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Active and passive microwave characteristics of diurnal soil freeze-thaw transitions and their relationships are crucial for developing retrieval algorithms of the soil liquid water content (θliq) and freeze/thaw state, which, however, have been less explored. This study investigates these microwave characteristics and relationships via analysis of ground-based measurements of brightness temperature (TB) and backscattering coefficients (σ⁰) in combination with simulations performed with the Tor Vergata discrete radiative transfer model. Both an L-band (1.4 GHz) radiometer ELBARA-III and a wide-band (1-10 GHz) scatterometer are installed in a seasonally frozen Tibetan meadow ecosystem to measure diurnal variations of TB and copolarized σ⁰ at both hh (σhh⁰) and vv (σ vv⁰) polarizations. Analysis of measurements collected between December 2017 and March 2018 shows that 1) diurnal cycles are observed in both TB and σ ⁰ due to the change in surface θliq caused by diurnal soil freeze-thaw transitions; 2) a negatively linear relationship is found between e and σ⁰ regardless of frequency, polarization combinations, and observation angles; 3) slopes (β ) of linearly fit equations between eH and σhh⁰ decrease with increasing observation angles of ELBARA-III, while the ones between eV and σvv⁰ increase with increasing observation angles; and 4) correlations between e and σ⁰ increase with decreasing microwave frequency of σ⁰ measurements and ELBARA-III observation angles, and magnitudes of diurnal σ⁰ cycles also increase with decreasing microwave frequency. Moreover, the calibrated Tor Vergata model shows capability to reproduce both diurnal e and σ⁰ variations as well as to quantify their relationships at different frequencies and observation angles.

During the New Space era small countries are becoming important players in the space business. While space activities are rapidly increasing globally, it is important to make operations in a sustainable and safe way in order to preserve satellite services for future generations. Unfortunately, the sustainability aspect has been largely overlooked in the existing surveys on space technologies. As a result, in this survey paper, we discuss the multi-layer networking approaches in the 6G era specifically from the sustainability perspective. Moreover, our comprehensive survey includes aspects of some interesting industrial, proprietary, and standardization views. We review the most important regulations and international guidelines and revisit a three-dimensional architecture vision to support the sustainability target for a variety of application areas. We then classify and discuss space safety paradigms that are important sustainability enablers of future satellite communications. These include space traffic management, debris detection, environmental impacts, spectrum sharing, and cyber security aspects. The paper also discusses advances towards a planned European connectivity constellation that could become a third flagship infrastructure along with the Galileo and Copernicus systems. Finally, we define potential research directions into the 2030s., Accepted for IEEE Access

We discuss a coherent synthetic aperture radar (SAR) formation where N identical sensors transmit at the same time, code, and frequency. This is a particular multiple-input-multiple-output (MIMO) configuration, where the transmitted waveforms interfere together, resulting in an illumination pattern that randomly changes in space and time. Similar to the single-input-multiple-output (SIMO) formations, the diversity provided by the N receiver phase centers can be used to mitigate this interference and reduce the pulse repetition frequency (PRF) for achieving large swath coverage. The good point, in the MIMO case, is that the signal-to-noise ratio (SNR) gain of the system increases, theoretically, with the square of the number of elements. However, residual spurious sidelobes may appear as ghosts of the multiple illuminators. In practice, the power gain is to be optimized, together with ambiguity rejection, sidelobes, and azimuth resolution. The actual performances achievable by these formations in terms of impulse response function (IRF), SNR, and sensitivity to the precise positioning of the sensors are discussed theoretically and based on simulations.

This document details how to use the ASAR sensor parameters of the ENVISAT satellite to focus the raw data from the level 0 files using the Omega--K algorithm. In addition, it serves as an alternative to focus through an Open Source tool with a low computational cost. As a preliminary result, pseudo-images of two regions of Venezuela were processed with the developed algorithm and a qualitative comparison with pseudo-images of level 1 of the same regions provided by the European Space Agency is discussed.

We propose a lightweight radar that autonomously measures snow depth over sea ice from an unmanned aerial vehicle (UAV). Development of this snow radar and its integration with an octocopter UAV is presented. Field trials of the UAV-mounted snow radar, conducted in Antarctica during the summer season of 2017/2018, are also described. The radar allows measurements of snow depths on sea ice between 10 and 100 cm. Additional reflections due to internal layers within the snow are evident at a few measurement points. The snow radar is evaluated for various flight parameters: stationary; flying at speeds between 1 and 3 m/s, and at heights from 5 to 15 m. Evaluation of snow-depth results indicates that a depth accuracy of ±3.2 cm is achieved with stationary measurements, and of ±9.1 cm with measurements at the various flight speeds.

