Several approaches have been proposed to suppress multipath ghost in through-the-wall radar imaging (TWRI). One classical approach, called Aspect Dependent (AD), exploits locations of ghosts in the images without demanding prior knowledge of the reflecting geometry. This operation strategy makes the method superior over multipath exploitation-based approaches. However, the AD method assumes a point target that emulates unreal environment. Therefore, reconstructing extended targets with this method leads to incorrect scene interpretation. This work proposes a ghost suppression method for extended targets based on the AD feature that exploits duo sub-apertures. Firstly, we evaluate the best suppression method using a performance metric called relative clutter peak. Next, the evaluated method is extended to encompass a target extent during sub-images reconstruction. Following this strategy, an effective image fusion method suitable for extended targets is proposed. The method considers pixel neighborhood to effectively recover the given extended target. Simulation results show that, when signal-to-noise ratio is 20dB, the proposed method significantly improves signal-to-clutter ratio and relative clutter peak by 8.8% and 23.8%, respectively, relative to the existing AD based methods under point target assumption.

已经提出了几种方法来抑制穿墙雷达成像 (TWRI) 中的多径重影。一种经典的方法，称为 Aspect Dependent (AD)，利用图像中重影的位置，而无需事先了解反射几何。这种操作策略使得该方法优于基于多路径利用的方法。但是，AD 方法假定模拟虚幻环境的点目标。因此，用这种方法重建扩展目标会导致不正确的场景解释。这项工作提出了一种基于 AD 特征的扩展目标鬼抑制方法，该方法利用了双子孔径。首先，我们使用称为相对杂波峰值的性能指标来评估最佳抑制方法。下一个，在子图像重建期间，评估的方法被扩展为包含目标范围。根据该策略，提出了一种适用于扩展目标的有效图像融合方法。该方法考虑像素邻域来有效地恢复给定的扩展目标。仿真结果表明，当信噪比为20dB时，该方法在点目标假设下，相对于现有的基于AD的方法，信噪比和相对杂波峰值分别显着提高了8.8%和23.8%。 .