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Jeffrey R Piepmeier

Publications and source records attributed to Jeffrey R Piepmeier.

10 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Soil Moisture Active/Passive (SMAP) L-band Microwave Radiometer Post-Launch Calibration Revisit: Approach and Performance

The SMAP microwave radiometer is a fully-polarimetric L-band radiometer flown on the SMAP satellite in a 6 AM / 6 PM sun-synchronous orbit at 685-km altitude. After the SMAP L1B_TB data product version4was released in 2018, the radiometer has undergonefurther calibration and validation. The goal isto reducethe difference between antenna temperature (TA) ofascending and descending orbits during the eclipse, andto reduce the dips in the calibration drift over the Cold Sky (CS) during the eclipse seasons in 2017 and 2018. The post-launch calibration algorithmhas been revisitedby retrieving all of the calibration parameters simultaneouslywith two different options for thehot calibration source(theglobal ocean, or the radiometer internal reference load). The performance of the two options are compared here. Theoption with the radiometer internal reference load has been chosen by the SMAP science team for data release version 5. In addition, a correction offset is applied to the input signal to account for offsets during the early-mission stages with theSMAP SAR transmitter operating alongside the radiometer.

Jinzheng Peng↗
NASA NTRS2021

Soil Moisture Active/Passive (SMAP) L-Band Microwave Radiometer Post-Launch Calibration Revisit: Approach and Performance

The soil moisture active passive (SMAP) microwave radiometer is a fully-polarimetric L -band radiometer flown on the SMAP satellite in a 6 AM /6 PM sun-synchronous orbit at 685-km altitude. After the SMAP L1B_TB data product version 4 was released in 2018, the radiometer has undergone further calibration and validation. The goal is to reduce the difference between antenna temperature of ascending and descending orbits during the eclipse, and to reduce the dips in the calibration drift over the cold sky (CS) during the eclipse seasons in 2017 and 2018. The postlaunch calibration algorithm has been revisited by retrieving all of the calibration parameters simultaneously with two different options for the hot calibration source (the global ocean, or the radiometer internal reference load). The performance of the two options are compared here. The option with the radiometer internal reference load has been chosen by the SMAP science team for data release version 5. In addition, a correction offset is applied to the input signal to account for offsets during the early-mission stages with the SMAP synthetic aperture radar transmitter operating alongside the radiometer.

calibration↗
NASA NTRS2021

Global L-band Observatory for Water Cycle Studies (GLOWS)

L-band observations have proven useful for estimating soil moisture and ocean salinity variables to study the land surface and ocean. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission was the first (2009-present) spaceborne L-band radiometer. This was followed by two L-band missions flown by the National Aeronautics and Space Administration (NASA) to measure sea surface salinity (Aquarius 2011-2015) and soil moisture (SMAP 2015-present). It is critical to continue the time series of L-band observations that these missions have begun. To address this need we propose a new low-cost instrument concept known as the Global L-band active/passive Observatory for Water cycle Studies (GLOWS) that will include an L-band radiometer and radar to provide data continuity. The new mission concept includes a deployable reflectarray lens antenna with a compact feed that can be flown on an Earth Venture class satellite in a EELV Secondary Payload Adapter (ESPA) Grande-class mission. GLOWS will continue the science observations of SMAP and SMOS at the same resolution and accuracy at substantially lower cost, size, and weight.

David Long↗
NASA NTRS2021

Microwave Radiometry at Frequencies From 500 to 1400 MHz: An Emerging Technology for Earth Observations

Microwave radiometry has provided valuable spaceborne observations of Earth's geophysical properties for decades. The recent SMOS, Aquarius, and SMAP satellites have demonstrated the value of measurements at 1400 MHz for observing surface soil moisture, sea surface salinity, sea ice thickness, soil freeze/thaw state, and other geophysical variables. However, the information obtained is limited by penetration through the subsurface at 1400 MHz and by a reduced sensitivity to surface salinity in cold or wind-roughened waters. Recent airborne experiments have shown the potential of brightness temperature measurements from 500–1400 MHz to address these limitations by enabling sensing of soil moisture and sea ice thickness to greater depths, sensing of temperature deep within ice sheets, improved sensing of sea salinity in cold waters, and enhanced sensitivity to soil moisture under vegetation canopies. However, the absence of significant spectrum reserved for passive microwave measurements in the 500–1400 MHz band requires both an opportunistic sensing strategy and systems for reducing the impact of radio-frequency interference. Here, we summarize the potential advantages and applications of 500–1400 MHz microwave radiometry for Earth observation and review recent experiments and demonstrations of these concepts. We also describe the remaining questions and challenges to be addressed in advancing to future spaceborne operation of this technology along with recommendations for future research activities.

microwave radiometry↗
NASA NTRS2020

SCoBi Multilayer: A Signals of Opportunity Reflectometry Model for Multilayer Dielectric Reflections

A multilayer module is incorporated into the Signals of Opportunity (SoOp) Coherent Bistatic Scattering model (SCoBi) for determining the reflections and propagation of electric fields within a series of multilayer dielectric slabs. This module can be used in conjunction with other SCoBi components to simulate complex, bistatic simulation schemes that include features such as surface roughness, vegetation, antenna effects, and multilayer soil moisture interactions on reflected signals. This paper introduces the physics underlying the multilayer module and utilizes it to perform a simulation study of the response of SoOp-R measurements with respect to subsurface soil moisture parameters. For a frequency range of 100–2400 MHz, it is seen that the SoOp-R response to a single dielectric slab is mostly frequency insensitive; however, the SoOp-R response to multilayer dielectric slabs will vary between frequencies. The relationship between SoOp-R reflectivity and the contributing depth is visualized, and the results show that SoOp-R measurements can display sensitivity to soil moisture below the penetration depth. By simulation of simple soil moisture profiles with different wetting and drying gradients, the dielectric contrast between layers is shown to be the greatest contributing factor to subsurface soil moisture sensitivity. Overall, it is observed that different frequencies can sense different areas of a soil moisture profile, and this behavior can enable subsurface soil moisture data products from SoOp-R observations.

