172 research outputs found
Identification of C-band radio frequency interferences from Sentinel-1 data
We propose the use of Sentinel-1 Synthetic Aperture Radar (SAR) to provide a continuous and global monitoring of Radio Frequency Interferences (RFI) in C-band. We take advantage of the first 8-10 echo measures at the beginning of each burst, a 50-70 MHz wide bandwidth and a ground beam coverage of ~25 km (azimuth) by 70 km (range). Such observations can be repeated with a frequency better than three days, by considering two satellites and both ascending and descending passes. These measures can be used to qualify the same Sentinel-1 (S1) dataset as well as to monitor the availability and the use of radio frequency spectrum for present and future spaceborne imagers and for policy makers. In the paper we investigate the feasibility and the limits of this approach, and we provide a first Radio Frequency Interference (RFI) map with continental coverage over Europe
Pre-Flight SAOCOM-1A SAR Performance Assessment by Outdoor Campaign
In the present paper, we describe the design, execution, and the results of an outdoor experimental campaign involving the Engineering Model of the first of the two Argentinean L-band Synthetic Aperture Radars (SARs) of the Satelite Argentino de Observacion con Microondas (SAOCOM) mission, SAOCOM-1A. The experiment's main objectives were to test the end-to-end SAR operation and to assess the instrument amplitude and phase stability as well as the far-field antenna pattern, through the illumination of a moving target placed several kilometers away from the SAR. The campaign was carried out in Bariloche, Argentina, during June 2016. The experiment was successful, demonstrating an end-to-end readiness of the SAOCOM-SAR functionality in realistic conditions. The results showed an excellent SAR signal quality in terms of amplitude and phase stability
Impact of scene decorrelation on geosynchronous SAR data focusing
We discuss the effects of the clutter on geosynchronous SAR systems exploiting long integration times (from minutes to hours) to counteract for two-way propagation losses and increase azimuth resolution. Only stable targets will be correctly focused whereas unstable targets will spread their energy along azimuth direction. We derive here a generic model for the spreading of the clutter energy based on the power spectral density of the clutter itself. We then assume the Billingsley Intrinsic Clutter Motion model, representing the clutter power spectrum as an exponential decay, and derive the expected GEOSAR signal-to-clutter ratio. We also provide some results from a Ground Based RADAR experiment aimed at assessing the long-term clutter statistics for different scenarios to complement the Internal Clutter Motion model, mainly derived for windblown trees. Finally, we discuss the expected performances of two GEOSAR systems with different acquisition geometries.Peer ReviewedPostprint (published version
Performance and requirements of GEO SAR systems in the presence of Radio Frequency Interferences
Geosynchronous Synthetic Aperture Radar (GEO SAR) is a possible next generation SAR system, which has the excellent performance of less than one-day revisit and hundreds of kilometres coverage. However, Radio Frequency Interference (RFI) is a serious problem, because the specified primary allocation frequencies are shared by the increasing number of microwave devices. More seriously, as the high orbit of GEO SAR makes the system have a very large imaging swath, the RFI signals all over the illuminated continent will interfere and deteriorate the GEO SAR signal. Aimed at the RFI impact in GEO SAR case, this paper focuses on the performance evaluation and the system design requirement of GEO SAR in the presence of RFI impact. Under the RFI impact, Signal-to-Interference-plus-Noise Ratio (SINR) and the required power are theoretically deduced both for the ground RFI and the bistatic scattering RFI cases. Based on the theoretical analysis, performance evaluations of the GEO SAR design examples in the presence of RFI are conducted. The results show that higher RFI intensity and lower working frequency will make the GEO SAR have a higher power requirement for compensating the RFI impact. Moreover, specular RFI bistatic scattering will give rise to the extremely serious impact on GEO SAR, which needs incredible power requirements for compensations. At last, real RFI signal behaviours and statistical analyses based on the SMOS satellite, Beidou-2 navigation satellite and Sentinel-1 A data have been given in the appendix
Geosynchronous SAR for Terrain & atmosphere with short revisit (GeoSTARe)
Geo STA Re would be a mission combining the continuous view capabilities from geostationary orbits of super-continental areas with the all-day, all-weather imaging capabilities of Synthetic Aperture Radar. It would complement Copernicus Sentinel-1 bringing the repeat time from days down to hours. In that, it would provide novel and unique observations. The well proven potentials of Radar in sensing roughness, deformations, and moisture, combined with the short time to get any image, from minutes to an hour, and the immediate data download and exploitation (thanks to the geostationary orbit) makes GeoSTARe a game changer in those fields where hourly-to-daily monitoring is a must
Cooperative Coherent Multistatic Imaging and Phase Synchronization in Networked Sensing
Coherent multistatic radio imaging represents a pivotal opportunity for
