A New Direct Sun Correction Algorithm for the Soil Moisture and Ocean Salinity Space Mission

The interferometric measurements provided by the Soil Moisture and Ocean Salinity (SMOS) satellite are contaminated by solar radiations due to a quasi-permanent presence of the Sun in the field of view of the instrument. A correction algorithm is developed and implemented in the SMOS image reconstruction processor to remove the contribution of these radiations. Since the Sun is seen under an angle much smaller than the angular resolution of SMOS, this algorithm assimilates the Sun disc to a single source located at its center. However, strong residuals persist in the retrieved images mainly due to the presence of different distributed smaller sources of brightness in the Sun disc. Thus, the performance of the algorithm degrades rapidly as soon as the dominant source is far from the center of the disc. This behavior shows the limitation of the algorithm and its strong dependencies to the position of the Sun. In this article, we propose two other algorithms to account for the solar radiations. The first one is an iterative optimization algorithm based on estimating the position of the dominant source of brightness inside the Sun disc. The second algorithm is based on estimating the contribution of the different sources of brightness within the Sun disc using an oversampled grid by solving a constrained least square optimization problem with an explicit solution.