Distributed Collaborative Adaptive Sensor networks for remote sensing applications

Enabled by a dense network of Doppler weather radars with overlapping coverage, Distributed Collaborative Adaptive Sensing (DCAS) represents a new paradigm in remote sensing. Rather than each radar periodically sampling its surroundings with sit-and-spin volume coverage patterns as with today´s NEXRAD weather radars, DCAS is an end-user driven approach that targets sensitivity when and where the needs of its end-users are greatest. The advantage is that by adaptively allocating sensitivity, higher quality measurements are possible due to the ability to dwell longer in volumes where echoes are weak, sample faster in volumes with rapidly evolving dynamics, and obtain multi-Doppler looks for high accuracy wind field retrieval. This paper describes the multiuser, multi-attribute utilities-based approach being used to coordinate the scanning activities of the weather radars in the first prototype DCAS system being fielded by the National Science Foundation sponsored Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA- ERC).