Dylan Boyd↗
NASA NTRS2020

Cramer-Rao Lower Bound for SoOp-R-Based Root-Zone Soil Moisture Remote Sensing

Signals of opportunity (SoOp) reflectometry (SoOp-R) is a maturing field for geophysical remote sensing as evidenced by the growing number of airborne and spaceborne experiments. As this approach receives more attention, it is worth analyzing SoOp-R’s capabilities to retrieve subsurface soil moisture (SM) by leveraging communication and navigation satellite transmitters. In this research, the CRLB is used to identify the effects of variable SoOp-R parameters on the best achievable estimation error for root-zone soil moisture (RZSM). This study investigates the use of multiple frequency, polarization, and incidence angle measurement configurations on a two-layered dielectric profile. The results also detail the effects of variable SM conditions on the capability of SoOp-R systems to predict subsurface SM. The most prevalent observation is the importance of using at least two frequencies to limit uncertainties from subsurface SM estimates. If at least two frequencies are used, the CRLB of a profile is retrievable within the root-zone depending on the surface SM content as well as the number of independent measurements of the profile. For a depth of 30 cm, it is observed that a CRLB corresponding to 4% RZSM estimation accuracy is achievable with as few as 2 dual-frequency-based SoOp-R measurements. For this depth, increasing number of measurements provided by polarization and incidence angle allow for sensing of increasingly wet SM profile structures. This study, overall, details a methodology by which SoOp-R receiver system can be designed to achieve a desired CRLB using a trade-off study between the available measurements and SM profile.

Signals of Opportunity (SoOp)↗
NASA NTRS2019

IceCube: Spaceflight Demonstration of 883-GHz Cloud Radiometer for Future Science

Cloud ice play important roles in Earth’s climate and weather systems through their interactions with atmospheric radiation, dynamics, energy and precipitation processes. Submillimeter (submm) wave remote sensing at 200-1000 GHz is able to provide the sensitivity not covered by visible (VIS)/infrared (IR) and low-frequency microwave (MW) sensors (10-183 GHz), and measure cloud ice in the middle-to-upper troposphere. The IceCube 883-GHz cloud radiometer is the latest of NASA’s efforts to advance the technology readiness level (TRL) of submm-wave receiver technology for future compact, low-cost implementation of Earth observing systems. Emerging CubeSat opportunities allow a fast-track development and spaceflight demonstration of IceCube on a 3-U CubeSat. Funded by NASA’s In-Space Validation of Earth Science Technologies (InVEST) program and Science Mission Directorate (SMD), IceCube is the first CubeSat developed and flown by Goddard Space Flight Center (GSFC) in 2.5 years, using commercial off-the-shelf (COTS) components and subsystems. It was successfully released from International Space Station (ISS) in May 2017, acquired 15-month science data and produced the first global map of the 883-GHz cloud ice. It achieved all mission objectives and provided a pathway for future cost-effective cloud observations from CubeSat constellation.

Submm-wave remote sensing↗
NASA NTRS2017

Soil Moisture ActivePassive (SMAP) L-Band Microwave Radiometer Post-Launch Calibration

The SMAP microwave radiometer is a fully-polarimetric L-band radiometer flown on the SMAP satellite in a 6 AM/ 6 PM sun-synchronous orbit at 685 km altitude. Since April, 2015, the radiometer is under calibration and validation to assess the quality of the radiometer L1B data product. Calibration methods including the SMAP L1B TA2TB (from Antenna Temperature (TA) to the Earth’s surface Brightness Temperature (TB)) algorithm and TA forward models are outlined, and validation approaches to calibration stability/quality are described in this paper including future work. Results show that the current radiometer L1B data satisfies its requirements.

radiometers↗
NASA NTRSDate not supplied

Lessons Learned from SMAP Radiometer Pre-/Post-launch Calibration

The Soil Moisture Active Passive(SMAP) mission was launched on 31stJanuary 2015 in a 6 AM/ 6 PM sun-synchronous orbit at 685 km altitude to measure soil moisture and free/thaw globally [1]. The passive instrument of SMAP is a fully polarimetric L-band radiometer (1.4GHz) operating with a bandwidth of 24MHz. The radiometer uses a combination of noise-diodes and Dicke-loads for internal calibration with a design similar to that used by the Aquarius or Jason series radiometers[2,3].Pre-launch calibration activities had been performed since 2012on the engineering model of the radiometer. Post-launch calibration activities have been performed to fine-tune and validate the results from the pre-launch calibration. The major calibration activities and lessons learned in the past 8 years will be described in the following sections.

Jinzheng Peng↗