Results for “Computational toolkit” — Page 7

NASA NTRS2011

Image Segmentation, Registration, Compression, and Matching

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity/topology components of the generated models. The highly efficient triangular mesh compression compacts the connectivity information at the rate of 1.5-4 bits per vertex (on average for triangle meshes), while reducing the 3D geometry by 40-50 percent. Finally, taking into consideration the characteristics of 3D terrain data, and using the innovative, regularized binary decomposition mesh modeling, a multistage, pattern-drive modeling, and compression technique has been developed to provide an effective framework for compressing digital elevation model (DEM) surfaces, high-resolution aerial imagery, and other types of NASA data.

Yadegar, Jacob↗

NASA NTRSDate not supplied

A 3D Simulation Platform for Decentralized Decision-Making in Advanced Air Mobility

This paper presents a general purpose, plug-and-play simulation platform for the use of future aviation stakeholders, such as urban airspace planners, air vehicle operators, ground operation managers, air traffic controllers and aviation researchers. The presented simulator platform is envisioned to serve as a toolkit to visualize, evaluate, and configure future advanced air mobility (AAM) operations. Highlighting features of this toolkit include a modular architecture that allows multiple smart unmanned aerial systems (UASs) to remotely connect to the simulation server and participate in decentralized decision-making scenario simulations. As an example of the decentralized decision-making scenario, an inter-agent negotiation-based conflict resolution use case is considered in this paper, where the UASs leverage the on-board/on-the-edge artificial intelligence (AI) capability to continually build situational awareness, and use this information to predict future conflicts and resolve them through machine-to-machine negotiation. As such operations are non-existent at scale currently, the presented simulation platform offers a viable and cost-effective alternative for assessing the efficacy of AAM research outcomes and challenges in future shared airspace usage. The simulation platform allows plug-n-play connectivity with AI and non-AI compute modules representing individual UAS’s flight control. Each module can interact with the simulation platform independently to communicate current and desired future states, situational awareness, and conflict resolution utilization costs for inter-agent negotiation. The simulation environment orchestrates realistic operational scenarios with spatiotemporal details, dynamic events, tactical conflict-resolution methods, interfaces for customizing air traffic control parameters, and information exchange uncertainties. In the future, this can serve as a community focused cloud simulation platform, incorporating multi-stakeholder airspace constraints from regulatory, government, city, and local agencies.

Aditya N Das↗

NASA NTRS2022

A 3D Simulation Platform for Decentralized Decision-Making in Advanced Air Mobility

This paper presents a general purpose, plug-and-play simulation platform for the use of future aviation stakeholders, such as urban airspace planners, air vehicle operators, ground operation managers, air traffic controllers and aviation researchers. The presented simulator platform is envisioned to serve as a toolkit to visualize, evaluate, and configure future advanced air mobility (AAM) operations. Highlighting features of this toolkit include a modular architecture that allows multiple smart unmanned aerial systems (UASs) to remotely connect to the simulation server and participate in decentralized decision-making scenario simulations. As an example of the decentralized decision-making scenario, an inter-agent negotiation-based conflict resolution use case is considered in this paper, where the UASs leverage the on-board/on-the-edge artificial intelligence (AI) capability to continually build situational awareness, and use this information to predict future conflicts and resolve them through machine-to-machine negotiation. As such operations are non-existent at scale currently, the presented simulation platform offers a viable and cost-effective alternative for assessing the efficacy of AAM research outcomes and challenges in future shared airspace usage. The simulation platform allows plug-n-play connectivity with AI and non-AI compute modules representing individual UAS’s flight control. Each module can interact with the simulation platform independently to communicate current and desired future states, situational awareness, and conflict resolution utilization costs for inter-agent negotiation. The simulation environment orchestrates realistic operational scenarios with spatiotemporal details, dynamic events, tactical conflict-resolution methods, interfaces for customizing air traffic control parameters, and information exchange uncertainties. In the future, this can serve as a community focused cloud simulation platform, incorporating multi-stakeholder airspace constraints from regulatory, government, city, and local agencies.

