Dynamic underwater sensor network for sparse field estimation

A coordinated dynamic network of autonomous underwater gliders to estimate 3D environmental sparse fields is proposed and tested. Field spatial sparsity is exploited in the estimation algorithm. Moreover field measurements are acquired by compressive sensing devices. Integration with a network of surface relay nodes and asynchronous consensus are used to distribute local information and achieve the global field estimate. Tests on simulated data demonstrate the feasibility of the approach with relative error performance within 10%