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An RFI Detection Algorithm for Microwave Radiometers Using Sparse Component AnalysisRadio Frequency Interference (RFI) is a threat to passive microwave measurements and if undetected, can corrupt science retrievals. The sparse component analysis (SCA) for blind source separation has been investigated to detect RFI in microwave radiometer data. Various techniques using SCA have been simulated to determine detection performance with continuous wave (CW) RFI.
Document ID
20170007313
Acquisition Source
Goddard Space Flight Center
Document Type
Presentation
Authors
Mohammed-Tano, Priscilla N. (Morgan State Univ. Baltimore, MD, United States)
Korde-Patel, Asmita (NASA Goddard Space Flight Center Greenbelt, MD United States)
Gholian, Armen (NASA Goddard Space Flight Center Greenbelt, MD, United States)
Piepmeier, Jeffrey R. (NASA Goddard Space Flight Center Greenbelt, MD United States)
Schoenwald, Adam (NASA Goddard Space Flight Center Greenbelt, MD United States)
Bradley, Damon (NASA Goddard Space Flight Center Greenbelt, MD United States)
Date Acquired
August 3, 2017
Publication Date
July 23, 2017
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN44744
Meeting Information
Meeting: 2017 IEEE International Geoscience and Remote Sensing Symposium
Location: Fort Worth, TX
Country: United States
Start Date: July 23, 2017
End Date: July 28, 2017
Sponsors: Institute of Electrical and Electronics Engineers
Funding Number(s)
CONTRACT_GRANT: NNG11HP16A
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
radiometers
microwaves

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