Strong RFI Mitigation Based on Channel Response Adjustment for SAIR on Chinese Ocean Salinity Satellite

The Chinese ocean salinity satellite mission is currently undergoing development and rigorous testing. The satellite will be equipped with an L-band Y-shaped synthetic aperture interferometric radiometer (SAIR), which is similar to the highly regarded MIRAS. Leveraging lessons learned from the SMOS mission, significant emphasis has been placed on addressing radio frequency interference (RFI). A prelaunch ground experiment has been conducted specifically for the SAIR payload of the Chinese ocean salinity satellite. This experiment aims to research and verify the efficacy of RFI processing algorithms. Notably, our observations indicate that the radiometer detects Gaussian thermal radiation noise, whereas RFIs consist of non-Gaussian signals, such as radar and wireless communication signals. This fundamental difference in signal types results in distinct system responses, leading to biases in RFI suppression, particularly for powerful RFI sources. To mitigate the suppression residuals of strong RFI, we have introduced an innovative adaptive channel response adjustment strategy. The core concept involves decomposing the covariance matrix to isolate the signal space dominated by intense RFI signals. By projecting the steering vector onto this signal space, we can accurately estimate the channel response of the RFI and make precise adjustments accordingly. Our experimental and simulation results are encouraging, demonstrating a marked improvement in RFI suppression effectiveness. This advancement is crucial for enhancing the accuracy and reliability of ocean salinity measurements from our satellite, ultimately contributing to a deeper understanding of our planet’s vital ocean ecosystems.