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A Demonstration of the Effects of Digitization on the Calculation of Kurtosis for the Detection of RFI in Microwave Radiometry

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2 Author(s)
Roger D. De Roo ; Dept. of Atmos., Univ. of Michigan, Ann Arbor, MI ; Sidharth Misra

Microwave radiometers detecting geophysical parameters are very susceptible to radio-frequency interference (RFI) from anthropogenic sources. RFI is always additive to a brightness observation, and so the presence of RFI can bias geophysical parameter retrieval. As microwave radiometers typically have the most sensitive receivers operating in their band, low-level RFI is both significant and difficult to identify. The kurtosis statistic can be a powerful means of identifying some types of low-level RFI, as thermal noise has a distinct kurtosis value of three, whereas thermal noise contaminated even with low-level nonthermal RFI often has other values of kurtosis. This paper derives some benign distortions of the kurtosis statistic due to digitization effects and demonstrates these effects with a laboratory experiment in which a known amount of low-level RFI is injected into a digital microwave radiometer.

Published in:

IEEE Transactions on Geoscience and Remote Sensing  (Volume:46 ,  Issue: 10 )