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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

NISAR L-Band Feed Antenna Tiles, Preliminary Design

Being developed in partnership between NASA and the Indian Space Research Organisation (ISRO), the NASA-ISRO Synthetic Aperture Radar (NISAR) satellite is planned to launch in late 2020. NISAR will measure many aspects of how Earth is changing with unprecedented accuracy on a global scale from a Low Earth Orbit (LEO) platform. With a 12m deployable mesh reflector, NISAR will feature one of the largest deployable mesh reflector ever launched for a scientific mission. Two large planar phased arrays will feed the reflector, one that will operate at L-Band and be developed by the Jet Propulsion Laboratory (JPL), and an S-band array that will be developed at the ISRO Space Application Centre (SAC). This paper describes the preliminary design of the L-Band feed array.

deployable mesh reflector↗
NASA NTRS2017

Preliminary Design of the NISAR L-Band Feed Antenna Tiles

Being developed in a partnership between NASA and the Indian Space Research Organisation (ISRO), the NASA-ISRO Synthetic Aperture Radar (NISAR) satellite is planned to launch in late 2020. NISAR will measure many aspects of how Earth is changing with unprecedented accuracy on a global scale from a Low Earth Orbit (LEO) platform. With a 12-meter deployable mesh reflector, NISAR will feature one of the largest deployable mesh reflectors ever launched for a scientific mission. Two large planar phased arrays will feed the reflector, one that will operate at L-Band and be developed by the Jet Propulsion Laboratory (JPL), and an S-band array that will be developed at the ISRO Space Application Centre (SAC). This paper describes the preliminary design of the L-Band feed array.

Metal Patch Antenna↗
NASA NTRS2008

L-Band Transmit/Receive Module for Phase-Stable Array Antennas

Interferometric synthetic aperture radar (InSAR) has been shown to provide very sensitive measurements of surface deformation and displacement on the order of 1 cm. Future systematic measurements of surface deformation will require this capability over very large areas (300 km) from space. To achieve these required accuracies, these spaceborne sensors must exhibit low temporal decorrelation and be temporally stable systems. An L-band (24-cmwavelength) InSAR instrument using an electronically steerable radar antenna is suited to meet these needs. In order to achieve the 1-cm displacement accuracy, the phased array antenna requires phase-stable transmit/receive (T/R) modules. The T/R module operates at L-band (1.24 GHz) and has less than 1- deg absolute phase stability and less than 0.1-dB absolute amplitude stability over temperature. The T/R module is also high power (30 W) and power efficient (60-percent overall efficiency). The design is currently implemented using discrete components and surface mount technology. The basic T/R module architecture is augmented with a calibration loop to compensate for temperature variations, component variations, and path loss variations as a function of beam settings. The calibration circuit consists of an amplitude and phase detector, and other control circuitry, to compare the measured gain and phase to a reference signal and uses this signal to control a precision analog phase shifter and analog attenuator. An architecture was developed to allow for the module to be bidirectional, to operate in both transmit and receive mode. The architecture also includes a power detector used to maintain a transmitter power output constant within 0.1 dB. The use of a simple, stable, low-cost, and high-accuracy gain and phase detector made by Analog Devices (AD8302), combined with a very-high efficiency T/R module, is novel. While a self-calibrating T/R module capability has been sought for years, a practical and cost-effective solution has never been demonstrated. By adding the calibration loop to an existing high-efficiency T/R module, there is a demonstrated order-of-magnitude improvement in the amplitude and phase stability.

