Improved Image Reconstruction Algorithms for Aperture Synthesis Radiometers

• Published in: IEEE transactions on geoscience and remote sensing Vol. 46; no. 1; pp. 146 - 158
• Main Authors: Camps, A., Vall-llossera, M., Corbella, I., Duffo, N., Torres, F.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.01.2008; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Aperture synthesis radiometers; Apertures; Applied geophysics; Bias; Brightness temperature; Decomposition; Earth sciences; Earth, ocean, space; errors; Exact sciences and technology; Image contrast; Image reconstruction; Internal geophysics; Layout; Marine; Microwave theory and techniques; Oceans; Payloads; Radiometers; Salinity; SMOS mission; soil moisture and ocean salinity (SMOS); Space missions; Studies; Synthesis; soil moisture and ocean salinity (SMOS); image reconstruction; Aperture synthesis radiometers; errors; bias; microwaves; satellites; synthesis; algorithms; salinity; shorelines; maps; soil moisture; high frequency; Space remote sensing; accuracy; decomposition; quality; instruments; brightness temperature; Synthetic aperture radar
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2007.907603

The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission aims at producing global and frequent maps of SMOS and will be launched in 2008. SMOS' single payload is a new type of radiometer called Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) operating at L-band in which brightness temperature images are formed by a Fourier synthesis technique. However, in the alias-free field of view where the brightness temperature images are reconstructed, a bias is present which has been found to be higher for high-contrast brightness temperature scenes (coastlines) and lower for homogeneous scenes (all oceans or lands). This scene-dependent bias will ultimately limit the achievable accuracy of the retrieved geophysical parameters, and it is particularly critical for the retrieval of sea surface salinity. This paper presents a general analysis of the origin of this bias, which is found to be actually due to the different measurement errors in the instrument observables (visibility samples). An improvement of the image reconstruction algorithm is then presented to mitigate it. As compared with the previous algorithm versions, the proposed improved reconstruction algorithm further decomposes the visibility samples into some new terms: ocean and land/iced sea, instead of just the Earth's disk over the sky background. This decomposition aims at further reducing the contrast (high-frequency components) in the differential image and, therefore, minimizes the impact of multiplicative errors, improving the radiometric accuracy. In addition, this approach proves to perform the image reconstruction in part of the alias regions and improves the quality of the reconstruction close to the coastlines.