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The linear inverse source and scattering problems are studied from theperspective of compressed sensing, in particular the idea that sufficientincoherence and sparsity guarantee uniqueness of the solution. By introducingthe sensor as well as target ensembles, the maximum number of recoverabletargets is proved to be at least proportional to the number of measurement datamodulo a log-square factor with overwhelming probability. Importantcontributions of the analysis include the discoveries of the thresholdaperture, consistent with the classical Rayleigh criterion, and the decoherenceeffect induced by random antenna locations. The prediction of theorems areconfirmed by numerical simulations.

Compressed Remote Sensing of Sparse Objects