对海面重拖尾杂波下相位梯度自聚焦算法的改进

Improvement of the PGA algorithm with Sea Clutter

由于海杂波的随机动态特性,用合成孔径雷达(Synthetic Aperture Radar,SAR)对海面上的舰船目标成像时,相位梯度自聚焦算法(Phase Gradient Autofocus,PGA)的聚焦效果变差.在统计海杂波的分布特性之后,在大多数情况下可以用α-stable分布模型比较好地描述海杂波的幅度特性,尤其对于拖尾较大的海杂波.用分数低阶统计模型和相位梯度自聚焦算法结合起来(PGA-FLOS),可以有效地改善海面上舰船目标的成像效果.仿真和对实测海面数据处理都证明了文中算法的有效性.

As the sea clutter is dynamic random sel on the sea, the focusing effect by phase gradie amplitude of sea clutter fits α-stable distribution clutter. In this paper, the combination of fraction to improve the imaging quality of the vessel on th , when Synthetic Aperture Radar （SAR） images a vesnt autofocus （PGA） becomes bad. It is proved that the module very well, especially for the heavy-tailed sea al low-order statistics （FLOS） and the PGA is adopted e sea. The results of simulation and practical data prom.