| Abstract: |
ESA Soil Moisture Ocean Salinity (SMOS) has shown the excellent instrument performance by providing the global maps of soil moisture and ocean salinity [1, 2]. In SMOS observation, Radio Frequency Interferences (RFI) are still observed as decreasing the overall performance. RFI has one of the barriers for synthetic aperture interferometric radiometer to overcome.
Thanks to the effort to report and turn off the RFI sources, many of them are removed. However, RFI sources are time-varying, and new RFI sources appear and disappear, which means they must be constantly monitored. Moreover, the RFI mitigation technique is required to improve the SAIR performance.
Synthetic Aperture Interferometric Radiometers (SAIR) such as SMOS have more serious contamination problem from RFI. Specifically, one strong RFI source easily contaminates a whole area of the snapshot. Therefore, a powerful mitigation method should be devised for SAIR.
Recently the sub-space method for SAIR imaging has been proposed, which deals RFI sources as strong signal measured from array system [3-5]. Based on the subspace of the covariance (visibility) matrix, the DOA the RFI sources can be estimated. The spatial filtering on the subspace is also applied for RFI filtering/mitigation of SAIR as well. The strong RFI sources have the large eigenvalues in the eigenvalue decomposition of the covariance matrix. Therefore, by filtering out (or suppressing) these large eigenvalues, the RFI mitigated covariance matrix is obtained, which finally generate the RFI mitigated brightness temperature.
In this work, the spatial filtering in covariance matrix used in the radio astronomy [6] is modified for the appropriate form to the Earth observation case like SMOS. Because of differences between two observation condition, the way in [6] cannot be directly used. The modified spatial filtering is tested by using several cases of SMOS RFI, e.g., single strong RFI, several RFI case, etc. Additionally, the mitigation of sun glint is also studied.
[1] J. Font, A. Camps, A. Borges, M. Martin-Neira, J. Boutin, N. Reul, Y. H. Kerr, A. Hahne, and S. Mecklenburg, “SMOS: The Challenging Sea Surface Salinity Measurement From Space,” Proc. IEEE, vol. 98, no. 5, pp. 649–665, 2010.
[2] SMOS-BEC, CP34-BEC, SMOS-BEC data distribution and visualization services. [Online]. Available: http://cp34-bec.cmima.csic.es
[3] H. Park, V. Gonzalez-Gambau, and A. Camps, “High Angular Resolution RFI Localization in Synthetic Aperture Interferometric Radiometers Using Direction-of-Arrival Estimation,” IEEE Geosci. Remote Sens. Lett., vol. 12, no. 1, pp. 102–106, 2015.
[4] H. Park, V. Gonzalez-Gambau, A. Camps, and M. Vall-llossera, “Improved MUSIC-Based SMOS RFI Source Detection and Geolocation Algorithm,” IEEE Trans. Geosci. Remote Sens., pp. 1–12, 2015.
[5] H. Park, V. Gonzalez-Gambau, A. Camps, and M. Vall-llossera, “Feasibility of RFI Mitigation in Synthetic Aperture Radiometry Based On Subspace Spatial Filtering,” IGARSS 2017, 2017, Jul, Fortworth. USA.
[6] A.-J. Boonstra, A.-J. van der Veen, and J. Raza, “Spatial filtering of continuous interference in radio astronomy,” in IEEE International Conference on Acoustics Speech and Signal Processing, 2002, p. III-2933-III-2936.
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