This work presents an overview of the activity developed in the frame of a project funded by the European Space Agency (ESA). The research was focused on the study of the potential applications of GNSS Reflectometry (GNSS- R) over land, with an emphasis on soil moisture (SM) and biomass. A study about the sensitivity with respect to the freeze–thaw dynamics was considered as well. The work started with an analysis of the sensitivity of GNSS-R reflec- tivity collected by the TechDemoSat-1 (TDS-1) experimental satellite, although, to a limited extent, the Cyclone GNSS (CyGNSS) constellation was considered as well. The en - couraging sensitivity outcomes led to the development of retrieval algorithms: three different approaches for SM and one for biomass based on neural networks. A more theoretical investigation was carried out to better understand and predict the signal from a satellite platform which required the updating of two different models. To - pography effects and sensitivity to moisture and roughness of a rough soil were included as well as the effect of vegeta- tion cover. The project was carried out by a large team involving different research groups in Europe. It has led to main con- clusions and recommendations derived from a beneficial collaboration and fertilization of ideas. The primary ap - proaches and outcomes are summarized here, including comparisons to the recent literature. This study has been conducted in the framework of the ESA contract 4000120299/17/NL/AF/hh, “Potential of Spaceborne GNSS-R for Land Applications.” The TDS-1 data have been freely collected from the MERRBYS portal at merrbys.co.uk. The CyGNSS and SMAP data were downloaded from the NASA Earthdata portal at podaac.jpl.nasa.gov and nsidc.org/data/smap, respectively. The SMOS data are made available from the ESA through the smos-diss.eo.esa.int website. This work has also been partially supported by the project of the Ministerio de Ciencia, Innovación y Universidades and EU ERDF ref. RTI2018-099008-B-C21/AEI/10.13089/E01100011083, “Sensing with Pioneering Opportunistic Techniques,” and grant MDM-2016-0600 to the CommSensLab-UPC “María de Maeztu” Excellent Research Unit. We thank the ISMN for the availability of soil moisture data.

International audience; This paper describes first results obtained from the SWIM (Surface Waves Investigation and Monitoring) instrument carried by CFOSAT (China France Oceanography Satellite), which was launched on October 29th, 2018. SWIM is a Ku-Band radar with a near-nadir scanning beam geometry. It was designed to measure the spectral properties of surface ocean waves. First, the good behavior of the instrument is illustrated. It is then shown that the nadir products (significant wave height, normalized radar cross-section and wind speed) exhibit an accuracy similar to standard altimeter missions, thanks to a new retracking algorithm, which compensates a lower sampling rate compared to standard altimetry missions. The off-nadir beam observations are analyzed in details. The normalized radar cross-section varies with incidence and wind speed as expected from previous studies presented in the literature. We illustrate that, in order to retrieve the wave spectra from the radar backscattering fluctuations, it is crucial to apply a speckle correction derived from the observations. Directional spectra of ocean waves and their mean parameters are then compared to wave model data at the global scale and to in situ data from a selection of case studies. The good efficiency of SWIM to provide the spectral properties of ocean waves in the wavelength range [70m-500m] is illustrated. The main limitations are discussed, and the perspectives to improve data quality are presented.

In Winter 2017, the University of Massachusetts Amherst's Imaging Wind and Rain Airborne Profiler (IWRAP) was flown on a National Oceanic and Atmospheric Administration (NOAA) WP-3D Hurricane Hunter aircraft under the direction of scientists from Center for Satellite Applications and Research (STAR) at NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) over the North Atlantic ocean out of Shannon, Ireland. IWRAP is a dual-frequency, conically scanning, profiling Doppler radar initially developed by Microwave Remote Sensing Laboratory (MIRSL) at the University of Massachusetts Amherst that is routinely installed on the NOAA WP-3D research aircraft. The flight on February 6, 2017, targeted a region of high winds (greater than 30 m/s) that was also observed by the Sentinel-1B satellite's synthetic aperture radar. Sentinel-1B was configured to observe in extended wide swath mode in both VV- and VH-polarizations, whereas the IWRAP C-band radar was configured to measure all of VV-, VH-, and HH-polarizations. IWRAP and Sentinel-1B VV and VH normalized radar cross section (NRCS) at the same Earthincidence angle along the flight path match reasonably well during the entire flight, but some additional trends between aircraft and satellite can be observed. IWRAP VV-polarized NRCS generally match the CMOD5.h geophysical model function (GMF), suggesting errors in the Sentinel-1B processing chain.

形態: カラー図版あり, Physical characteristics: Original contains color illustrations, Accepted: 2020-05-16, 資料番号: PA2110047000

Under extreme weather conditions, the imprints of kilometer-scale marine atmospheric boundary layer roll vortices on the ocean surface are clearly visible in synthetic aperture radar (SAR) images of storms. Therefore, information about wind direction in storms can be obtained by analyzing SAR image features caused by boundary layer rolls. VH-polarized SAR imagery captures the structural features of storms well and shows prominent image gradients along the radial directions of the storm. The signal-to-noise ratios of VH-polarized images are small in low wind speed areas, but they are large in the same regions of VV-polarized images. Also, the capability of retrieving the atmospheric rolls orientation in VV-polarization is found to be sensitive to incidence angle, with better performances for larger incidence angles. Thus, there is the potential to retrieve the storm's wind directions using a combination of the VH- and VV-polarized SAR observations. In this article, we use the local gradient method to estimate tropical cyclone (TC) wind directions from C-band RADARSAT-2 and Sentinel-1A dual-polarization (VV & x002B; VH) SAR imagery. As a case study, wind directions with a spatial resolution of 25 km are derived by using both wide-swath VV- and VH-polarized SAR imagery over two hurricanes (Earl and Bertha) and one Typhoon (Meranti). We compare wind directions derived from ten dual-polarization SAR images with collocated wind directions from buoys, Global Positioning System (GPS) dropsondes, scatterometer, and radiometer. Statistical comparisons show that the wind direction bias and root-mean-square error are, respectively, -0.54 & x00B0; and 14.78 & x00B0; for VV-polarization, 0.38 & x00B0; and 14.25 & x00B0; for VH-polarization, 0.20 & x00B0; and 13.30 & x00B0; for VV- and VH-polarization, suggesting dual-polarization SAR is more suitable for the estimation of TC wind directions than VV- or VH-polarization SAR.

