适合P波段UWBSAR的改进PGA算法

相位梯度自聚焦（PGA）算法是一种高效的自聚焦算法，其优良的聚焦性能是建立在合理的统计模型和高信杂比的基础上。对于信杂比较低的P波段超宽带合成孔径雷达（UWBSAR）图像来说，传统PGA算法的聚焦效果并不理想。对此，文中提出了将对比度准则和传统PGA算法相结合的改进PGA算法，有效地削弱了图像信杂比对PGA聚焦性能的影响。文中还提出了“参考点对齐”法来校正PGA算法聚焦所产生的图像平移（沿方位向）失真问题。文中所提算法已经成功运用于某P波段UWBSAR实测图像数据的聚焦处理，并得到了比传统PGA算法更好的聚焦处理结果。

A Refined PGA Algorithm for P-band UWB SAR

The phase gradient autofocus(PGA) algorithm has been proved to be an efficient autofocus method.It's good focusing performance is build on the base of fit statistical model and high signal-to-clutter ratio.But for the P band Ultra-Wideband Synthetic Aperture Radar(UWB SAR) image whose signal-to-clutter ratio is poor,the focusing result of PGA applied to it is not ideal.In this paper,we proposed the modified algorithm,which combined the contrast principle with tie traditional PGA algorithm.In the modified algorithm,the influence to the performance of PGA algorithm due to the low signal-to-clutter ratio of the degraded image will be effectively reduced.At the same time,this paper proposed the reference scatterer coregistration method,which can remove the shift(along the azimuth) distortion in the focused image that was caused by PGA algorithm.The algorithm proposed in this paper has been successfully used to focus some P band UWB SAR raw images data,and better-focused results were got as compared to the traditional PGA.