Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Multi-Sensor”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

A TRMM-Calibrated Infrared Rainfall Algorithm Over Brazil

An improved version of the Convective/Stratiform Technique (CST) and its application over Brazil are presented. Keeping the major components of traditional CST, we have modified the scheme for classing convective and stratiform rainfall and tested various schemes to eliminate non-raining cirrus clouds. The parameters of the technique are calibrated using Tropical Rainfall Measuring Mission (TRMM) multi-sensor observations, including TMI, PR and Visible Infrared Scanner (VIRS). This technique takes advantage of the high temporal sampling rate of geosynchronous infrared channel and the better instantaneous rain observation of TRMM Microwave Imager (TMI) and PR. Moreover, sparse TMI rain estimates are used to dynamically calibrate the parameters of the technique to improve its performance. The technique is applied to make rainfall estimates on various time scales and to study rainfall statistics such as the distributions of rain intensity and storm duration over a four-month period beginning January 1999. The study period coincides with the TRMM/Large-Scale Biosphere-Atmosphere experiment in Amazonia (LBA) ground validation experiment, and observations from the LBA radar are used to validate the technique. Results show the mean diurnal cycle of precipitation over the LBA area, and are compared to radar data from the Tropical Oceans and Global Atmosphere (TOGA) radar. When the larger geographic region is considered, the analysis of the mean hourly estimates revealed the pronounced effects of rivers, topography and local circulations on the rainfall.

Negri, Andrew J.↗
NASA NTRS2001

AVHRR-Based Polar Pathfinder Products: Evaluation, Enhancement, and Transition to MODIS

The AVHRR-Based Polar Pathfinder (APP) products include calibrated AVHRR channel data, surface temperatures, albedo, satellite scan and solar geometries, and a cloud mask composited into twice- per-day images, and daily averaged fields of sea ice motion, for regions poleward of 50 deg. latitude. Our goals under this grant, in general, are four-fold: 1. To quantify the APP accuracy and sources of error by comparing Pathfinder products with field measurements. 2. To determine the consistency of mean fields and trends in comparison with longer time series of available station data and forecast model output. 3. To investigate the consistency of the products between the different AVHRR instruments over the 1982-present period of the NOAA program. 4. To compare an annual cycle of the AVHRR Pathfinder products with MODIS to establish a baseline for extending Pathfinder-type products into the new ESE period. Year One tasks include intercomparisons of the Pathfinder products with field measurements, testing of algorithm assumptions, collection of field data, and further validation and possible improvement of the multi-sensor ice motion fields. Achievements for these tasks are summarized below.

Fowler, Charles↗
NASA NTRS2001

Structure and Characteristics of Precipitation Systems Observed by TRMM

Multi-sensor measurements of total lightning (in-cloud plus cloud-to-ground) from the Lightning Imaging Sensor (LIS) aboard the TRMM satellite has been combined with passive microwave ice scattering and precipitation radar reflectivity profile information previously cataloged for precipitation features observed by TRMM. These precipitation features are defined by their surface rainfall or ice scattering signatures, with horizontal scales approx. 100 - 10000 sq km. Additionally, convective scale (approx. 100 sq km) storms are defined by the lightning data. Over the U.S. the national cloud-to-ground lightning observations are used to also determine the ratio of in-cloud to cloud-to-ground lightning, where it is hypothesized these ratios are related to the vertical profile of reflectivity and concentration of precipitation-sized ice. Combining the LIS, TRMM Microwave Imager (TMI), and Precipitation Radar (PR) for these storms allows investigation of the convective structures and convective regimes leading to observed lightning, scattering, and reflectivity signatures. Application of this approach to a global, multi-year data set (1998-2000) furthers our understanding of convective processes in different climatological regimes. The figure shows the distribution of high flash rate storms.

