A Comparison of Autofocus Algorithms for Backprojection Synthetic Aperture Radar

In this work, the performance and efficiency of variations of two autofocus algorithms for backprojection algorithm (BPA) synthetic aperture radar (SAR) are evaluated and compared through a Monte Carlo simulation. The two considered autofocus algorithms are maximum sharpness autofocus (MSA) and generalized phase gradient autofocus (GPGA). With the Monte Carlo simulation, the root mean squared error (RMSE) and run-time of each autofocus algorithm is evaluated over different transmitter/receiver position errors (i.e., different phase errors), different signal-to-noise ratios, and different SAR scene types. The results demonstrate the trade-off between performance and efficiency among each of the autofocus algorithms and provide useful information to system designers for choosing a BPA SAR autofocus algorithm.