一种基于PFA的多子阵聚束合成孔径声呐成像方法

文章提出了一种基于极坐标格式算法（Polar Format Algorithm，PFA）进行聚束多子阵合成孔径声呐成像的改进方法，建立了非“停-走-停”条件下的斜视成像模型，推导了信号由时域到波数域的解析表达式，给出了信号处理流程。该方法首先使用场景中心点的精确距离史对平台运动误差进行补偿，并通过极坐标算法处理得到粗聚焦的图像。其次，为了解决非场景中心点的残余空变相位误差的补偿问题，对粗聚焦图像进行分块自聚焦处理，使场景边缘点的聚焦效果得到改善。最后，经过子图拼接及几何校正后得到完整的精聚焦图像。仿真及分析结果表明，该方法提高了方位向性能指标，同时也能准确补偿平台运动误差，可以很好地应用于多子阵声呐成像。该方法在大运动误差、大斜视情况下仍具有较好的鲁棒性。

A PFA based imaging method for multiple receiver spotlight synthetic aperture sonar

In this paper, an improved imaging method for multiple receiver spotlight synthetic aperture sonar (SAS) based on the polar format algorithm (PFA) is proposed, a squint imaging model under the condition of non-stop-start-stop is established, the analytical expression of the signal converted from the time domain to the wavenumber domain is derived, and the flow chart of signal processing is given. Firstly, the accurate round-trip range history of the scene center is used to compensate the platform motion error, and the coarse-focused image is obtained by PFA processing. Secondly, in order to compensate the residual phase error, the block-wise autofocus is performed in the image domain, which improves the imaging accuracy of edge points. Finally, a full fine focusing image can be obtained after subimage mosaic and geometric correction. The simulation results show that the proposed method can improve the azimuth imaging performance effectively and compensate platform motion error accurately. The proposed method can work well for multiple receiver SAS data, even though the data has large motion error and big squint angle.