基于自聚焦的变门限SAR/GMTI动目标检测方法

SAR/GMTI Moving Target Detection Algorithm Based on Autofocus and Variable Threshold CFAR Detection

高分辨率合成孔径雷达(Synthetic aperture radar,SAR)合成孔径时间长导致动目标散焦严重、信杂噪比(Signal clutter noise ratio,SCNR)降低,增加了对动目标的检测难度。针对这种情况,本文提出了一种基于自聚焦的变门限SAR/(Ground moving target indication,GMTI)动目标检测算法。该算法利用距离相位误差和方位相位误差之间存在的固定关系实现对动目标的两维相位误差的估计与补偿,达到提高SCNR的目的。通过两级不同门限的恒虚警率(Constant false alarm rate,CFAR)检测分别实现动目标检测和排除虚警。实测数据结果表明,本文算法能有效地检测动目标,降低虚警概率。

The defocusing of moving target and the reduction of signal clutter noise ratio （SCNR） caused by long coherent time in high-resolution SAR lead to increasing difficulty of moving target detection. In view of this situation, we propose an SAR/GMTI moving target detection algorithm based on autofocus and variable threshold constant false alarm rate（CFAR） detection. To increase SCNR of moving targets, this algorithm makes use of the fixed relationship between range phase error and azimuth phase error to estimate and compensate two-dimensional phase error of moving target. CFAR detection with different thresholds is also realized to detect moving target and exclude the false alarm, respectively. Experimental results verify the feasibility of this algorithm that it can detect moving target and reduce false alarm ratio sufficiently.