PIMoghaddam, Mahta OrgUniversity of Michigan
Award #AIST-05-0044Managing CenterGRCStatusOpen
TitleSoil Moisture Smart Sensor Web Using Data Assimilation and Optimal Control

The proposed project addresses the topic of "Smart Sensing." It is motivated by a sensor-web measurement scenario including spaceborne and in-situ assets. The objective of the technology proposed 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. The sensor nodes are guided to perform as a macro-instrument measuring processes at the scale of the satellite footprint, hence meeting the requirements for the difficult problem of validation of satellite measurements. The science measurement considered is the surface-to-depth profiles of soil moisture estimated from satellite radars and radiometers, with calibration/validation using in-situ sensors. Satellites allow global mapping but with coarse footprints. The total variability in soil-moisture fields comes from variability in processes on various scales. Installing an in-situ network to sample the field for all ranges of variability is impractical. Our hypothesis is that 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 data assimilation system. The design and demonstration of the smart sensor web including the control architecture, assimilation framework, and logic actuation are the goals of this project.

The proposed technology enables, for the first time, a guided/adaptive sampling strategy for generating optimal, statistically unbiased, calibration/validation data for space-based measurements. The project duration is three years with entry and exit TRLs of 2 and 5, respectively.