Automatic dependent surveillance-broadcast (ADS-B) is an emerging air traffic surveillance technology that overcomes the limitations of today's radar technology and enhances the air traffic control. To provide authenticity, integrity in ADS-B and to improve the computation, communications efficiency, in this paper, we propose a new, efficient, and secure pairing-free ADS-B authentication scheme with Batch Verification in ID-based framework. The proposed scheme is proven secure and is more efficient than the existing schemes.

This paper describes the development of an Airborne Wind Vector Scatterometer for low-resolution wind speed measurements. The scatterometer is designed to meet a wind speed accuracy requirement of 1 m/s. In this ad hoc and low-budget project, the development of the instrument exploited some already existing subsystems. The development started from the definition of the scientific system requirements and ended with two experimental flights for wind vector retrieval from three test areas in the Gulf of Finland, the Baltic Sea. One of the flights was planned for a simultaneous overpass with the TDS-1 satellite that was conducting Global Navigations Satellite System – Reflectometry (GNSS-R) measurements. The results confirm the measurement capabilities of the GNSS-R technology and the desired 1 m/s wind speed accuracy of the scatterometer that was developed.

Accurate absolute radiometric calibration of spaceborne synthetic aperture radar (SAR) sensor is of great importance in quantitative oceanic monitoring. Traditionally, the calibration constant is determined by analyzing measurements of man-made calibrators deployed on land at a high expense. In this paper, a technique called numerical weather prediction (NWP)-based ocean calibration method for estimating the calibration constant on the basis of SAR observations over ocean is applied to the first Chinese C-band SAR satellite Gaofen-3 (GF-3). The ocean calibration is performed on GF-3 wave mode SAR images at VV and HH polarizations over a period of one year from September 2017 to August 2018. Verification against the independent scatterometer-derived winds shows that after NWP-based ocean recalibration, the accuracy of wind speed retrieval from GF-3 wave mode imagery could reach the wind speed estimation performance using the state-of-the-art of SAR data. These results indicate that GF-3 wind retrievals are promising for operational oceanic products and applications if the SAR data are appropriately calibrated by the proposed NWP-based ocean calibration approach.

形態: カラー図版あり, Physical characteristics: Original contains color illustrations, Accepted: 2018-09-11, 資料番号: PA1910022000

The required accuracy performance of a high-precision oceanographic radar altimeter can be achieved by designing a height-tracking system. The optimal discriminator of the tracking system is synthesized in this letter, and the calculation methods for its discriminating characteristics and measurement error performance are investigated. The structure of the optimized tracking system is outlined. Using the obtained results, the dependence of the limiting accuracy of a single delay-time measurement on the signal-to-noise ratio is determined. The limiting accuracy obtained by the discriminator can be specified as the measurement performance of the altimeter system.

Accepted: 2018-11-14, 資料番号: SA1180363000

In this paper, we consider the problem of true transmitter polarization state estimation for circular compact SAR modes. We employ two methods—the first using point targets such as trihedral reflectors, and the second, a new method, based on the Pauli phase observed over distributed targets like forest canopy. We first show how compact modes allow estimation of the Pauli phase for reflection symmetric scatterers. We show that this phase remains remarkably constant over forest canopies, depending primarily on the dielectric constant of constituent volume particles. We show that small imperfections in the transmit polarization state then lead to large errors in this phase estimate. These errors can then be used as the basis for a calibration strategy that allows estimation of a set of candidate true transmitter states. These can then be compared with the trihedral estimates for validation. We illustrate using L-band compact data from the JAXA ALOS-2 satellite and C-band data from the ISRO RISAT-1 satellite.

The high penetration of P -band signals (300–600 MHz) into dense vegetation and the higher temporal stability at low frequencies are key advantages for the estimation of forest properties using synthetic aperture radar (SAR). However, existing services at those frequencies make P -band SAR imagers more vulnerable to the radio frequency interference (RFI). In this paper, a method to detect and geolocate the RFI using digital beamforming (DBF) is presented. The method is implemented using NASA's EcoSAR measurements. This P -band multichannel radar uses a sniffing pulse interleaved during the DBF SAR operation to sense the RFI. RFI detection is implemented with time-bandpass filters while DBF is used to estimate the angle-of-arrival and geolocate the interference. The method is demonstrated for an interferer how EcoSAR could be used to assess the RFI threats to spaceborne missions.

