Deep-learning Based Wall Mitigation Method for Through-the-wall Radar Imaging

Overview & Synopsis

Through-the-wall radar imaging is used for imaging targets hidden behind walls. However, the presence of a wall acting as a spatial filter impacts the scattering quality of the target’s field, influencing the resultant image’s clarity. Various f iltering strategies have been developed to separate the target’s and the wall’s responses. While effectively distinguishing the target and differentiating between multiple targets, these techniques also affect the imaging capability and the discrimination process. Here, we propose a deep-learning-based wall mitigation method to avoid this.