A Review of Point Target Spectra for Bistatic SAR Processing

Bistatic SAR data are more complicated to process than monostatic data because of the versatile sensor geometry and the non-stationary properties of the received data. Recent approaches to the processing of bistatic SAR data have revolved around 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 is Loffeld’s Bistatic Formula (LBF), which consists of a quasi-monostatic phase term and a bistatic phase term. The second spectrum makes use of Rocca’s smile operator, which transforms bistatic data in a defined configuration to a monostatic equivalent. The third spectrum is derived using the method of series reversion (MSR). Simulations are performed to illustrate the focusing accuracies of each form of the spectrum.