Aditya Das↗

NASA NTRS2015

Parameter Estimation for Compact Binaries with Ground-Based Gravitational-Wave Observations Using the LALInference

The Advanced LIGO and Advanced Virgo gravitational wave (GW) detectors will begin operation in the coming years, with compact binary coalescence events a likely source for the first detections. The gravitational waveforms emitted directly encode information about the sources, including the masses and spins of the compact objects. Recovering the physical parameters of the sources from the GW observations is a key analysis task. This work describes the LALInference software library for Bayesian parameter estimation of compact binary signals, which builds on several previous methods to provide a well-tested toolkit which has already been used for several studies. We show that our implementation is able to correctly recover the parameters of compact binary signals from simulated data from the advanced GW detectors. We demonstrate this with a detailed comparison on three compact binary systems: a binary neutron star (BNS), a neutron star - black hole binary (NSBH) and a binary black hole (BBH), where we show a cross-comparison of results obtained using three independent sampling algorithms. These systems were analysed with non-spinning, aligned spin and generic spin configurations respectively, showing that consistent results can be obtained even with the full 15-dimensional parameter space of the generic spin configurations. We also demonstrate statistically that the Bayesian credible intervals we recover correspond to frequentist confidence intervals under correct prior assumptions by analysing a set of 100 signals drawn from the prior. We discuss the computational cost of these algorithms, and describe the general and problem-specific sampling techniques we have used to improve the efficiency of sampling the compact binary coalescence (CBC) parameter space.

gravitational wave↗

NASA NTRS2001

Gridded Hourly Text Products: A TRMM Data Reduction Approach

The quantity of precipitation data from satellite-based observations is a blessing and a curse. The sheer volume of the data makes it difficult for many researchers to use in targeted applications. This volume increases further as algorithm improvements lead to the reprocessing of mission data. In addition to the overall volume of data, the size and format complexity of orbital granules contribute to the difficulty in using all the available data. Finally, the number of different instruments available to measure rainfall and related parameters further contributes to the volume concerns. In summary, we have an embarrassment of riches. The science team of the Tropical Rainfall Measuring Mission (TRMM) recognized this dilemma and has developed a strategy to address it. The TRMM Science Data and Information System (TSDIS) produces, at the direction of the Joint TRMM Science Team, a number of instantaneous rainfall products. The TRMM Microwave Imager (TMI), the Precipitation Radar and a Combined TMI/PR are the key "instruments" used in this production. Each of these products contains an entire orbit of data. The algorithm code computes not just rain rates but a large number of other physical parameters as well as information needed for monitoring algorithm performance. That makes these products very large. For example, a single orbit of TMI rain rate product is 99 MB, a single orbit of the combined product yields a granule that is 158 MB, while the 80 vertical levels of rain information from the PR yields an orbital product of 253 MB. These are large products that are often difficult for science users to electronically transfer to their sites especially if they want a large period of time. Level 3 gridded products are much smaller, but their 5 or 30 day temporal resolution is insufficient for many researchers. In addition, TRMM standard products are produced in the HDF format. While a large number of user-friendly tools are available to hide the details of the format (including a toolkit developed at TSDIS for the TRMM science team), many potential users shy away

Stocker, Erich↗

NASA NTRS2021

ANOPP2’s Farassat Formulations Internal Functional Module (AFFIFM) Reference Manual

This manual documents version 1.4.0 of ANOPP2’s Farassat Formulations Internal Functional Modules (AFFIFMs) developed by NASA Langley Research Center’s Aeroacoustics Branch. The AFFIFMs provide the capability of calculating an acoustic pressure time history (APTH), or similar metric, provided one or more Ffowcs Williams and Hawkings (FWH) surfaces. AFFIFMs also allow for compact line sources. This application programming interface (API) is part of a larger toolkit called the Aircraft NOise Prediction Program 2 (ANOPP2). The goal of ANOPP2 is to provide the ability to independently: (1) assess aircraft system noise; (2) assess aircraft component noise; and (3) evaluate aircraft noise reduction technologies and flight procedures. Additionally, ANOPP2 is designed to provide a capability for understanding the fundamental physics involved in noise generation to support experiments and flight demonstration activities. As a component of ANOPP2, ANOPP2’s Farassat Formulations Internal Functional Modules and this document may be included as part of the ANOPP2 distribution, or they may be provided independent of that distribution. This is the ANOPP2 internal version of this document. It supersedes the NASA Internal Distribution(NID), US General Distribution (UGD), and General Public Distribution (GPD) versions.

