Landmine Detection Based on Riemannian Phasor Quaternion Self-Organizing Map

Ground penetrating radar (GPR) based landmine detection has advantages such as high safety and high efficiency. There are various methods to process data acquired from GPR systems. A common method is the Riemannian quaternion self-organizing map (RQSOM), which effectively enables self-organization of polarization data in quaternion form for visualization. However, RQSOM does not take into account the phase information of scattering components. Studies have shown that phase information is correlated with polarization information and can be effectively integrated into a new form, phasor quaternion (PQ). To visualize PQ-type feature vectors, in this paper, we propose a novel algrithm, Riemannian phasor quaternion self-organizing map (RPQSOM). RPQSOM utilizes the geometric characteristics of the phasor part to effectively learn useful information in PQ, thereby achieving superior visualization performance. We conduct experiments for visualizing a mock landmine. The experimental results demonstrate that RPQSOM fulfills our design objectives and gets better visualization results compared to RQSOM.