A Compressive Sensing Method for One Bit Coded Synthetic Aperture Radar Imaging

In synthetic aperture radar (SAR) system, the requirement of high resolution always leads to large amount of echo data, which is a burden on analog-to-digital convertor (ADC) and onboard memory. In the compressive sensing (CS) framework, the goal is to reconstruct sparse signals at reduced sampling rate, while in this paper, the total bit rate that is taken into account can be reduced. This paper proposes a compressive sensing method for one bit coded SAR imaging. Simulation experiments verify the effectiveness of the proposed method. Compared with the matched filtering approach, this method cannot only reduce the total bit rate but also suppress the sidelobes and false targets. Moreover, this method also out performs traditional multi-bit CS approaches when the signal to noise ratio (SNR) is low.