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.

The paper addresses the temporal stability of distributed targets, particularly referring to vegetation, to evaluate the degradation affecting synthetic aperture radar (SAR) imaging and repeat-pass interferometry, and provide efficient SAR simulation schemes for generating big dataset from wide areas. The models that are mostly adopted in literature are critically reviewed, and aim to study decorrelation in a range of time (from hours to days), of interest for long-term SAR, such as ground-based or geosynchronous, or repeat-pass SAR interferometry. It is shown that none of them explicitly account for a decorrelation occurring in the short-term. An explanation is provided, and a novel temporal decorrelation model is proposed to account for that fast decorrelation. A formal method is developed to evaluate the performance of SAR focusing, and interferometry on a homogenous, stationary scene, in terms of Signal-to-Clutter Ratio (SCR), and interferometric coherence. Finally, an efficient implementation of an SAR simulator capable of handling the realistic case of heterogeneous decorrelation over a wide area is discussed. Examples are given by assuming two geostationary SAR missions in C and X band.

The paper analyses an along-track multistatic Synthetic Aperture Radar (SAR) formation. The formation aims at achieving a high azimuth resolution maintaining at the same time a large swath width. The case with one transmitting sensor and all receiving is analyzed (Single Input Multiple Output, SIMO). An effective and novel reconstruction, in the two-dimensional frequency domain is introduced that is able to keep low the azimuth ambiguity and achieve a recombination gain close to the theoretical one. Degradation of the system performance due to the loss of the control of formation position is analyzed using probabilistic considerations. Moreover, some innovative methods to mitigate the loss of optimality are introduced and evaluated using simulations. Finally, considerations on the impact of the across-track non zero baseline are discussed.

BIOMASS is ESA’s seventh Earth Explorer mission, scheduled for launch in 2022. The satellite will be the first P-band SAR sensor in space and will be operated in fully polarimetric interferometric and tomographic modes. The mission aim is to map forest above-ground biomass (AGB), forest height (FH) and severe forest disturbance (FD) globally with a particular focus on tropical forests. This paper presents the algorithms developed to estimate these biophysical parameters from the BIOMASS level 1 SAR measurements and their implementation in the BIOMASS level 2 prototype processor with a focus on the AGB product. The AGB product retrieval uses a physically-based inversion model, using ground-canceled level 1 data as input. The FH product retrieval applies a classical PolInSAR inversion, based on the Random Volume over Ground Model (RVOG). The FD product will provide an indication of where significant changes occurred within the forest, based on the statistical properties of SAR data. We test the AGB retrieval using modified airborne P-Band data from the AfriSAR and TropiSAR campaigns together with reference data from LiDAR-based AGB maps and plot-based ground measurements. For AGB estimation based on data from a single heading, comparison with reference data yields relative Root Mean Square Difference (RMSD) values mostly between 20% and 30%. Combining different headings in the estimation process significantly improves the AGB retrieval to slightly less than 20%. The experimental results indicate that the implemented retrieval scheme provides robust results that are within mission requirements.

Fully-focusing of radar altimeters is a recent concept that has been introduced to allow further improvement of along-track resolution in high pulse repetition frequency (PRF) radar altimeters. The straight potentiality of this new perspective reflects into a more accurate estimation of geophysical parameters in some applications such as sea-ice observation. However, as documented in a recent paper, such capability leaves unsolved the problem of the high computational effort required. In this paper, we face the problem of adapting for altimeters the Omega-Kappa SAR focusing algorithm that is performed in the two-dimensional wavenumber domain, accounting for the difference existing between SAR and altimeter from geometry (looking and swath width) and instrument (echoes are deramped onboard on receiving) point of view. Simulations and an application using in-orbit data show the effectiveness of the proposed approach and the highly reduced computational effort.

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.