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High-Resolution Wide-Swath Synthetic Aperture Radar (HRWS-SAR) imaging is highly desirable since it allows one to produce high-resolution SAR images of large areas during a short visit time. In this paper, Staggered Coprime Pulse Repetition Frequencies Synthetic Aperture Radar (SCopSAR) is proposed. It divides the time during which a scatterer is illuminated by the antenna beam-pattern into two halves where, in each half, pulses are transmitted at the rate of one of two sub-Nyquist Pulse Repetition Frequencies (PRFs). Such PRFs are related to the Nyquist PRF using two coprime sub-sampling factors. This allows extending the maximum range swath width that can be imaged by a number of times that equals the smaller sub-sampling factor at the expense of a reduction in the azimuth resolution by half. It further allows for a reduction in the amount of data to be stored and communicated. SCopSAR is an imaging modality suitable for scenes that contain a small number of bright scatterers over a dark background which, for instance, is the case when imaging ships in a calm sea background. Compared to the techniques recently proposed in the literature, SCopSAR simplifies the Radar requirements since it uses only one carrier frequency, one waveform, and one channel. Simulations and real ERS-2 satellite raw data are used to validate the theoretical findings presented in this paper.

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Abstract-It has been shown that the Discrete Fourier Transform (DFT) can be computed in sublinear time from a sublinear number of samples when the target spectrum is sparse. However, this is usually only expressed qualitatively in terms of the order of number of computations/samples. Here we investigate the explicit time-data tradeoff for the Sparse Fourier Transform (SFT) algorithm proposed by Pawar and Ramchandran using coding theoretic tools. This leads to an optimal oversampling rate and algorithm configuration that minimises computation while keeping the required number of time domain samples close to the minimum value.