This work develops a four–dimensional data assimilation methodology to retrieve deep soil moisture profiles using the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and other associated data. Several case study data sets have been selected for analysis and will use the WindSat satellite data as a surrogate for future NPOESS microwave imager/sounder sensor data. Sensitivity intercomparisons between NPOESS simulation software and the CSU Microwave Land Surface Model (MWLSM) are shown. This intercomparison work is an essential part of the testing and exercise of NPOESS software systems. The CSU system makes use of observed WindSat data and special US Army soil moisture data sets. Progress using the 4-dimensional variational (4DVAR) Regional Atmospheric Mesoscale Data Assimilation System (RAMDAS) research is presented. Our goal is to identify paths to soil moisture performance objective (soil moisture at depths between 0- 80 cm) for US Army use, and to identify and mitigate algorithm impediments to its potential performance. The validation aspects of this work will also enable the Army to more accurately determine the NPOESS Soil Moisture EDR impacts upon DoD-related trafficability, off-road mobility, counter-mine operations, and hydrological streamflow estimation. This research was supported by the DoD Center for Geosciences/Atmospheric Research at Colorado State University under Cooperative Agreements DAAD19-02-2-0005 and W911NF-06-2-0015 with the Army Research Laboratory and by the NPOESS Inter Governmental Studies (IGS) Program.