Compressed Remote Sensing of Sparse Objects

Abstract. The linear inverse source and scattering problems are studied from the perspective of compressed sensing, in particular the idea that sufficient incoherence and sparsity guarantee uniqueness of the solution. By introducing the sensor as well as target ensembles, the maximum number of recoverable targets (MNRT) is proved to be at least proportional to the number of measurement data modulo a log-square factor with overwhelming probability. Important contributions include the discoveries of the threshold aperture, consistent with the classical Rayleigh criterion, and the decoherence effect induced by random antenna locations. The prediction of theorems are confirmed by numerical simulations.

• Type: Journal
• Year: 2010
• Where: SIAMIS
• Authors: Albert Fannjiang, Thomas Strohmer, Pengchong Yan
• Keywords: Classical Rayleigh Criterion, Linear Inverse Source, SIAMIS 2010, Sparsity Guarantee Uniqueness