD) and false alarm ratio (FAR) statistics. Of the algorithm parameters tested, sigma-level (metric of lightning jump strength) and flash rate threshold influenced the system's performance the most. Finally, verification methodologies are investigated. It is discovered that minor changes in verification methodology can dramatically impact the evaluation of the lightning jump system.

lightning jump↗
NASA NTRS2016

Comparative Results of AIRS/AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

The AIRS Science Team Version-6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRS/AMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrIS/ATMS is the only scheduled follow on to AIRS/AMSU. The objective of this research is to prepare for generation of long term CrIS/ATMS CDRs using a retrieval algorithm that is scientifically equivalent to AIRS/AMSU Version-7.

AIRS AMSU↗
NASA NTRS2017

A Non-Intrusive Algorithm for Sensitivity Analysis of Chaotic Flow Simulations

We demonstrate a novel algorithm for computing the sensitivity of statistics in chaotic flow simulations to parameter perturbations. The algorithm is non-intrusive but requires exposing an interface. Based on the principle of shadowing in dynamical systems, this algorithm is designed to reduce the effect of the sampling error in computing sensitivity of statistics in chaotic simulations. We compare the effectiveness of this method to that of the conventional finite difference method.

Blonigan, Patrick J.↗
NASA NTRS2016

ICAROUS - Integrated Configurable Algorithms for Reliable Operations Of Unmanned Systems

NASA's Unmanned Aerial System (UAS) Traffic Management (UTM) project aims at enabling near-term, safe operations of small UAS vehicles in uncontrolled airspace, i.e., Class G airspace. A far-term goal of UTM research and development is to accommodate the expected rise in small UAS traffic density throughout the National Airspace System (NAS) at low altitudes for beyond visual line-of-sight operations. This paper describes a new capability referred to as ICAROUS (Integrated Configurable Algorithms for Reliable Operations of Unmanned Systems), which is being developed under the UTM project. ICAROUS is a software architecture comprised of highly assured algorithms for building safety-centric, autonomous, unmanned aircraft applications. Central to the development of the ICAROUS algorithms is the use of well-established formal methods to guarantee higher levels of safety assurance by monitoring and bounding the behavior of autonomous systems. The core autonomy-enabling capabilities in ICAROUS include constraint conformance monitoring and contingency control functions. ICAROUS also provides a highly configurable user interface that enables the modular integration of mission-specific software components.

Consiglio, María↗
NASA NTRS2017

Updated MISR Dark Water Research Aerosol Retrieval Algorithm - Part 1: Coupled 1.1 km Ocean Surface Chlorophyll a Retrievals with Empirical Calibration Corrections

As aerosol amount and type are key factors in the 'atmospheric correction' required for remote-sensing chlorophyll alpha concentration (Chl) retrievals, the Multi-angle Imaging SpectroRadiometer (MISR) can contribute to ocean color analysis despite a lack of spectral channels optimized for this application. Conversely, an improved ocean surface constraint should also improve MISR aerosol-type products, especially spectral single-scattering albedo (SSA) retrievals. We introduce a coupled, self-consistent retrieval of Chl together with aerosol over dark water. There are time-varying MISR radiometric calibration errors that significantly affect key spectral reflectance ratios used in the retrievals. Therefore, we also develop and apply new calibration corrections to the MISR top-of-atmosphere (TOA) reflectance data, based on comparisons with coincident MODIS (Moderate Resolution Imaging Spectroradiometer) observations and trend analysis of the MISR TOA bidirectional reflectance factors (BRFs) over three pseudo-invariant desert sites. We run the MISR research retrieval algorithm (RA) with the corrected MISR reflectances to generate MISR-retrieved Chl and compare the MISR Chl values to a set of 49 coincident SeaBASS (SeaWiFS Bio-optical Archive and Storage System) in situ observations. Where Chl(sub in situ) less than 1.5 mg m(exp -3), the results from our Chl model are expected to be of highest quality, due to algorithmic assumption validity. Comparing MISR RA Chl to the 49 coincident SeaBASS observations, we report a correlation coefficient (r) of 0.86, a root-mean-square error (RMSE) of 0.25, and a median absolute error (MAE) of 0.10. Statistically, a two-sample Kolmogorov- Smirnov test indicates that it is not possible to distinguish between MISR Chl and available SeaBASS in situ Chl values (p greater than 0.1). We also compare MODIS-Terra and MISR RA Chl statistically, over much broader regions. With about 1.5 million MISR-MODIS collocations having MODIS Chl less than 1.5 mg m(exp -3), MISR and MODIS show very good agreement: r = 0.96, MAE = 0.09, and RMSE = 0.15. The new dark water aerosol/Chl RA can retrieve Chl in low-Chl, case I waters, independent of other imagers such as MODIS, via a largely physical algorithm, compared to the commonly applied statistical ones. At a minimum, MISR's multi-angle data should help reduce uncertainties in the MODIS-Terra ocean color retrieval where coincident measurements are made, while also allowing for a more robust retrieval of particle properties such as spectral single-scattering albedo.

