A dual-frequency polarized scatterometer (DPSCAT) is proposed for the Chinese Water Cycle Observation Mission (WCOM) to be launched around 2020. DPSCAT is used to measure the snow water equivalent (SWE) and the freeze/thaw state, which requires a measurement precision of 0.5 dB and a relatively higher spatial resolution (2-5 km) than the regular scatterometers (about 25 km). Therefore, the conventional range-gate dechirping along with the Doppler beam sharpening (DBS) technique is used by DPSCAT to achieve high range and azimuth resolution simultaneously. However, DBS cannot improve the azimuth resolution over the nadir swath; thus, a new data processing, namely regularized deconvolution method (RDM), is explored to address this problem. In this paper, a quantitative analysis model is developed for RDM in order to study two crucial issues, i.e., the spatial resolution (mainly for the nadir swath) and the accuracy/precision of the backscatter measurements after resolution enhancement. Normally, the measurement precision and spatial resolution cannot be improved simultaneously using RDM. The accuracy/precision degrades as the spatial resolution improves, and vice versa. Moreover, they both degrade as the measurement noise or uncertainty increases, which latter is usually defined as the normalized standard deviation of the measurements (K-p). In case of SWE retrieval that requires a reconstructed measurement precision of 0.5 dB, the best spatial resolution resolved by RDM is 3 km for K-p = 7%, 4 km for K-p = 10%, and 5 km for K-p = 12%.
