The Soil Moisture Active-Passive (SMAP) Mission was designed to produce globally-derived soil-moisture maps every 2-3 days. At a spatial resolution of 3-10 kilometers, the soil moisture maps were intended to improve long-range weather and seasonal forecasting, and to set the stage for a new generation of hydrologic models capable of predicting and studying floods and droughts. The original SMAP mission concept relied on synergistic measurements from both radar and radiometer instruments, with radar information produced at higher spatial resolutions than radiometer measurements. Data products were planned to use both radar and radiometer information to provide higher resolution products. Unfortunately, the loss of the radar instrument on July 7, 2015, only six months after launch, compromised the ability to meet spatial resolution mission requirements for soil moisture and freeze-thaw products. Fortunately, the radiometer version of the Scatterometry Image Reconstruction (rSIR) technique, which has been successfully used to enhance spatial resolution of similar passive microwave sensors, can be used to enhance the spatial resolution of the SMAP radiometer brightness temperature (TB) data. Characterized by large fields-of-view and oversampled measurements, SMAP measurements are ideally suited to application of the rSIR technique. This document describes the theoretical basis for application of the rSIR algorithm to improve spatial resolution of gridded SMAP radiometer measurements, with details applicable to the contents of rSIR-SMAP (nsidc0738) v2 files.