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Statistical Approach to Spectrogram Analysis for Radio-Frequency Interference Detection and Mitigation in an L-Band Microwave Radiometer
- Source :
- Sensors, Vol 19, Iss 2, p 306 (2019), Sensors, Volume 19, Issue 2, Sensors (Basel, Switzerland)
- Publication Year :
- 2019
- Publisher :
- MDPI AG, 2019.
-
Abstract
- For the elimination of radio-frequency interference (RFI) in a passive microwave radiometer, the threshold level is generally calculated from the mean value and standard deviation. However, a serious problem that can arise is an error in the retrieved brightness temperature from a higher threshold level owing to the presence of RFI. In this paper, we propose a method to detect and mitigate RFI contamination using the threshold level from statistical criteria based on a spectrogram technique. Mean and skewness spectrograms are created from a brightness temperature spectrogram by shifting the 2-D window to discriminate the form of the symmetric distribution as a natural thermal emission signal. From the remaining bins of the mean spectrogram eliminated by RFI-flagged bins in the skewness spectrogram for data captured at 0.1-s intervals, two distribution sides are identically created from the left side of the distribution by changing the standard position of the distribution. Simultaneously, kurtosis calculations from these bins for each symmetric distribution are repeatedly performed to determine the retrieved brightness temperature corresponding to the closest kurtosis value of three. The performance is evaluated using experimental data, and the maximum error and root-mean-square error (RMSE) in the retrieved brightness temperature are served to be less than approximately 3 K and 1.7 K, respectively, from a window with a size of 100 &times<br />100 time&ndash<br />frequency bins according to the RFI levels and cases.
- Subjects :
- Mean squared error
skewness
0211 other engineering and technologies
02 engineering and technology
Astrophysics::Cosmology and Extragalactic Astrophysics
lcsh:Chemical technology
Biochemistry
Symmetric probability distribution
Article
Standard deviation
Analytical Chemistry
microwave radiometer
spectrogram
0202 electrical engineering, electronic engineering, information engineering
lcsh:TP1-1185
Electrical and Electronic Engineering
Instrumentation
021101 geological & geomatics engineering
Mathematics
Remote sensing
Radiometer
kurtosis
radio-frequency interference (RFI)
Microwave radiometer
020206 networking & telecommunications
Atomic and Molecular Physics, and Optics
Skewness
Brightness temperature
electrical_electronic_engineering
Kurtosis
Spectrogram
Subjects
Details
- Language :
- English
- ISSN :
- 14248220
- Volume :
- 19
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Sensors
- Accession number :
- edsair.doi.dedup.....ead9c5abc27b3815504e64f494ffd146