Limbacher, James A.↗
NASA NTRS2017

DSP Synthesis Algorithm for Generating Florida Scrub Jay Calls

A prototype digital signal processing (DSP) algorithm has been developed to approximate Florida scrub jay calls. The Florida scrub jay (Aphelocoma coerulescens), believed to have been in existence for 2 million years, living only in Florida, has a complicated social system that is evident by examining the spectrograms of its calls. Audio data was acquired at the Helen and Allan Cruickshank Sanctuary, Rockledge, Florida during the 2016 mating season using three digital recorders sampling at 44.1 kHz. The synthesis algorithm is a first step at developing a robust identification and call analysis algorithm. Since the Florida scrub jay is severely threatened by loss of habitat, it is important to develop effective methods to monitor their threatened population using autonomous means.

Florida scrub jay↗
NASA NTRS2018

A Simple, Velocity Dependent, Collision Probability Algorithm for Small Combined Hard Body Radii Close Approach Events

Over the last few years progress has been made in the velocity dependent collision probability problem. Recent progress in this problem has been approached via integration of the probability flux into the surface of the combined hard body object. The algorithm presented uses the surface flux approach and is designed to compute the collision probability rate between two objects given their time dependent states and state error covariance matrices. With regards to the computation of the collision probability (Pc) rate, two major differences exist between the development of this algorithm and the usual Pc algorithm. First, the shape of the at-risk volume is assumed to be a cube rather than a sphere. The size of the cube is chosen so that it circumscribes the usual hard body sphere chosen for the spherical Pc problem. This will result in half the length of a side of the cube being equal to the hard body radius (HBR) of the sphere. Second, it is assumed that the HBR of the cube is much smaller than the smallest combined position uncertainty (σ(sub min) > 5*HBR) at each time point of evaluation. This is necessary as the actual collision probability calculation is based on a first order, small variable expansion in the position components of the Gaussian probability density function. This leads to the collision probability rate being to second order in the combined HBR. The collision probability rate is in a concise, closed form containing exponential and error functions.

Frisbee, Joe↗
NASA NTRS2019

A Segmentation Algorithm for Characterizing Rise and Fall Segments in Seasonal Cycles: An Application to XCO2 to Estimate Benchmarks and Assess Model Bias