Internationally recognized prognostic models of rain fade on terrestrial and Earth-space extremely high frequency (EHF) links rely fundamentally on distributions of 1-min rain rates. In Rec. ITU-R P.837-6, these distributions are estimated from the data provided by Numerical Weather Products (NWPs). NWP yields rain accumulations over regions typically larger than 100 km across and over intervals of 6 h. Over the tropics, the Tropical Rain Measuring Mission (TRMM) satellite data yield instantaneous rain rates over regions 5 km across. This paper uses TRMM data to estimate rain rate distributions for telecommunications regulation over the tropics. Rain rate distributions are calculated for each 1° square between 35° south to 35° north. These distributions of instantaneous rain rates over 5 km squares are transformed to distributions over 1 km squares using a correction calculated from U.K. Nimrod radar data. Results are compared to rain distributions in DBSG3, the database of ITU-R Study Group 3. A comparison with the new Rec. ITU-R P.837-7 is also presented. A table of 0.01% exceeded rain rates over the tropics is provided as associated data.

International audience; Surface wind speed estimation from synthetic aperture radar (SAR) data is principally based on empirical (EP) approaches, e.g., CMOD functions. However, it is necessary and significant to compare radar backscattering modeling based on EP and electromagnetic (EM) approaches for enhancing the understanding of the physical processes between radar signal and sea surface, which is important for the design of radar sensors (e.g., cyclone global navigation satellite system). Indeed, through comparisons, it is worth noticing that the scattering of wave breaking is not taken into account in the physical modeling of radar backscattering. Surface wind speed is selected here as a reference parameter for investigating the difference between EP and EM models, due to its important role in radar backscattering modeling. In addition, wind speed estimates can be easily compared to in situ measurements. For EP approach, CMOD5.N and Komarov's model are selected for wind speed estimation from Sentinel-1 images. The CMOD5.N can offer wind speed estimates up to 25-35 m/s, while wind speed estimation based on Komarov's model does not require wind direction input. For EM approach, the asymptotic models, i.e., composite two-scale model, small-slope approximation (SSA), and resonant curvature approximation (RCA), are investigated for wind speed retrieval. They are studied with two models of surface roughness spectrum: semi-EP spectrum and EP model. In general, normalized radar cross section (NRCS) calculated by CMOD5.N and SSA/RCA is quite similar for incidence angles below 40° in vertical polarized and below 30° in horizontal polarized. For larger ones, significant NRCS deviations between two approaches are demonstrated, due to the lack of wave breaking scattering in EM models. As a result, wind speed estimates by CMOD5.N and SSA/RCA are very close for low and moderate incidence angles, while SSA-/RCA-based wind speeds are overestimated for larger ones.

In this paper, a dual-band photonics-based radar system used for precise displacement measures in a multitarget scenario is described. The radar was designed for monitoring applications to prevent both structural failures of buildings and landslides. The radar system exploits the technique of stepped frequency continuous wave signal modulation and the displacement of the targets is evaluated through differential phase measurements. In this work, encouraged by the results already achieved in the single-target scenario, we present an investigation extended to the case of multiple targets. We aim to evaluate the accuracy of the displacement estimation both from a simulated and experimental point of view, and to understand how multiple targets impact on the final estimate of displacements. Simulation results demonstrate that it is possible to achieve a typical accuracy of less than 0.2 mm for distances up to 400 m. These results are confirmed by preliminary experimental outcomes, which take into account different operative conditions with multiple targets. Finally, concluding remarks and perspectives draw the agenda for our future investigations.

By packing big antennas into small satellites, JPL engineers are making space science cheap

The articles in this special section focus on advancements in radar systems for current commercial applications. Radar was developed during World War II for defense and security applications, and it was initially used for detecting aircrafts and missiles, replacing short range and narrow field of- view acoustic devices. This special section is part of a two-part series. The goal of both parts is to show the main techniques applied in different scenarios by different systems, focusing particularly on some of the new civil and commercial applications. There are, however, no articles dedicated specifically to defense, harbor, or airtraffic control nor on long-range remote sensing.

Rainfall estimation based on the impact of rain on electromagnetic waves is a novel methodology that has had notable advancements during the last few years. Many studies conducted on this topic in the past considered only the electromagnetic waves with frequencies greater than 10 GHz since the rainfall impact on the electromagnetic wave attenuation is reduced at lower frequencies. Over the last few years, some authors have demonstrated that there can be a non-negligible attenuation even on the signals received on a global system for mobile communications mobile terminal in presence of rain. In this paper, we propose a new classification method based on a probabilistic neural network to obtain an accurate classification between four rainfall intensities (no rain, weak rain, moderate rain, and heavy rain). The innovative rainfall classification method is based on three received signal level (RSL) local features of the 4G/LTE: the instantaneous RSL, the average RSL value, and its variance calculated by using a sliding window. The proposed method exhibits good performance, obtaining an overall correct classification rate of 96.7%. Almost all papers on this topic present in the literature focus on electromagnetic waves with frequencies greater than 10 GHz, in which the rain impact is more relevant, according to the rain attenuation model. However, only the 4G/LTE signal has such widespread geographic coverage, so the proposed classification method can provide noticeable improvements in the creation of rainfall maps with higher spatial resolution.

