The Copernicus program, and particularly Sentinel-1, are among the largest Earth Observation SAR data providers, serving an ever-increasing number of services, users, and applications. A key aspect of the program is the constant provision of quality data, which requires long term engagement to carefully monitor, preserve, and even improve the system performances. These tasks are mainly carried out within the SAR Mission Performance Cluster (SAR-MPC), an international consortium of SAR experts in charge of the continuous monitoring of the Sentinel-1 instruments status and of the L1 and L2 products quality. This paper provides an update on the monitoring and the actions implemented by the SAR-MPC during 2022 and 2023. The analysis regards the monitoring of the instrument status, the evaluation of the instrument radiometric and geometric accuracy, and the updates of the S-1 Instrument Processing Facility.

The paper provides the main results of the SAOCOM-1B independent commissioning phase carried out by Aresys in the framework of a collaboration with Argentinian space agency CONAE. The reported results include: azimuth and elevation pointing, IRF assessment, geolocation accuracy and radiometric and polarimetric calibration.

Radio Frequency Interference (RFI) is a well-known issue since the early days of telecommunications. Traditionally considered an occasional event in the Earth Observation domain, RFI is becoming a severe problem due to the surge of wireless LANs and the increasing number of operational EO missions. In the near future, RFI will eventually be treated as an additional source of noise, to be addressed not only for mitigation, but also during mission design. Sentinel-1 (S-1) is a constellation of two spaceborne C-band synthetic aperture radar (SAR) sensors developed and operated by the European Space Agency under the Copernicus programme. In this paper, S-1 thermal noise measurements are used to create an automatic monitoring system generating world RFI maps with a periodicity of 12 days. For tuning the system, the RFI power is calibrated against a radiometer operating at the same range of frequencies. Analysing the strength and geographical distribution of the RFI, the most affected regions are identified and probability maps are extracted.

In the framework of the EU/ESA co-funded Copernicus program [RD-1] (formerly known as Global Monitoring for Environment and Security - GMES). ESA is developing and operating a series of Sentinel missions with the objective to provide routinely Earth Observation data for supporting the implementation of operational Copernicus services and for existing or future national service initiatives.

The paper describes an end-to-end simulator for Geosynchronous SAR data. The tool is composed of two modules: a raw data time domain simulator and a processor for the generation of the L1 products. The simulated raw data include the effects of atmospheric and clutter decorrelation. The end-to-end simulator is a powerful and flexible tool to be used during the system design phase for the verification of the expected performance.

Sentinel-1 (S-1) is a constellation of two C-band SAR satellites [1] whose development is co-funded by the European Space Agency (ESA) and the European Commission (EC) as part of the Copernicus space program. S-1A was launched in May 2014 followed by the S-1B unit two years after. The constellation is operational since September 2016 after the successful commissioning of the second unit. This paper provides an update of the constellation performance and recalls the last result achieved in terms of radiometric and geometric accuracy.

The Sentinel-1 constellation provides high resolution radiometrically calibrated SAR images with 6 days revisit and global coverage. The radiometric calibration was established during the Commissioning Phase exploiting transponders and natural targets. The paper describes the elevation antenna pattern verification based on the S-1 Antenna Model and the necessary refinements performed to achieve the requested radiometric accuracy.

We study the impact of atmospheric turbulence, specifically the wet tropospheric delay, in that synthetic aperture radar (SAR) with very long integration time, from minutes to hours, and wide swaths, such as the geosynchronous or geostationary SAR. In such systems, the atmospheric phase screen (APS) cannot be assumed frozen in time as for Low Earth Orbit or airborne SARs nor constant in space as for the ground-based SAR. The impact of space-time turbulence on SAR focusing is quantitatively assessed, and a novel focusing method that integrates APS estimation and compensation is proposed. Performances are evaluated as a function of SAR parameters, mainly the wavelength, based on a parametric model of the APS variogram, and results achieved by a simulating realistic scenario are shown.

This paper addresses the results of the instrument and product performance verification, radiometric and geometric calibration achieved since the end of the respective Sentinel-1 A and B commissioning phases.

The paper focuses on the decorrelation of natural targets like fields, crops and forests as observed by Radar in time intervals from seconds to months. The models proposed in literature, the exponentials and the Intrinsic Clutter Model, are reviewed and cross-checked by exploiting space-borne SAR data, for C and X band and ground based Radar campaigns in Ku band. Results provides useful information for evaluating performances in applications like Differential Interferometry or focusing over long term, like for geosynchronous SARs.

The paper introduces a couple of techniques for the enhanced processing of TOPSAR data. Both techniques are based on repeated passes of the sensor over the same area. The first technique combines two “de-synchronized” acquisitions, useless for interferometric purposes, to obtain an “enhanced resolution” image of the coherent scatterers in the scene. The second technique exploits the Permanent Scatterers imaged in the overlap between sub-swaths to perform a relative cross-calibration of the TOPSAR beams. Results on real TOPSAR Sentinel-1A data are shown.

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.