There is more useful information in the time series of satellite-derived column-averaged carbon dioxide (XCO2) than is typically characterized. Often, the entire time series is treated at once without considering detailed features at shorter timescales, such as nonstationary changes in signal characteristics – amplitude, period and phase. In many instances, signals are visually and analytically differentiable from other portions in a time series. Each rise (increasing) and fall (decreasing) segment in the seasonal cycle is visually discernable in a graph of the time series. The rise and fall segments largely result from seasonal differences in terrestrial ecosystem production, which means that the segment's signal characteristics can be used to establish observational benchmarks because the signal characteristics are driven by similar underlying processes. We developed an analytical segmentation algorithm to characterize the rise and fall segments in XCO2 seasonal cycles. We present the algorithm for general application of the segmentation analysis and emphasize here that the segmentation analysis is more generally applicable to cyclic time series. We demonstrate the utility of the algorithm with specific results related to the comparison between satellite- and model-derived XCO2 seasonal cycles (2009–2012) for large bioregions across the globe. We found a seasonal amplitude gradient of 0.74–0.77 ppm for every 10∘ of latitude in the satellite data, with similar gradients for rise and fall segments. This translates to a south–north seasonal amplitude gradient of 8 ppm for XCO2, about half the gradient in seasonal amplitude based on surface site in situ CO2 data (∼19 ppm). The latitudinal gradients in the period of the satellite-derived seasonal cycles were of opposing sign and magnitude (−9 d per 10∘ latitude for fall segments and 10 d per 10∘ latitude for rise segments) and suggest that a specific latitude (∼2∘ N) exists that defines an inversion point for the period asymmetry. Before (after) the point of asymmetry inversion, the periods of rise segments are lesser (greater) than the periods of fall segments; only a single model could reproduce this emergent pattern. The asymmetry in amplitude and the period between rise and fall segments introduces a novel pattern in seasonal cycle analyses, but, while we show these emergent patterns exist in the data, we are still breaking ground in applying the information for science applications. Maybe the most useful application is that the segmentation analysis allowed us to decompose the model biases into their correlated parts of biases in amplitude, period and phase independently for rise and fall segments. We offer an extended discussion on how such information about model biases and the emergent patterns in satellite-derived seasonal cycles can be used to guide future inquiry and model development.

Calle, Leonardo↗
NASA NTRS2019

A Comparison of the GPROF Algorithm Results in the 2A-CLIM and 2A Data Products

The GPROF algorithm is used to retrieve precipitation values from all the GPM mission partner radiometers (i.e. GMI, MHS, ATMS, SSMIS, AMSR2). GPM produces two precipitation retrieval products (processing at level 2) using the GPROF algorithm. One has the type designation 2A and the other the designation 2A-CLIM. As a result understanding the difference between the two products is important for using and understanding them. Both of these GPROF products use exactly the same algorithm and a-priori databases. The only difference between the two types is the ancillary products used in the initial processing step. In the case of the 2A-CLIM products, ECMWF ERA-I is used as ancillary data. In the case of the 2A products, JMA's GANAL product is used as ancillary data. This presentation will provide a comparison between the two products using zonal mean comparisons. It will provide comparisons separately for land and ocean retrievals. It will compare the GMI differences over the entire current GPM mission life. As the only difference between the two products is the ancillary information used to create them, the comparison provides an elementary sensitivity study of the variables used from the reanalysis products and their impact on the GPROF retrieval. The purpose of the presentation is to provide users with an insight into the two GPROF products and provide them key information useful when using either of the products in scientific studies. Lastly, the presentation also discusses the reasons why only the 2A-CLIM product can be produced for the 17+ years of TRMM era data products.

GPM↗
NASA NTRS2019

Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product

The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with a mean latency of ~2.5 days. The underlying L4_SM algorithm assimilates SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially-distributed ensemble Kalman filter. Version 4 of the L4_SM modeling system includes a reduction in the upward recharge of surface soil moisture from below under non-equilibrium conditions, resulting in reduced bias and improved dynamic range of L4_SM surface soil moisture compared to earlier versions. This change and additional technical modifications to the system reduce the mean and standard deviation of the observation-minus-forecast Tb residuals and overall soil moisture analysis increments while maintaining the skill of the L4_SM soil moisture estimates versus independent in situ measurements; the average, bias-adjusted RMSE in Version 4 is 0.039 m(exp 3) m(exp -3) for surface and 0.026 m(exp 3) m(exp -3) for root-zone soil moisture. Moreover, the coverage of assimilated SMAP observations in Version 4 is near-global owing to the use of additional satellite Tb records for algorithm calibration. L4_SM soil moisture uncertainty estimates are biased low (by 0.01-0.02 m(exp 3) m(exp -3)) against actual errors (computed versus in situ measurements). L4_SM runoff estimates, an additional product of the L4_SM algorithm, are biased low (by 35 mm year (exp -1)) against streamflow measurements. Compared to Version 3, bias in Version 4 is reduced by 46% for surface soil moisture uncertainty estimates and by 33% for runoff estimates.

RMSE↗