High-resolution inputs of rainfall are important in hydrological sciences, especially for urban hydrology. This is mainly because heavy rainfall-induced events such as flash floods can have a tremendous impact on society given their destructive nature and the short time scales in which they develop. With the development of technologies such as radars, satellites and (commercial) microwave links (CMLs), the spatiotemporal resolutions at which rainfall can be retrieved are becoming higher and higher. For the land surface of The Netherlands, we evaluate here four rainfall products, i.e., link-derived rainfall maps, Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) Final Run (IMERG--Global Precipitation Measurement mission), Meteosat Second Generation Cloud Physical Properties (CPP), and Nighttime Infrared Precipitation Estimation (NIPE). All rainfall products are compared against gauge-adjusted radar data, considered as the ground truth given its high quality, resolution, and availability. The evaluation is done for seven months at 30 min and 24,h. Overall, we found that link-derived rainfall maps outperform the satellite products and that IMERG outperforms CPP and NIPE. We also explore the potential of a CML network to validate satellite rainfall products. Usually, satellite derived products are validated against radar or rain gauge networks. If data from CMLs would be available, this would be highly relevant for ground validation in areas with scarce rainfall observations, since link-derived rainfall is truly independent of satellite-derived rainfall. The large worldwide coverage of CMLs potentially offers a more extensive platform for the ground validation of satellite estimates over the land surface of the Earth.

Synthetic Aperture Radar (SAR) is a well established technique for observing the earth on a global scale. As applications become more demanding, it is desirable to overcome the limitations imposed by the SAR principle, one of which is the trade-off between the swath width and the instantaneous azimuth bandwidth, determining the resolution. Recombination of multiple channels with displaced phase centers has been proposed as a convenient way to create high resolution wideswath images. We analyze various approximations made in the channel Transfer functions and their impact on the reconstruction result using examples inspired by current imaging modes of the TerraSARX and TanDEM-X missions. In order to do so, we introduce an efficient method to assess the quality of reconstruction filters for an arbitrary number of channels without the need of full time-domain simulations.

The first results of internal solitary wave (ISW) observations over the ice-free Laptev Sea derived from 354 ENVISAT Advanced Synthetic Aperture Radar (ASAR) images acquired in May–October 2011 are reported. Analysis of the data reveals the key regions of ISW distribution that are primarily found over the outer shelf/slope regions poleward the M2 critical latitude. Most of the ISWs are observed in regions where enhanced tide-induced vertical mixing and heat fluxes have been previously reported. This suggests that spaceborne SAR observations may serve as a tool to infer local mixing hot spots over the ice-free Arctic Ocean.

A new precipitation retrieval algorithm for the AMSR2 is described. The algorithm is based on the cloud dynamics and radiation database (CDRD) Bayesian approach and represents an evolution of the previous version applied to SSMIS observations, and used operationally within the EUMETSAT H-SAF program. This new product presents as main innovation the use of a very large database entirely empirical, derived from coincident radar and radiometer observations from the NASA/JAXA GPM-CO launched on February 28, 2014. The other new aspects are: 1) a new rain-/no-rain screening approach; 2) use of EOF and CCA for dimensionality reduction; 3) use of new ancillary variables to categorize the database and mitigate the problem of non-uniqueness of the retrieval solution; and 4) development and implementations of modules for computation time minimization. A verification study for case studies over Italy and for coincident AMSR2/GPM-CO observations over the MSG full disk area has been carried out. Results show remarkable AMSR2 capabilities for RR retrieval over ocean (for RR > 0.1 mm/h), good capabilities over vegetated land (for RR > 1 mm/h), while for coastal areas the results are less certain. Comparisons with NASA GPM products, and with ground-based radar data, show that the new CDRD for AMSR2 is able to depict very well the areas of high precipitation over all surface types. The algorithm is also able to handle an extremely large observational database available from GPM-CO and to provide rainfall estimate with minimum latency, making it suitable for NRT hydrological and operational applications.

Observations from spaceborne radar contain considerable information about vegetation dynamics. The ability to extract this information could lead to improved soil moisture retrievals and the increased capacity to monitor vegetation phenology and water stress using radar data. The purpose of this review paper is to provide an overview of the current state of knowledge with respect to backscatter from vegetated (agricultural) landscapes and to identify opportunities and challenges in this domain. Much of our understanding of vegetation backscatter from agricultural canopies stems from SAR studies to perform field-scale classification and monitoring. Hence, SAR applications, theory, and applications are considered here too. An overview will be provided of the knowledge generated from ground-based and airborne experimental campaigns that contributed to the development of crop classification, crop monitoring, and soil moisture monitoring applications. A description of the current vegetation modeling approaches will be given. A review of current applications of spaceborne radar will be used to illustrate the current state of the art in terms of data utilization. Finally, emerging applications, opportunities and challenges will be identified and discussed. Improved representation of vegetation phenology and water dynamics will be identified as essential to improve soil moisture retrievals, crop monitoring, and for the development of emerging drought/water stress applications.