Acoustics↗

NASA NTRS2010

Simulating Future GPS Clock Scenarios with Two Composite Clock Algorithms

Using the GPS Toolkit, the GPS constellation is simulated using 31 satellites (SV) and a ground network of 17 monitor stations (MS). At every 15-minutes measurement epoch, the monitor stations measure the time signals of all satellites above a parameterized elevation angle. Once a day, the satellite clock estimates the station and satellite clocks. The first composite clock (B) is based on the Brown algorithm, and is now used by GPS. The second one (G) is based on the Greenhall algorithm. The composite clock of G and B performance are investigated using three ground-clock models. Model C simulates the current GPS configuration, in which all stations are equipped with cesium clocks, except for masers at USNO and Alternate Master Clock (AMC) sites. Model M is an improved situation in which every station is equipped with active hydrogen masers. Finally, Models F and O are future scenarios in which the USNO and AMC stations are equipped with fountain clocks instead of masers. Model F is a rubidium fountain, while Model O is more precise but futuristic Optical Fountain. Each model is evaluated using three performance metrics. The timing-related user range error having all satellites available is the first performance index (PI1). The second performance index (PI2) relates to the stability of the broadcast GPS system time itself. The third performance index (PI3) evaluates the stability of the time scales computed by the two composite clocks. A distinction is made between the "Signal-in-Space" accuracy and that available through a GNSS receiver.

global positioning system↗

NASA NTRS2013

NASA Tech Briefs, April 2013

Topics covered include: Fully Integrated, Miniature, High-Frequency Flow Probe Utilizing MEMS Leadless SOI Technology; Nanoscale Surface Plasmonics Sensor With Nanofluidic Control; Advanced Dispersed Fringe Sensing Algorithm for Coarse Phasing Segmented Mirror Telescopes; Neural Network Back-Propagation Algorithm for Sensing Hypergols; Bulk Moisture and Salinity Sensor; Change-Based Satellite Monitoring Using Broad Coverage and Targetable Sensing; Circularly Polarized Microwave Antenna Element with Very Low Off-Axis Cross-Polarization; Ultra-Low Heat-Leak, High-Temperature Superconducting Current Leads for Space Applications; Flash Cracking Reactor for Waste Plastic Processing; An Automated Safe-to-Mate (ASTM) Tester; Wireless Chalcogenide Nanoionic-Based Radio-Frequency Switch; Compute Element and Interface Box for the Hazard Detection System; DOT Transmit Module; Composite Aerogel Multifoil Protective Shielding; Li-Ion Electrolytes with Improved Safety and Tolerance to High-Voltage Systems; Polymer-Reinforced, Non-Brittle, Lightweight Cryogenic Insulation; Controlled, Site-Specific Functionalization of Carbon Nanotubes with Diazonium Salts; Regenerable Sorbent for CO2 Removal; Sprayable Aerogel Bead Compositions With High Shear Flow Resistance and High Thermal Insulation Value; Lexan Linear Shaped Charge Holder with Magnets and Backing Plate; Robotic Ankle for Omnidirectional Rock Anchors; Wind, Wave, and Tidal Energy Without Power Conditioning; An Active Heater Control Concept to Meet IXO Type Mirror Module Thermal-Structural Distortion Requirement; Waterless Clothes-Cleaning Machine; Integrated Electrical Wire Insulation Repair System; LVGEMS Time-of-Flight Mass Spectrometry on Satellites; Surface Inspection Tool for Optical Detection of Surface Defects; Per-Pixel, Dual-Counter Scheme for Optical Communications; Certification-Based Process Analysis; Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization; Smart-Divert Powered Descent Guidance to Avoid the Backshell Landing Dispersion Ellipse; Estimating Foreign-Object-Debris Density from Photogrammetry Data; Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria; Building a 2.5D Digital Elevation Model From 2D Imagery; Eyes on the Earth 3D; Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles; Adams-Based Rover Terramechanics and Mobility Simulator - ARTEMIS; ISTP CDF Skeleton Editor; Uplink Summary Generator (ULSGEN) Version 1.0; Robotics On-Board Trainer (ROBoT); Software Engineering Tools for Scientific Models; Automatic Data Filter Customization Using a Genetic Algorithm; Tracker Toolkit; Towards Efficient Scientific Data Management Using Cloud Storage; On a Formal Tool for Reasoning About Flight Software Cost Analysis; A Nanostructured Composites Thermal Switch Controls Internal and External Short Circuit in Lithium Ion Batteries; Spacecraft Crew Cabin Condensation Control; and Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex.

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