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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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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Observations and Mitigation of RFI in ALOS PALSAR SAR Data; Implications for the Desdyni Mission

Initial examination of ALOS PALSAR synthetic aperture radar (SAR) data has indicated significant radio frequency interference (RFI) in several geographic locations around the world. RFI causes significant reduction in image contrast, introduces periodic and quasi-periodic image artifacts, and introduces significant phase noise in repeat pass interferometric data reduction. The US National Research Council Decadal Survey of Earth Science has recommended DESDynI, a Deformation, Ecosystems, and Dynamics of Ice satellite mission comprising an L-band polarimetric radar configured for repeat pass interferometry. There is considerable interest internationally in other future L-band and lower frequency systems as well. Therefore the issues of prevalence and possibilities of mitigation of RFI in these crowded frequency bands is of considerable interest. RFI is observed in ALOS PALSAR in California, USA, and in southern Egypt in data examined to date. Application of several techniques for removing it from the data prior to SAR image formation, ranging from straightforward spectral normalization to time-domain, multi-phase filtering techniques are considered. Considerable experience has been gained from the removal of RFI from P-band acquired by the GeoSAR system. These techniques applied to the PALSAR data are most successful when the bandwidth of any particular spectral component of the RFI is narrow. Performance impacts for SAR imagery and interferograms are considered in the context of DESDynI measurement requirements.

InSAR↗
NASA NTRS2016

First Image Products from EcoSAR - Osa Peninsula, Costa Rica

Designed especially for forest ecosystem studies, EcoSAR employs state-of-the-art digital beamforming technology to generate wide-swath, high-resolution imagery. EcoSARs dual antenna single-pass imaging capability eliminates temporal decorrelation from polarimetric and interferometric analysis, increasing the signal strength and simplifying models used to invert forest structure parameters. Antennae are physically separated by 25 meters providing single pass interferometry. In this mode the radar is most sensitive to topography. With 32 active transmit and receive channels, EcoSARs digital beamforming is an order of magnitude more versatile than the digital beamforming employed on the upcoming NISAR mission. EcoSARs long wavelength (P-band, 435 MHz, 69 cm) measurements can be used to simulate data products for ESAs future BIOMASS mission, allowing scientists to develop algorithms before the launch of the satellite. EcoSAR can also be deployed to collect much needed data where BIOMASS satellite wont be allowed to collect data (North America, Europe and Arctic), filling in the gaps to keep a watchful eye on the global carbon cycle. EcoSAR can play a vital role in monitoring, reporting and verification schemes of internationals programs such as UN-REDD (United Nations Reducing Emissions from Deforestation and Degradation) benefiting global society. EcoSAR was developed and flown with support from NASA Earth Sciences Technology Offices Instrument Incubator Program.

InSAR↗
NASA NTRS2016

Development of RFI Mitigation Techniques with Digital Beamforming

Remote sensing radars with longer wavelengths penetrate deeper into the observed scene and are more suitable for the scientific observation of ice sheets or vegetation. Therefore, SAR systems are moving to lower frequencies like L- or P-band. However, as the frequency spectrum is a limited resource, this means that the occupied frequency band has to be shared with existing users. These users can have serious impact on the imaging quality. Radio frequency interference (RFI) that arrives at the antenna together with the SAR backscatter is causing a drop of the signal-to-noise ratio. Despite the high processing gain of the SAR signal, artifacts can appear in the image if the RFI is strong enough. This can lead to a corruption of the acquired data and make it unsuitable for scientific purposes. Hence, the investigation of methods for RFI mitigation is critical to the performance of radar missions and to ensure they meet their main task.

Digital Beamforming↗
NASA NTRS2016

Radio Frequency Interference Detection and Mitigation Techniques Using Data from Ecosar 2014 Flight Campaign

Radio frequency interference (RFI) has strong influence on wide band airborne radar systems, especially operaingat L-band (1-2 GHz) or lower frequencies. EcoSAR is a P-band digital beamforming radar system, and RFI has tobe removed from raw echoes to obtain science quality data. In this paper we describe the current methodologyused to tackle RFI with EcoSAR, and provide an example on its performance. Finally, we discuss the advantagesand disadvantages of the method and mention potential improvements.

