A Soil Moisture Smart Sensor Web using Data Assimilation and Optimal Control: Formulation and First Laboratory Demonstration

We have developed a new concept for a smart sensor web technology for measurements of soil moisture that include spaceborne and in-situ assets. The objective of the technology is to enable a guided/adaptive sampling strategy for the in-situ sensor network to meet the measurement validation objectives of the spaceborne sensors with respect to resolution and accuracy. One potential application is the Soil Moisture Active/Passive (SMAP) mission. The science measurements considered are the surface-to-depth profiles of soil moisture estimated from satellite radars and radiometers, with calibration and validation using in-situ sensors. Installing an in-situ network to sample the field for all ranges of variability is impractical. However, a sparser but smarter network can provide the validation estimates by operating in a guided fashion with guidance from its own sparse measurements. The feedback and control take place in the context of a dynamic data assimilation system subject to energy and accuracy constraints. The overall design of the smart sensor web including the control architecture, assimilation framework, and actuation hardware are presented in this paper. We also present results of initial numerical and laboratory demonstrations of the sensor web concept, which includes a small number of soil moisture.