An improved phase gradient autofocus approach for stripmap SAR imaging

The phase gradient autofocus (PGA) technique is applied over a wide range of imagery and phase error corrections for synthetic aperture radar (SAR). In this paper, we propose an improved PGA method to increase the phase error estimation accuracy by selectively increasing the pool of quality synchronization sources. This improved method operates mainly in three steps. Firstly, after compressing the deramped data by taking FFT, strong targets can be identified and selected out according to the pixel magnitudes over the two-dimensional (2-D) image. Secondly, sort the selected targets by computing their contrast in the azimuth direction and select out the ones with good contrast. Thirdly, sort the selected targets by computing their peak signal-to-noise (PSNR) in the azimuth direction and select out the good quality targets. After these three times filtering, those selected scatterers are optimal in terms of having sufficient signalto- noise energy with negligible impulse response interference to the neighboring targets and clutter scatterers. With these selected quality scatterers, the proposed modified PGA method can achieve a better focusing performance. Advantages and effectiveness of the proposed algorithm are verified on the real stripmap SAR data.