The presence of anthropogenic RFI is expected to adversely impact soil moisture measurement by NASA's Soil Moisture Active Passive mission. The digital signal processing approach and preliminary design for detecting and mitigating this RFI is presented in this paper. This approach is largely based upon the work of Johnson [1] and Ruf [2].Index Terms-SMAP, Soil Moisture Active Passive, Digital Radiometer, Filterbank, Kurtosis done for the Hydros mission [7] as its basis, the SMAP digital backend will provide both time and frequency diversity data at each footprint to enable the ground processing algorithms to detect and remove RFI. To do so, it will use digital signal processing (DSP) techniques to measure 1200 samples in time and frequency for each SMAP footprint. This paper summarizes the DSP algorithms and electronics implementation using field-programmable gate arrays (FPGAs) in the SMAP preliminary design.
RFI is a persistent and growing problem experienced by spaceborne microwave radiometers. Recent missions such as SMOS, SMAP, and GPM have all detected RFI in L, C, X, and K bands. To proactively deal with this issue, microwave radiometers must include digital back-end processors that generate data products that facilitate the detection and excision of RFI from desired brightness temperature measurements. The wideband digital signal processing testbed is a platform that allows rapid development of various RFI detection and mitigation algorithms using digital hardware akin to that which might be used for final spaceflight implementation. On it, we evaluate an improved version of the SMAP RFI Digital Signal Processor (DSP) that utilizes the new complex signal kurtosis algorithm as opposed to the real signal kurtosis that is used on the SMAP radiometer. In addition, we show how we scale the DSP to operate at 8.3 times the bandwidth of the SMAP radiometer for operation in K-band.
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