Title :
Identification of Ocean-Reflected Radio-Frequency Interference Using WindSat Retrieval Chi-Square Probability
Author :
Adams, Ian S. ; Bettenhausen, Michael H. ; Gaiser, Peter W. ; Johnston, William
Author_Institution :
Remote Sensing Div., Naval Res. Lab., Washington, DC, USA
fDate :
4/1/2010 12:00:00 AM
Abstract :
Ocean retrievals using passive microwave radiometers are sensitive to small fluctuations in ocean brightness temperatures. As such, the signals emanating from geostationary satellites that reflect off the ocean surface can result in large errors in ocean retrievals. Since geostationary communication satellites maintain fixed positions above the Earth and constantly transmit to predetermined regions while most other error sources, e.g., precipitation, are transient, time-averaged retrieval error statistics can be used to identify regions of measurements contaminated with radio-frequency interference (RFI). This letter describes a new method of identifying regions of ocean where ocean retrievals are affected by geostationary communication (television) satellites by using geophysical retrieval chi-square probability (goodness-of-fit) estimates. A three-month time-averaged collection of retrieval chi-square estimates is used to identify regions of the ocean where RFI may be present. This information is combined with information on geostationary satellite bandwidths, locations, and antenna contours to identify the source of the RFI. A mask derived from the analysis is used, in conjunction with satellite geometry calculations, to flag individual channels for RFI. These channels can then be ignored in the geophysical retrieval processing in order to produce uncontaminated ocean retrievals.
Keywords :
ocean temperature; oceanographic techniques; radiometry; remote sensing; sea level; WindSat retrieval chi-square probability; geophysical retrieval processing; geostationary communication satellite; geostationary satellite bandwidths; microwave remote sensing; ocean brightness temperature; ocean retrievals; ocean surface; ocean-reflected radio-frequency interference; passive microwave radiometers; satellite geometry calculations; time-averaged retrieval error statistics; Microwave remote sensing; WindSat; radio-frequency interference (RFI);
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2009.2037446