一种适用于宽带条带式合成孔径声纳的相位梯度自聚焦算法

Phase Gradient Autofocus Algorithm Applied to Broad Band Stripmap Synthetic Aperture Sonar

传统的相位梯度自聚焦(PGA,phase gradient autofocus)算法仅适用于窄带聚束式合成孔径成像。提出了一种适用于宽带条带式合成孔径声纳的相位梯度自聚焦(SPGA,stripmap phase gradient autofocus)算法。SPGA算法通过多普勒频移估计线性侧摆;SPGA算法消除了侧摆对回波信号包络的影响,使成像模糊仅仅是由方位向相位误差引起的,这样才可以由Dechirp后的距离压缩域数据的相位误差梯度得到侧摆的估计;SPGA算法利用估计得到的侧摆对距离徙动校正前的回波数据进行包络和相位补偿。仿真表明该算法有效地估计出了侧摆,提高了成像质量,且成像没有发生方位向偏移,明确地确定出了目标的位置。

Classic phase gradient autofocus （PGA） algorithm can be only applied to narrow band spotlight synthetic aperture imaging. Stripmap phase gradient autofocus （SPGA） algorithm which may be used for broad band stripmap synthetic aperture sonar is proposed. SPGA algorithm estimates linear sway by Doppler shift; SPGA algorithm eliminates the effect that sway has on echo envelope, so the image blurring is only begotten by the phase error and the sway may be estimated by phase error gradient; SPGA algorithm compensates the envelope and phase of the echo signal which has not be corrected range migration. The simulation results using SPGA algorithm show that SPGA algorithm estimates the sway effectively and the image quality is improved without along track shift, so the targets are oriented exactly.