Compressive Sensing of SAR Signals via Fourier Coefficients

Processing of SAR signals requires high sampling rates which is difficult to attain in practice. Consequently, sampling rate reduction is of high practical value in radar imaging. In this paper, we introduce a new algorithm, equivalent to the well-known Range-Doppler method, to process SAR data using the Fourier coefficients of the raw signals. We then demonstrate how to exploit the new algorithm features, in order to reduce the sampling rate and process the signals at sub-Nyquist rates. This also results in computational cost saving, both in time and memory. The performance of the algorithms is assessed using simulated data sets.