Abstract
A novel radio frequency interference (RFI) detection method is introduced for satellite-borne passive microwave radiometer observations. This method is based on factor analysis, in which variability among observed and correlated variables is described in terms of factors. In the present study, this method is applied to the Tropical Rainfall Measuring Mission (TRMM)/TRMM Microwave Imager (TMI) and Aqua/Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) satellite measurements over the land surface to detect the RFI signals, respectively, in 10 and 6 GHz channels. The RFI detection results are compared with other traditional methods, such as spectral difference method and principal component analysis (PCA) method. It has been found that the newly proposed method is able to detect RFI signals in the C- and X-band radiometer channels as effectively as the conventional PCA method.
| Original language | English |
|---|---|
| Pages (from-to) | 436–443 |
| Number of pages | 8 |
| Journal | Meteorological Applications |
| Volume | 22 |
| Issue number | 3 |
| Early online date | 29 Aug 2014 |
| DOIs | |
| Publication status | Published - 14 Jul 2015 |
Research Groups and Themes
- Water and Environmental Engineering
Keywords
- radio frequency interference
- TRMM Microwave Imager
- Advanced Microwave Scanning Radiometer
- EarthObserving System
- passive microwave radiometry
- land surface retrieval
- identification algorithm