Formulation of a general imaging algorithm for high-resolution synthetic aperture radar

We consider the application of an alternative imaging algorithm to the inversion of strip-mapping synthetic aperture radar (SAR) data. The algorithm was originally developed and successfully applied in the area of geophysics to estimate the conductivity distribution from wellbore induction measurements. The SAR measurement relation satisfies the same form of integral equation describing the wellbore problem. By exploiting the form of the measurement kernel, we derive a SAR image formation algorithm involving deconvolution-backprojection. Unlike correlation-based SAR image formation, our approach is more general, without simplifying assumptions on the range function, and is robust to measurement noise, at the expense of increased computational complexity. Simulation results are presented that demonstrate the effectiveness of the proposed algorithm