Osmanoglu, Batuhan↗
NASA NTRS2015

Signals of Opportunity Airborne Demonstrator (SoOP-AD)

In the second year of the SoOp-AD project, a brassboard analog section has been completed, along with working designs for the digital section and an antenna compatible with the NASA Langley B-200 or UC-12B aircraft. Resource requirements for the digital section FPGA are being finalized. One technical challenge at P-band is that the low transmitted data rate makes isolation of the direct and reflected signals using path delay, the conventional practice for GNSS reflectometry, difficult. Any retrieval of surface reflectivity from these measurements must account for the combination of direct and reflected signal in both the sky-view and Earth-view antennas. We have approached this challenge on several fronts; First, through null steering of the antenna. Second, through the formulation of an empirical calibration function for the reflectivity; and finally through estimating the direct and reflected signal powers as independent states in a Kalman filter. In addition to the direct-reflected interference from the same transmitter, there is also the possibility of interference due to transmissions, in adjacent bands, from other satellites in the constellation. Ground-based repeaters are also present in the S-band spectrum. Digital filters are being designed to isolate these repeaters, using simulations to verify the magnitude of their effect on the reflectivity and soil moisture retrievals. Other contributions to the error budget include the uncertainty in aircraft altitude, and the antenna pattern.

Radar↗
NASA NTRS2018

Digital Beamforming Based RFI Mitigation for Synthetic Aperture Radar

An increasing challenge for P-band Synthetic Aperture Radar (SAR) is Radio Frequency Interference (RFI). RFI results in image distortions and degrades the derived science products. This makes it critical to apply RFI removal techniques to restore the image quality. New advanced techniques can be achieved with Digital Beamforming (DBF) radars such as EcoSAR. In this paper, we present a Range-Dependent Time Minimum Variance Distortionless Response (RDTMVDR) Beamformer and apply it to EcoSAR flight data during post-processing. The antenna pattern (AP) is adaptively changed for each range line which increases the RFI suppression compared to a fixed AP for each pulse. The interferometric image quality is assessed before and after RFI suppression.

Bollian, Tobias↗
NASA NTRS1996

Repeat Pass Aircraft Interferometry Results at Portage Lake, Maine, and Innisfail, Australia

The NASA/JPL AIRSAR/TOPSAR instruments have the capability fo collecting fully polarimetric radar data at three wavelengths (C, L and P-Bands) and dual antenna interferometry at C-Band, and more recently, L-Band. In order to understand frequency and baseline dependent scattering effects in vegetated regions, repeat pass interferometry data was collected for two vegetated regions in 1993....Preliminary analysis if the data show that the smaller the wavelength, the greater the temporal decorrelation between passes, and the longer the wavelength, the greater the penetration depth for some types of vegetation canopies...

AIRSAR/TOPSAR↗
NASA NTRS1997

Estimating Soil Moisture in a Boreal Old Jack Pine Forest

Polarimetric L- and P-band AIRSAR data, corresponding model simulations, and classification algorithms have shown that in a boreal old jack pine (OJP) stand, the principal scattering mechanism responsible for radar backscatter is the double-bounce mechanism between the tree trunks and the ground.

Soil↗
NASA NTRSDate not supplied

Planning Satellite Swarm Measurements for Climate Models: Comparing Dynamic Constraint Processing and MILP Methods

We present D-SHIELD, a challenging climate science application to plan coordinated measurements (observations) for a constellation of satellites, each containing two different sensors, each with 61 pointing angle options. The L-band and P-band radar sensors collect data fed into a soil moisture model which tracks and predicts soil moisture across 1.67 million Ground Positions (GP). Soil moisture is an important predictor of wildfires, and then a predictor of floods, landslides and debris flow after a fire. Each measurement covers multiple GP due to the sensor footprint. Each GP has a "model error" which represents the uncertainty of the the soil moisture state prediction. Model error changes at different rates for each GP as the time since last observation increases and after significant events like rain. The planner's goal is to select measurements which maximize soil moisture model improvement (reduce model uncertainty). This problem is combinatorically explosive, involving many degrees of freedom for planner choices. Good domain heuristics can find solutions within a reasonable time for our application needs but cannot be proven optimal. In this paper we compare two different planning approaches to this problem: Dynamic Constraint Processing (DCP) and Mixed Integer Linear Programming (MILP). We match inputs and metrics for both DCP and MILP algorithms to enable a direct apples-to-apples comparison. We demonstrate and discuss the trades between DCP flexibility and performance vs. MILP's promise of provable optimality.