Goodman, Steve↗
NASA NTRS2001

Microwave Remote Sensing and the Cold Land Processes Field Experiment

The Cold Land Processes Field Experiment (CLPX) has been designed to advance our understanding of the terrestrial cryosphere. Developing a more complete understanding of fluxes, storage, and transformations of water and energy in cold land areas is a critical focus of the NASA Earth Science Enterprise Research Strategy, the NASA Global Water and Energy Cycle (GWEC) Initiative, the Global Energy and Water Cycle Experiment (GEWEX), and the GEWEX Americas Prediction Project (GAPP). The movement of water and energy through cold regions in turn plays a large role in ecological activity and biogeochemical cycles. Quantitative understanding of cold land processes over large areas will require synergistic advancements in 1) understanding how cold land processes, most comprehensively understood at local or hillslope scales, extend to larger scales, 2) improved representation of cold land processes in coupled and uncoupled land-surface models, and 3) a breakthrough in large-scale observation of hydrologic properties, including snow characteristics, soil moisture, the extent of frozen soils, and the transition between frozen and thawed soil conditions. The CLPX Plan has been developed through the efforts of over 60 interested scientists that have participated in the NASA Cold Land Processes Working Group (CLPWG). This group is charged with the task of assessing, planning and implementing the required background science, technology, and application infrastructure to support successful land surface hydrology remote sensing space missions. A major product of the experiment will be a comprehensive, legacy data set that will energize many aspects of cold land processes research. The CLPX will focus on developing the quantitative understanding, models, and measurements necessary to extend our local-scale understanding of water fluxes, storage, and transformations to regional and global scales. The experiment will particularly emphasize developing a strong synergism between process-oriented understanding, land surface models and microwave remote sensing. The experimental design is a multi-sensor, multi-scale (1-ha to 160,000 km ^ {2}) approach to providing the comprehensive data set necessary to address several experiment objectives. A description focusing on the microwave remote sensing components (ground, airborne, and spaceborne) of the experiment will be presented.

Kim, Edward J.↗
NASA NTRS2001

Ocean Drifters Get the Facts

With the help of Small Business Innovation Research (SBIR) funding from NASA's Goddard Space Flight Center, of Greenbelt, Maryland, Clearwater Instrumentation, of Watertown, Massachusetts, created the ClearSat-Autonomous Drifting Ocean Station (ADOS). The multi-sensor array ocean drifting station was developed to support observations of Earth by NASA satellites. It is a low-cost device for gathering an assortment of data necessary to the integration of present and future satellite measurements of biological and physical processes. Clearwater Instrumentation developed its ADOS technology based on Goddard's Sea-viewing Wide Field-of-view Sensor (SeaWiFS) project, but on a scale that is practical for commercial use. ADOS is used for the in situ measuring of ocean surface layer properties such as ocean color, surface thermal structure, and surface winds. Thus far, multiple ADOS units have been sold to The Scripps Institution of Oceanography, where they are being applied in the field of academic science research. Fisheries can also benefit, because ADOS can locate prime cultivation conditions for this fast-growing industry.

Source record↗
NASA NTRS2002

Simulation of Guidance, Navigation, and Control Systems for Formation Flying Missions

Concepts for missions of distributed spacecraft flying in formation abound. From high resolution interferometry to spatially distributed in-situ measurements, these mission concepts levy a myriad of guidance, navigation, and control (GNC) requirements on the spacecraft/formation as a single system. A critical step toward assessing and meeting these challenges lies in realistically simulating distributed spacecraft systems. The Formation Flying TestBed (FFTB) at NASA Goddard Space Flight Center's (GSFC) Guidance, Navigation, and Control Center is a hardware-in-the-loop simulation and development facility focused on GNC issues relevant to formation flying systems. The FFTB provides a realistic simulation of the vehicle dynamics and control for formation flying missions in order to: (1) conduct feasibility analyses of mission requirements, (2) conduct and answer mission and spacecraft design trades, and (3) serve as a host for GNC software and hardware development and testing. The initial capabilities of the FFTB are based upon an integration of high fidelity hardware and software simulation, emulation, and test platforms developed or employed at GSFC in recent years, including a high-fidelity Global Positioning System (GPS) simulator which has been a fundamental component of the GNC Center's GPS Test Facility. The FFTB will be continuously evolving over the next several years from a tool with capabilities in GPS navigation hardware/software-in-the-loop analysis and closed loop GPS-based orbit control algorithm assessment. Eventually, it will include full capability to support all aspects of multi-sensor, absolute and relative state determination and control, in all (attitude and orbit) degrees of freedom, as well as information management for satellite clusters and constellations. A detailed description of the FFTB architecture is presented in the paper.