In the last few years, there has been tremendous improvement in the calibration of ocean surface vector winds from scatterometers and polarimetric radiometers. This is the first detailed investigation of across-swath consistency in scatterometer-derived (i.e., QSCAT, ASCAT-A, OSCAT, and ASCAT-B) vorticity (curl of the ocean surface vector winds). Spatial derivatives of the winds fields are very important for atmospheric boundary-layer processes, upper ocean forcing, and deep ocean forcing. Improvements in wind calibration imply improvements in derivatives of these winds; however, it does not imply consistency. This study demonstrates near consistency in across-swath vorticity and near consistency between platforms.

In this fifth historical interview, a fascinating conversation with Paul Rosen by Riccardo Lanari, both valued members of the Institute of Electrical and Electronics Engineers (IEEE) Aerospace and Electronic Systems Society (AESS), AESS offers our members insight into the people behind the many great contributions that grace our field. While these interviews document historical events, they are also intended to give readers insights into the events and critical decisions that shaped the research, technical accomplishments, and career of our society's most legendary contributors.

This article examines advances in interferometric synthetic aperture radar (InSAR) satellite measurement technologies to understand their relevance, utilization, and limitations for bridge monitoring. Waterloo Bridge is presented as a case study to explore how InSAR data sets can be combined with traditional measurement techniques including sensors installed on the bridge and automated total stations. A novel approach to InSAR bridge monitoring was adopted by the installation of physical reflectors at key points of structural interest on the bridge, in order to supplement the bridge’s own reflection characteristics and ensure that the InSAR measurements could be directly compared and combined with in situ measurements. The interpretation and integration of InSAR data sets with civil infrastructure data are more than a trivial task, and a discussion of uncertainty of measurement data is presented. Finally, a strategy for combining and interpreting varied data from multiple sources to provide useful insights into each of these methods is presented, outlining the practical applications of this data analysis to support wider monitoring strategies.

11 pages, 6 figures, 2 tables.-- © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works, To address the growing demand for accurate high-resolution ocean wind forcing from the ocean modeling community, we develop a new forcing product, ERA*, by means of a geolocated scatterometer-based correction applied to the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis or ERA-interim (hereafter referred to as ERAi). This method successfully corrects for local wind vector biases present in the ERAi output globally. Several configurations of the ERA* are tested using complementary scatterometer data [advanced scatterometer (ASCAT)-A/B and oceansat-2 scatterometer (OSCAT)] accumulated over different temporal windows, verified against independent scatterometer data [HY-2A scatterometer (HSCAT)], and evaluated through spectral analysis to assess the geophysical consistency of the new stress equivalent wind fields (U10S). Due to the high quality of the scatterometer U10S, ERA* contains some of the physical processes missing or misrepresented in ERAi. Although the method is highly dependent on sampling, it shows potential, notably in the tropics. Short temporal windows are preferred, to avoid oversmoothing of the U10S fields. Thus, corrections based on increased scatterometer sampling (use of multiple scatterometers) are required to capture the detailed forcing errors. When verified against HSCAT, the ERA* configurations based on multiple scatterometers reduce the vector root-mean-square difference about 10% with respect to that of ERAi. ERA* also shows a significant increase in small-scale true wind variability, observed in the U10S spectral slopes. In particular, the ERA* spectral slopes consistently lay between those of HSCAT and ERAi, but closer to HSCAT, suggesting that ERA* effectively adds spatial scales of about 50 km, substantially smaller than those resolved by global numerical weather prediction (NWP) output over the open ocean (about 150 km), The work was supported by the Spanish Research and Development Plan under the FPI grant (BES-2013-064521) from the project MIDAS-7 (reference AYA2012-39356-C05-03) and the R&D project L-BAND (reference ESP2017-89463-C3-2-R), With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)

The Precipitation Radar (PR) on the Tropical Rainfall MeasuringMission satellite has already provided reliable observations for more than 15 years. There is a potential possibility to assess long-term data of ground-based radar (GR) in the China new generation weather radar network through comparison between PR and GR. In this letter, stratiform precipitation above and below bright bands is used to implement reflectivity comparison for PR and the ground-based weather radar in Nanjing from 2003 to 2014. The results show that the accuracy of GR reflectivity is well correlated with the distance from GR, and there are several unusual years in which GR did not work properly. The comparison also indicates that bias of reflectivity between PR and GR is negative above bright bands but positive below bright bands, and the bias has high correlation with GR reflectivity. The proposed scheme provides a practical method for a sanity check of GR data.

