Aperture undersampling using compressive sensing for synthetic aperture stripmap imaging

Synthetic aperture imaging is a high-resolution imaging technique employed in radar and sonar applications, which construct a large aperture by constantly transmitting pulses while moving along a scene of interest. In order to avoid azimuth image ambiguities, spatial sampling requirements have to be fulfilled along the aperture trajectory. The latter, however, limits the maximum speed and, therefore, the coverage rate of the imaging system. This paper addresses the emerging field of compressive sensing for stripmap synthetic aperture imaging using transceiver as well as single-transmitter and multi-receiver systems so as to overcome the spatial Nyquist criterion. As a consequence, future imaging systems will be able to significantly reduce their mission time due to an increase in coverage rate. We demonstrate the capability of our proposed compressive sensing approach to at least double the maximum sensor speed based on synthetic data and real data examples. Simultaneously, azimuth image ambiguities are successfully suppressed. The real acoustical measurements are obtained by a small-scale ultrasonic synthetic aperture laboratory