Rich Levinson↗
NASA NTRS2021

Potential of Full-polarimetric P- and L-band Sar Data in Characterizing Post-fire Recovery of Arctic Tundra

We used the airborne full polarimetric L-band and P-band SAR (PolSAR) data collected from recent NASA ABoVE Arctic Boreal Vulnerability Experiment (ABoVE) airborne campaign to understand the sensitivity of longwave radar backscatter intensity and phase to post-fire recovery process of Arctic tundra. The 2007 Anaktuvuk River fire was used as a case study. At 10-year post-fire, we observed a strong increase (>~4 dB) in both the P- and L-band radar backscatter in the severely burned areas, in contrast to limited backscatter differences (VV, VH) between burned and unburned areas at C-band. The polarimetric target decomposition analysis indicated a general trend towards more random surface scattering, and strong increases of the double-bounce and volumetric scattering power at both P- and L-band in the burned areas. Large differences were also observed in the Pauli phase angle and the dominant-scattering-type Touzi phase angle between the burned and unburned areas. The above changes are likely caused by increasing surface roughness and microtopography due to thermokarst development and ice degradation, and increasing subsurface scattering due to an overall drier and deeper active layer in the burned areas

Miller, Charles E.↗
NASA NTRSDate not supplied

Integral Equation Model of the Martian Surface layer for the Detection of Buried Ice Deposits in Support of the international Ice Mapping Mission Synthetic Aperture Radar

This work implemented a 3-D Electromagnetic Scattering model to gain a better understanding in the observations of L- and P-band radar returns from the multi-layered Martian upper surface layer. The model is based on the Integral Equation Model (IEM) developed by Adrian Fung. Our model implementation treats the upper surface (regolith) layer as an inhomogeneous medium with irregular boundaries for a range of Martian surface and shallow subsurface scenarios. The model is well suited to study the near subsurface (upper 10 meters of surface sediments) ice detection capability of the L-band (32 cm wavelength) Synthetic Aperture Radar (SAR) planned for the international Mars Ice Mapping (I-MIM) mission launching later in the 2020s.

surface roughness, Integral Equation Model (IEM)↗
NASA NTRSDate not supplied

Biomass Harmonization and SAR Analysis with the Multi-mission Algorithm and Analysis Platform (MAAP)

