Salvatore Dinardo

SAR Altimeter Backscattered Waveform Model

The backscatters power single-look waveform recorded by a synthetic aperture radar altimeter is approximated in a closed-form model. The model, being expressed in terms of parameterless functions, allows for efficient computation of the waveform and a clear understanding of how the various sea state and instrument parameters affect the waveform.

Satellite Altimetry: sailing closer to the coast

In this chapter we review the history of coastal altimetry. We illustrate the challenges associated with data processing, improvement and exploitation, including: (1) what altimeter data are available today and what are the issues in coastal zones; (2) what efforts are underway to fill the gaps in coastal altimetry and what still needs to be done; (3) how coastal altimetry can be used in support of coastal oceanography. After nearly two decades of data collection near coasts, the planned reprocessing of the multi-mission global record now appears to be necessary for full exploitation of satellite altimetry for coastal oceanography. We will focus on the European research efforts, in particular the main outcomes of the COASTALT project, by showcasing improved corrections (with special emphasis on the wet tropospheric effect), waveform analysis and novel retracking techniques, as well as the structure of the new processor for Envisat RA-2 coastal records. This is of interest to a broad range of data integrators who will be able to use the improved altimeter data in their operational products or services.

Sentinel-3 STM SAR ocean retracking algorithm and SAMOSA model

The SRAL Radar Altimeter, on board of the ESA Mission Sentinel-3 (S-3), has the capacity to operate either in the Pulse-Limited Mode (also known as LRM) or in the novel Synthetic Aperture Radar (SAR) mode. Thanks to the initial results from SAR Altimetry obtained exploiting CryoSat-2 data, lately the interest by the scientific community in this new technology has significantly increased and consequently the definition of accurate processing methodologies (along with validation strategies) has now assumed a capital importance. In this paper, we present the algorithm proposed to retrieve from S-3 STM SAR return waveforms the standard ocean geophysical parameters (ocean topography, wave height and sigma nought) and the validation results that have been so far achieved exploiting the CryoSat-2 data as well as the simulated data. The inversion method (retracking) to extract from the return waveform the geophysical information is a curve best-fitting scheme based on the bounded Levenberg-Marquardt Least-Squares Estimation Method (LEVMAR-LSE). The S-3 STM SAR Ocean retracking algorithm adopts, as return waveforms model, the “SAMOSA” model [Ray et al, 2014], named after the R&D project SAMOSA (led by Satoc and funded by ESA), in which it has been initially developed. The SAMOSA model is a physically-based model that offers a complete description of a SAR Altimeter return waveform from ocean surface, expressed in the form of maps of reflected power in Delay-Doppler space (also known as stack) or expressed as multilooked echoes. SAMOSA is able to account for an elliptical antenna pattern, mispointing errors in roll and yaw, surface scattering pattern, non-linear ocean wave statistics and spherical Earth surface effects. In spite of its truly comprehensive character, the SAMOSA model comes with a compact analytical formulation expressed in term of Modified Bessel functions. The specifications of the retracking algorithm have been gathered in a technical document (DPM) and delivered as baseline for industrial implementation. For operational needs, thanks to the fine tuning of the fitting library parameters and the usage of look-up table for Bessel functions computation, the CPU execution time was accelerated over 100 times and made the execution in par with real time. In the course of the ESA-funded project CryoSat+ for Ocean (CP4O), new technical evolutions for the algorithm have been proposed (as usage of PTR width look up table and application of a stack masking). One of the main outcomes of the CP4O project was that, with these latest evolutions, the SAMOSA SAR retracking was giving equivalent results to CNES CPP retracking prototype, which was built with a totally different approach, which enforces the validation results. Work actually is underway to align the industrial implementation with the last new evolutions. Further, in order to test the algorithm with a dataset as realistic as possible, a set of simulated Test Data Set (generated by S-3 STM End-to-End Simulator) has been created by CLS following the specifications as described in a test data set requirements document drafted by ESA. In this work, we will show the baseline algorithm details, the evolutions, the impact of the evolutions and the results obtained processing the CryoSat-2 data and the simulated test data set.

An extended analysis of along-track antenna pattern compensation for SAR altimetry

One of the main benefits of the along-track processing in Synthetic Aperture Radar altimetry [1] is the speckle reduction that is achieved by averaging all the observations accumulated for a same scattering area. Being the different observations obtained by looking at the same scattering area from different positions of the instrument along the orbit, they result to be modulated by the along-track antenna pattern. By compensating the along-track antenna pattern before averaging, a higher speckle reduction can be achieved. This paper is aimed at presenting this processing method and at evaluating the possible improvement in the sense of the effective number of looks and of the precision of the physical parameters retrieved from the power waveforms.