Andricos, Constantine↗
NASA NTRS2001

Ground-Based Passive Microwave Remote Sensing Observations of Soil Moisture at S and L Band with Insight into Measurement Accuracy

Accurate estimates of spatially heterogeneous algorithm variables and parameters are required in determining the spatial distribution of soil moisture using radiometer data from aircraft and satellites. A ground-based experiment in passive microwave remote sensing of soil moisture was conducted in Huntsville, Alabama from July 1-14, 1996 to study retrieval algorithms and their sensitivity to variable and parameter specification. With high temporal frequency observations at S and L band, we were able to observe large scale moisture changes following irrigation and rainfall events, as well as diurnal behavior of surface moisture among three plots, one bare, one covered with short grass and another covered with alfalfa. The L band emitting depth was determined to be on the order of 0-3 or 0-5 cm below 0.30 cubic centimeter/cubic centimeter with an indication of a shallower emitting depth at higher moisture values. Surface moisture behavior was less apparent on the vegetated plots than it was on the bare plot because there was less moisture gradient and because of difficulty in determining vegetation water content and estimating the vegetation b parameter. Discrepancies between remotely sensed and gravimetric, soil moisture estimates on the vegetated plots point to an incomplete understanding of the requirements needed to correct for the effects of vegetation attenuation. Quantifying the uncertainty in moisture estimates is vital if applications are to utilize remotely-sensed soil moisture data. Computations based only on the real part of the complex dielectric constant and/or an alternative dielectric mixing model contribute a relatively insignificant amount of uncertainty to estimates of soil moisture. Rather, the retrieval algorithm is much more sensitive to soil properties, surface roughness and biomass.

Laymon, Charles A.↗
NASA NTRS2022

Robustness of Vegetation Optical Depth Retrievals Based on L-Band Global Radiometry

Microwave vegetation optical depth (VOD) and soil moisture (SM) can be simultaneously retrieved based on L-band radiometry with polarization information. VOD is indicative of the vegetation water content (VWC) because it captures the extinction of land surface emission. If the connectivity of VOD to VWC is robust, the pair of VWC-SM observations can be viable bases for understanding soil–plant–atmosphere water relations, providing new perspectives on ecosystem science. Simultaneous SM–VOD retrievals are feasible by inverting the τ−ω model with two independent datasets in dual-channel algorithms. However, given correlated satellite vertical and horizontal brightness temperatures (TBs; TB v and TB h ), an ill-posed inverse problem arises where TB errors result in high uncertainties of retrievals. In this study, we apply the degrees-of-information (DoI) metric and propose a signal-to-noise ratio (SNR) metric to assess the “retrievability” of VOD given the Soil Moisture Active Passive (SMAP) TB v –TB h linear dependence. The application of these metrics allows determining where the VOD retrievals are robust and reliable. This is a necessary step in supporting the applications of VOD in ecology and hydrology. Results show that regions with mainly nonwoody vegetation have the best potential for VOD retrievals, though regularization is necessary. We then assess VOD time variations from two regularization products that reduce the impact of underdetermined inversions: the L3 dual-channel algorithm (L3-DCA) and the multitemporal dual-channel algorithm (MTDCA), which constrain VOD time dynamics with and without using a priori VOD climatology, respectively. Though they both reduce noise, especially in the VOD retrievals, they result in differences in VOD seasonal amplitude and coupling to SM at high frequencies as we outline here.

Microwave↗
NASA NTRS1980

L-band radar sensing of soil moisture

The performance of an L-band, 25 cm wavelength imaging synthetic aperture radar was assessed for soil moisture determination, and the temporal variability of radar returns from a number of agricultural fields was studied. A series of three overflights was accomplished over an agricultural test site in Kern County, California. Soil moisture samples were collected from bare fields at nine sites at depths of 0-2, 2-5, 5-15, and 15-30 cm. These gravimetric measurements were converted to percent of field capacity for correlation to the radar return signal. The initial signal film was optically correlated and scanned to produce image data numbers. These numbers were then converted to relative return power by linear interpolation of the noise power wedge which was introduced in 5 dB steps into the original signal film before and after each data run. Results of correlations between the relative return power and percent of field capacity (FC) demonstrate that the relative return power from this imaging radar system is responsive to the amount of soil moisture in bare fields. The signal returned from dry (15% FC) and wet (130% FC) fields where furrowing is parallel to the radar beam differs by about 10 dB.

