一种基于动目标聚焦的SAR-GMTI方法

由于输入信杂噪比(Signal to Clutter Noise Ratio, SCNR)较低，杂波抑制后超高频(Ultra-High Frequency, UHF)波段合成孔径雷达(Synthetic Aperture Radar, SAR)图像中剩余静止目标杂波导致系统虚警概率较高。该文提出一种动目标筛选方法，能够判断恒虚警概率(Constant False Alarm Rate, CFAR)检测器检测到的目标是否为动目标。提出一种动目原始数据恢复方法，能够从整幅SAR图像中恢复任意孤立点的多普勒相位历史。采用距离多普勒处理对恢复的数据成像，然后采用方位自聚焦处理对所成子图像进行重新聚焦。如果子图像中目标为静止目标，则聚焦前后子图像不变，否则图像被重新聚集。通过检测图像的变化可以排除虚假动目标。仿真及实测数据处理结果说明了该方法的有效性。

A SAR-GMTI Approach Based on Moving Target Focusing

Due to the low Signal to Clutter Noise Ratio (SCNR), the residual stationary targets in a clutter suppressed multichannel Ultra-High Frequency (UHF) band Synthetic Aperture Radar (SAR) image may lead to an unacceptable false alarm rate. A method of moving target screening is presented in this paper, which can determine whether the target detected by the Constant False Alarm Rate (CFAR) detector is a real moving one. A moving target data recovery method is described, which can recover the Doppler phase history of any isolated target within a full-K SAR image. The recovered data is processed again into a sub-image by range Doppler processing, and the sub-image is refocused with azimuth autofocus processing. The sub-image will not change after refocusing if the target in it is a stationary one, and it will be refocused if the target is a moving one. The false moving target can be eliminated by detecting this change. The proposed method is demonstrated on simulated and real SAR Ground Moving Target Indication (GMTI) data.