LANDMINE DETECTION BASED ON GENERALIZED RIEMANNIAN 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 the data obtained from GPR systems. One of the common methods is Riemannian quaternion self-organizing map (RQSOM), which can effectively make the polarization data self-organize for visualization. However, RQSOM cannot take into account the spatial degree of polarization (DoP) of the extracted data. Spatial DoP contains useful information for landmine visualization. To overcome the limitation, in this paper, we propose a novel algorithm, generalized Riemannian quaternion self-organizing map (GRQSOM), which utilize both polarization and spatial DoP during self-organization. Thus, better visualization performance can be obtained. We conduct experiments for the visualization of a mock landmine. The experimental results show that GRQSOM achieves our design and gets better visualization results compared with RQSOM.