The purpose of this study was to improve the accuracy of sea surface wind retrieval from the X-band spaceborne synthetic aperture radar (SAR) TerraSAR-X (TS-X) and TanDEM-X (TD-X) data in horizontal–horizontal (HH) polarization. Geophysical model functions (GMFs), e.g., XMOD1, XMOD2, and SIRX-MOD were developed for X-band SAR data in vertical–vertical (VV) polarization to retrieve sea surface wind fields. To date, the polarization ratio model for X-band SAR (XPR), which is only dependent on incidence angle, has only been available for sea surface wind retrieval from TS-X HH polarization images, in conjunction with an X-band GMF. In our previous study, it was found that the polarization ratio of TS-X dual-polarization data showed a particular relationship with sea surface wind speed. Therefore, in this study, we propose an improved X-band polarization ratio model, herein called XPR2, which is dependent on both incidence angle and sea surface wind speed. The XPR2 was tuned through 56 TS-X/TD-X dual-polarization (HH and VV polarization) images and the collocated European Centre for Medium-Range Weather Forecasts reanalysis wind data. The model was further validated by comparing the retrieved sea surface wind speed from another 38 TS-X HH polarization images against in situ buoy measurements. The comparison shows a root mean square error (RMSE) of 1.79 m/s and a bias of 0.68 m/s, which is better than the results achieved using the existing XPR with an RMSE of 2.31 m/s and a bias of 0.93 m/s.

Recently, the Cassini RADAR has been used as a sounder to probe the depth and constrain the composition of hydrocarbon seas on Saturn's largest moon, Titan. Altimetry waveforms from observations over the seas are generally composed of two main reflections: the first from the surface of the liquid and the second from the seafloor. The time interval between these two peaks is a measure of sea depth, and the attenuation from the propagation through the liquid is a measure of the dielectric properties, which is a sensitive property of liquid composition. Radar measurements are affected by uncertainties that can include saturation effects, possible receiver distortion, and processing artifacts, in addition to thermal noise and speckle. To rigorously treat these problems, we simulate the Ku-band altimetry echo received from Titan's seas using a two-layer model, where the surface is represented by a specular reflection and the seafloor is modeled using a facet-based synthetic surface. The simulation accounts for the thermal noise, speckle, analog-to-digital conversion, and block adaptive quantization and allows for possible receiver saturation. We use a Monte Carlo method to compare simulated and observed waveforms and retrieve the probability distributions of depth, surface/subsurface intensity ratio, and subsurface roughness for the individual double-peaked waveform of Ligeia Mare acquired by the Cassini spacecraft in May 2013. This new analysis provides an update to the Ku-band attenuation and results in a new estimate for its loss tangent and composition. We also demonstrate the ability to retrieve bathymetric information from saturated altimetry echoes acquired over Ontario Lacus in December 2008.

RapidScat, which is a Ku-band scatterometer mounted on the International Space Station, observes the Earth's surface in a non-sun-synchronous orbit allowing for different local time-of-day (LTOD) observations as the orbit progresses. The unique orbit and different LTOD observations provide surface observations that are composited to describe the diurnal variability of Ku-band normalized backscatter $(\sigma^{0})$ measurements over land globally. Previous sun-synchronous scatterometers providing twice-daily surface observations have been used to demonstrate some diurnal changes in $\sigma^{0}$ in several regions globally, but instrument cross-calibration concerns prevent identifying diurnal changes by combining $\sigma^{0}$ observations from multiple sensors. As a result, the full extent of diurnal changes to $\sigma^{0}$ has not been determined until now. In this paper, RapidScat is used to identify diurnal changes to $\sigma^{0}$ globally. Vegetation type is discussed with respect to the diurnal changes in $\sigma^{0}$ regionally. The global diurnal changes to $\sigma^{0}$ are discussed with emphasis on the Amazon, Congo, and Upper Danube river regions. Diurnal cycles are described that could not previously be identified with sun-synchronous instruments. Global means and the magnitude of the diurnal cycle are discussed. With the diurnal changes identified and quantified, RapidScat can be used for future cross-platform calibrations using land targets.

Special experiments using the Precipitation Radar (PR) onboard the Tropical Rainfall Measuring Mission satellite during descent after the orbital maintenance fuel was depleted are reported in this paper. In these special observation experiments, a 90 deg yaw maneuver experiment, a wide swath width experiment, and the dense sampling experiments were carried out. The key operation of these experiments was a large change in the phase shifter settings of the transmitter and receiver, which was not tested before or after the launch. In addition, the 90 deg yaw experiment required the special operation of the satellite, whereas the other two experiments were implemented by changing only the PR operation. During the experiments, the PR was operated, and the expected data were obtained. The preliminary results suggest the possibility of future radar observation from space, and the results of these experiments will be utilized as basic data to improve the algorithm of the dual-frequency PR onboard the Global Precipitation Measurement mission core satellite and the design of future spaceborne PRs., 形態: カラー図版あり, Physical characteristics: Original contains color illustrations, 資料番号: PA1610016000

The work presented in this letter exploits the long synthetic aperture radar (SAR) of a single TerraSAR-X Staring Spotlight (ST) acquisition to derive absolute heights. Here, the slight azimuth defocusing effect due to height mismatch between the true height and the height assumed in SAR focusing is analyzed. The impact is almost negligible for most of acquisition modes. In contrast, spaceborne modes with very long aperture, such as the TerraSAR-X ST acquisition mode, present sensibility that can be used to retrieve absolute heights. The accuracy depends on incidence angle, orbit type, and mainly on signal-to-clutter ratio. Two different results are presented to demonstrate that absolute heights can be retrieved with accuracy of few meters using a single TerraSAR-X ST acquisition.