Chang, A. T. C.↗
NASA NTRS1990

The design of a linear L-band high power amplifier for mobile communication satellites

A linear L-band solid state high power amplifier designed for the space segment of the Mobile Satellite (MSAT) mobile communication system is described. The amplifier is capable of producing 35 watts of RF power with multitone signal at an efficiency of 25 percent and with intermodulation products better than 16 dB below carrier.

Whittaker, N.↗
NASA NTRS2005

The Impact of the Sun on Passive Remote Sensing at L-band

The sun is a strong source of radiation at L-band behaving roughly like a thermal source with a temperature ranging between 10(exp 5) - 10(exp 7) K, depending on solar activity. This is an important consideration at 1.4 GHz (the window set aside for passive use only) where future satellite sensors will operate to monitor soil moisture and sea surface salinity (e.g. SMOS, Aquarius, and Hydros). Straight forward calculations show that such a source of radiation can be a significant issue for these remote sensing applications, especially in the case of remote sensing of sea surface salinity. Radiation from the sun impacts passive remote sensing systems in several ways. First, is the solar radiation that comes directly from the sun (line-of-sight from sun to spacecraft that enters the radiometer through antenna side lobes). This is a particular problem for sensors in sunsynchronous orbits near the terminator (e.g. orbits with equatorial crossing times near 6am/6pm) because the spacecraft is in the sun most of the time. Second, is solar radiation that is reflected (specularly) from the mean surface to the radiometer. This contribution can be nearly as large as the direct ray, especially when the reflection is from the ocean surface which has a high reflection coefficient. Finally, there is "incoherent" signal reflected from the surface structure (roughness) to the radiometer antenna. Examples illustrating the significance of these terms is presented for the case of a pushbroom radiometer such as Aquarius and a conically scanning radiometer such as proposed for Hydros. Calculations are made using a set of theoretical patterns for these beams together with data on solar radiation obtained from by a worldwide network of observing stations known as Radio Solar Telescope Network (RSTN). Near solar minimum, solar contamination is not a problem unless the sun enters near the main beam. But near solar maximum, account must be made for radiation from the sun even when the signal enters in sidelobes far from the main beam.

LeVine, David M.↗
NASA NTRSDate not supplied

Mapping Inundation from Hurricane Florence (2018) with L-Band Synthetic Aperture Radar, Commercial Imagery, and Ancillary Data via Random Forest Classification

Mapping the extent of floodwaters following extreme rainfall aids in the distribution of resources, recovery efforts, and damage assessment practices. Development of a land cover classification system focused on mapping inundation after major hurricane events using synthetic aperture radar (SAR) data could allow for the production of near-real-time inundation mapping, enabling government and emergency response entities to get a preliminary idea of a developing situation. In response to Hurricane Florence of 2018, NASA JPL collected numerous swaths of quad-pol L-band SAR data with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument observing the record-setting river stages across North and South Carolina. The resulting fully-polarized SAR images allow for mapping of inundation extent at a high spatial resolution with a unique advantage over optical imaging stemming from the sensor’s ability to penetrate cloud cover and dense vegetation. This study seeks to determine how accurately maps of inundation can be generated from L-band SAR imagery through Random Forest classification. Once the extent of water and inundated vegetation is classified, cleanup operations are performed using fuzzy logic to reduce false detections. Estimates of water extent are then combined with datasets describing the distribution of population, buildings, and roads throughout the domain to evaluate societal impacts. Results from the Hurricane Florence case study will be discussed along with the limitations of available validation data for assessment of the classifier’s accuracy.

Alexander Melancon↗
NASA NTRS1991

Radar measurement of L-band signal fluctuations caused by propagation through trees

Fluctuations of an L-band, horizontally polarized signal that was transmitted from the ground through a coniferous forest canopy to an airborne radar are examined. The azimuth synthetic aperture radar (SAR) impulse response in the presence of the measured magnitude fluctuations shows increased sidelobes over the case with no trees. Statistics of the observed fluctuations are similar to other observations.

