Bistatic SAR data are more complicated to process than monostatic data because of the versatile sensor geometry and thenon-stationary properties of the received data. Recent approaches to the processing of bistatic SAR data have revolvedaround finding an accurate representation of the two-dimensional spectrum for a point target.In this paper, we review past methods of obtaining the spectrum, then present a new method based on a power series.We then establish the relationship between three independently-derived bistatic point target spectra. The first spectrum isLoffeld’s Bistatic Formula (LBF), which consists of a quasi-monostatic phase term and a bistatic phase term. The secondspectrum makes use of Rocca’s smile operator, which transforms bistatic data in a defined configuration to a monostaticequivalent. The third spectrum is derived using the method of series reversion (MSR). Simulations are performed toillustrate the focusing accuracies of each form of the spectrum.
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