The European Space Agency's (ESA) BIOMASS mission is a pioneering Earth observation satellite mission launched on April 29, 2025. Utilizing a P-band synthetic aperture radar (SAR), the objective of BIOMASS is to deliver estimates of above-ground forest biomass, forest height (FH), and forest disturbance (FD), with unprecedented accuracy. The mission's primary scientific goal is to quantify the distribution and changes in forest biomass, thereby reducing uncertainties in carbon flux estimates and informing climate models. The satellite's advanced instrumentation and innovative approach allow it to penetrate dense forest canopies, capturing data even in challenging environments. The mission will operate in two distinct phases: the tomographic phase and the interferometric phase, which will support polarimetric interferometric SAR (Pol-InSAR) and tomographic SAR (TomoSAR) processing. Additionally, BIOMASS will provide valuable observational data for ice sheets, deserts, the ionosphere, below canopy topography, and other domains.

The Biomass mission is the 7th Earth Explorer Mission within the frame of the ESA Earth Observation Programme. The primary objective of Biomass is to determine the worldwide distribution of forest above-ground biomass in order to reduce the major uncertainties in calculations of carbon stocks and fluxes associated with the terrestrial biosphere. To meet these objectives Biomass will carry, for the first time in space, a fully polarimetric P-band synthetic aperture radar (SAR) supporting also interferometric acquisitions. This paper provides an overview of the Biomass system design and development status.

The paper tackles the problem of the RFI coming from active LEO systems and affecting a nearly-geostationary SAR system (GEOSAR). The GEOSAR considered operates in the X-Band with a low-inclined (zero), low-eccentric orbit, while the interfering systems are the presently operating X-Band LEOSARs. After the definition of the model, based on the link budget equation, it is described the processing exploited to derive the RFI power estimation for the present day scenario and the related performance of the considered system. Finally it is introduced a statistical model aimed to the prediction of the RFI power for a generic (future) scenario.

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.

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.

The paper analyzes the problem of achieving a coherent operation in Geostationary SAR (GEOSAR) missions intended for continuous monitoring of land surfaces. In contrast to LEOSAR missions, GEOSAR uses very long SAR integration times (from minutes to hours). Accordingly phase errors due to orbit perturbations, radar master oscillator drift, atmosphere propagation and other sources must be conveniently compensated during SAR processing to avoid image defocusing. A network of Active Radar Calibrators (ARC) distributed on the observed scene is proposed, providing echo envelope and phase observations before Synthetic Aperture Processing. In this way the radar antenna phase center trajectory and other phase error sources can be continuously tracked and compensated using a pyramidal sub-aperture processing approach.

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.

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.

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.

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.