Burns, Rich↗
NASA NTRS2003

Estimating Uncertainty in GPCP and TRMM Multi-Satellite Precipitation Estimates

One of the high-priority problems in satellite precipitation estimation is developing algorithms for estimating the errors in precipitation retrievals by individual sensors and subsequent multi-satellite combinations. Classically, we distinguish between "random" and "bias" errors, which do and do not, respectively average to zero over a "big enough" time/space sample. The current operational GPCP and TRMM multi-satellite algorithms are nearly unique in estimating random error for the monthly precipitation estimates from individual sensor systems (including gauge), following Huffman, and then making multi-sensor combinations. No routinely operational global precipitation produces estimates of bias error. Subsequently, a similar scheme has been followed to provide random error estimates for the Multi-satellite Precipitation Analysis (MPA) being computed in real time and after real time for TRMM. The Huffman algorithm for random error is briefly reviewed, including a discussion of the limitations imposed on the algorithm by standard monthly precipitation data sets. Starting from a very simple theoretical treatment of the histogram of precipitation samples in a month, an equation is developed that depends on the estimated average precipitation rate for the month, the number of samples in the month, and two constants. The constants are set separately for each source of precipitation estimate (such as "raingauge") by calibration at selected ground sites. We discuss recent work validating the random error estimates to highlight the successes and limitations of this first-generation approach. We then consider what information is needed from the individual sensor algorithms to facilitate additional accuracy in the estimation of random errors across the time/space span of climate regimes which a global estimation system must handle. In addition, the thorny issue of estimating bias is raised. Finally, the role of error estimates (and the qualitative errors!) in creating combinations of precipitation estimates from different individual sensors is discussed. This issue is particularly important when fine scales in space and time are being considered, say the 0.25 x 0.25-deg 3-hourly estimates in the MPA.

Huffman, G. J.↗
NASA NTRS2003

Application of Satellite Altimeter Data to Studies of Ocean Surface Heat Flux and Upper Ocean Thermal Processes

This is a one-year cost extension of previous grant but carrying a new award number for the administrative purpose. Supported by this one-year extension, the following research has continued and obtained significant results. 20 papers have been published (9) or submitted (11) to scientific journals in this one-year period. A brief summary of scientific results on: 1. A new method for estimation of the sensible heat flux using satellite vector winds, 2. Pacific warm pool excitation, earth rotation and El Nino Southern Oscillations, 3. A new study of the Mediterranean outflow and Meddies at 400-meter isopycnal surface using multi-sensor data, 4. Response of the coastal ocean to extremely high wind, and 5. Role of wind on the estimation of heat flux using satellite data, are provided below as examples of our many research results conducted in the last year,

Yan, Xiao-Hal↗
NASA NTRS2004

Initial Validation of NDVI time seriesfrom AVHRR, VEGETATION, and MODIS

The paper will address Theme 7: Multi-sensor opportunities for VEGETATION. We present analysis of a long-term vegetation record derived from three moderate resolution sensors: AVHRR, VEGETATION, and MODIS. While empirically based manipulation can ensure agreement between the three data sets, there is a need to validate the series. This paper uses atmospherically corrected ETM+ data available over the EOS Land Validation Core Sites as an independent data set with which to compare the time series. We use ETM+ data from 15 globally distributed sites, 7 of which contain repeat coverage in time. These high-resolution data are compared to the values of each sensor by spatially aggregating the ETM+ to each specific sensors' spatial coverage. The aggregated ETM+ value provides a point estimate for a specific site on a specific date. The standard deviation of that point estimate is used to construct a confidence interval for that point estimate. The values from each moderate resolution sensor are then evaluated with respect to that confident interval. Result show that AVHRR, VEGETATION, and MODIS data can be combined to assess temporal uncertainties and address data continuity issues and that the atmospherically corrected ETM+ data provide an independent source with which to compare that record. The final product is a consistent time series climate record that links historical observations to current and future measurements.

Morisette, Jeffrey T.↗
NASA NTRS2002

Multi-Image Registration for an Enhanced Vision System

An Enhanced Vision System (EVS) utilizing multi-sensor image fusion is currently under development at the NASA Langley Research Center. The EVS will provide enhanced images of the flight environment to assist pilots in poor visibility conditions. Multi-spectral images obtained from a short wave infrared (SWIR), a long wave infrared (LWIR), and a color visible band CCD camera, are enhanced and fused using the Retinex algorithm. The images from the different sensors do not have a uniform data structure: the three sensors not only operate at different wavelengths, but they also have different spatial resolutions, optical fields of view (FOV), and bore-sighting inaccuracies. Thus, in order to perform image fusion, the images must first be co-registered. Image registration is the task of aligning images taken at different times, from different sensors, or from different viewpoints, so that all corresponding points in the images match. In this paper, we present two methods for registering multiple multi-spectral images. The first method performs registration using sensor specifications to match the FOVs and resolutions directly through image resampling. In the second method, registration is obtained through geometric correction based on a spatial transformation defined by user selected control points and regression analysis.

