Jinzheng Peng | Engineering Papers

NASA NTRS2022

The Fourth Stokes Parameter for Geolocation in Passive Microwave Remote Sensing from Space

Polarimetric microwave radiometers such as SMAP are capable of measuring the fourth Stokes parameter in brightness temperature over the Earth surface. The value of this parameter is normally small but exhibits sharp spikes when the scene includes large differences in emission from the surface, such occur at land/water boundaries. In this manuscript, it is shown that these spikes can be used to accurately locate coastlines with potential application to geolocation in passive microwave remote sensing from space. Examples are presented using the L-band radiometer on SMAP, first with theory using calculations with the SMAP antenna pattern and orbit and then with SMAP measurements of the fourth Stokes parameter over Madagascar. Using the SMAP data, the coastline is located with a standard deviation less than 2 km. The results are consistent with the conventional approach used for geolocation of the SMAP radiometer footprint.

Passive Microwave Remote Sensing↗

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

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 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 NTRS2019

Improving Brightness Temperature Measurements near Coastal Areas for SMAP

The Soil Moisture Active Passive (SMAP) mission is designed to acquire L-band radiometer measurements for the estimation of soil moisture with 0.04 m3/m3 volumetric accuracy in the top 5 cm for vegetation with water content of less than 5 kg/m2. In regions near the coast or near inland bodies of water, the signal measured by the SMAP radiometer contains emissions from land and water, resulting in errors in the soil moisture estimation. In this paper, the effort to extract the brightness temperature (TB) according to the land fraction or water fraction (depending on the center of the footprint location) from the affected SMAP measurements was addressed. A single pixel correction algorithm was applied and its performance was evaluated over simulated data. A data-driven approach for the estimation of land and water TB for data correction was developed. The correction algorithm was then applied to real data and its performance was assessed over the SMAP soil moisture retrievals. We showed that the single pixel algorithm is an effective and computationally efficient algorithm for removing land or water TB contamination from the SMAP data.

Julian Chaubell↗

NASA NTRS2019

Multi-Channel Correlator Array-Fed Microwave Radiometer

Multiband passive microwave imagery in X to W Bands has a nearly 40-year history of utilization for measurement of multiple geophysical parameters (e.g., precipitation rate, ocean surface wind speed, sea ice concentration, and land surface temperature). Spatial resolution is limited by aperture size, and although aperture sizes have grown to 1-2 meters, current capability will not meet future spatial resolution needs. As aperture size increases, new antenna feed techniques are needed to maintain contiguous coverage and obtain Nyquist sampling. Here we apply the correlator array fed radiometer architecture adapted from radio astronomy and show how it can meet emerging needs. Simulation results of a 0.8-m, 36.5-GHz, array-fed reflector (equivalent to 20 meters at 1.41 GHz) show the feasibility of creating multiple over-lapping beams.

Microwave radiometer↗

NASA NTRS2019

Soil Moisture Active/Passive (SMAP) L-Band Microwave Radiometer Post-Launch Calibration Upgrade

The Soil Moisture Active/Passive (SMAP) microwave radiometer is a fully polarimetric L-band radiometer flown on theSMAP satellite in a 6 AM/6 PM sun-synchronous orbit at 685 km altitude. After the SMAP L1B_TB data product version 3 was released in 2016, the radiometer has been undergoing further calibration and validation with the goal of reducing both the bias in the cold-sky measurements and calibration drift in the global ocean measurements experienced during eclipse seasons in data product version 3. The post-launch calibration algorithm has been upgraded by using new estimates of the reflector emissivity as well as using multiple scenes to calibrate the radiometer internal reference sources and antenna gain simultaneously. In addition, a correction offset is applied to the ocean roughness model for horizontal polarization based on nadir observations. Test and validation results show that the goal is achieved (e.g., biases are removed and the calibration stability achieved for data release version 4 is 0.1 K(rms) over both the global ocean and CS).

Calibratio↗

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

SMAP RFI Change Detection

The Soil Moisture Active Passive (SMAP) mission, launched on January 31, 2015, has completed its primary 3-year mission and is currently in its extended mission. Although operation occurs within the protected frequency allocation of 1400-1427 MHz, the SMAP radiometer is impacted by radio frequency interference (RFI). The radiometer was designed to provide detection and filtering of RFI in order to meet error budget requirements. A time series algorithm was developed to monitor, detect and report the changing environment with the objective of detecting new RFI sources as well as existing persistent sources. The detection of sources are used in RFI reporting to NASA spectrum management with the hope that interfering sources will be turned off by the necessary administrations.

Priscilla N Mohammed↗

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↗

NASA NTRSDate not supplied

Total Variation Majorization Minimization (TV-MM) Approach to Radiometer Brightness Temperature Gridding and Reconstruction

This paper presents the implementation of an algorithm to enhance the image resolution of the Earth's surface brightness temperature (T B ) data measured by radiometers such as the one onboard of the Soil Moisture Active Passive (SMAP) mission. A key step in radiometer T B processing is the conversion of the swath-based calibrated antenna temperature (T A ) measurements to the Level 3 Earth-centered grid. The simplest algorithm to transform this data from swath to gridded format is called drop-in-the-bucket which simply averages surrounding noisy T A samples to form a T B value at the gridded location. This method reduces noise, however produces low resolution products. To obtain a higher resolution product, SMAP uses other techniques such the Backus-Gilbert (BG) algorithm, which is the conventional method used in microwave radiometry. Although this method performs the required interpolation, it is not effective in denoising and removing blurring effects due to antenna filtering of the radiometer image data. Our motivation for this development is to further improve the resolution through post-processing of the radiometer T B image, a highly cost-effective method of image enhancement. The approach adapted in this work is based on the minimization of the Total Variation (TV) regularized objective function that is used extensively in solving general ill-posed linear inverse problems in image processing. Since the TV-based objective function is convex but not everywhere differentiable, there exists many numerical algorithms that can estimate the solution and the one selected for this work is called Majorization- Minimization (MM). By applying this algorithm, simulation experiments were performed based on synthetic data from the Geophysical model as well as real SMAP data to demonstrate the effectiveness of the technique. Results were then compared against the BG method.

Wing Lee↗