NONITERATIVE QUALITY PHASE-GRADIENT AUTOFOCUS (QPGA) ALGORITHM FOR SPOTLIGHT SAR IMAGERY

The phase-gradient autofocus (PGA) technique is robust over a wide ran ge of imagery and phase error functions, but the convergence usually r equires four-six iterations. It is necessarily iterative in an attempt to converge on a dominant target against clutter interference, while sufficiently capturing the blur function. In this paper, we propose to speed the estimation convergence by selectively increasing the pool o f quality synchronization sources and not be limited by the range pixe ls of the SAR map. This is highly probable since each range bin contai ns more than one prominent scatterer across the integration aperture. It is also highly probable that the least-brightest selected scatterer in a range gate may turn out to be of higher energy as compared to th e maximum brightest scatterer of another gate. With appropriate target filtering to final select the quality scatterers out of the large poo l and with higher order phase error measurement tool, the new algorith m achieves near-convergence focusing quality without iteration. We nam ed this solution the quality PGA (QPGA) algorithm.