The paper provides the description of a flexible frequency domain background clutter simulator for GMTI applications. The clutter module is able to simulate different acquisition geometries, including very high squint cases, and accounts for scene temporal decorrelation. The clutter simulator operates in frequency domain allowing good computational performance. Details on the simulation algorithm and an overview of the simulator results are provided.

This paper presents the results of a RADAR experiment aimed to assess and eventually complement the Internal Clutter Motion model (ICM) provided by Billingsley, for medium and long integration time SAR imaging. Employing a real-aperture rotating antenna ground-based RADAR, rural areas have been observed in different periods of the year according to two different modes, properly designed to obtain short-term and long-term clutter de-correlation analysis. The results showed interesting aspects of the phenomenon. In particular a non-stationary behavior with time, say from minutes to hours, and a day/night characteristic. Furthermore, the experiment showed how, for a long integration time, the model parameters are different from the ones foreseen by Billingsley.

The paper provides a theoretical model for the Geosynchronous SAR focused data, including clutter and atmosphere decorrelation effects. The focused data model is exploited to generate realistic GEOSAR demonstrative products, on the basis of the preliminary design of a regional GEOSAR system. The provided demo products are useful for a preliminary evaluation of the expected system performances.

The Advanced Radar Geosynchronous Observation System is proposed to be a multiple-input-multiple-output synthetic aperture radar (SAR) system hosted on a swarm of minisatellites in quasi-geostationary orbits. The system is made of N iso-frequency sensors, each of them transmitting and receiving the signals. The system would combine the continuous imaging capabilities of a geostationary SAR, gaining a factor N2in signalto-noise ratio (SNR). The real aperture would be achievable in ~40 min, enabling applications so far unseen, such as monitoring fast deformations, landslides, and other applications for emergency and security. Still, the SNR of the long acquisition time would be conserved. The optimal design of the swarm is addressed, in order to trade resolution, coverage, and revisit time.

The paper evaluates the effects of Atmospheric Phase Screen on focused Geosynchronous SAR data. We derive theoretical models for the resolution, the interferometric de-correlation and the induced clutter in presence of an APS, whose joint time and space power spectrum is modeled as an extension of the Kolmogorov power law. Finally we provide some statistics gathered from a GB RADAR experiment.

In this paper, the impact of the internal clutter motion in GEOSAR acquisitions is analyzed. A nearly zero inclination with low eccentricity geosynchronous orbit is considered and, therefore, long integration, in order of 20-30 min (for 1-2 Km resolution) or even hours (for tenths of meters resolution), is required in order to reach the desired synthetic aperture length and the required along-track resolution. Moderate transmitted powers and antenna sizes are considered in the analysis. The power link budget of a long integration GEOSAR acquisition is presented and the limitations imposed by the clutter decorrelation are studied. The minimum target RCS to assure the correct performance of the system under clutter interference scenarios is evaluated. Finally, experimental data from Ground Based SAR X-band acquisitions will be used to validate the Billingsley model in long integration acquisitions.

We propose an efficient method for the azimuth compression and Atmospheric Phase Screen estimation of Geosynchronous SAR data. The method is based on the iterative processing of sub-apertures of increasing size, allowing to gradually refine the quality of the focused data and of the estimated APS. The whole processing can be easily parallelized. Results over simulated data are shown.

In this work, a numerical method optimizer for SAR polarimetric calibration is proposed. The method makes use of the information provided by a Distributed Target and a Corner Reflector in order to jointly estimate the system polarimetric distortion parameters and the Faraday Rotation. The different order of magnitude of cross-talks and Faraday Rotation is exploited to overcome the intrinsic ambiguity related to the problem. Tests have been conducted both on simulated data, confirming the ability of the proposed method to provide realistic estimation of the distortion parameters, even in case of low quality Corner Reflector.

A refinement technique of the antenna model considered to compute Synthetic Aperture Radar (SAR) data pattern is proposed in this work. The accurate knowledge of the antenna patterns of a SAR sensor is of main importance for precise SAR image processing. This requirement, coupled with tight needs for a short duration of the calibration process, have made necessary the investigation of innovative methods to calibrate complex SAR systems. When considering active arrays, the antenna patterns computed from homogeneous SAR data is often in disagreement with those obtained from a mathematical model (the antenna model). In this paper a correction factor is introduced within the antenna model, in order to overcome this discrepancy. This parameter is expressed as a corrected version of the matrix indicating the working status of the antenna. It is estimated through inversion by exploiting the patten information of SAR data, and it can be used for effective antenna model calibration. The effectiveness of the proposed method is assessed by considering ENVISAT ASAR rain forest-images.

In this paper a method for calculating the antenna contribution to the Doppler Centroid is presented. The Antenna Doppler Contribution (ADC) is originated by the non idealities affecting the TR modules of the active antenna arrays. It is an undesired effect for SAR applications requiring stringent performances on the Doppler Centroid control capability. The first part of this paper introduces the problem and shows how it is possible to predict the ADC by exploiting a suitable Antenna Model. The second part of the paper presents a comparison between the ADC calculated with an Antenna Model and the ADC retrieved from real ASAR data.