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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
20180003464
Acquisition Source
Goddard Space Flight Center
Document Type
Conference Paper
Authors
Mohammed, 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 J. (NASA Goddard Space Flight Center Greenbelt, MD, United States)
Bradley, Damon C. (NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
June 5, 2018
Publication Date
July 23, 2017
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN57064
Report Number: GSFC-E-DAA-TN57064
Meeting Information
Meeting: 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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