A Review on Compressive Sensing in Synthetic Aperture Radar (SAR)?

The system parameters have been specified in view of all the constraints and practical limitations. The performance metrics of the system such as range resolution and cross-range resolution, etc. have been worked out and the system level specification has been worked out keeping in view the desired performance. Using MATLAB as major tool, the specified system parameters have been tested for their accuracy and correctness. A simulation of Pulse Doppler radar is completed which includes waveform design, target modeling, LFM pulse compression, side lobe control and threshold detection. This paper surveys the use of sparse reconstruction algorithms and randomized measurement strategies in radar processing. Although the two themes have a long history in radar literature, the accessible framework provided by compressed sensing illuminates the impact of joining these themes. Potential future directions are conjectured both for extension of theory motivated by practice and for modification of practice based on theoretical insights. A SAR image formation algorithm (Doppler Beam Sharpening) has been implemented in MATLAB.