Hines, Glenn↗
NASA NTRS2004

Post Eruption Hazards at Mt. Pinatubo, Philippines

Our project focused on the investigation of the post-eruption hazards at Mt. Pinatubo (Philippines) using remote sensing data, and field observations of the 1991 eruption deposits. Through the use of multiple satellite images, field work, and the 1996/2000 PacRim data sets, we conducted studies of the co- and post-eruption hazards of the volcano due to erosion and re-deposition of the extensive pyroclastic flow deposits. A major part of this project was the assembly and analysis of a database of over 50 high resolution (1 - 50 m/pixel) images that will facilitate this study. We collected Ikonos, SPOT, SIR-C/X-SAR, Landsat, ERS, RADARSAT, and ASTER images of the area around Mt. Pinatubo. An example of the changes that could be seen in these data is shown. Our investigation focused on a retrospective analysis of the erosion, redeposition, and re-vegetation of the 1991 pyroclastic flow deposits of Mt. Pinatubo. The primary geologic goal of our work was the analysis of the spatial distribution and volume change of the sources and sinks of materials associated with mudflow ('lahar') events. This included the measurement of river valley gradients and cross-sections using TOPSAR digital elevation data, as we are participating in the PacRim 2000 deployment to the Philippines specifically so that we can collect a second set of TOPSAR data that can then be used to create a topographic difference image of the volcano. The main results from this multi-sensor study have been published as Torres et al.. A discussion of the methodology that we used to assemble an appropriate database was included in Mouginis-Mark and Domergue-Schmidt. As part of an educational outreach effort, we also helped the Philippine Institute of Volcanology and Seismology (PHIVOLCS) in the Philippines to use NASA data to study Mt. Pinatubo and other Filipino volcanoes.

Mouginis-Mark, Peter J.↗
NASA NTRS2004

Radiance Data Products at the GES DAAC

The Goddard Earth Sciences Distributed Active Archive Center (GES DAAC) has been archiving and distributing Radiance data, and serving science and application users of these data, for over 10 years now. The user-focused stewardship of the Radiance data from the AIRS, AVHRR, MODIS, SeaWiFS, SORCE, TOMS, TOVS, TRMM, and UARS instruments exemplifies the GES DAAC tradition and experience. Radiance data include raw radiance counts, onboard calibration data, geolocation products, radiometric calibrated and geolocated-calibrated radiance/reflectance. The number of science products archived at the GES DAAC is steadily increasing, as a result of more sophisticated sensors and new science algorithms. Thus, the main challenge for the GES DAAC is to guide users through the variety of Radiance data sets, provide tools to visualize and reduce the volume of the data, and provide uninterrupted access to the data. This presentation will describe the effort at the GES DAAC to build a bridge between multi-sensor data and the effective scientific use of the data, with an emphasis on the heritage of the science products. The intent is to inform users of the existence of this large collection of Radiance data; suggest starting points for cross-platform science projects and data mining activities; provide data services and tools information; and to give expert help in the science data formats and applications.

Savtchenko, A.↗
NASA NTRS2004

Registration and Fusion of Multiple Source Remotely Sensed Image Data

Earth and Space Science often involve the comparison, fusion, and integration of multiple types of remotely sensed data at various temporal, radiometric, and spatial resolutions. Results of this integration may be utilized for global change analysis, global coverage of an area at multiple resolutions, map updating or validation of new instruments, as well as integration of data provided by multiple instruments carried on multiple platforms, e.g. in spacecraft constellations or fleets of planetary rovers. Our focus is on developing methods to perform fast, accurate and automatic image registration and fusion. General methods for automatic image registration are being reviewed and evaluated. Various choices for feature extraction, feature matching and similarity measurements are being compared, including wavelet-based algorithms, mutual information and statistically robust techniques. Our work also involves studies related to image fusion and investigates dimension reduction and co-kriging for application-dependent fusion. All methods are being tested using several multi-sensor datasets, acquired at EOS Core Sites, and including multiple sensors such as IKONOS, Landsat-7/ETM+, EO1/ALI and Hyperion, MODIS, and SeaWIFS instruments. Issues related to the coregistration of data from the same platform (i.e., AIRS and MODIS from Aqua) or from several platforms of the A-train (i.e., MLS, HIRDLS, OMI from Aura with AIRS and MODIS from Terra and Aqua) will also be considered.

