Search ETDs:
Radio Frequency Interference Characterization and Detection in L-band Microwave Radiometry
Aksoy, Mustafa

2015, Doctor of Philosophy, Ohio State University, Electrical and Computer Engineering.
Radio Frequency Interference (RFI) is a major issue in microwave radiometry and prevents correct estimation of geophysical parameters via remote sensing. This problem is reported even in the protected portion of the L-band (1400-1427MHz) which is allocated for only remote sensing of Earth from space. RFI contamination in radiometric measurements and the methods to mitigate it have previously been discussed in the literature. On the other hand, a comprehensive characterization of the RFI environment and an optimal RFI detection procedure which combines multiple RFI detection algorithms to effectively operate in that environment have yet to be presented. This dissertation aims to fill this gap for L-band microwave remote sensing research efforts. First, the RFI problem in microwave radiometry and previously developed RFI detection algorithms and their applications in current microwave radiometers are reported. Then, the L-band RFI environment is characterized in terms of its temporal, spectral, spatial, and statistical properties using space-borne and air-borne measurements from European Space Agency (ESA) and National Aeronautics and Space Administration (NASA) missions as well as local air-borne campaigns. It is demonstrated that RFI is a global problem, and its temporal, spectral and statistical properties may change significantly. Thus, classical RFI detection algorithms based on certain assumptions on these properties are insufficient to resolve the RFI problem and a more sophisticated approach is needed. This dissertation introduces NASA’s Soil Moisture and Active Passive (SMAP) radiometer which was launched on January 31, 2015 as one of the first radiometers which implements such a multifaceted RFI detection technique. SMAP’s comprehensive multi-domain RFI detection approach is summarized and analyzed in terms of its performance under different RFI exposure scenarios using pre-launch and post-launch RFI studies. Finally, several improvements to the SMAP baseline algorithm, and future investigations to obtain a more efficient RFI mitigation are discussed.
Joel Johnson (Advisor)
Fernando Teixeira (Committee Member)
Chi-Chih Chen (Committee Member)
205 p.

Recommended Citations

Hide/Show APA Citation

Aksoy, M. (2015). Radio Frequency Interference Characterization and Detection in L-band Microwave Radiometry. (Electronic Thesis or Dissertation). Retrieved from https://etd.ohiolink.edu/

Hide/Show MLA Citation

Aksoy, Mustafa. "Radio Frequency Interference Characterization and Detection in L-band Microwave Radiometry." Electronic Thesis or Dissertation. Ohio State University, 2015. OhioLINK Electronic Theses and Dissertations Center. 25 Sep 2017.

Hide/Show Chicago Citation

Aksoy, Mustafa "Radio Frequency Interference Characterization and Detection in L-band Microwave Radiometry." Electronic Thesis or Dissertation. Ohio State University, 2015. https://etd.ohiolink.edu/

Files

Mustafa_Aksoy_Dissertation_12012015.pdf (11.19 MB) View|Download