Comparison of Polarimetric Algorithm With Other Algorithms in Detecting Radio Frequency Interference

Abstract

Anthropogenic radio frequency interference (RFI) is an increasing problem in microwave remote sensing radiometry. Therefore, there is growing interest in RFI counteraction methods, including detection and blanking. In this study, the performance of polarimetric algorithm has been studied and compared with several other detection algorithms with respect to their capability to detect different potential types of RFI, such as continuous wave (CW), pulse modulated, and quadrature phase shift keying (QPSK) modulated. The mission scenario and parameters applied correspond to a typical space-borne, polar-orbiting, conically scanning microwave radiometer. Therefore, the results obtained help to estimate the achievable RFI detection limits (in terms of the brightness temperature) for similar future satellite instruments if polarimetry or other algorithms analyzed here were applied. The results obtained suggest that the RFI detection limit in the 1-K range can be achieved in the scenario under study. Incorporating multiple and complementary RFI detection algorithms in the overall system, e.g., in a digital RFI processor, enables a wide range of different RFI types to be detected. The results suggest that polarimetry and spectral density estimation are sensitive in detecting constant envelope signals (such as CW or QPSK), while kurtosis and spectral kurtosis are effective in detecting pulsed RFI. A detection limit as low as 0.1 K can be achieved for pulsed RFI with low duty cycles. These findings confirm and extend earlier results. To the best knowledge of the authors, this is the first quantitative study on the performance of the RFI detection algorithms to include polarimetry.