An introduction to factor analysis for radio frequency interference detection on satellite observations

Meteorological applications

article

Tanvir Islam¹  Prashant K. Srivastava³  Qiang Dai³  Manika Gupta⁶  Lu Zhuo³ 

[1] NOAA/NESDIS Center for Satellite Applications and Research, College Park;Cooperative Institute for Research in the Atmosphere, Colorado State University;Department of Civil Engineering, University of Bristol;NASA Goddard Space Flight Center;Earth System Science Interdisciplinary Center, University of Maryland, College Park;Department of Civil Engineering, Indian Institute of Technology Delhi

关键词: radio frequency interference;    TRMM Microwave Imager;    Advanced Microwave Scanning Radiometer – Earth Observing System;    passive microwave radiometry;    land surface retrieval;    identification algorithm;   

DOI  :  10.1002/met.1473

学科分类：社会科学、人文和艺术（综合）

来源: Wiley

【 摘 要 】

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.

【 授权许可】

CC BY|CC BY-NC|CC BY-NC-ND