Durden, Stephen L.↗
NASA NTRS1984

Estimating net rainfall, evaporation and water storage of a bare soil from sequential L-band emissivities

A general method to use a time series of L-band emissivities as an input to a hydrological model for continuously monitoring the net rainfall and evaporation as well as the water content over the entire soil profile is proposed. The model requires a sufficiently accurate and general relation between soil emissivity and surface moisture content. A model which requires the soil hydraulic properties as an additional input, but does not need any weather data was developed. The method is shown to be numerically consistent.

Stroosnijder, L.↗
NASA NTRSDate not supplied

SMOS Salinity Retrieved from New Seawater Dielectric Constant Models at L-band

The accuracy of the Sea Surface Salinity (SSS) retrieved from L-Band radiometer measurements is strongly dependent on the accuracy of the modelling of the dielectric constant. Two new parametrizations have recently been developed based on one hand on the Soil Moisture and Ocean Salinity (SMOS) satellite multi-angular brightness temperature measurements [1] (BV) and on the other hand on new laboratory measurements [3] (GW2020). These two approaches are fully independent. The brightness temperatures, Tb, simulated with the BV and GW2020 parametrizations are compared with each other and with the ones derived from dielectric constant models previously in use in the SMOS, Soil Moisture Active Passive (SMAP) and Aquarius SSS retrievals. Tb simulated with the BV and GW2020 parametrizations agree particularly well for most SSS and SST commonly observed over the open ocean and are found to be in closer agreement than with earlier parametrizations. Nevertheless, uncertainty remains at low SST where a ∼ 0.1 K relative difference between the two models is observed. A complete reprocessing of SMOS SSS (2010–2020) has been performed using the BV parametrization instead of the Klein and Swift (1977) model previously used in SMOS processing. When compared with Argo derived near surface salinity maps, clear improvements are observed in warm and cold regions. Remaining uncertainties in cold waters will be discussed relatively to the uncertainties in SMOS Tb linked to sea ice contamination and given the constraints given by the GW2020 laboratory measurements.

J. Boutin↗
NASA NTRS1988

Omni-directional L-band antenna for mobile communications

The principle and design of an L-band omni-directional mobile communication antenna are discussed. The antenna is a circular wave guide aperture with hybrid circuits attached to higher order mode excitation. It produces polarized and symmetric two split beams in elevation. The circular waveguide is fed by eight probes with a 90 degree phase shift between their inputs. Radiation pattern characteristics are controlled by adjusting the aperture diameter and mode excitation. This antenna satisfies gain requirements as well as withstanding the harsh environment.

Kim, C. S.↗
NASA NTRS2012

L-Band H Polarized Microwave Emission During the Corn Growth Cycle

Hourly L-band (1.4 GHz) horizontally (H) polarized brightness temperatures (T(sub B))'s measured during five episodes (more than two days of continuous measurements) of the 2002 corn growth cycle are analyzed. These T(sub B)'s measurements were acquired as a part of a combined active/passive microwave field campaign, and were obtained at five incidence and three azimuth angles relative to the row direction. In support of this microwave data collection, intensive ground sampling took place once a week. Moreover, the interpretation of the hourly T(sub B)'s could also rely on the data obtained using the various automated instruments installed in the same field. In this paper, the soil moisture and temperature measured at fixed time intervals have been employed as input for the tau-omega model to reproduce the hourly T(sub B). Through the calibration of the vegetation and surface roughness parameterizations, the impact of the vegetation morphological changes on the microwave emission and the dependence of the soil surface roughness parameter, h(sub r), on soil moisture are investigated. This analysis demonstrates that the b parameter, appearing in the representation of the canopy opacity, has an angular dependence that varies throughout the growing period and also that the parameter hr increases as the soil dries in a portion of the dry-down cycle. The angular dependence of the b parameter imposes the largest uncertainty on T(sub B) simulations near senescence as the response of b to the incidence is also affected by the crop row orientation. On the other hand, the incorporation of a soil moisture dependent h(sub r) parameterization was responsible for the largest error reduction of T(sub B) simulations in the early growth cycle.

Joseph, A. T.↗