Detection and Analysis of C-Band Radio Frequency Interference in AMSR2 Data over Land
A simplified generalized radio frequency interference (RFI) detection method and principal component analysis (PCA) method are utilized to detect and attribute the sources of C-band RFI in AMSR2 L1 brightness temperature data over land during 1−16 July 2017. The results show that the consi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/11/10/1228 |
| _version_ | 1819004465539186688 |
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| author | Ying Wu Bo Qian Yansong Bao Meixin Li George P. Petropoulos Xulin Liu Lin Li |
| author_facet | Ying Wu Bo Qian Yansong Bao Meixin Li George P. Petropoulos Xulin Liu Lin Li |
| author_sort | Ying Wu |
| collection | DOAJ |
| description | A simplified generalized radio frequency interference (RFI) detection method and principal component analysis (PCA) method are utilized to detect and attribute the sources of C-band RFI in AMSR2 L1 brightness temperature data over land during 1−16 July 2017. The results show that the consistency between the two methods provides confidence that RFI may be reliably detected using either of the methods, and the only difference is that the scope of the RFI-contaminated area identified by the former algorithm is larger in some areas than that using the latter method. Strong RFI signals at 6.925 GHz are mainly distributed in the United States, Japan, India, Brazil, and some parts of Europe; meanwhile, RFI signals at 7.3 GHz are mainly distributed in Latin America, Asia, Southern Europe, and Africa. However, no obvious 7.3 GHz RFI appears in the United States or India, indicating that the 7.3 GHz channels mitigate the effects of the C-band RFI in these regions. The RFI signals whose position does not vary with the Earth azimuth of the observations generally come from stable, continuous sources of active ground-based microwave radiation, while the RFI signals which are observed only in some directions on a kind of scanning orbit (ascending/descending) mostly arise from reflected geostationary satellite signals. |
| first_indexed | 2024-12-20T23:37:20Z |
| format | Article |
| id | doaj.art-ff5917c78fb4472f96ef5dea543267b1 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-20T23:37:20Z |
| publishDate | 2019-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-ff5917c78fb4472f96ef5dea543267b12022-12-21T19:23:11ZengMDPI AGRemote Sensing2072-42922019-05-011110122810.3390/rs11101228rs11101228Detection and Analysis of C-Band Radio Frequency Interference in AMSR2 Data over LandYing Wu0Bo Qian1Yansong Bao2Meixin Li3George P. Petropoulos4Xulin Liu5Lin Li6Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, CMA Key Laboratory for Aerosol-Cloud-Precipitation, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, CMA Key Laboratory for Aerosol-Cloud-Precipitation, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, CMA Key Laboratory for Aerosol-Cloud-Precipitation, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, CMA Key Laboratory for Aerosol-Cloud-Precipitation, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaSchool of Mineral Resources Engineering, Technical University of Crete, Kounupidiana Campus, 73100 Crete, GreeceBeijing Meteorological Observation Center, Beijing 100089, ChinaBeijing Meteorological Observation Center, Beijing 100089, ChinaA simplified generalized radio frequency interference (RFI) detection method and principal component analysis (PCA) method are utilized to detect and attribute the sources of C-band RFI in AMSR2 L1 brightness temperature data over land during 1−16 July 2017. The results show that the consistency between the two methods provides confidence that RFI may be reliably detected using either of the methods, and the only difference is that the scope of the RFI-contaminated area identified by the former algorithm is larger in some areas than that using the latter method. Strong RFI signals at 6.925 GHz are mainly distributed in the United States, Japan, India, Brazil, and some parts of Europe; meanwhile, RFI signals at 7.3 GHz are mainly distributed in Latin America, Asia, Southern Europe, and Africa. However, no obvious 7.3 GHz RFI appears in the United States or India, indicating that the 7.3 GHz channels mitigate the effects of the C-band RFI in these regions. The RFI signals whose position does not vary with the Earth azimuth of the observations generally come from stable, continuous sources of active ground-based microwave radiation, while the RFI signals which are observed only in some directions on a kind of scanning orbit (ascending/descending) mostly arise from reflected geostationary satellite signals.https://www.mdpi.com/2072-4292/11/10/1228AMSR2radio frequency interference (RFI)C-bandgeneralized RFI detection methodprincipal component analysis (PCA) method |
| spellingShingle | Ying Wu Bo Qian Yansong Bao Meixin Li George P. Petropoulos Xulin Liu Lin Li Detection and Analysis of C-Band Radio Frequency Interference in AMSR2 Data over Land Remote Sensing AMSR2 radio frequency interference (RFI) C-band generalized RFI detection method principal component analysis (PCA) method |
| title | Detection and Analysis of C-Band Radio Frequency Interference in AMSR2 Data over Land |
| title_full | Detection and Analysis of C-Band Radio Frequency Interference in AMSR2 Data over Land |
| title_fullStr | Detection and Analysis of C-Band Radio Frequency Interference in AMSR2 Data over Land |
| title_full_unstemmed | Detection and Analysis of C-Band Radio Frequency Interference in AMSR2 Data over Land |
| title_short | Detection and Analysis of C-Band Radio Frequency Interference in AMSR2 Data over Land |
| title_sort | detection and analysis of c band radio frequency interference in amsr2 data over land |
| topic | AMSR2 radio frequency interference (RFI) C-band generalized RFI detection method principal component analysis (PCA) method |
| url | https://www.mdpi.com/2072-4292/11/10/1228 |
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