Technological issues in compressive sensing

摘要: Compressive sensing (aka compressive sampling or CS) is a new technology field that characterized by the possibility to sample radiometric and spectroscopic signals at lower rate without losing significant source / target information. This option made possible specific signal feature called sparsity. A sparse does not convey whole information predicted traditional theory, irrespective of maximum frequency contained in its spectrum. The mathematical representation admitted can be accessible an instrument throughout dedicated integral transformation would performed optical subsystem. belongs compression domain, main advantage takes place before registration, during phase. Due this feature, promises outstanding savings terms ADC specs, required memory for temporary data storage, bandwidth necessary down-link, electrical power consumption. above lesser requirements originate supplementary reduction mass, volume, cost budgets. impact these expectations on future space missions could remarkable, motivating investigations research programs concerning technology. In paper we review architecture implementations CS. CS application instruments devoted Earth observation, measurement planetary surfaces will discussed. remotely sensed assumed constituted sampled images collected passive device spectral range from visible up thermal infrared, with discrimination ability, e.g. hyperspectral imaging. We examine bottlenecks affecting utilization describe forthcoming ESA ITI-B Project focusing topics. show practical implementation demands light modulators 2dim detector arrays high frame rate. further necessarily employs multiplexing architecture, which spite reach projected SNR advantage.