Bistatic frequency-modulated continuous wave (FMCW) synthetic aperture radar (SAR) mounts the radar transmitter and receiver on separate platforms, which offers considerable capabilities, reliability and flexibility in designing FMCW SAR missions. Moreover, the spatial separation achieves better isolation between transmission and reception channels compared with the monostatic FMCW SAR where the two separate dedicated antennas are fixed on one platform. In this study, a bistatic FMCW SAR signal model is proposed to formulate the bistatic slant range history in bistatic FMCW configuration. Based on the preceding model, an approach is presented to deal with the double-square-root (DSR) term, and thus an accurate FMCW bistatic point target reference spectrum (BPTRS) is derived. Besides accurately addressing the signal characteristics of bistatic FMCW SAR, the proposed spectrum also significantly simplifies the signal processing of bistatic FMCW SAR, which will really push the applications of bistatic FMCW SAR in remote sensing fields. Furthermore, based on the proposed BPTRS, an extended inverse chirp-Z transform (EICZT) algorithm is proposed to process the bistatic FMCW SAR data by introducing a perturbation function to deal with the range-variance of second-and third-order range-azimuth coupling terms. Two simulation experiments are carried out to verify the accuracy of this novel formulation and highlight the performance of the proposed focusing approach.

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To obtain sufficient resolution, the operating band of synthetic aperture radar (SAR) must extend over several tens of megahertz. Consequently, SAR reception occurs across frequency bands allocated for other broadcasting stations and SAR often suffers radio frequency interference (RFI). This study proposes a novel approach to suppress RFI in SAR. The authors combine the classical spectral analysis method singular spectrum analysis, with an efficient subspace tracking method fast approximated power iteration (FAPI) which has the most economical computational cost among state-of-the-art algorithms. Furthermore, they supply a gap of FAPI so that it can achieve rank tracking based on eigenvalues distribution of the covariance matrix of the observed SAR record and in that way can detect the number of RFIs along the SAR azimuth time. The proposed algorithm is a time domain processing method and performs on SAR range records one-by-one. Finally, well-focused SAR imagery is obtained from the 'decontaminated' SAR data using classical SAR imaging algorithms. The proposed algorithm could be applied in complicated interference circumstances no matter the styles of RFI. Imaging results of artificial and real data have proved the validity and robustness of this algorithm.