Studies of radio frequency interference detection methods in microwave radiometry

Recent surveys conducted from orbiting radiometers have shown that corruption of radiometric data due to Radio Frequency Interference (RFI) may significantly impact the accuracy of the retrieved environmental data. These findings have sparked an interest in RFI detection and mitigation methods; several future microwave remote sensing satellites, like the SMAP (Soil Moisture Active and Passive) mission of NASA, plan to incorporate RFI mitigation strategies in their design. A digital radiometer with very high temporal and spectral resolution developed at OSU/ESL may be used to address this issue; versions of this radiometer working at L-band and C-band are called L-band/C-band Interference Suppressing Radiometer (LISR/CISR), respectively. Although the high resolution obtained with this radiometer makes its use in a space based system unlikely due to the stringent datarate requirements required in such systems (unless data is further integrated after mitigating RFI onboard or flagging the data), LISR/CISR sensors are very beneficial for learning about time and frequency domain characteristics of the existing RFI environment, for serving as "ground-truthing" devices for other radiometers, and for analyzing the effectiveness of pulse and cross-frequency detection methods against observed RFI sources.;In this thesis, results from several groundborne and airborne radiometric campaigns performed using LISR/CISR systems are given. RFI sources observed in these experiments and RFI mitigation methods that use the high resolution obtained via LISR/CISR to remove such sources are described. Effectiveness of RFI mitigation methods against the diverse RFI sources encountered in campaigns is analyzed. The ability of LISR/CISR in eliminating very weak RFI sources even on the order of natural geophysical variations is demonstrated. Comparisons with other radiometers that participated in these campaigns are given when possible.;A novel method for RFI detection that uses the Shapiro-Wilk test of normality is also elucidated. Comparisons are made with another method based on the normality of thermal noise, the kurtosis detection technique, for the pulsed sinusoidal RFI case. Results prove that the Shapiro-Wilk technique is a viable alternative for RFI mitigation in actual systems. The thesis is concluded with a theoretical performance comparison against pulsed sinusoidal RFI using the three most commonly used RFI detection methods: Pulse detection, cross-frequency detection, and kurtosis detection. Particular emphasis is given to the cross-frequency detection method. It is shown that cross-frequency detection method provides good detection performance regardless of duty cycle for this important type of RFI.