LeMoigne, Jacqueline↗
NASA NTRS2004

Distributive On-line Processing, Visualization and Analysis System for Gridded Remote Sensing Data

The ability to use data stored in the current Earth Observing System (EOS) archives for studying regional or global phenomena is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. Gaining this understanding and applying it to data reduction is a time- consuming task that must be undertaken before the core investigation can begin. This is an especially difficult challenge when science objectives require users to deal with large multi-sensor data sets that are usually of different formats, structures, and resolutions, for example, when preparing data for input into modeling systems. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has taken a major step towards meeting this challenge by developing an infrastructure with a Web interface that allows users to perform interactive analysis online without downloading any data, the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni." Giovanni provides interactive, online, analysis tools for data users to facilitate their research. There have been several instances of this interface created to serve TRMM users, Aerosol scientists, Ocean Color and Agriculture applications users. The first generation of these tools support gridded data only. The user selects geophysical parameters, area of interest, time period; and the system generates an output on screen in a matter of seconds. The currently available output options are: Area plot averaged or accumulated over any available data period for any rectangular area; Time plot time series averaged over any rectangular area; Time plots image view of any longitude-time and latitude-time cross sections; ASCII output for all plot types; Image animation for area plot. In the future, we will add correlation plots, GIS-compatible outputs, etc. This allow user to focus on data content (i.e. science parameters) and eliminate the need for expensive learning, development and processing tasks that are redundantly incurred by an archive's user community. The current implementation utilizes the GrADS-DODS Server (GDS), a stable, secure data server that provides subsetting and analysis services across the Internet for any GrADS-readable dataset. The subsetting capability allows users to retrieve a specified temporal and/or spatial subdomain from a large dataset, eliminating the need to download everything simply to access a small relevant portion of a dataset. The analysis capability allows users to retrieve the results of an operation applied to one or more datasets on the server. In our case, we use this approach to read pre-processed binary files and/or to read and extract the needed parts from HDF or HDF-EOS files. These subsets then serve as inputs into GrADS processing and analysis scripts. It can be used in a wide variety of Earth science applications: climate and weather events study and monitoring; modeling. It can be easily configured for new applications.

Leptoukh, G.↗
NASA NTRS2004

Multi sensor transducer and weight factor

A multi-sensor transducer and processing method allow insitu monitoring of the senor accuracy and transducer `health`. In one embodiment, the transducer has multiple sensors to provide corresponding output signals in response to a stimulus, such as pressure. A processor applies individual weight factors to reach of the output signals and provide a single transducer output that reduces the contribution from inaccurate sensors. The weight factors can be updated and stored. The processor can use the weight factors to provide a `health` of the transducer based upon the number of accurate versus in-accurate sensors in the transducer.

Immer, Christopher D.↗
NASA NTRS2026

Incremental Learning for Passive Microwave Precipitation Retrievals using Advanced Technology Microwave Sounder

Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.

Mahyar Garshasbi↗
DOE OSTI2025

Infrastructure-Based Cooperative Perception at a Traffic Intersection: Overview and Challenges

Traffic intersections are crucial and challenging nodes in transportation networks where multiple lanes of vehicles and pedestrians converge. About one-quarter of traffic fatalities and about one-half of all traffic injuries in the United States happen at traffic intersections . Effective management of these intersections is important to ensure safety and efficiency of all users - vehicles, pedestrians, cyclists, and vulnerable road users (VRUs). With advancements in sensor perception technologies such as radar, light detection and ranging (lidar), and cameras, traffic intersections are developing into dynamic and data-rich environments. By using these data to create a real-time digital twin, we can enable real-time data-driven decision making and a range of applications such as sharing perception information to connected vehicles (CVs) and connected autonomous vehicles (CAVs), safety affirmative signaling, and curb optimizing to improve efficiency and enhance safety.This paper presents an overview of the concept and examines the challenges involved in implementing an infrastructure-based cooperative perception engine at a traffic intersection. In addition to outlining the physical components, this study also addresses important challenges involved in a multi-sensor system. We present results from deploying the National Renewable Energy Laboratory's (NREL's) Infrastructure Perception and Control (IPC) mobile trailer at a traffic intersection in the city of Colorado Springs, Colorado, USA that employed multiple radars and lidars to capture the data. This study provides necessary practical learning for the Cooperative Driving Automation (CDA) and traffic engineering communities for next-generation infrastructure-based cooperative perception that promises improvements in signal control for optimized traffic flow, among other applications, and documents findings for ongoing research and development efforts in other areas.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