This paper reports on the absolute 3-D localization of radar corner reflectors and persistent scatterers (PSs) by stereo synthetic aperture radar (SAR) carried out with TerraSAR-X and TanDEM-X. The novel combination of rigorously linearized range-Doppler equations with thorough sensor modeling, consideration of atmospheric delays, geodynamic signals, satellite dynamics, and geometrical calibration allows a direct target localization at the centimeter level. Therefore, there is no need for the application of geocoding since our approach delivers 3-D positions directly in the International Terrestrial Reference Frame (ITRF) 2008. Four radar corner reflectors located at the Wettzell Geodetic Observatory, Metsahovi Geodetic Observatory, and German Antarctic Receiving Station O'Higgins were localized in 3-D with a precision better than 4 cm. By introducing an updated geometrical calibration of TerraSAR-X and TanDEM-X, the absolute accuracy of the same level becomes possible, which was demonstrated by externally validating the reflector positions at Metsahovi and Wettzell against results of terrestrial geodetic surveying. Furthermore, PSs located in Berlin were retrieved with a precision of 10 cm, making the method a suitable tool for radar “positioning” in urban environments. Potential fields of application for our approach are the joint analysis with phase-based methods, geometrical calibration of radar satellites, and direct integration of SAR observations into Global Navigation Satellite System networks.

Two novel approaches for measuring the ionospheric total electron content (TEC) from single-polarized spaceborne SAR data were proposed in the mentioned paper, i.e., the TEC autofocus method and the systematic alternate up/down pulse methodology. The up/down pulse methodology indicates that ionospheric TEC could be estimated using the difference between range-compressed phase distributions of the up and down chirps. However, it can be shown theoretically that the difference between the up and down chirps after compression is not expected. Thus, the estimation of TEC from alternating up versus down chirp combinations might not be feasible.

The Global Precipitation Measurement (GPM) Core Observatory will carry a Dual-frequency Precipitation Radar (DPR) consisting of a Ku-band precipitation radar (KuPR) and a Ka-band precipitation radar (KaPR). In this study, “at-launch” codes of DPR precipitation algorithms, which will be used in GPM ground systems at launch, were evaluated using synthetic data based upon the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data. Results from the codes (Version 4.20131010) of the KuPR-only, KaPR-only, and DPR algorithms were compared with “true values” calculated based upon drop size distributions assumed in the synthetic data and standard results from the TRMM algorithms at an altitude of 2 km over the ocean. The results indicate that the total precipitation amounts during April 2011 from the KuPR and DPR algorithms are similar to the true values, whereas the estimates from the KaPR data are underestimated. Moreover, the DPR estimates yielded smaller precipitation rates for rates less than about 10 mm/h and greater precipitation rates above 10 mm/h. Underestimation of the KaPR estimates was analyzed in terms of measured radar reflectivity (Zm) of the KaPR at an altitude of 2 km. The underestimation of the KaPR data was most pronounced during strong precipitation events of Zm 26 (moderate attenuation cases). The results suggest that the underestimation is caused by a problem in the attenuation correction method, which was verified by the improved codes., Accepted: 2014-04-19, 資料番号: PA1510027000

This study discusses the capability assessment of fully polarimetric L-band spaceborne synthetic aperture radar (SAR) for detection of seasonal snow covered areas. In this paper, ALOS PALSAR time-series data sets obtained in quad-pol modes have been investigated to evaluate the polarimetric signal scattered from a snow-covered mountainous ecosystem in Niigata, Japan. Results show that changes in the scattering mechanism across the various snow states can be identified from polarimetric parameters. In particular, different polarimetric parameters offer complementary information on the snow properties. Based on the characteristic seasonal changes of polarimetric parameters, a new method to map snow-covered areas is proposed in this study using an information fusion approach. Snow extent can be identified successfully by combining polarimetric indices with an overall accuracy of 74.4% as compared with in situ measurements and 77.0% as compared with optical images.

This paper presents results of a spaceborne radar interferometry technique application for land subsidence observations in a coal mining area in Kuzbass, Russia. Joint analysis of radar interferometry measurements with simultaneous seismic observations shows that the land subsidence is triggered by seismic events, both natural and caused by human underground activity. Surface displacements are linked typically to the boundaries of block structures and correlate with the location of clusters of seismic events.

In this paper, a survey of the techniques and data sets used to evaluate earthquake damages using remote sensing data is presented. After a few preliminary definitions about earthquake damage, their evaluation scale, and the difference between identification of damage “extent” and identification of damage “level,” the advantages and limits of different remote sensing data sets are presented. Furthermore, a survey of proposed algorithms for data interpretation and earthquake damage extraction is presented, and two examples of these algorithms and their results are discussed. According to the outcome of this survey, some open issues are finally presented and discussed, identifying possible research lines as well as working solutions.