forthcoming wireless networks, which involves distributed nodes cooperating to
achieve accurate sensing resolution and robustness. This paper delves into
cooperative coherent imaging for vehicular radar networks. Herein, multiple
radar-equipped vehicles cooperate to improve collective sensing capabilities
and address the fundamental issue of distinguishing weak targets in close
proximity to strong ones, a critical challenge for vulnerable road users
protection. We prove the significant benefits of cooperative coherent imaging
in the considered automotive scenario in terms of both probability of correct
detection, evaluated considering several system parameters, as well as
resolution capabilities, showcased by a dedicated experimental campaign wherein
the collaboration between two vehicles enables the detection of the legs of a
pedestrian close to a parked car. Moreover, as \textit{coherent} processing of
several sensors' data requires very tight accuracy on clock synchronization and
sensor's positioning -- referred to as \textit{phase synchronization} -- (such
that to predict sensor-target distances up to a fraction of the carrier
wavelength), we present a general three-step cooperative multistatic phase
synchronization procedure, detailing the required information exchange among
vehicles in the specific automotive radar context and assessing its feasibility
and performance by hybrid Cram\'er-Rao bound.Comment: 13 page
Motion Estimation and Compensation in Automotive MIMO SAR
With the advent of self-driving vehicles, autonomous driving systems will
have to rely on a vast number of heterogeneous sensors to perform dynamic
perception of the surrounding environment. Synthetic Aperture Radar (SAR)
systems increase the resolution of conventional mass-market radars by
exploiting the vehicle's ego-motion, requiring a very accurate knowledge of the
trajectory, usually not compatible with automotive-grade navigation systems. In
this regard, this paper deals with the analysis, estimation and compensation of
trajectory estimation errors in automotive SAR systems, proposing a complete
residual motion estimation and compensation workflow. We start by defining the
geometry of the acquisition and the basic processing steps of Multiple-Input
Multiple-Output (MIMO) SAR systems. Then, we analytically derive the effects of
typical motion errors in automotive SAR imaging. Based on the derived models,
the procedure is detailed, outlining the guidelines for its practical
implementation. We show the effectiveness of the proposed technique by means of
experimental data gathered by a 77 GHz radar mounted in a forward looking
configuration.Comment: 14 page
G-CLASS: geosynchronous radar for water cycle science - orbit selection and system design
The mission geosynchronous – continental land atmosphere sensing system (G-CLASS) is designed to study the diurnal water cycle, using geosynchronous radar. Although the water cycle is vital to human society, processes on timescales less than a day are very poorly observed from space. G-CLASS, using C-band geosynchronous radar, could transform this. Its science objectives address intense storms and high resolution weather prediction, and significant diurnal processes such as snow melt and soil moisture change, with societal impacts including agriculture, water resource management, flooding, and landslides. Secondary objectives relate to ground motion observations for earthquake, volcano, and subsidence monitoring. The orbit chosen for G-CLASS is designed to avoid the geosynchronous protected region and enables integration times of minutes to an hour to achieve resolutions down to ∼20 m. Geosynchronous orbit (GEO) enables high temporal resolution imaging (up to several images per hour), rapid response, and very flexible imaging modes which can provide much improved coverage at low latitudes. The G-CLASS system design is based on a standard small geosynchronous satellite and meets the requirements of ESA's Earth Explorer 10 call
Meteorological OSSEs for new zenith total delay observations: impact assessment for the hydroterra geosynchronous satellite on the October 2019 Genoa event
Along the Mediterranean coastlines, intense and localized rainfall events are responsible for numerous casualties and several million euros of damage every year. Numerical forecasts of such events are rarely skillful, because they lack information in their initial and boundary conditions at the relevant spatio-temporal scales, namely O(km) and O(h). In this context, the tropospheric delay observations (strongly related to the vertically integrated water vapor content) of the future geosynchronous Hydroterra satellite could provide valuable information at a high spatio-temporal resolution. In this work, Observing System Simulation Experiments (OSSEs) are performed to assess the impact of assimilating this new observation in a cloud-resolving meteorological model, at different grid spacing and temporal frequencies, and with respect to other existent observations. It is found that assimilating the Hydroterra observations at 2.5 km spacing every 3 or 6 h has the largest positive impact on the forecast of the event under study. In particular, a better spatial localization and extent of the heavy rainfall area is achieved and a realistic surface wind structure, which is a crucial element in the forecast of such heavy rainfall events, is modele
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