The Multi‐mission Algorithm and Analysis Platform (MAAP) is a collaborative effort between NASA and the European Space Agency (ESA) to support above ground biomass (AGB) research in an open science framework. MAAP brings together relevant data, algorithms, and computing capabilities in a common cloud environment to address the challenges of sharing and processing data from field, airborne and satellite measurements. MAAP was publicly released in October 2021, providing computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of data. MAAP has allowed scientists from both North America and Europe to collaborate on the generation and analysis/visualization of data derived from multiple, discipline-adjacent missions in an open, collaborative environment that has reached beyond traditional scientific investigation. MAAP has been used to support multiple scientific activities. To date, existing LiDAR data from multiple platforms has been calibrated with field measurements and combined for more comprehensive and accurate estimates of above ground biomass AGB; these LiDAR platforms include airborne (e.g. LVIS), the International Space Station (NASA’s Global Ecosystem Dynamics Investigation (GEDI), and satellites (e.g. ICESat-2). The current challenge is to effectively and seamlessly combine the aforementioned LiDAR-based data with new data sources such as P-band RADAR from ESA’s upcoming BIOMASS mission, existing ESA Sentinel-1 C-band SAR, and the 30 PB/yr of high cadence global coverage L-band SAR data from the upcoming NASA-ISRO SAR (NISAR) mission. Recent analysis using MAAP merged ICESat-2 and optical data (Harmonized Landsat Sentinel) produced the most comprehensively precise estimate of boreal-wide AGB to date. Another effort using MAAP is the production and open distribution of global comparisons of AGB map estimates, including from ICESat-2 and GEDI, to bolster stakeholder uptake for policy applications. These map estimates will feed into the Intergovernmental Panel on Climate Change (IPCC) database, likely aiding the next Global Carbon Stocktake of the UNFCCC. Furthermore, the biomass retrieval intercomparison exercise BRIX-2 could benefit from the MAAP providing standardized test cases (based on airborne campaign and spaceborne data) allowing the community to develop and apply retrieval algorithms based on these test cases, while forthcoming SAR data training curricula could also use the MAAP as a teaching and learning platform. The MAAP is meeting the challenges inherent in international, open science collaboration and large scale computing with a platform that is entirely open source and cloud native, using open standards for data access, manipulation, protocols, and formats. The MAAP data system consists of a dedicated data store whose data is indexed in an online catalog conforming to established metadata, application programmatic interfaces (APIs), and service interface standards, using an implementation of the open sourced NASA Common Metadata Repository. Federation of user identities allows users from either NASA or ESA to access and consume services from the other using a unified metadata catalog for the data utilized across the ESA and NASA MAAP platforms. Similarly, we are exploring how to increase interoperability to achieve a common approach to packaging, orchestrating and executing algorithms, with interoperable access to data for subsetting, fast browse, and cloud-optimized access, all using interoperable standards such as those from the Open Geospatial Consortium (OGC). Designed for interoperability, ESA and NASA utilize a common architecture for the software platform. It provides a cloud-based algorithm development environment (ADE) that enables scientists to develop algorithms collaboratively with access to the MAAP data catalog as well as other data archives. MAAP provides an Eclipse Che-based ADE supporting both Python and R languages, popular in this biomass community. Algorithms developed and containerized within the ADE can be deployed to run to thousands of computational nodes in the MAAP’s data processing system (DPS), dramatically speeding up processing and giving scientists a rapid, iterative turnaround of results. NASA’s implementation of the DPS is based on the Hybrid Science Data System (HySDS) framework, used by NASA flight projects to produce Earth science standard products.

cloud computing↗
NASA NTRS2023

The Dielectric Constant of Sea Water and Extension to High Salinity

Accurate knowledge of the dielectric constant of sea water is important for remote sensing of surface parameters such as sea surface temperature (SST) and sea surface salinity (SSS). The advent of sensors in space, SMOS [1], Aquarius [2] and SMAP [3] capable of measuring SSS motivated modern measurements [4,5] and modelling [5,6] of the dielectric constant at L-band (1.4 GHz). In the past, the range of salinity included in the data used to create these models has been restricted to values typically encountered in the open ocean (e.g., less than 40 psu). However, there are many smaller water bodies with much higher salinity. Notable examples are the Great Salt Lake in Utah with salinity on the order of 180 psu and Garabogazköl lagoon in Turkmenistan with even higher salinity. Unfortunately, existing models for the dielectric constant can’t necessarily just be extended to higher values of salinity. The problem is that the polynomials in salinity and temperature used to represent the unknown parameters in the models are not constrained outside the range of SSS and SST used to determine their coefficients. While the models for the dielectric constant may be very good within that range, outside that range they can lead to unrealistic behavior. Research is underway to develop a model that represents the dielectric constant well over the ocean and behaves well at high salinity. In preparation for possible wideband remote sensing of salinity [7,8 ,9], the laboratory measurements made at 1.413 GHz [4,5] are being repeated at 0.707 GHz (P-band) and the plan is to include values of high salinity (50, 100, 150 psu).

D.M. Le Vine↗
NASA NTRS2000

Spaceborne SAR at UHF

Explore the source record for details and available documents.

synthetic aperture radar UHF P-Band↗
NASA NTRS2012

Overview of the NASA/JPL UAVSAR and Porting to the Global Hawk

UAVSAR has demonstrated the combined Precisions Autopilot coupled with the L-band electronically steered allow for robust repeat pass radar interferometric collections. Science results in the areas of soil moisture, volcanology, solid earth science, glaciology, and ecosystem system science have been achieved using the UAVSAR platform.

Uninhabited Aerial Vehicle Synthetic Aperture Rada↗